Indiana University-Purdue University Indianapolis (IUPUI)

Heating, ventilation and air conditioning systems (HVAC) are the single largest consumer of energy in commercial and residential sectors. Minimizing its energy consumption without compromising indoor air quality (IAQ) and thermal comfort would result in environmental and financial benefits. Currently, most buildings still utilize constant air volume (CAV) systems with on/off control to meet the thermal loads. Such systems, without any consideration of occupancy, may ventilate a zone excessively and result in energy waste. Previous studies showed that CO2-based demand-controlled ventilation (DCV) methods are the most widely used strategies to determine the optimal level of supply air volume. However, conventional CO2 mass balanced models do not yield an optimal estimation accuracy. In this study, feed-forward neural network algorithm (FFNN) was proposed to estimate the zone occupancy using CO2 concentrations, observed occupancy data and the zone schedule. The occupancy prediction result was then utilized to optimize supply fan operation of the air handling unit (AHU) associated with the zone. IAQ and thermal comfort standards were also taken into consideration as the active constraints of this optimization. As for the validation, the experiment was carried out in an auditorium located on a university campus. The results revealed that utilizing neural network occupancy estimation model can reduce the daily ventilation energy by 74.2% when compared to the current on/off control.

Indiana University-Purdue University Indianapolis (IUPUI)

The following thesis looks into modeling a chilled water system equipped with variable speed drives on different piece of equipment and optimization of system setpoints to achieve energy savings. The research was done by collecting data from a case-study and developing a system of component models that could be linked to simulate the overall system operation.

Indiana University-Purdue University Indianapolis (IUPUI)

The Air Handling Unit (AHU), which serves the entire basement of Engineering and Technology (ET) building on IUPUI campus, had constant set points of discharge air temperature and supply air static pressure. Two reset schedules were investigated to determine which was the best control strategy to minimize energy consumption of the AHU. In this research, a gray box model was established to create the baseline of energy consumption with constant set points and predict the energy savings using two di↵erent reset schedules. The mathematical model was developed in Engineering Equation Solver (EES). It was validated using two sets of sub hourly real time data. The model performance was evaluated employing Mean Absolute Percentage Error (MAPE) and Root Mean Square Deviation (RMSD). Additionally, uncertainty propagation identified outside air temperature, supply airflow rate and return air temperature were the key parameters that had an impact in overall energy consumption. Discharge air temperature was reset based on return air temperature (RA-T) with a linear reset schedule from March 4 to March 7. Static pressure was reset based on the widest open Variable Air Volume (VAV) box damper from March 20 to March 23. Results indicated that 17% energy savings was achieved using discharge air temperature reset while the energy consumption reduced by 7% using static pressure reset.

Indiana University-Purdue University Indianapolis (IUPUI)

Natural gas substitution for diesel can result in significant reduction in pollutant emissions. Based on current fuel price projections, operating costs would be lower. With a high ignition temperature and relatively low reactivity, natural gas can enable promising approaches to combustion engine design. In particular, the combination of low reactivity natural gas and high reactivity diesel may allow for optimal operation as a reactivity-controlled compression ignition (RCCI) engine, which has potential for high efficiency and low emissions. In this computational study, a lean mixture of natural gas is ignited by direct injection of diesel fuel in a model of the heavy-duty CAT3401 diesel engine. Dual-fuel combustion of natural gas-diesel (NGD) may provide a wider range of reactivity control than other dual-fuel combustion strategies such as gasoline-diesel dual fuel. Accurate and efficient combustion modeling can aid NGD dual-fuel engine control and optimization. In this study, multi-dimensional simulation was performed using a nite-volume computational code for fuel spray, combustion and emission processes. Adaptive mesh refinement (AMR) and multi-zone reaction modeling enables simulation in a reasonable time. The latter approach avoids expensive kinetic calculations in every computational cell, with considerable speedup. Two approaches to combustion modeling are used within the Reynolds averaged Navier-Stokes (RANS) framework. The first approach uses direct integration of the detailed chemistry and no turbulence-chemistry interaction modeling. The model produces encouraging agreement between the simulation and experimental data. For reasonable accuracy and computation cost, a minimum cell size of 0.2 millimeters is suggested for NGD dual-fuel engine combustion. In addition, the role of different chemical reaction mechanism on the NGD dual-fuel combustion is considered with this model. This work considers fundamental questions regarding combustion in NGD dual-fuel combustion, particularly about how and where fuels react, and the difference between combustion in the dual fuel mode and conventional diesel mode. The results show that in part-load working condition main part of CH4 cannot burn and it has significant effect in high level of HC emission in NGD dual-fuel engine. The CFD results reveal that homogeneous mixture of CH4 and air is too lean, and it cannot ignite in regions that any species from C7H16 chemical mechanism does not exist. It is shown that multi-injection of diesel fuel with an early main injection can reduce HC emission significantly in the NGD dual-fuel engine. In addition, the results reveal that increasing the air fuel ratio by decreasing the air amount could be a promising idea for HC emission reduction in NGD dual-fuel engine, too.

