+publisher:"University of Texas – Austin" +contributor:("Baldea, Michael")

University of Texas – Austin

1. -4966-8063. Energy focused modeling and optimization of a radiant tube roller hearth austenization furnace.

Degree: MSin Engineering, Chemical Engineering, 2015, University of Texas – Austin

► In this thesis, we develop a two-dimensional energy-focused model of a roller hearth heat treating furnace. The two-dimensional model is based on first-principles, detailed representations… (more)

Subjects/Keywords: Heat treating furnace; Furnace energy

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APA (6^th Edition):

-4966-8063. (2015). Energy focused modeling and optimization of a radiant tube roller hearth austenization furnace. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/31750

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Chicago Manual of Style (16^th Edition):

-4966-8063. “Energy focused modeling and optimization of a radiant tube roller hearth austenization furnace.” 2015. Masters Thesis, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/31750.

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Author name may be incomplete

MLA Handbook (7^th Edition):

-4966-8063. “Energy focused modeling and optimization of a radiant tube roller hearth austenization furnace.” 2015. Web. 05 Mar 2021.

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Author name may be incomplete

Vancouver:

-4966-8063. Energy focused modeling and optimization of a radiant tube roller hearth austenization furnace. [Internet] [Masters thesis]. University of Texas – Austin; 2015. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/31750.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-4966-8063. Energy focused modeling and optimization of a radiant tube roller hearth austenization furnace. [Masters Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/31750

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Author name may be incomplete

University of Texas – Austin

2. James, Corey Matthew, 1976-. Reducing the cost of operational water on military bases through modeling, optimization, and control.

Degree: PhD, Chemical Engineering, 2017, University of Texas – Austin

URL: http://hdl.handle.net/2152/62970

► Military municipal water systems provide safe and clean water to the surrounding community while also supporting the intense and often unpredictable training schedules of the… (more)

▼ Military municipal water systems provide safe and clean water to the surrounding community while also supporting the intense and often unpredictable training schedules of the tenant units. Much like their civilian counterparts, military water systems are also consumers of great amounts of energy and capital. As a part of the Army Net Zero program in 2011, an annual water inventory conducted on eight U.S. Army installations concluded that consumption was 5.5 billion gallons. Using the Environmental Protection Agency’s average national estimate of 1,500 kWh of energy consumed for every 1,000 gallons of treated water, it is readily apparent that the department of defense is a heavy consumer of both water and energy. Because the scale of the military’s usage is so vast, so too is their waste. Waste in water systems is common and commonly neglected, as many were initially constructed decades ago and the commodity that they transport is relatively inexpensive. However, recent droughts affecting regions of the United States highlighted the need to conserve and avoid waste, regardless of the commodity price. The efficiency of water systems is highly dependent upon developing accurate models and using those models to accurately deal with disturbances such as demand and chlorine concentration. This work extends water distribution system modeling, optimization, and control to a military setting where constraints are tighter for resiliency purposes, demands are often unpredictable, and saving money and water improves defense capabilities. First, a discretized nonlinear, equation based model of a known system at an existing U.S. Army installation that accurately predicts system behavior under typical demand considerations. The model is calibrated for accuracy using actual system data from a military installation and employed in a nonlinear optimization program to study reduction of costs, minimizing waste, and improvements in energy efficiency. Demand profiles were constructed from residential data and scaled to better represent demand on military bases. With very little adjustment, this model can be used to optimize similar systems in the military inventory. Water and energy savings exceed 10% in the optimized system, which predicts the Army could save greater than $1.5 million per year in the continental United States if rigorous optimization was conducted on storage and pumping at every base. It is shown that a reduced order empirical model is a viable alternative to the computationally expensive equation based approach. The empirical model is used to implement model predictive control, providing the system protection against large and unpredictable disturbances. This method adds an additional manipulated variable, chlorine injection, to ensure efficient constraint compliance. Experimental results show this method further supports the aforementioned savings in the optimized system alone, while efficiently handling disturbances. This research closes previous gaps in research, particularly on military installations. First,… Advisors/Committee Members: Edgar, Thomas F. (advisor), Webber, Michael E., 1971- (advisor), Rochelle, Gary T (committee member), Baldea, Michael (committee member), Werth, Charles J (committee member).

Subjects/Keywords: Control; Optimization; Water; Energy; Military

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APA (6^th Edition):

James, Corey Matthew, 1. (2017). Reducing the cost of operational water on military bases through modeling, optimization, and control. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/62970

Chicago Manual of Style (16^th Edition):

James, Corey Matthew, 1976-. “Reducing the cost of operational water on military bases through modeling, optimization, and control.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/62970.

MLA Handbook (7^th Edition):

James, Corey Matthew, 1976-. “Reducing the cost of operational water on military bases through modeling, optimization, and control.” 2017. Web. 05 Mar 2021.

Vancouver:

James, Corey Matthew 1. Reducing the cost of operational water on military bases through modeling, optimization, and control. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/62970.

Council of Science Editors:

James, Corey Matthew 1. Reducing the cost of operational water on military bases through modeling, optimization, and control. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/62970

University of Texas – Austin

3. Perez, Krystian Xavier. Analysis, modeling and optimization of residential energy use from smart meter data.

Degree: PhD, Chemical engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/46454

► Approximately 38% of electricity consumption within the United States can be attributed to residential buildings, a vast share of which is in heating, ventilation and… (more)

▼ Approximately 38% of electricity consumption within the United States can be attributed to residential buildings, a vast share of which is in heating, ventilation and cooling. The load placed on the grid by residential consumers is highly variable and strongly influenced by weather and human activity patterns. Meeting fluctuations in demand is challenging and expensive for electricity producers and grid operators. Reducing variability in residential energy use can contribute significantly to increasing the uniformity of energy demand on the grid and diminish reliance on inefficient, polluting “peaking” plants that are used to meet extremely high demands. Achieving this goal requires tight coordination between energy consumption and generation, as well as the means to store energy generated in periods of low demand for use during the time intervals when consumer demand peaks. There is a common perception that a single home has a minor impact on the entire grid. However, owing to the fact that consumption patterns of homes are similar, while a single home does not have a large impact on the grid, entire neighborhoods do. Motivated by the above, this work explores the interaction between residential energy consumption and the electric grid. An analysis, modeling and optimization framework on smart meter data is developed to anticipate and modulate energy usage of ensembles of residential homes in order to reduce peak power demand. Much of the data used in this work come from Pecan Street, Inc., a smart grid demonstration project in Austin, TX. First, a nonintrusive load monitoring algorithm is developed to isolate air-conditioning (A/C) energy use from whole-house energy consumption data. Subsequently, a simplified reduced-order model is derived from smart meter data and thermostat set-point data to predict A/C energy use. The models of an ensemble of homes are placed within a centralized model predictive control scheme to minimize peak community A/C energy use. Reductions in peak energy use are achieved by shifting the thermostat set-points of individual homes. The approach is further expanded by simultaneously scheduling the operation of time-shiftable appliances to further reduce the community peak load. This integrated operation reduces peak loads by an average of 25.5%. This work also considers the impact of control and optimization techniques on designing a micro-grid that operates near autonomously from the electric power grid. Lastly, this work presents a tool to compare energy demand patterns of houses from smart meter data and indicates that high-energy houses would benefit from energy audits to improve energy efficiency. Advisors/Committee Members: Edgar, Thomas F. (advisor), Baldea, Michael (advisor), Novoselac, Atila (committee member), Webber, Michael E (committee member), Rochelle, Gary T (committee member).

Subjects/Keywords: Residential energy; Home energy management

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APA (6^th Edition):

Perez, K. X. (2016). Analysis, modeling and optimization of residential energy use from smart meter data. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46454

Chicago Manual of Style (16^th Edition):

Perez, Krystian Xavier. “Analysis, modeling and optimization of residential energy use from smart meter data.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/46454.

MLA Handbook (7^th Edition):

Perez, Krystian Xavier. “Analysis, modeling and optimization of residential energy use from smart meter data.” 2016. Web. 05 Mar 2021.

Vancouver:

Perez KX. Analysis, modeling and optimization of residential energy use from smart meter data. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/46454.

Council of Science Editors:

Perez KX. Analysis, modeling and optimization of residential energy use from smart meter data. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/46454

University of Texas – Austin

4. -0020-5212. Dynamic modeling of post-combustion amine scrubbing for process control strategy development.

Degree: PhD, Chemical engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/39612

► Intensified process designs with advanced solvents have been proposed to decrease both capital and operating costs of post-combustion carbon capture with amine scrubbing. These advanced… (more)

▼ Intensified process designs with advanced solvents have been proposed to decrease both capital and operating costs of post-combustion carbon capture with amine scrubbing. These advanced flowsheets create process control challenges because process variables are designed to operate near constraints and the degrees of freedom are increased due to heat recovery. Additionally, amine scrubbing is tightly integrated with the upstream power plant and downstream enhanced oil recovery (EOR) facility. This work simulated an amine scrubbing plant that uses an intercooled absorber and advanced flash stripper configuration with aqueous piperazine to capture CO2 from a 550 MWe coal-fired power plant. The objective of this research was to develop a process control strategy that resulted in favorable closed-loop dynamics and near-optimal conditions in response to disturbances and off-design operation. Two models were created for dynamic simulation of the amine scrubbing system: a medium-order model of an intercooled absorber column and a low-order model of the entire plant. The purpose of the medium-order model was to accurately predict the absorber temperature profile in order to identify a column temperature that can be controlled by manipulating the solvent circulation rate to maintain a constant liquid to gas ratio. The low-order model, which was shown to sufficiently represent dynamic process behavior through validation with pilot plant data, was used to develop a plantwide control strategy. A regulatory control layer was implemented and tested with bounding cases that represent either electricity generation requirements, CO2 emission regulations, or EOR constraints dominating the control strategy. Satisfying the operational and economic objectives of one system component was found to result in unfavorable dynamic performance for the remainder of the system. Self-optimizing control variables were identified for the energy recovery flowrates of the advanced flash stripper that maintained good energy performance in off-design conditions. Regulatory control alone could not satisfactorily achieve the set point for CO2 removal rate from the flue gas. A supervisory model predictive controller was developed that manipulates the set point for the stripper pressure controller in order to control removal. The straightforward single-input, single-output constrained linear model predictive controller exhibited a significant improvement compared to PI control alone. Advisors/Committee Members: Rochelle, Gary T. (advisor), Edgar, Thomas F. (advisor), Baldea, Michael (committee member), Akella, Maruthi R (committee member), Chen, Eric (committee member).

Subjects/Keywords: Amine scrubbing; Dynamic modeling; Process control; Carbon capture

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APA (6^th Edition):

-0020-5212. (2016). Dynamic modeling of post-combustion amine scrubbing for process control strategy development. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/39612

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Chicago Manual of Style (16^th Edition):

-0020-5212. “Dynamic modeling of post-combustion amine scrubbing for process control strategy development.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/39612.