Indiana University-Purdue University Indianapolis (IUPUI)

Radiation Therapy has been one of the most common techniques to treat various types of cancers, in particular is Head and Neck Cancer (HNC) which accounts for three percent of all cancers in the United States. During the treatment procedure, the patient is immobilized using immobilization devices such as the full head face mask, bite blocks, stereotactic frame, etc. to get accurate location of tumor. The disadvantage of these devices is that they are very uncomfortable to the patient especially people suffering from Post-Traumatic Stress Disorder (PTSD) and claustrophobia who cannot wear any confined masked system such as the full head mask or bite block during the treatment procedure. To mitigate this problem, there has been a lot of research in modifying such immobilizing devices without neglecting the accurate location of tumor. To this end, the research presented in this thesis focuses on developing a mask less system with accurately locating the position of tumor using the technique of coordinate transformation at the same time fulfilling the three important characteristics: • Comfort • Accuracy • Low price Such a system is comfortable to the patient because no confining mask system is used and we choose minimal contact points on the patient for fixing the patient. Traditionally, such type of cancer treatment is carried out in two stages: Diagnosis stage, which identifies the location of the tumor and the external markers and the Treatment stage where the tumor is treated with immobilization device being common in both the stages. In the new system, the immobilization devices vary at the two stages. The head position is monitored by using pressure sensor assembly where spring and pressure sensor setup detects the amount and direction of head deviation. We also prepare a customized 3D printed nose bridge part for extra referencing in the treatment room. Also, it is important that we use material for our immobilization devices which does not contain any metal and MRI compatible. Once the patient lies down on the treatment couch and is immobilized using the immobilization devices, then tumor location is calculated using the theory of coordinate transformation and transformation matrix in the Diagnosis and Treatment Stage. To validate the system, simulation of immobilization devices used in the new design was carried out using ANSYS Workbench 15.0 and LS-Dyna software’s Explicit Dynamics method. The simulation for the head-fixing device showed a deflection of ±0.1974 mm with respect to machine isocenter with a load of 60 N, which is lower than the customer requirement of ±3 mm with respect to machine isocenter of head deviation. The material used for the external markers for patient positioning was selected to be polyetheretherketone (PEEK) which is a radiolucent and widely used MRI compatible material. The system also takes into consideration the effect of weight loss, which is one of the drawbacks of the current systems. Although still in the…

Indiana University-Purdue University Indianapolis (IUPUI)

The passenger safety is one of the most important factors in the automotive industries. At the same time, in order to improve the overall efficiency of passenger cars, lightweight structures are preferred while designing the vehicle structures. Among various structural optimization techniques, topology optimization techniques are usually preferred to address the issue of crashworthiness. The hybrid cellular automaton (HCA) is a truly nonlinear explicit topology design method developed for obtaining conceptual designs of crashworthy vehicle components. In comparison to linear implicit methods, such as equivalent static loads, and partially nonlinear implicit methods, the HCA method fully captures all the relevant aspect of a fully nonlinear, transient dynamic crash simulation. Traditionally, the focus of the HCA method has been on designing load paths in the crash component that increase the uniform internal energy absorption ability; thus far, other relevant crashworthiness indicators such as peak crushing force and displacement have been less studied. The objective of this research is to extend the HCA method to synthesize load paths to obtain the different acceleration-displacement profiles, which allow reduced peak crushing force as well as reduced penetration during a crash event. To achieve this goal, this work introduces the concept of achieving uniform energy distribution at variable design simulation times. In the proposed work, the design time is used as a new design parameter in topology optimization. The desired volume fraction of the final design and the design time provided two dimensional design space for topology optimization, which is followed by the formulation of design of experiments (DOEs). The nonlinear analyses of the corresponding DOEs are performed using nonlinear explicit code LS-DYNA, which is followed by topology synthesis in HCA. The performance of the resulting structures showed that the short design times lead to design obtained by linear optimizers, while long simulation times lead to designs obtained by the traditional HCA method. To achieve the target crucial crash responses such as maximum acceleration and maximum displacement of the structure under the dynamic load, the geological predictor has been implemented. The concept of design time is further developed to improve structural performance of a vehicle component under the multiple loads using the method of multi-design time. Finally, the design time is implemented to generated merged designs by performing binary operations on topology-optimized designs. Numerical example of the simplified front frame is utilized to demonstrate the capabilities of the proposed approach.

2019-11-21

Indiana University-Purdue University Indianapolis (IUPUI)

Electric demand charge is a large portion (usually 40%) of electric bill in residential, commercial, and manufacturing sectors. This charge is based on the greatest of all demands that have occurred during a month recorded by utility provider for an end-user. During the past several years, electric demand forecasting have been broadly studied by utilities on account of the fact that it has a crucial impact on planning resources to provide consumers reliable power at all time; on the other hand, not many studies have been conducted on consumer side. In this thesis, a novel Maximum Daily Demand (MDD) forecasting method, called Adaptive-Rate-of-Change (ARC), is proposed by analysing real-time demand trend data and incorporating moving average calculations as well as rate of change formularization to develop a forecasting tool which can be applied on either utility or consumer sides. ARC algorithm is implemented on two different real case studies to develop very short-term load forecasting (VSTLF), short-term load forecasting (STLF), and medium-term load forecasting (MTLF). The Chi-square test is used to validate the forecasting results. The results of the test reveal that the ARC algorithm is 84% successful in forecasting maximum daily demands in a period of 72 days with the P-value equals to 0.0301. Demand charge is also estimated to be saved by $8,056 (345.6 kW) for the first year for case study I (a die casting company) by using ARC algorithm. Following that, a new Maximum Demand Management (MDM) method is proposed to provide electric consumers a complete package. The proposed MDM method broadens the electric consumer understanding of how MDD is sensitive to the temperature, production, occupancy, and different sub-systems. The MDM method are applied on two different real case studies to calculate sensitivities by using linear regression models. In all linear regression models, R-squareds calculated as 0.9037, 0.8987, and 0.8197 which indicate very good fits between fitted values and observed values. The results of proposed demand forecasting and management methods can be very helpful and beneficial in decision making for demand management and demand response program.

Indiana University-Purdue University Indianapolis (IUPUI)

Suspension has been the most important subsystem of the vehicle viewed as a system. The ride comfort and vehicle handling performance are affected by the suspension design. Automotive technology has been continuously incorporating developments over the past few decades to provide the end users with a better comfort of driving. Multi-objective optimization of MR damper with objective function of maximizing damping force generated by MR damper with the geometrical parametric constraint function is achieved in this research using pattern search optimization technique. Research focuses on design, modeling, and simulation of active suspension using non-linear theory of the Magneto-Rheological (MR) damper with consideration of the hysteresis behavior for a quarter car model. The research is based on the assumption that each wheel experiences same disturbance excitation. Hysteresis is analyzed using Bingham, Dahl’s, and Bouc-Wen models. Research includes simulation of passive, Bingham, Dahl, and Bouc-wen models. Modeled systems are analyzed for the six road profiles, including road type C according to international standards ISO/TC108/SC2N67. Furthermore, the comparative study of the models for the highest comfort with less overshoot and settling time of vehicle sprung mass are executed. The Bouc-Wen model is 36.91 percent more comfortable than passive suspension in terms of damping force requirements and has a 26.16 percent less overshoot, and 88.31 percent less settling time. The simulation of the Bouc-Wen model yields a damping force requirement of 2003 N which is 97.63 percent in agreement with analytically calculated damping force generated by MR damper. PID controller implementation has improved the overshoot response of Bouc-Wen model in the range of 17.89 percent-81.96 percent for the different road profiles considered in this research without compromising on the settling time of system. PID controller implementation further improves the passenger comfort and vehicle ride handling capabilities. The interdisciplinary approach of systems engineering principles for the suspension design provides unique edge to this research. Classical systems engineering tools and MBSE approach are applied in the design of the MR damper. Requirement traceability successfully validates the optimized MR damper.