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Author name may be incomplete

MLA Handbook (7^th Edition):

-0020-5212. “Dynamic modeling of post-combustion amine scrubbing for process control strategy development.” 2016. Web. 05 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-0020-5212. Dynamic modeling of post-combustion amine scrubbing for process control strategy development. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/39612.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-0020-5212. Dynamic modeling of post-combustion amine scrubbing for process control strategy development. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/39612

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University of Texas – Austin

5. Abdulla, Thaer Adnan. An experimental investigation of batch distillation column control.

Degree: PhD, Chemical Engineering, 2019, University of Texas – Austin

URL: http://dx.doi.org/10.26153/tsw/5871

► The development of an inferential soft sensor for a pilot-plant distillation column separating an ethanol-water mixture using neural network (NN) models has been investigated in… (more)

▼ The development of an inferential soft sensor for a pilot-plant distillation column separating an ethanol-water mixture using neural network (NN) models has been investigated in this work. Inferential sensors are increasingly used in the process industries to infer the value of the main quality variable while utilizing much easier to measure secondary variables of the process. The lags between the input variables and the output variables vary due to changes in operating conditions. Previous studies have introduced different methods to estimate lags for input and output variables, but all of them have assumed these lags to be constant regardless of the changes in the operating conditions. In this work, an inferential sensor that can predict the composition of ethanol at the top product using time lags for the input variables and varied first-order time constant lags with the output variable has been developed. The developed inferential sensor is based on a neural network (NN) model. Principal Component Analysis (PCA) and Projection to Latent Structures (PLS) methods are used in this work to remove the outliers from the input variables set and to determine the most correlated values of the input variables and their lags with the output variable Xa (ethanol composition of distillate product) respectively. The model adaptively selects the correct first-order time constant lags of an output variable according to the instantaneous operating condition (the composition of ethanol is increased or decreased) and assigns a best value for each case. The experimental data resulting from the operation of pilot-scale batch distillation column of ethanol-water system has been used to build these NN models first and then to validate their performance. The proposed NN model structure with time lags for input variables and varied first-order time constant lags for output variable gave higher accuracy compared with the NN model without any time lag for input and output variables. This new developed NN based soft sensor has been used in an inferential proportional-integral (PI) control scheme to control the ethanol composition of the distillate. The initial inferential control results of using one tuning parameter set during the whole operation showed imperfect control results. So, using updated tuning parameter sets (gain scheduling/adaptive tuning) within this inferential PI control scheme based on the ethanol mole fraction region is necessary to improve the control performance. The results of this new developed PI control scheme showed a good control performance compared with the initial control results of this inferential controller using one set of tuning parameters. Then, this new developed NN based soft sensor has also been used in an advanced control scheme (model predictive control or MPC scheme). Two DeltaV MPC control schemes (MPC11 and MPC22) have been developed in this work. The control results of DeltaV MPC22 control scheme showed better control performance compared with other control schemes (inferential PI and MPC11… Advisors/Committee Members: Edgar, Thomas F. (advisor), Baldea, Michael (committee member), Rochelle, Gary T. (committee member), Akella, Maruthi R. (committee member).

Subjects/Keywords: Data-driven soft sensors; ANN; Batch distillation; Inferential PI control; Model predictive control (MPC)

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APA (6^th Edition):

Abdulla, T. A. (2019). An experimental investigation of batch distillation column control. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/5871

Chicago Manual of Style (16^th Edition):

Abdulla, Thaer Adnan. “An experimental investigation of batch distillation column control.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://dx.doi.org/10.26153/tsw/5871.

MLA Handbook (7^th Edition):

Abdulla, Thaer Adnan. “An experimental investigation of batch distillation column control.” 2019. Web. 05 Mar 2021.

Vancouver:

Abdulla TA. An experimental investigation of batch distillation column control. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2021 Mar 05]. Available from: http://dx.doi.org/10.26153/tsw/5871.

Council of Science Editors:

Abdulla TA. An experimental investigation of batch distillation column control. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/5871

University of Texas – Austin

6. DeRosa, Sean Edward. Impact of natural gas and natural gas liquids on chemical manufacturing in the United States.

Degree: PhD, Chemical engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/39644

► Natural gas and natural gas liquids production in the United States has increased dramatically since 2005, due primarily to recent advancements in horizontal drilling and… (more)

Subjects/Keywords: Petrochemical; Network model; Agent-based model; Life cycle assessment

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APA (6^th Edition):

DeRosa, S. E. (2016). Impact of natural gas and natural gas liquids on chemical manufacturing in the United States. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/39644

Chicago Manual of Style (16^th Edition):

DeRosa, Sean Edward. “Impact of natural gas and natural gas liquids on chemical manufacturing in the United States.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/39644.

MLA Handbook (7^th Edition):

DeRosa, Sean Edward. “Impact of natural gas and natural gas liquids on chemical manufacturing in the United States.” 2016. Web. 05 Mar 2021.

Vancouver:

DeRosa SE. Impact of natural gas and natural gas liquids on chemical manufacturing in the United States. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/39644.

Council of Science Editors:

DeRosa SE. Impact of natural gas and natural gas liquids on chemical manufacturing in the United States. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/39644

University of Texas – Austin

7. Ganesh, Hari Sai. Modeling, control, and optimization of an industrial austenitization furnace.

Degree: PhD, Chemical Engineering, 2019, University of Texas – Austin

URL: http://dx.doi.org/10.26153/tsw/1047

► Steel production and processing is both energy-intensive (2% of overall energy consumption) and one of the biggest contributors to CO₂ emissions. Its use is projected… (more)

▼ Steel production and processing is both energy-intensive (2% of overall energy consumption) and one of the biggest contributors to CO₂ emissions. Its use is projected to increase by 1.5 times that of present levels (around 1.6 billion metric tonnes per year) by 2050 to meet the needs of a growing population. The main goal of this research is to minimize the energy consumption of a steel quench hardening (or heat treating) process, currently in operation at an industrial partner, by mathematical modeling, optimization, advanced control, and heat integration. The quench hardening processes consists of heating pre-finished metal parts to a certain temperature in a continuously operating furnace (austenitization), followed by rapid cooling (quenching) in water, brine or oil to induce desired metallurgical properties like hardness, toughness, shear strength, tensile strength, etc. The novelty of this work lies in the two scale modeling approach considered to solve the furnace energy consumption minimization problem. We improve a previously developed two-dimensional (2D) physicsbased model of the heat treating furnace that computes the energy usage of the furnace and the part temperature distribution as a function of time and position within the furnace under temperature feedback control. We predict the effect of process variables on microstructural evolution of the parts using an empirical relation reported in the literature and their consequent effects on the metallurgical properties of the quenched product. The physics-based model combined with the empirical model is used to simulate the furnace operation for a batch of parts processed sequentially under heuristic temperature set points with a simple linear control strategy suggested by the operators of the plant. We then minimize the energy consumption of the furnace without compromising the product quality by real-time optimization (RTO), model predictive control (MPC), and heat integration using radiant recuperators. Energy savings of 3.7%, 15.93%, and 20.88% were obtained under model predictive control, heat integration, and optimized set points respectively compared to reference heuristic operation case without heat integration and MPC. Advisors/Committee Members: Baldea, Michael (advisor), Edgar, Thomas F. (advisor), Ezekoye, Ofodike A. (committee member), Rochelle, Gary T. (committee member).

Subjects/Keywords: Austenitization; Furnace; Modeling; Optimization; Control

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APA (6^th Edition):

Ganesh, H. S. (2019). Modeling, control, and optimization of an industrial austenitization furnace. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/1047

Chicago Manual of Style (16^th Edition):

Ganesh, Hari Sai. “Modeling, control, and optimization of an industrial austenitization furnace.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://dx.doi.org/10.26153/tsw/1047.

MLA Handbook (7^th Edition):

Ganesh, Hari Sai. “Modeling, control, and optimization of an industrial austenitization furnace.” 2019. Web. 05 Mar 2021.

Vancouver:

Ganesh HS. Modeling, control, and optimization of an industrial austenitization furnace. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2021 Mar 05]. Available from: http://dx.doi.org/10.26153/tsw/1047.

Council of Science Editors:

Ganesh HS. Modeling, control, and optimization of an industrial austenitization furnace. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/1047

University of Texas – Austin

8. Kumar, Ankur, Ph. D. Model based operation of industrial steam methane reformers using large scale sensor data.

Degree: PhD, Chemical engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/46443

► Large quantities of hydrogen are consumed in refineries and for production of important chemicals such as ammonia and methanol. Declining crude-oil quality and increased fertilizer… (more)

▼ Large quantities of hydrogen are consumed in refineries and for production of important chemicals such as ammonia and methanol. Declining crude-oil quality and increased fertilizer demands, among others, have led to further increase in hydrogen demand. A significant portion (~80%) of industrial hydrogen consumption is met via natural-gas steam methane reforming. This process takes place in a large scale, high-temperature, and highly energy-intensive unit called a steam methane reformer (SMR), where endothermic reforming reactions are carried out in hundreds of catalyst-filled tubes placed in a gas-fired furnace. A typical modern hydrogen production plant consumes a substantial amount (~10⁵ GJ) of natural gas per day. The overall productivity (energy consumed per unit H2 produced) of the plant is strongly dependent on how efficiently the SMR is operated, which further depends on the spatial temperature distribution inside the furnace, where a more uniform distribution paves the way for reduced plant-wide energy use. Controlling the temperature distribution is, however, a challenging task due to the distributed nature of the system and the difficulty of obtaining distributed temperature measurements (the latter associated with the extreme operating conditions and the complex geometry of the furnace). In this thesis, results concerning the monitoring of temperature distribution in an industrial SMR furnace using a large array of infrared camera sensors, which produce a significant stream of data regarding the furnace temperature distribution, are presented. Specifically, strategies for homogenization of reformer tube-wall temperature distribution, also called furnace balancing, using reduced-order and physics-based models are developed. First, for a proof-of-concept study, a computational fluid dynamics (CFD) model of a small scale SMR system is developed as a substitute for a real plant. A proper orthogonal decomposition-based reduced-order linear model is used to modulate the fuel distribution among the burners. It is shown that a reduced-order empirical model with much lower computational requirements, when trained with sufficiently rich data, can be a viable substitute to the detailed modeling of the complex thermal and flow interactions in the furnace. Next, the data-driven modeling approach is extended to a real full-scale industrial SMR furnace. Shortcomings in popular empirical modeling approaches such as partial least squares (PLS) and ordinary least squares (OLS) are highlighted and a novel egg-crate SMR (EC-SMR) model is proposed. The model is calibrated using temperature measurements from the infrared cameras. Experimental results confirm that the proposed framework has excellent performance providing a 44% improvement in temperature distribution non-uniformity. While computationally intensive CFD models are not suitable for use in furnace efficiency optimization calculations, empirical models (data-driven reduced-order models) have limited accuracy when wide changes in operating conditions are… Advisors/Committee Members: Edgar, Thomas F. (advisor), Baldea, Michael (advisor), Bonnecaze, Roger T (committee member), Ezekoye, Ofodike A (committee member), Beaman, Joseph J (committee member).

Subjects/Keywords: Steam methane reformer; Distributed parameter control; Plantwide optimization; Hydrogen plant optimization; Smart manufacturing

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APA (6^th Edition):

Kumar, Ankur, P. D. (2016). Model based operation of industrial steam methane reformers using large scale sensor data. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46443

Chicago Manual of Style (16^th Edition):

Kumar, Ankur, Ph D. “Model based operation of industrial steam methane reformers using large scale sensor data.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/46443.

MLA Handbook (7^th Edition):

Kumar, Ankur, Ph D. “Model based operation of industrial steam methane reformers using large scale sensor data.” 2016. Web. 05 Mar 2021.

Vancouver:

Kumar, Ankur PD. Model based operation of industrial steam methane reformers using large scale sensor data. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/46443.

Council of Science Editors:

Kumar, Ankur PD. Model based operation of industrial steam methane reformers using large scale sensor data. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/46443

University of Texas – Austin

9. Pattison, Richard C. Equation-oriented modeling, simulation, and optimization of integrated and intensified process and energy systems.

Degree: PhD, Chemical engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/46459

► Process intensification, defined as unconventional design and/or operation of processes that results in substantial performance improvements, represents a promising route toward reducing capital and operating… (more)

▼ Process intensification, defined as unconventional design and/or operation of processes that results in substantial performance improvements, represents a promising route toward reducing capital and operating expenses in the chemical/petrochemical process industry, while simultaneously achieving improved safety and environmental performance. In this dissertation, intensification is approached from three different angles: reactor design and control, process flowsheet design and optimization, and production scheduling and control. In the first part of the dissertation, three novel concepts for improving the controllability of intensified microchannel reactors are introduced. The first concept is a latent energy storage-based temperature controller, where a phase change material is confined within the walls of an autothermal reactor to improve local temperature control. The second concept is a segmented catalyst layer which modulates the rate of heat generation and consumption along the length of an autothermal reactor. Finally, the third concept is a thermally actuated valve, which uses small-scale bimetallic strips to modulate flow in a microchannel reactor in response to temperature changes. The second part of the dissertation introduces a novel framework for equation-oriented flowsheet modeling, simulation and optimization. The framework consists of a pseudo-transient reformulation of the steady-state material and energy balance equations of process unit operations as differential-algebraic equation (DAE) systems that are statically equivalent to the original model. I show that these pseudo-transient models improve the convergence properties of equation-oriented process flowsheet simulations by expanding the convergence basin in comparison to conventional steady state equation-oriented simulators. A library of pseudo-transient unit operation models is developed, and several case studies are presented. Models for more complex unit operations such as a pseudo-transient multistream heat exchanger and a dividing-wall distillation column are later introduced, and can easily be included in the flowsheet optimization framework. In the final part of the dissertation, a paradigm for calculating the optimal production schedule in a fast changing market situation is introduced. This is accomplished by including a model of the dynamics of a process and its control system into production scheduling calculations. The scheduling-relevant dynamic models are constructed to be of lower order than a detailed dynamic process model, while capturing the closed-loop behavior of a set of scheduling-relevant variables. Additionally, a method is given for carrying out these production scheduling calculations online and in "closed scheduling loop,"' i.e., recalculating scheduling decisions upon the advent of scheduling-relevant process or market events. An air separation unit operating in a demand response scenario is used as a representative case study. Advisors/Committee Members: Baldea, Michael (advisor), Edgar, Thomas F. (committee member), Rochelle, Gary T (committee member), Bonnecaze, Roger T (committee member), Biros, George (committee member).

Subjects/Keywords: Process modeling; Process control; Flowsheet optimization; Integration of scheduling and control; Equation-oriented modeling; Process intensification; Process integration

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APA (6^th Edition):

Pattison, R. C. (2016). Equation-oriented modeling, simulation, and optimization of integrated and intensified process and energy systems. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/46459

Chicago Manual of Style (16^th Edition):

Pattison, Richard C. “Equation-oriented modeling, simulation, and optimization of integrated and intensified process and energy systems.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/46459.

MLA Handbook (7^th Edition):

Pattison, Richard C. “Equation-oriented modeling, simulation, and optimization of integrated and intensified process and energy systems.” 2016. Web. 05 Mar 2021.

Vancouver:

Pattison RC. Equation-oriented modeling, simulation, and optimization of integrated and intensified process and energy systems. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/46459.

Council of Science Editors:

Pattison RC. Equation-oriented modeling, simulation, and optimization of integrated and intensified process and energy systems. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/46459

University of Texas – Austin

10. Ondeck, Abigail Devin. The economic feasibility of combined heat and power as a utility producer for the residential sector.

Degree: PhD, Chemical Engineering, 2017, University of Texas – Austin

URL: http://hdl.handle.net/2152/60378

► Combined heat and power (CHP) plants are a very promising prospect to reducing CO₂ emissions and increasing efficiency in the power generation sector, especially when… (more)

▼ Combined heat and power (CHP) plants are a very promising prospect to reducing CO₂ emissions and increasing efficiency in the power generation sector, especially when combined with residential solar photovoltaic (PV) power generation. By utilizing natural gas, a cleaner fuel than coal, CHP plants can reduce CO₂ emissions, while exploiting the waste heat from electricity production to generate a useful thermal energy, increasing the overall efficiency of the plant. While incorporating residential solar PV power generation has important environmental benefits, it can - if not properly managed - lead to an over-generation situation with very high power plant ramp rates. Most current power plants are unlikely to be able to withstand such rapid changes in generation rates. If PV generation is incorporated into the design and operation of the CHP plant, both thermal and electrical energy storage systems can be included, opening the door to more strategies for controlling photovoltaic generation and increased PV power generation. The ability to combine thermal and electrical energy generation in an efficient manner, on a medium to large scale, suggests that CHP plants with rooftop PV panels and energy storage are an appealing choice as an integrated utility supplier for the neighborhood of the future. Yet, there are currently no CHP plants that serve exclusively residential neighborhoods in the United States. Thus, the objective of this research was to determine the most economical design and operation of a CHP plant with integrated residential solar PV power generation to meet all the energy demands of a residential neighborhood. After determining that a CHP plant could meet all the electricity, heating, and cooling demands of a residential neighborhood, a multi-scale economical optimization formulation to simultaneously determine the design and operation of a CHP plant with PV generation was constructed. The optimal CHP plant produced extra energy, so the optimization formulation was updated to include both thermal and electrical energy storage. Utilizing the results from these optimizations, the monetary values of PV generation and energy storage were evaluated, giving a guide for future economic targets for these technologies. Advisors/Committee Members: Edgar, Thomas F. (advisor), Baldea, Michael (advisor), Baldick, Ross (committee member), Novoselac, Atila (committee member), Truskett, Thomas (committee member).

Subjects/Keywords: Combined heat and power; Energy; Renewables; Residential district utilities

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APA (6^th Edition):

Ondeck, A. D. (2017). The economic feasibility of combined heat and power as a utility producer for the residential sector. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/60378

Chicago Manual of Style (16^th Edition):

Ondeck, Abigail Devin. “The economic feasibility of combined heat and power as a utility producer for the residential sector.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/60378.

MLA Handbook (7^th Edition):

Ondeck, Abigail Devin. “The economic feasibility of combined heat and power as a utility producer for the residential sector.” 2017. Web. 05 Mar 2021.

Vancouver:

Ondeck AD. The economic feasibility of combined heat and power as a utility producer for the residential sector. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/60378.

Council of Science Editors:

Ondeck AD. The economic feasibility of combined heat and power as a utility producer for the residential sector. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/60378

University of Texas – Austin

11. Park, Jungup. Data-driven modeling and optimization of sequential batch-continuous process.

Degree: PhD, Chemical engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/39461

► Driven by the need to lower capital expenditures and operating costs, as well as by competitive pressure to increase product quality and consistency, modern chemical… (more)

▼ Driven by the need to lower capital expenditures and operating costs, as well as by competitive pressure to increase product quality and consistency, modern chemical processes have become increasingly complex. These trends are manifest, on the one hand, in complex equipment configurations and, on the other hand, in a broad array of sensors (and control systems), which generate large quantities of operating data. Of particular interest is the combination of two traditional routes of chemical processing: batch and continuous. Batch to continuous processes (B2C), which constitute the topic of this dissertation, comprise of a batch section, which is responsible for preparing the materials that are then processed in the continuous section. In addition to merging the modeling, control and optimization approaches related to the batch and continuous operating paradigms – which are radically different in many aspects – challenges related to analyzing the operation of such processes arise from the multi-phase flow. In particular, we will be considering the case where a particulate solid is suspended in a liquid ``carrier'', in the batch stage, and the two-phase mixture is conveyed through the continuous stage. Our explicit goal is to provide a complete operating solution for such processes, starting with the development of meaningful and computationally efficient mathematical models, continuing with a control and fault detection solution, and finally, a production scheduling concept. Owing to process complexity, we reject out of hand the use of first-principles models, which are inevitably high dimensional and computationally expensive, and focus on data-driven approaches instead. Raw data obtained from chemical industry are subject to noise, equipment malfunction and communication failures and, as such, data recorded in process historian databases may contain outliers and measurement noise. Without proper pretreatment, the accuracy and performance of a model derived from such data may be inadequate. In the next chapter of this dissertation, we address this issue, and evaluate several data outlier removal techniques and filtering methods using actual production data from an industrial B2C system. We also address a specific challenge of B2C systems, that is, synchronizing the timing of the batch data need with the data collected from the continuous section of the process. Variable-wise unfolded data (a typical approach for batch processes) exhibit measurement gaps between the batches; however, this type of behavior cannot be found in the subsequent continuous section. These data gaps have an impact on data analysis and, in order to address this issue, we provide a method for filling in the missing values. The batch characteristic values are assigned in the gaps to match the data length with the continuous process, a procedure that preserves meaningful process correlations. Data-driven modeling techniques such as principal component analysis (PCA) and partial least squares (PLS) regression are well-established for modeling batch… Advisors/Committee Members: Edgar, Thomas F. (advisor), Baldea, Michael (advisor), Djurdjanovic, Dragan (committee member), Rochelle, Gary T (committee member), Truskett, Thomas M (committee member).

Subjects/Keywords: Sequential batch-continuous process; Data-driven modeling; Time scale bridging model; Scheduling; Control; Real-time optimization

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APA (6^th Edition):

Park, J. (2016). Data-driven modeling and optimization of sequential batch-continuous process. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/39461

Chicago Manual of Style (16^th Edition):

Park, Jungup. “Data-driven modeling and optimization of sequential batch-continuous process.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/39461.

MLA Handbook (7^th Edition):

Park, Jungup. “Data-driven modeling and optimization of sequential batch-continuous process.” 2016. Web. 05 Mar 2021.

Vancouver:

Park J. Data-driven modeling and optimization of sequential batch-continuous process. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/39461.

Council of Science Editors:

Park J. Data-driven modeling and optimization of sequential batch-continuous process. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/39461

University of Texas – Austin

12. -0903-5467. High density thermal energy stores utilizing phase change materials for shifting of peak cooling loads.