Indiana University-Purdue University Indianapolis (IUPUI)

The compressed air system is widely used throughout the industry. Air compressors are one of the most costly systems to operate in industrial plants in terms of energy consumption. Therefore, it becomes one of the primary targets when it comes to electrical energy and load management practices. Load forecasting is the first step in developing energy management systems both on the supply and user side. A comprehensive literature review has been conducted, and there was a need to study if predicting compressed air system’s load is a possibility. System’s load profile will be valuable to the industry practitioners as well as related software providers in developing better practice and tools for load management and look-ahead scheduling programs. Feed forward neural networks (FFNN) and long short-term memory (LSTM) techniques have been used to perform 15 minutes ahead prediction. Three cases of different sizes and control methods have been studied. The results proved the possibility of the forecast. In this study two control methods have been developed by using the prediction. The first control method is designed for variable speed driven air compressors. The goal was to decrease the maximum electrical load for the air compressor by using the system's full operational capabilities and the air receiver tank. This goal has been achieved by optimizing the system operation and developing a practical control method. The results can be used to decrease the maximum electrical load consumed by the system as well as assuring the sufficient air for the users during the peak compressed air demand by users. This method can also prevent backup or secondary systems from running during the peak compressed air demand which can result in more energy and demand savings. Load management plays a pivotal role and developing maximum load reduction methods by users can result in more sustainability as well as the cost reduction for developing sustainable energy production sources. The last part of this research is concentrated on reducing the energy consumed by load/unload controlled air compressors. Two novel control methods have been introduced. One method uses the prediction as input, and the other one doesn't require prediction. Both of them resulted in energy consumption reduction by increasing the off period with the same compressed air output or in other words without sacrificing the required compressed air needed for production.

2019-12-05

Indiana University-Purdue University Indianapolis (IUPUI)

Computer Numerical Control (CNC) is widely used in many industries that needs high speed machining of the parts with high precision, accuracy and good surface finish. In order to avail this the generation of the CNC part program size will be immensely big and leads to an inefficient process, which increases the delivery time and cost of products. This work presents the automation of high-accuracy CNC tool trajectory planning from CAD to G-code generation through optimal NURBs surface approximation. The proposed optimization method finds the minimum number of NURBS control points for a given admissible theoretical cord error between the desired and manufactured surfaces. The result is a compact part program that is less sensitive to data starvation than circular and spline interpolations with potential better surface finish. The proposed approach is demonstrated with the tool path generation of an involute gear profile and a topologically optimized structure is developed using this approach and then finally it is 3D printed.

Indiana University-Purdue University Indianapolis (IUPUI)

The purpose of this research is to analyze the overall energy consumption of an industrial compressed air system, and identify the impact of various energy saving of individual subsystem on the overall system. Two parameters are introduced for energy consumption evaluation and potential energy saving: energy efficiency (e) and process effectiveness (n). An analytical energy model for air compression of the overall system was created taking into consideration the modeling of individual sub-system components: air compressor, after-cooler, filter, dryer and receiver. The analytical energy model for each subsystem included energy consumption evolution using the theoretical thermodynamic approach. Furthermore, pressure loss models of individual components along with pipe friction loss were included in the system overall efficiency calculation. The efficiency analysis methods and effectiveness approach discussed in this study were used to optimize energy consumption and quantify energy savings. The method was tested through a case study on a plant of a die-casting manufacturing company. The experimental system efficiency was 76.2% vs. 89.3% theoretical efficiency. This showed model uncertainty at ~15%. The effectiveness of reducing the set pressure increases as the difference in pressure increase. The effectiveness of using outside air for compressors intake is close to the compressors work reduction percentage. However, it becomes more effective when the temperature difference increase. This is mainly due to extra heat loss. There is potential room of improvement of the various component using the efficiency and effectiveness methods. These components include compressor, intercooler and dryer. Temperature is a crucial parameter that determines the energy consumption applied by these components. If optimum temperature can be determined, plenty of energy savings will be realized.