Degree: PhD, Civil Engineering, 2018, University of Texas – Austin

URL: http://hdl.handle.net/2152/70611

► Air conditioning cooling loads consume 11% of the electricity produced in the United States, and can be as high as 27% of total electric production… (more)

▼ Air conditioning cooling loads consume 11% of the electricity produced in the United States, and can be as high as 27% of total electric production in warm, humid climates. During the summer months these HVAC cooling loads can comprise more than 50% of peak electric load, with much of the demand coming from small commercial or residential electric customers. Thermal storage systems offer the ability to shift these peak cooling loads to non- peak periods, which allows for a more efficient operation of baseload electric power plants by better utilizing capital equipment and available capacity. In addition, thermal storage systems allow for the more effective use of intermittent, renewable energy sources by shifting cooling loads to periods of renewable energy availability. Finally, thermal storage systems reduce the capital equipment cost for HVAC compressor systems by allowing the equipment to be sized for average, rather than peak, loads. Given that residential and small commercial buildings generate the majority of peak cooling load in warm, humid climates, a thermal storage system compatible with these structures and sites is necessary. These sites may not have the space necessary for common chilled water thermal storage systems, which utilize the temperature change of a working fluid (frequently water) to store sensible energy in large storage tanks. For residential and small commercial applications, a more compact, high-density thermal storage system will be required. Latent thermal storage, which utilizes the energy associated with a change in phase of a material to store thermal energy, shows promise for use in high-density thermal storage systems. This research develops a latent thermal energy storage system based on phase change materials (PCM) suitable for use in applications where the size of the thermal store is critical, such as for existing residences and small commercial structures. Numerical, analytical, and experimental methods are used to design, test, and model a tube-encapsulated PCM-based thermal storage system with a capacity and performance suitable for HVAC applications. This research provides both general and specific design criteria sufficient to allow engineers to utilize this thermal store design for specific applications. Advisors/Committee Members: Novoselac, Atila (advisor), Corsi, Richard (committee member), Baldea, Michael (committee member), Xu, Ying (committee member), da Silva, Alexandre (committee member).

Subjects/Keywords: Latent thermal storage; Phase change material (PCM); Load shift

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APA (6^th Edition):

-0903-5467. (2018). High density thermal energy stores utilizing phase change materials for shifting of peak cooling loads. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/70611

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16^th Edition):

-0903-5467. “High density thermal energy stores utilizing phase change materials for shifting of peak cooling loads.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/70611.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

-0903-5467. “High density thermal energy stores utilizing phase change materials for shifting of peak cooling loads.” 2018. Web. 05 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-0903-5467. High density thermal energy stores utilizing phase change materials for shifting of peak cooling loads. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/70611.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-0903-5467. High density thermal energy stores utilizing phase change materials for shifting of peak cooling loads. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/70611

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

University of Texas – Austin

13. -7739-8836. Data-driven methods for improved decision-making in the chemical process industries.

Degree: PhD, Chemical Engineering, 2020, University of Texas – Austin

URL: http://dx.doi.org/10.26153/tsw/9108

► Recent decades have prompted chemical manufacturers to consider new operating paradigms. Globalization and other market trends have reduced profit margins and emphasized the need for… (more)

▼ Recent decades have prompted chemical manufacturers to consider new operating paradigms. Globalization and other market trends have reduced profit margins and emphasized the need for processes to operate in a more flexible and agile manner, e.g., to rapidly shift productions targets in response to real-time economic data, or to benefit from participation in short-term electricity markets. The twin prongs of (dynamic) process modeling and mathematical optimization have been key in meeting these challenges. One example is the widely adopted model-predictive control, an optimization-based feedback control framework which uses a dynamic model to determine an optimal sequence of control inputs. More broadly, there is a growing trend toward integrating modeling / optimization problems across the decisional hierarchy, ranging from design and long-term planning to the scheduling and real-time operation of process units. In this dissertation, I propose data-driven solutions that address some of these problems. The first part of this dissertation is concerned with the problem of model quality maintenance for model predictive controllers. I propose a statistical method for locating and estimating plant-model mismatch in these systems, formulated as an optimization problem which minimizes the discrepancy between theoretical and empirical statistics associated with the process variables. The method is capable of detecting and estimating the magnitude of plant-model mismatch in industrially relevant controllers, i.e., using state-space dynamic models and including state estimation. Furthermore, the procedure can be applied to data collected from normal process operation, without requiring costly system re-identification tests. Case studies demonstrate very good performance of the proposed method. The second part of this dissertation is focused on the problem of integrating process scheduling with (nonlinear) dynamics of the control system and the process itself. Such efforts are motivated by the increasing overlap in the time scales of the respective layers in the decisional hierarchy: as scheduling decisions are made more frequently, e.g., as modulation of throughput for participation in demand response; and/or as plant-wide dynamics become slower, e.g., with greater energy/material integration. These trends require integrated solution methods in order to obtain optimal operating policies. First, I propose a framework for explicitly representing the behavior of dynamic systems under model-predictive control within scheduling optimization problems. My approach converts this large-scale bi-level problem into a single-level "mathematical problem with complementarity constraints,'' in which the optimality conditions of the lower-level MPC problem are embedded directly in the upper-level scheduling problem. Reformulations of the resulting nonlinear optimization problem are proposed to improve computational performance. Two case studies demonstrate that the integrated problem achieves better performance relatively to alternative (i.e.,… Advisors/Committee Members: Baldea, Michael (advisor), Edgar, Thomas F (committee member), Bakolas, Efsthathios (committee member), Bonnecaze, Roger T (committee member), Djurdjanovic, Dragan (committee member).

Subjects/Keywords: Process systems engineering; Optimal scheduling and control

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APA (6^th Edition):

-7739-8836. (2020). Data-driven methods for improved decision-making in the chemical process industries. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/9108

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16^th Edition):

-7739-8836. “Data-driven methods for improved decision-making in the chemical process industries.” 2020. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://dx.doi.org/10.26153/tsw/9108.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

-7739-8836. “Data-driven methods for improved decision-making in the chemical process industries.” 2020. Web. 05 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-7739-8836. Data-driven methods for improved decision-making in the chemical process industries. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2020. [cited 2021 Mar 05]. Available from: http://dx.doi.org/10.26153/tsw/9108.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-7739-8836. Data-driven methods for improved decision-making in the chemical process industries. [Doctoral Dissertation]. University of Texas – Austin; 2020. Available from: http://dx.doi.org/10.26153/tsw/9108

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

14. Wang, Ray Chen. Geometric fault detection using 3D Kiviat plots and their applications.

Degree: PhD, Electrical and Computer Engineering, 2017, University of Texas – Austin

URL: http://hdl.handle.net/2152/47439

► The surge in large-scale data being collected through various social and economic systems comes along with the ever-increasing need to understand and gain insight from… (more)

▼ The surge in large-scale data being collected through various social and economic systems comes along with the ever-increasing need to understand and gain insight from the data being collected. This has spurred on the development and advent of big data analytics in many different areas such as healthcare, e-commerce, and group-sharing applications. This applies also to the process industry as well, as the development of more complex processes, which in turn require increased monitoring, mean that a larger amount of data are being collected than previously seen. This data is not only high in volume (measurements taken with a high sampling frequency), but also high in dimensionality (many sensors set up throughout the process). Process monitoring requires the continuous observation of such high dimensional and high volume data, but current visualization techniques do not lend themselves to do doing so. Furthermore, parallel to process monitoring is the desire for fault detection capability – to detect faults as soon as they occur or predict them before they occur. For that reason it is ideal if there is a visualization technique that also contributes to fault detection efforts, so that both process monitoring and fault detection is satisfied. To that end, in this dissertation the development of three-dimensional (3D) Kiviat diagrams and its use in fault detection is explored in great detail. In Kiviat diagrams, axes are laid out radially around a center point, in contrast to axes being perpendicular to one another in traditional score plots, or in parallel to one another as seen in parallel coordinates. This theoretically allows for an infinite number of axes, and therefore high dimensional data, to be plotted on one figure at once. Due to the time-explicit nature of process data, the addition of a third axis normal to the Kiviat diagram is proposed as well. In the Kiviat diagram representation, each sample forms a polygon on the plot. This is taken advantage of for fault detection purposes by condensing each polygon into its centroid. By doing so the state of the process at every point in time can be represented by its centroid – this allows for multivariate fault detection to be performed. Using these centroids, a variety of fault detection mechanisms are proposed specific to the types of processes the data is obtained from. The mechanisms are developed for 3 process types commonly seen in industry – continuous processes, batch processes, and periodic processes. For each process type the fault detection mechanism is detailed and case studies are laid out, demonstrating the application of the method. Advisors/Committee Members: Baldick, Ross (advisor), Baldea, Michael (advisor), Arapostathis, Ari (committee member), Edgar, Thomas F (committee member), Ghosh, Joydeep (committee member).

Subjects/Keywords: Fault detection; Data visualization; 3D Kiviat plots; Fault detection capability; Process monitoring; Kiviat diagrams; High dimensional data; Process data

11 more images…

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APA (6^th Edition):

Wang, R. C. (2017). Geometric fault detection using 3D Kiviat plots and their applications. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/47439

Chicago Manual of Style (16^th Edition):

Wang, Ray Chen. “Geometric fault detection using 3D Kiviat plots and their applications.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/47439.

MLA Handbook (7^th Edition):

Wang, Ray Chen. “Geometric fault detection using 3D Kiviat plots and their applications.” 2017. Web. 05 Mar 2021.

Vancouver:

Wang RC. Geometric fault detection using 3D Kiviat plots and their applications. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/47439.

Council of Science Editors:

Wang RC. Geometric fault detection using 3D Kiviat plots and their applications. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/47439

University of Texas – Austin

15. Sherman, Brent Joseph. Thermodynamic and mass transfer modeling of aqueous hindered amines for carbon dIoxide capture.

Degree: PhD, Chemical engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/39630

► With the detrimental effects of global climate change beginning to be felt, there is a growing consensus that something must be done. One part of… (more)

▼ With the detrimental effects of global climate change beginning to be felt, there is a growing consensus that something must be done. One part of the solution is carbon capture and storage using amine scrubbing to capture 90% of the CO2 from power plants burning coal and natural gas. To actualize this solution, process models are necessary. A process model requires an accurate thermodynamic and mass transfer model with physically meaningful parameters. While hindered amines are commercially used, the reason for their mass transfer rates is still an open question. These two needs are addressed in this work. To improve thermodynamic modeling, the physical significance of the electrolyte non-random two-liquid (eNRTL) regressed binary interaction parameters were examined. To improve mass transfer modeling, a response surface methodology (RSM) approach was used to give statistically significant regressed parameters. The mass transfer of two hindered amines, 2-amino-2-methyl-propan-1-ol (AMP) and 2-piperidineethanol (2PE) was studied to determine the role of carbamate. The absolute difference in eNRTL binary interaction parameters was found to moderately correlate with the pKa of the amine. An analogy method was developed to enable thermodynamic model creation for amines in the absence of some physical property data. The carbamate reaction plays a determining role in mass transfer of hindered amines. Based on Bronsted plots, 2PE appears to form carbamate using the same mechanism as unhindered, cyclic secondary amines, while AMP does not seem to use the same mechanism as unhindered, primary amines. The rate constant for bicarbonate formation for both amines is a factor of twelve faster than predicted from tertiary amine bicarbonate formation, indicating that neither seems to form bicarbonate using the tertiary amine mechanism. The six models constructed in this work enable process modeling and economic comparisons of solvents. Four binary interaction parameters were the most physically significant and should be regressed for future solvents. The high bicarbonate reaction rate of the hindered amines should be further investigated to determine if the mechanism is different or if this is model artifice, as either outcome will substantially improve mass transfer modeling for all amines. Advisors/Committee Members: Rochelle, Gary T. (advisor), Baldea, Michael (committee member), Chen, Chau-Chyun (committee member), Chen, Eric (committee member), Hwang, Gyeong (committee member).