Indiana University-Purdue University Indianapolis (IUPUI)

Energy management has become a major concern in the past two decades with the increasing energy prices, overutilization of natural resources and increased carbon emissions. According to the department of Energy the industrial sector solely consumes 22.4% of the energy produced in the country [1]. This calls for an urgent need for the industries to design and implement energy efficient practices by analyzing the energy consumption, electricity data and making use of energy efficient equipment. Although, utility companies are providing incentives to consumer participating in Demand Response programs, there isn’t an active implementation of energy management principles from the consumer’s side. Technological advancements in controls, automation, optimization and big data can be harnessed to achieve this which in other words is referred to as “Smart Manufacturing”. In this research energy management techniques have been designed for two SEU (Significant Energy Use) equipment HVAC systems, Compressors and load shifting in manufacturing environments using control and optimization. The addressed energy management techniques associated with each of the SEUs are very generic in nature which make them applicable for most of the industries. Firstly, the loads or the energy consuming equipment has been categorized into flexible and non-flexible loads based on their priority level and flexibility in running schedule. For the flexible loads, an optimal load scheduler has been modelled using Mixed Integer Linear Programming (MILP) method that find carries out load shifting by using the predicted demand of the rest of the plant and scheduling the loads during the low demand periods. The cases of interruptible loads and non-interruptible have been solved to demonstrate load shifting. This essentially resulted in lowering the peak demand and hence cost savings for both “Time-of-Use” and Demand based price schemes. The compressor load sharing problem was next considered for optimal distribution of loads among VFD equipped compressors running in parallel to meet the demand. The model is based on MILP problem and case studies was carried out for heavy duty (>10HP) and light duty compressors (<=10HP). Using the compressor scheduler, there was about 16% energy and cost saving for the light duty compressors and 14.6% for the heavy duty compressors HVAC systems being one of the major energy consumer in manufacturing industries was modelled using the generic lumped parameter method. An Electroplating facility named Electro-Spec was modelled in Simulink and was validated using the real data that was collected from the facility. The Mean Absolute Error (MAE) was about 0.39 for the model which is suitable for implementing controllers for the purpose of energy management. MATLAB and Simulink were used to design and implement the state-of-the-art Model Predictive Control for the purpose of energy efficient control. The MPC was chosen due to its ability to easily handle Multi Input…

Indiana University-Purdue University Indianapolis (IUPUI)

The energy efficiency of space heaters is rated by Annual Fuel Utilization Efficiency (AFUE) governed by the Department of Energy in the United States which is a simple ratio of usable heat and fuel usage of a single heating device. It doesn't consider the overall performance of the heating system including not only the heating devices but also the characteristics of the building in different applications. The current AFUE method calculates only the energy efficiency which is thermodynamics first law efficiency. In this research, the systematic efficiency of a heating system rather than simple device efficiency has been defined and investigated. The systematic efficiency considers the overall efficiency of the whole heating system and it varies in the different applications even though with the same heating device. So it represents the performance of the system more precisely. Analytical models have been built to calculate both the systematic energy efficiency and exergy efficiency, and to evaluate the systematic energy and exergy efficiency of heating systems for direct fired and indirect fired heaters. Efficiency performances of the systems with these two types of heaters are compared. Sensitivities of input parameters for systematic energy efficiency are studied to show the impact towards systematic energy efficiency. Indoor carbon dioxide concentration level of direct fired heating system is also studied. In a case study, results show that systematic energy efficiency of indirect fired heating system is always constant at heater device efficiency which is 80% while systematic energy efficiency of direct fired heating system varies from 40%-92% under different condition (heat loss coefficient, ambient temperature and air change requirement), indicating that simple device efficiency is not capable to evaluate the overall performance of heating system. New efficiency method such as systematic energy efficiency used in this research is needed to better describe the performance of the heating system. Results of indoor carbon dioxide level of direct fired heating system, from 1000 to 4500 PPM under different conditions, show that indoor air quality needs to be considered while using direct fired heating.