Subjects/Keywords: eNRTL; Separations; Carbamate stability; Wetted-wall column; Blend solvent; Amine scrubbing

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APA (6^th Edition):

Sherman, B. J. (2016). Thermodynamic and mass transfer modeling of aqueous hindered amines for carbon dIoxide capture. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/39630

Chicago Manual of Style (16^th Edition):

Sherman, Brent Joseph. “Thermodynamic and mass transfer modeling of aqueous hindered amines for carbon dIoxide capture.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/39630.

MLA Handbook (7^th Edition):

Sherman, Brent Joseph. “Thermodynamic and mass transfer modeling of aqueous hindered amines for carbon dIoxide capture.” 2016. Web. 05 Mar 2021.

Vancouver:

Sherman BJ. Thermodynamic and mass transfer modeling of aqueous hindered amines for carbon dIoxide capture. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/39630.

Council of Science Editors:

Sherman BJ. Thermodynamic and mass transfer modeling of aqueous hindered amines for carbon dIoxide capture. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/39630

University of Texas – Austin

16. -9912-2897. Embedding dynamics and control considerations in operational optimization of process and energy systems.

Degree: PhD, Chemical engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/39556

► Embedding dynamics and control considerations within operational optimization decisions can result in improved performance of processes and energy systems. These efforts are motivated by modern… (more)

▼ Embedding dynamics and control considerations within operational optimization decisions can result in improved performance of processes and energy systems. These efforts are motivated by modern sustainability initiatives, in particular demand response and demand management strategies for improving the efficiency of the electric grid. In these scenarios residential, commercial, and industrial electricity consumers are provided with a financial incentive to shift their demand such that the total load on the grid can be satisfied using efficient generation technologies and renewable energy sources. The financial incentive is typically a time-dependent price structure, where rates reflect the demand level and stress on the grid. Reacting to such fast-changing energy markets requires that process and energy systems be highly flexible, which is a significant departure from traditional steady state operation under fixed market conditions. In this context, flexibility means the ability to make frequent changes to the system operation (e.g., production setpoints, constraint levels, etc.) while still maintaining stability and satisfying operating constraints at all times. This necessitates the development of advanced control and decision making strategies which are aware of system dynamics. Accounting for dynamics by incorporating detailed, first-principles models of a system into optimization-based controllers or scheduling calculations would provide ample dynamic information. However, the resulting dynamic optimization formulations would be plagued by a large problem size, numerical difficulties associated with stiff equations and multiple time scales, and the presence of integer decisions. In this dissertation, we address these challenges through hierarchical controller designs and novel scheduling (and rescheduling) formulations including low-order models of relevant system dynamics, which are identified through an appropriate model reduction or system identification procedure. Case studies involving the built environment and chemical processes are used to demonstrate the proposed methods. Advisors/Committee Members: Baldea, Michael (advisor), Edgar, Thomas F (committee member), Truskett, Thomas M (committee member), Bonnecaze, Roger T (committee member), Novpselac, Atila (committee member).

Subjects/Keywords: Optimization; Control

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APA (6^th Edition):

-9912-2897. (2016). Embedding dynamics and control considerations in operational optimization of process and energy systems. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/39556

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16^th Edition):

-9912-2897. “Embedding dynamics and control considerations in operational optimization of process and energy systems.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/39556.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

-9912-2897. “Embedding dynamics and control considerations in operational optimization of process and energy systems.” 2016. Web. 05 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-9912-2897. Embedding dynamics and control considerations in operational optimization of process and energy systems. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/39556.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-9912-2897. Embedding dynamics and control considerations in operational optimization of process and energy systems. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/39556

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

University of Texas – Austin

17. Duribe, Victor Chijioke. Capacitance resistance modeling for improved characterization in waterflooding and thermal recovery projects.

Degree: PhD, Chemical engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/45711

► Rates are typically one of the most measured in an oil recovery project. The abundance of these types of data is explained partly by their… (more)

▼ Rates are typically one of the most measured in an oil recovery project. The abundance of these types of data is explained partly by their relative ease of collection. Additionally, their collection and reporting is often required for logistical as well as financial purposes. Numerous researchers have shown the potency of using these data for characterization and management of oil reservoirs under primary or secondary recovery. Reduced-order models typically use these measurements as input to characterize reservoirs. The capacitance resistance model (CRM) is one such reduced order modeling method. This model uses well rates (and bottomhole pressure data, if available) to characterize a reservoir in a cheap and fast way. In characterizing an oil reservoir, the CRM and its linear counterpart (the Integrated Capacitance Resistance Model or ICRM) use historical data available at the wells to infer connectivity and flow paths between these wells through a set of model parameters. This use of readily available data, enabled by the speed of these models, creates a powerful tool that can be used as an alternative or as a complement to more expensive and time consuming traditional reservoir management tools. The CRM was initially developed for secondary recovery (i.e., water-flooding) but has been shown to work very well for primary recovery and many enhanced oil recovery (EOR) processes. The increasing industry acceptance of this modeling method is because of the work researchers who have contributed in expanding the capabilities of this modeling approach. However, key questions such as the impact of noise of CRM and ICRM performance remain. Additionally, a rigorous way of designing injection rates (a key input into the CRM model) such that parameter estimation is optimal has not been addressed. Finally, ideas about the applicability of the CRM modeling method to thermal EOR processes has not been explored. This research aims to address these questions. By addressing these questions, this work aims to contribute towards deepening current under-standing of the CRM modeling method and to opening new avenues for its application and research. Advisors/Committee Members: Edgar, Thomas F. (advisor), Lake, Larry W. (advisor), Sanchez, Isaac C (committee member), Baldea, Michael (committee member), Lasdon, Leon S (committee member).

Subjects/Keywords: Capacitance resistance model; CRM; ICRM; Water flooding; Hot water floods

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APA (6^th Edition):

Duribe, V. C. (2016). Capacitance resistance modeling for improved characterization in waterflooding and thermal recovery projects. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/45711

Chicago Manual of Style (16^th Edition):

Duribe, Victor Chijioke. “Capacitance resistance modeling for improved characterization in waterflooding and thermal recovery projects.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/45711.

MLA Handbook (7^th Edition):

Duribe, Victor Chijioke. “Capacitance resistance modeling for improved characterization in waterflooding and thermal recovery projects.” 2016. Web. 05 Mar 2021.

Vancouver:

Duribe VC. Capacitance resistance modeling for improved characterization in waterflooding and thermal recovery projects. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/45711.

Council of Science Editors:

Duribe VC. Capacitance resistance modeling for improved characterization in waterflooding and thermal recovery projects. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/45711

University of Texas – Austin

18. Sachde, Darshan Jitendra. Absorber performance and configurations for CO2 capture using aqueous piperazine.

Degree: PhD, Chemical engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/39631

► Absorber design for CO2 capture with amine solvents is complicated by the presence of temperature gradients and multiple rate controlling mechanisms (chemical reaction and convective… (more)

▼ Absorber design for CO2 capture with amine solvents is complicated by the presence of temperature gradients and multiple rate controlling mechanisms (chemical reaction and convective mass transfer). The development of rigorous rate-based models has created the opportunity to study the performance limiting mechanisms in detail. A structured approach was developed to validate absorber models, identify limiting phenomena, and develop configurations that specifically address limiting mechanisms. A rate-based model utilizing concentrated aqueous piperazine (PZ) was the focus of model validation and process development. The model was validated using pilot plant data, matching the number of transfer units (NTU) within + 1% while identifying a systematic bias (loading measurement) between the model and pilot plant data. The validated model was used to define limiting cases (isothermal and adiabatic absorbers) to study the effects of operating conditions on the formation of temperature-induced mass transfer pinches. The method allowed for screening of intercooling benefits – high CO2 applications (15% - 27% CO2) require intercooling over the entire practical loading range for PZ and benefit significantly from simple in-and-out intercooling with limited additional benefit expected from advanced design. Low CO2 (4% CO2) applications are expected to benefit the most from improved intercooling, but also have the largest operating window without the need for intercooling (< 0.22 mol CO2/mol alkalinity for 8 m PZ). An analogous approach was developed to study rate mechanisms. A mass transfer parameter sensitivity analysis approach was developed to identify the relative contribution to overall mass transfer resistance of each mechanism as a function of operating conditions and position in the absorber column. The pseudo-first order and instantaneous reaction asymptotic solutions to the reaction-diffusion problem were used to define a dimensionless parameter that quantifies the approach of the modeling results to the limiting conditions and was found to be predictive of the relative liquid film resistance (diffusion vs. reaction) at all conditions. The results of the analysis indicated that the absorber is strongly diffusion controlled, has limited gas-film resistance, and that equilibrium constraints at the rich end of the absorber (depletion of free amine) significantly increase diffusion limitations. Finally, the validation and mechanistic studies provided the basis for four new absorber configurations: 1) integration of a spray nozzle in the intercooling loop, 2) solvent recycle intercooling, 3) integrated flue gas and solvent cooling functions, 4) hybrid intercooling (high intensity contacting with intercooling). Each approach coupled mass transfer enhancement with intercooling and provided new degrees of freedom for operation and design of absorbers for CO2 capture. Advisors/Committee Members: Rochelle, Gary T. (advisor), Baldea, Michael (committee member), Bhown, Abhoyjit (committee member), Chen, Eric (committee member), Hwang, Gyeong (committee member).

Subjects/Keywords: CO2 capture; Piperazine; Absorber; Amine scrubbing; Mass transfer; Intercooling

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APA (6^th Edition):

Sachde, D. J. (2016). Absorber performance and configurations for CO2 capture using aqueous piperazine. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/39631

Chicago Manual of Style (16^th Edition):

Sachde, Darshan Jitendra. “Absorber performance and configurations for CO2 capture using aqueous piperazine.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/39631.

MLA Handbook (7^th Edition):

Sachde, Darshan Jitendra. “Absorber performance and configurations for CO2 capture using aqueous piperazine.” 2016. Web. 05 Mar 2021.

Vancouver:

Sachde DJ. Absorber performance and configurations for CO2 capture using aqueous piperazine. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/39631.

Council of Science Editors:

Sachde DJ. Absorber performance and configurations for CO2 capture using aqueous piperazine. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/39631

University of Texas – Austin

19. Sowa, Steven William. Development of new strategies to map and regulate large RNA regulatory networks.

Degree: PhD, Microbiology, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/72689

► Global regulators are critical controllers of cellular function. They possess the ability to coordinate multiple cellular pathways simultaneously to orchestrate a unified response to environmental… (more)

▼ Global regulators are critical controllers of cellular function. They possess the ability to coordinate multiple cellular pathways simultaneously to orchestrate a unified response to environmental change. Recent research has demonstrated that both proteins and RNAs can function in key regulatory roles and each provides unique advantages in their control characteristics. Given the power of these regulators, there is strong interest in utilizing regulatory systems in a variety of metabolic engineering applications including coordination of metabolic pathways and as dynamic pathway controllers. However, the potential to utilize these systems to produce dynamic and coordinated metabolic responses is only beginning to be realized. My dissertation focuses on characterizing global regulatory systems and specifically small RNA (sRNA) based regulatory systems for their use as dynamic global controllers for metabolic engineering. Chapter 2 starts by discussing a computational analysis of how a group of genes dynamically controlled by a single regulator can produce higher metabolite levels over time. This Chapter demonstrates dynamic control as an underutilized strategy to improve metabolite production. Chapter 3 evaluates how to characterize large regulatory systems using the E. coli Carbon Storage Regulator as a case study. It interweaves multiple lines of omics evidence and follow up experiments to determine the regulatory targets of the Csr system. Using these data, we constructed a thermodynamic model to predict if CsrA will cause repression of cellular genes (Chapter 4). The work in these chapters represents a new way of thinking about sRNA regulators and their role in metabolic engineering and has broad applicability to other Protein-RNA regulators and other regulatory elements. Advisors/Committee Members: Contreras, Lydia M. (advisor), Baldea, Michael (advisor), Barrick, Jeffrey (committee member), Iyer, Vishwanath (committee member), Harshey, Rasika (committee member).

Subjects/Keywords: Csr; Metabolic engineering; Global regulator; Microbiology; Optimization; Thermodynamic modeling; sRNA

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Sowa, S. W. (2016). Development of new strategies to map and regulate large RNA regulatory networks. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/72689

Chicago Manual of Style (16^th Edition):

Sowa, Steven William. “Development of new strategies to map and regulate large RNA regulatory networks.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/72689.

MLA Handbook (7^th Edition):

Sowa, Steven William. “Development of new strategies to map and regulate large RNA regulatory networks.” 2016. Web. 05 Mar 2021.

Vancouver:

Sowa SW. Development of new strategies to map and regulate large RNA regulatory networks. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/72689.

Council of Science Editors:

Sowa SW. Development of new strategies to map and regulate large RNA regulatory networks. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/72689

University of Texas – Austin

20. -9524-1741. Addressing uncertainty and modeling error in the design and control of process systems : methods and applications.

Degree: PhD, Chemical engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/41993

► A process system faces the challenge of uncertainty throughout its lifetime. At the design stage, uncertainty originates from inaccurate knowledge of design parameters and unmeasured… (more)

▼ A process system faces the challenge of uncertainty throughout its lifetime. At the design stage, uncertainty originates from inaccurate knowledge of design parameters and unmeasured or unmeasurable ambient disturbances. Oftentimes, designers choose to increase system size to account for uncertainty and fluctuations; however, this approach has an economic limit, past which the capital expenditure outweighs the potential operational benefits. In the operational stage, uncertainty is manifest, amongst others, in fluctuations in operating conditions, market demand and raw material availability. Another type of uncertainty in (modern) process operations is related to the quality of process models that are used for making control and operational decisions. Of particular importance is the quality of the dynamic models that are used in real-time optimal control computations. The chemical industry has been the pioneer (and is currently the leader) of model predictive control (MPC) implementations, whereby the control moves are computed, over a receding time horizon, by solving an optimal control problem at each time step. While uniquely able to deal with large-scale, non-square constrained systems, MPC is vitally dependent on the predictive abilities of the built-in model. Changes in plant conditions are a a source of uncertainty in this case as-well, leading to a discrepancy (mismatch) between the model predictions and the true plant behavior. In this dissertation, I address the problems of design under uncertainty and plant-model mismatch. For the former, identification-based optimization (IBO) framework is proposed as a new, computationally efficient framework for optimizing the design of dynamic systems under uncertainty problem. The framework uses properly designed pseudo-random multilevel signals (PRMS) to represent time-varying uncertain variables. This allows us to formulate the design under uncertainty problem as a dynamic optimization problem. A solution algorithm is proposed using a sequential approach. Several application examples are discussed, demonstrating the superior computational performance of the IBO approach. Furthermore, an extension of the method that explicitly considers the tradeoff between conservativeness and dynamic performance is introduced. The latter, plant-model mismatch problem, is addressed using a novel autocovariance-based approach. Under appropriate assumptions, an explicit relation is established between the autocovariance of the process output and the plant-model mismatch terms, represented either in a step response model or a transfer function model. It is demonstrated that an asymptotically correct set of estimates of the values of plant-model mismatch for each model parameters is the global minimizer of the discrepancy between the autocovariance predicted using the relation and the autocovariance calculated from a data set collected from closed-loop operating data. Extensions of this approach handle cases where the active set of the MPC is changing over time and there are setpoint… Advisors/Committee Members: Baldea, Michael (advisor), Edgar, Thomas F. (committee member), Rochelle, Gary T. (committee member), Truskett, Thomas M. (committee member), Biros, George (committee member).

Subjects/Keywords: Uncertainty; MPC; Modeling error; Control of process systems; Applications; Methods

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APA (6^th Edition):

-9524-1741. (2016). Addressing uncertainty and modeling error in the design and control of process systems : methods and applications. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/41993

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16^th Edition):

-9524-1741. “Addressing uncertainty and modeling error in the design and control of process systems : methods and applications.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/41993.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

-9524-1741. “Addressing uncertainty and modeling error in the design and control of process systems : methods and applications.” 2016. Web. 05 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-9524-1741. Addressing uncertainty and modeling error in the design and control of process systems : methods and applications. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/41993.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-9524-1741. Addressing uncertainty and modeling error in the design and control of process systems : methods and applications. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/41993

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

University of Texas – Austin

21. Hale, Renee. Enhancing the cooling capacity of heat pipes : wicking in micropillar arrays and electrowetting-based droplet pumping.

Degree: PhD, Chemical Engineering, 2018, University of Texas – Austin

URL: http://hdl.handle.net/2152/71457

► Thermal management is an important consideration for many technologies, ranging from electronic devices to solar thermal energy. Heat pipes transfer heat by cyclically evaporating and… (more)

▼ Thermal management is an important consideration for many technologies, ranging from electronic devices to solar thermal energy. Heat pipes transfer heat by cyclically evaporating and condensing a working fluid, and their main benefits are high thermal conductance and little to no power consumption. In a standard heat pipe, an internal wicking structure utilizes capillary action to drive fluid circulation. Heat transfer capacity is limited by the maximum fluid velocity the wick can sustain, among other factors. Because viscous pressure losses increase with distance, the maximum heat transfer capacity of a heat pipe decreases over extended distances. This work explores two ways to increase the maximum cooling capacity of heat pipes: first, by designing an alternative wicking geometry, and second, by removing the wick entirely and replacing it with electrowetting-based droplet pumping technology. The capillary limit is largely determined by the permeability and driving capillary pressure of the wick. These two factors typically depend on the same geometric parameter, such that the two are inseparable and inversely related. Micropillar arrays are wicking materials where the distances between pillars are independent and variable, which could lead to a decoupled capillary pressure and permeability. The first half of this dissertation work designs, optimizes, manufactures, and tests micropillar wicks for use in a heat pipe. To accomplish this, an analytical model for fluid flow through a micropillar array with independent x- and y- dimensions is developed, enabling the exploration of non-symmetrical pillar arrangements. For pillar dimensions outside of the range of the analytical model, numerical simulations are employed. Using these models, the dimensions of pillar arrays are optimized for maximum fluid flow rate. The findings indicate that arrays where the pillars are arranged in a rectangular pattern exhibit the ability to maintain high capillary pressures even at high porosities, which increases the overall cooling capacity above square arrays by 1.5x in the absence of gravity and 5x – 7x in the presence of gravity. To verify the maximum fluid velocities predicted by modeling, a range of pillar configurations are manufactured and tested. However, conclusions about the fluid velocity are obscured because atmospheric conditions of the experimental apparatus allow the boiling limit to occur before the capillary limit. Electrowetting is a microfluidic pumping technique which operates by applying a voltage across a liquid droplet to change the surface energy balance of the liquid/solid interface. If several electrodes are placed in succession, a discrete droplet can be pulled along a surface. Replacing the internal wick of a heat pipe with an electrowetting system reduces the viscous pressure losses of a long pipe, potentially revolutionizing heat transfer over long distances. The second half of this dissertation work explores the feasibility of replacing the internal wick in a heat pipe with electrowetting-based droplet… Advisors/Committee Members: Bonnecaze, R. T. (Roger T.) (advisor), Hidrovo, Carlos (advisor), Bahadur, Vaibhav (advisor), Sharma, Mukul (committee member), Bogard, David (committee member), Baldea, Michael (committee member).

Subjects/Keywords: Heat pipe; Micropillar; Electrowetting

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APA (6^th Edition):

Hale, R. (2018). Enhancing the cooling capacity of heat pipes : wicking in micropillar arrays and electrowetting-based droplet pumping. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/71457

Chicago Manual of Style (16^th Edition):

Hale, Renee. “Enhancing the cooling capacity of heat pipes : wicking in micropillar arrays and electrowetting-based droplet pumping.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/71457.

MLA Handbook (7^th Edition):

Hale, Renee. “Enhancing the cooling capacity of heat pipes : wicking in micropillar arrays and electrowetting-based droplet pumping.” 2018. Web. 05 Mar 2021.

Vancouver:

Hale R. Enhancing the cooling capacity of heat pipes : wicking in micropillar arrays and electrowetting-based droplet pumping. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/71457.

Council of Science Editors:

Hale R. Enhancing the cooling capacity of heat pipes : wicking in micropillar arrays and electrowetting-based droplet pumping. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/71457

University of Texas – Austin

22. Elhag, Amro Salah. Selection of switchable amine surfactants for stable CO2 – in – water foams for high temperature CO2 mobility control: Selection of switchable amine surfactants for stable carbon dioxide – in – water foams for high temperature carbon dioxide mobility control.

Degree: PhD, Chemical engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/43724

► The generation of stable carbon dioxide-in-water (C/W) foams at high temperatures is hindered by lack of surfactant solubility in the aqueous phase and acceleration in… (more)

Subjects/Keywords: CO2 in water foams; High temperature; Switchable surfactant; Amine surfactant; Wormlike micelles; Viscoelastic lamellae

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Elhag, A. S. (2016). Selection of switchable amine surfactants for stable CO2 – in – water foams for high temperature CO2 mobility control: Selection of switchable amine surfactants for stable carbon dioxide – in – water foams for high temperature carbon dioxide mobility control. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/43724

Chicago Manual of Style (16^th Edition):

Elhag, Amro Salah. “Selection of switchable amine surfactants for stable CO2 – in – water foams for high temperature CO2 mobility control: Selection of switchable amine surfactants for stable carbon dioxide – in – water foams for high temperature carbon dioxide mobility control.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/43724.

MLA Handbook (7^th Edition):

Elhag, Amro Salah. “Selection of switchable amine surfactants for stable CO2 – in – water foams for high temperature CO2 mobility control: Selection of switchable amine surfactants for stable carbon dioxide – in – water foams for high temperature carbon dioxide mobility control.” 2016. Web. 05 Mar 2021.

Vancouver:

Elhag AS. Selection of switchable amine surfactants for stable CO2 – in – water foams for high temperature CO2 mobility control: Selection of switchable amine surfactants for stable carbon dioxide – in – water foams for high temperature carbon dioxide mobility control. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/43724.

Council of Science Editors:

Elhag AS. Selection of switchable amine surfactants for stable CO2 – in – water foams for high temperature CO2 mobility control: Selection of switchable amine surfactants for stable carbon dioxide – in – water foams for high temperature carbon dioxide mobility control. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/43724

University of Texas – Austin

23. Roach, Bailee Jeanee. A design model for dividing wall distillation columns.

Degree: PhD, Chemical Engineering, 2017, University of Texas – Austin

URL: http://hdl.handle.net/2152/61965

► Traditionally, the production of three high purity products from a three component mixture requires the use of two distillation columns. A Dividing Wall Column (DWC)… (more)

▼ Traditionally, the production of three high purity products from a three component mixture requires the use of two distillation columns. A Dividing Wall Column (DWC) offers an alternative to this approach. The DWC contains a vertical partition, dividing the column into two sides. The feed side separates the lowest and highest boiling products, while the product side separates the intermediate component. This configuration reduces capital costs by utilizing only one column, reboiler, and condenser and reduces the thermodynamic losses by partitioning the feed and side product. Previous theoretical studies have found that a DWC can also produce as high as 30-50 percent energy savings over a traditional multi-column scheme. Despite these advantages, validated predictive models, which will facilitate widespread adoption of the technology, are lacking. In this research, experimental results were obtained over a wide range of operating conditions using a constructed six inch diameter pilot plant data is used to develop a fully validated DWC. The pilot DWC ran several experimental tests with both an alcohol and hydrocarbon feed. Both systems were tested with an equimolar and a 10/80/10 feed composition. Internal flow rate and composition data were available that has not been published in research, allowing for a complete model validation, including heat loss and heat transfer across the dividing wall. Both Model Predictive Control and traditional PID control was tested and resulted in high quality steady state data obtained. An extensive hydraulic study was conducted for both structured and random packing. Mass transfer studies and air-water experiments were conducted to fundamentally characterize the column hydraulics. These studies included confirming the vapor split is determined by the wall location and not impacted by the pressure drop. Pressure drop and wetted area studies were performed on circular and dividing wall column structures. The dry pressure drop, irrigated pressure drop, and hold-up were compared with existing correlations. Additionally, the dividing wall wetted area was determined. A DWC model was validated with the experimental pilot data obtained as well as comparing with open literature data. With the results from the validated model, optimizations were conducted to aid in DWC design. It was shown that feed temperature is an important variable to consider in design. The vapor split did not have as much of an impact on energy savings as the liquid split. An accurate energy calculation was performed on a pilot scale column and a scale-up to industrial column diameters. The scale-up shows that the impacts from heat loss and heat transfer are not as significant in a large scale column for product purities and column liquid and vapor loads. DWC columns averaged approximately 30% energy savings. The comprehensive validated model lays the groundwork for DWC industrial expansion. Advisors/Committee Members: Baldea, Michael (advisor), Eldridge, R. Bruce (advisor), Seibert, Albert F (committee member), Bonnecaze, Roger T (committee member), Rochelle, Gary T (committee member), Owens, Scott A (committee member).

Subjects/Keywords: Dividing wall distillation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Roach, B. J. (2017). A design model for dividing wall distillation columns. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/61965

Chicago Manual of Style (16^th Edition):

Roach, Bailee Jeanee. “A design model for dividing wall distillation columns.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/61965.

MLA Handbook (7^th Edition):

Roach, Bailee Jeanee. “A design model for dividing wall distillation columns.” 2017. Web. 05 Mar 2021.

Vancouver:

Roach BJ. A design model for dividing wall distillation columns. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/61965.

Council of Science Editors:

Roach BJ. A design model for dividing wall distillation columns. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/61965

University of Texas – Austin

24. Xu, Ph. D., Shu. Data cleaning and knowledge discovery in process data.

Degree: PhD, Chemical engineering, 2015, University of Texas – Austin

URL: http://hdl.handle.net/2152/32920

► This dissertation presents several methods for overcoming the Big Data challenges, with an emphasis on data cleaning and knowledge discovery in process data. Data cleaning… (more)

▼ This dissertation presents several methods for overcoming the Big Data challenges, with an emphasis on data cleaning and knowledge discovery in process data. Data cleaning and knowledge discovery is chosen as a main research area here due to its importance from both theoretical and practical points of view. Theoretical background and recent developments of data cleaning methods are reviewed from four aspects: missing data imputation, outlier detection, noise removal and time delay estimation. Moreover, the impact of contaminated data on model performance and corresponding improvement obtained by data cleaning methods are analyzed through both simulated and industrial case studies. The results provide a starting point for further advanced methodology development. It is hard to find a universally applicable method for data cleaning since every data set may have its own distinctive features. Thus, we have to customize available methods so that the quality of the data set is guaranteed. An integrated data cleaning scheme is proposed, which incorporates model building and performance evaluation, to provide guidance in tuning the parameters of data cleaning methods and prevent over-cleaning. A case study based on industrial data has been used to verify the feasibility and effectiveness of the proposed new method, during which a partial least squares (PLS) model was built and three univariate data cleaning procedures is tested. A time series Kalman filter (TSKF) is proposed that successfully handles outlier detection in dynamic systems, where normal process changes often mask the existence of outliers. The TSKF method combines a time series model fitting procedure with a modified Kalman filter to deal with additive outlier (AO) and innovational outlier (IO) detection problems in dynamic process data set. A comparative analysis of TSKF and available methods is performed on simulated and real chemical plant data. Root cause diagnosis of plant-wide oscillations, as a concrete example of data cleaning and knowledge discovery in the process data, is provided. Plant-wide oscillations can negatively influence the overall control performance of the process and the detection results are often affected by noise at different frequency ranges. To address such a problem, an information transfer method combining spectral envelope algorithm with spectral transfer entropy is proposed to detect and diagnose such oscillations within a specific frequency range, mitigating the effects from measurement noise. The feasibility and effectiveness of the proposed method are verified and compared with available methods through both simulated and industrial case studies. Advisors/Committee Members: Edgar, Thomas F. (advisor), Wojsznis, Willy (committee member), Djurdjanovic, Dragan (committee member), Rochelle, Gary T. (committee member), Baldea, Michael (committee member), Daniels, Michael J. (committee member).

Subjects/Keywords: Data cleaning; Knowledge discovery

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APA (6^th Edition):

Xu, Ph. D., S. (2015). Data cleaning and knowledge discovery in process data. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32920

Chicago Manual of Style (16^th Edition):

Xu, Ph. D., Shu. “Data cleaning and knowledge discovery in process data.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/32920.

MLA Handbook (7^th Edition):

Xu, Ph. D., Shu. “Data cleaning and knowledge discovery in process data.” 2015. Web. 05 Mar 2021.

Vancouver:

Xu, Ph. D. S. Data cleaning and knowledge discovery in process data. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/32920.

Council of Science Editors:

Xu, Ph. D. S. Data cleaning and knowledge discovery in process data. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32920

25. Wang, Ray Chen. Visualization of multivariate process data for fault detection and diagnosis.

Degree: MSin Engineering, Chemical Engineering, 2014, University of Texas – Austin

URL: http://hdl.handle.net/2152/26246

► This report introduces the concept of three-dimensional (3D) radial plots for the visualization of multivariate large scale datasets in plant operations. A key concept of… (more)

Subjects/Keywords: Visualization; Big data; Fault detection

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APA (6^th Edition):

Wang, R. C. (2014). Visualization of multivariate process data for fault detection and diagnosis. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/26246

Chicago Manual of Style (16^th Edition):

Wang, Ray Chen. “Visualization of multivariate process data for fault detection and diagnosis.” 2014. Masters Thesis, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/26246.

MLA Handbook (7^th Edition):

Wang, Ray Chen. “Visualization of multivariate process data for fault detection and diagnosis.” 2014. Web. 05 Mar 2021.

Vancouver:

Wang RC. Visualization of multivariate process data for fault detection and diagnosis. [Internet] [Masters thesis]. University of Texas – Austin; 2014. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/26246.

Council of Science Editors:

Wang RC. Visualization of multivariate process data for fault detection and diagnosis. [Masters Thesis]. University of Texas – Austin; 2014. Available from: http://hdl.handle.net/2152/26246

26. -7708-2444. Modeling methods of a rotary hearth forging furnace.

Degree: MSin Engineering, Mechanical Engineering, 2018, University of Texas – Austin

URL: http://hdl.handle.net/2152/64123

► A series of single-physics heat and mass transfer models of a rotary hearth forging furnace are studied for design, selection, and implementation into a multi-physics… (more)

Subjects/Keywords: Heat transfer; Industrial furnace; System modeling; Radiative heat transfer

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APA (6^th Edition):

-7708-2444. (2018). Modeling methods of a rotary hearth forging furnace. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/64123

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16^th Edition):

-7708-2444. “Modeling methods of a rotary hearth forging furnace.” 2018. Masters Thesis, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/64123.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

-7708-2444. “Modeling methods of a rotary hearth forging furnace.” 2018. Web. 05 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-7708-2444. Modeling methods of a rotary hearth forging furnace. [Internet] [Masters thesis]. University of Texas – Austin; 2018. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/64123.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-7708-2444. Modeling methods of a rotary hearth forging furnace. [Masters Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/64123

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

27. -6298-5138. Controlling trace impurities in a dividing wall distillation column.

Degree: PhD, Chemical Engineering, 2019, University of Texas – Austin

URL: http://dx.doi.org/10.26153/tsw/2788

► Dividing wall distillation columns (DWCs) separate a feed mixture into three pure product streams using one column shell. Though attractive due to capital and operational… (more)

▼ Dividing wall distillation columns (DWCs) separate a feed mixture into three pure product streams using one column shell. Though attractive due to capital and operational savings, DWCs have yet to gain widespread industrial acceptance. One notable concern is controllability. The research within this document examines a four component feed mixture to evaluate the operational flexibility of a fixed-design DWC through experimental and simulation-based studies. A pilot DWC was successfully controlled at multiple operating points, and a dynamic model was developed to reflect the pilot dividing wall column. As a form of process intensification, DWCs have a higher risk for controller interaction making conventional PID control potentially inadequate. This work successfully used two PID temperature controllers to maintain the column at steady state, transition the column between steady states, and reject feed disturbances without controller interaction. These controller pairings were determined using conventional controller design techniques. Therefore, for this chemical system and column design, traditional approaches to distillation control are sufficient to handle the intensified nature of DWCs. Because more components are present in DWCs in larger amounts, there is concern that temperature control will no longer imply composition control. Temperature control proved successful in this study. Controlling two temperatures maintained column operation against feed disturbances. In addition, prefractionator temperature correlated well with reboiler duty for multiple feed qualities therefore serving as a promising control variable though more disturbances such as feed composition should be examined. The minimum energy controller was not tested experimentally. A steady state model with heat transfer matching the pilot data was scaled to the size of an industrial tower and used to generate a minimum energy response surface for different vapor and liquid split values. In summary, this research investigated the operational flexibility of a fixed-design DWC using a four component mixture, tested the ability of conventional distillation control design techniques to determine control structures for a DWC, and created a minimum energy operating surface that could be used to examine control structures. A technique to determine the overall heat transfer coefficients was developed, and the model closely matched experimental steady state data. Advisors/Committee Members: Baldea, Michael (advisor), Eldridge, R. Bruce (advisor), Downs, Jim J (committee member), Edgar, Thomas (committee member), Rochelle, Gary (committee member).

Subjects/Keywords: Distillation; Control

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APA (6^th Edition):

-6298-5138. (2019). Controlling trace impurities in a dividing wall distillation column. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/2788

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16^th Edition):

-6298-5138. “Controlling trace impurities in a dividing wall distillation column.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://dx.doi.org/10.26153/tsw/2788.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

-6298-5138. “Controlling trace impurities in a dividing wall distillation column.” 2019. Web. 05 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-6298-5138. Controlling trace impurities in a dividing wall distillation column. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2021 Mar 05]. Available from: http://dx.doi.org/10.26153/tsw/2788.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-6298-5138. Controlling trace impurities in a dividing wall distillation column. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/2788

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

28. -5100-5600. Improving process monitoring and modeling of batch-type plasma etching tools.

Degree: PhD, Chemical Engineering, 2015, University of Texas – Austin

URL: http://hdl.handle.net/2152/30486

► Manufacturing equipments in semiconductor factories (fabs) provide abundant data and opportunities for data-driven process monitoring and modeling. In particular, virtual metrology (VM) is an active… (more)

▼ Manufacturing equipments in semiconductor factories (fabs) provide abundant data and opportunities for data-driven process monitoring and modeling. In particular, virtual metrology (VM) is an active area of research. Traditional monitoring techniques using univariate statistical process control charts do not provide immediate feedback to quality excursions, hindering the implementation of fab-wide advanced process control initiatives. VM models or inferential sensors aim to bridge this gap by predicting of quality measurements instantaneously using tool fault detection and classification (FDC) sensor measurements. The existing research in the field of inferential sensor and VM has focused on comparing regressions algorithms to demonstrate their feasibility in various applications. However, two important areas, data pretreatment and post-deployment model maintenance, are usually neglected in these discussions. Since it is well known that the industrial data collected is of poor quality, and that the semiconductor processes undergo drifts and periodic disturbances, these two issues are the roadblocks in furthering the adoption of inferential sensors and VM models. In data pretreatment, batch data collected from FDC systems usually contain inconsistent trajectories of various durations. Most analysis techniques requires the data from all batches to be of same duration with similar trajectory patterns. These inconsistencies, if unresolved, will propagate into the developed model and cause challenges in interpreting the modeling results and degrade model performance. To address this issue, a Constrained selective Derivative Dynamic Time Warping (CsDTW) method was developed to perform automatic alignment of trajectories. CsDTW is designed to preserve the key features that characterizes each batch and can be solved efficiently in polynomial time. Variable selection after trajectory alignment is another topic that requires improvement. To this end, the proposed Moving Window Variable Importance in Projection (MW-VIP) method yields a more robust set of variables with demonstrably more long-term correlation with the predicted output. In model maintenance, model adaptation has been the standard solution for dealing with drifting processes. However, most case studies have already preprocessed the model update data offline. This is an implicit assumption that the adaptation data is free of faults and outliers, which is often not true for practical implementations. To this end, a moving window scheme using Total Projection to Latent Structure (T-PLS) decomposition screens incoming updates to separate the harmless process noise from the outliers that negatively affects the model. The integrated approach was demonstrated to be more robust. In addition, model adaptation is very inefficient when there are multiplicities in the process, multiplicities could occur due to process nonlinearity, switches in product grade, or different operating conditions. A growing structure multiple model system using local PLS and PCA models have been… Advisors/Committee Members: Edgar, Thomas F. (advisor), Stuber, John D (committee member), Djurdjanovic, Dragan (committee member), Ekerdt, John G (committee member), Bonnecaze, Roger T (committee member), Baldea, Michael (committee member).

Subjects/Keywords: PLS; Fault detection; Soft sensor; Inferential sensor; Virtual metrology; Variable selection; Time warping; Multiple model systems; PCA; Partial least squares; Etching; Semiconductor; Control; Data-driven; Multivariate; Machine learning

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APA (6^th Edition):

-5100-5600. (2015). Improving process monitoring and modeling of batch-type plasma etching tools. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/30486

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16^th Edition):

-5100-5600. “Improving process monitoring and modeling of batch-type plasma etching tools.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/30486.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

-5100-5600. “Improving process monitoring and modeling of batch-type plasma etching tools.” 2015. Web. 05 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-5100-5600. Improving process monitoring and modeling of batch-type plasma etching tools. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/30486.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-5100-5600. Improving process monitoring and modeling of batch-type plasma etching tools. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/30486

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

29. Lin, Yu-Jeng. Modeling advanced flash stripper for carbon dioxide capture using aqueous amines.

Degree: PhD, Chemical engineering, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/41988

► The intensive energy use is the major obstacle to deployment of CO2 capture. Alternative stripper configurations is one of the most promising ways to reduce… (more)

▼ The intensive energy use is the major obstacle to deployment of CO2 capture. Alternative stripper configurations is one of the most promising ways to reduce the energy consumption of CO2 regeneration and compression. The advanced flash stripper (AFS) proposed in this work provides the best energy performance among other alternatives. A systematic irreversibility analysis was performed instead of examining all the possible alternatives. The overhead condenser and the cross exchanger were identified the major sources of lost work that causes process inefficiencies. The AFS reduces the reboiler duty by 16% and the total equivalent work by 11% compared to the simple stripper using aqueous piperazine. The AFS was demonstrated in a 0.2 MW equivalent pilot plant and showed over 25% of heat duty reduction compared to previous campaigns, achieving 2.1 GJ/tonne CO2 of heat duty and 32 kJ/mol CO2 of total equivalent work. The proposed bypass control strategy was successfully demonstrated and minimized the reboiler duty. Approximate stripper models (ASM) were developed to generalize the effect of solvent properties on energy performance and guide solvent selections. High heat of absorption can increase partial pressure of CO2 at elevated temperature and has potential to reduce compression work and stripping steam heat. The optimum heat of absorption was quantified as 70–125 kJ/mol CO2 at various conditions, which is generally higher than existing amines with 60–80 kJ/mol. The energy performance of AFS is not sensitive to the heat of absorption. A techno-economic analysis with process optimization that minimizes the annualized regeneration cost was performed to demonstrate the profitability of the AFS. The AFS reduces the annualized regeneration cost by 13% and the major savings come from the reduction of the OPEX, which counts for over 70% of the regeneration cost. The compressor and the cross exchanger are the major components of the CAPEX. The optimum lean loading is around 0.22 mol CO2/mol alkalinity for PZ but is flat between 0.18 and 0.24 with less than 1% difference. The AFS was demonstrated as a flexible system that can be applied to a wide range of solvent properties and operating conditions while still maintaining remarkable energy performance. Further improvement of energy efficiency by process modifications is expected to be marginal. Increasing solvent capacity will give the most energy and cost reduction in the future. Advisors/Committee Members: Rochelle, Gary T. (advisor), Baldea, Michael (committee member), Chen, Eric (committee member), Hwang, Gyeong S. (committee member), Miller, David (committee member).

Subjects/Keywords: Amine scrubbing; Alternative stripper; CO2 capture; Aspen plus; Process design

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APA (6^th Edition):

Lin, Y. (2016). Modeling advanced flash stripper for carbon dioxide capture using aqueous amines. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/41988

Chicago Manual of Style (16^th Edition):

Lin, Yu-Jeng. “Modeling advanced flash stripper for carbon dioxide capture using aqueous amines.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/41988.

MLA Handbook (7^th Edition):

Lin, Yu-Jeng. “Modeling advanced flash stripper for carbon dioxide capture using aqueous amines.” 2016. Web. 05 Mar 2021.

Vancouver:

Lin Y. Modeling advanced flash stripper for carbon dioxide capture using aqueous amines. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/41988.

Council of Science Editors:

Lin Y. Modeling advanced flash stripper for carbon dioxide capture using aqueous amines. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/41988

30. Alfadhli, Fahad Mohammed. Reducing environmental impacts of petroleum refining : a case study of industrial flaring.

Degree: PhD, Chemical Engineering, 2012, University of Texas – Austin

URL: http://hdl.handle.net/2152/ETD-UT-2012-08-5962

► Industrial flaring can have negative impacts on regional air quality and recent studies have shown that flares are often operated at low combustion efficiency, which… (more)

▼ Industrial flaring can have negative impacts on regional air quality and recent studies have shown that flares are often operated at low combustion efficiency, which exacerbates these air quality impacts. This thesis examines industrial flaring with the objectives of (1) assessing the air quality impacts of flares operating at a variety of conditions, (2) examining the extent to which improvements in flare operations could reduce emissions, (3) identifying opportunities for recycling flared gases in fuel gas networks, and (4) identifying opportunities for reducing the generation of flared gases, using the improved control of catalytic cracking operations as a case study. The work presented in this thesis demonstrates that flares operating at low combustion efficiency can increase localized ambient ozone concentrations by more than 15 ppb under some conditions. The impact of flares on air quality depends most strongly on combustion efficiency, the flow rates to the flares and the chemical composition (photochemical reactivity) of the emissions. Products of incomplete combustion and nitrogen oxides emissions from flaring generally had a smaller impact on air quality than unburned flare gases. The combustion efficiency at which a flare can operate can be constrained by the flare’s design. In a case study of an air-assisted flare, it was demonstrated that choices in blower configurations could lead to emissions that were orders of magnitude greater or less than those predicted using an assumed combustion efficiency of 98%. Designing flares with air-assist rates that can be finely tuned can significantly reduce emissions. Similarly, flaring can be reduced by integrating sources of waste gases into fuel gas networks. Analyses for a petroleum refinery indicated that this integration can often be accomplished with little net cost by expanding boiler capacities. Finally, flared gases can be reduced at their source. A case study of a fluid catalytic cracking indicated that using better temperature control could significantly minimize flared gases. Advisors/Committee Members: Allen, David T. (advisor), Edgar, Thomas F. (committee member), McDonald-Buller, Elena (committee member), Baldea, Michael (committee member), Torres, Vincent M. (committee member).

Subjects/Keywords: Low combustion efficiency; Industrial flares; Destruction removal efficiency

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APA (6^th Edition):

Alfadhli, F. M. (2012). Reducing environmental impacts of petroleum refining : a case study of industrial flaring. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-08-5962

Chicago Manual of Style (16^th Edition):

Alfadhli, Fahad Mohammed. “Reducing environmental impacts of petroleum refining : a case study of industrial flaring.” 2012. Doctoral Dissertation, University of Texas – Austin. Accessed March 05, 2021. http://hdl.handle.net/2152/ETD-UT-2012-08-5962.

MLA Handbook (7^th Edition):

Alfadhli, Fahad Mohammed. “Reducing environmental impacts of petroleum refining : a case study of industrial flaring.” 2012. Web. 05 Mar 2021.

Vancouver:

Alfadhli FM. Reducing environmental impacts of petroleum refining : a case study of industrial flaring. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2012. [cited 2021 Mar 05]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-08-5962.

Council of Science Editors:

Alfadhli FM. Reducing environmental impacts of petroleum refining : a case study of industrial flaring. [Doctoral Dissertation]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-08-5962

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