Indiana University-Purdue University Indianapolis (IUPUI)

One of the most common concern among patients who need orthodontic treatment is treatment duration. The ability to accelerate orthodontic tooth movements would be bene cial to reduce the undesired side-effects of prolonged treatment. Methods have been used in conjugate with common orthodontic appliances to shorten the treatment. One of them is to use vibrational force (VF), which is non-invasive. The VF stimulates bone modeling and remodeling, which is essential to tooth movement. However, commercial devices used in the clinic failed to deliver consistent outcomes. The effects of the VF highly depend on its intensity the tooth receives. There must be a range of stimulation that optimizes the ffeects. The stimulation outside the range either have no effects or creates damages, which adversely affects the orthodontic treatment. Since these devices have generic mouthpiece and teeth are in di erent heights, hence some teeth cannot get force stimulation and others may be overloaded. The current designs also do not have ability to adjust the level of VF intensity that individual tooth needs, as in some cases orthodontists are required to move a tooth faster than others or even slower, which needs the device to be personalized. There- fore, the primary cause of inconsistent clinical outcomes is the inadequate design of the mouthpiece of the current device. The goal of this study is to design a better vibratory device that not only guarantees VF delivery but also enables orthodontists to control the level of VF on the individual tooth, which meets the patient's treat- ment needs. This is a preliminary study to understand the effects of different design parameters affecting the VF distribution on teeth. A nite element model, which consists of human upper and lower jaws in their occlusal positions and a mouthpiece, was created. The VF was from a vibratory source with a peak load of 0.3N and speci ed frequencies (30 and 120 Hz). The element size was determined through a convergence test and the model was validated experimentally. Results showed that the VF distribution among the teeth relies on the material property of the mouthpiece. The distribution is uneven, meaning some teeth bearing much more load than others. This means, with the current device design, teeth would be a ected with di erent level of force stimulation, which results in di erent clinical outcomes consequently. Dynamic load (VF) changes the force distribution on the teeth comparing to the dis- tribution from a static load. Frequency does not affect the peak load. Finally, the study demonstrated that the level of VF stimulation can be adjusted by introducing clearance or interference between the teeth and mouthpiece. It is feasible to control the level of the VF intensity for individual tooth based on treatment requirement.

Indiana University-Purdue University Indianapolis (IUPUI)

Heating, ventilation, and air conditioning (HVAC) is the technology responsible to maintain temperature levels and air quality in buildings to certain standards. In a commercial setting, HVAC systems accounted for more than 50% of the total energy cost of the building in 2013 [13]. New control methods are always being worked on to improve the effectiveness and efficiency of the system. These control systems include model predictive control (MPC), evolutionary algorithm (EA), evolutionary programming (EP), and proportional-integral-derivative (PID) controllers. Such control tools are used on new HVAC system to ensure the ultimate efficiency and ensure the comfort of occupants. However, there is a need for a system that can monitor the energy performance of the HVAC system and ensure that it is operating in its optimal operation and controlled as expected. In this thesis, an air handling unit (AHU) of an HVAC system was modeled to analyze its performance using real data collected from an operating AHU using a wireless monitoring system. The purpose was to monitor the AHU's performance, analyze its key parameters to identify flaws, and evaluate the energy waste. This system will provide the maintenance personnel to key information to them to act for increasing energy efficiency. The mechanical model was experimentally validated first. Them a baseline operating condition was established. Finally, the system under extreme weather conditions was evaluated. The AHU's subsystem performance, the energy consumption and the potential wastes were monitored and quantified. The developed system was able to constantly monitor the system and report to the maintenance personnel the information they need. I can be used to identify energy savings opportunities due to controls malfunction. Implementation of this system will provide the system's key performance indicators, offer feedback for adjustment of control strategies, and identify the potential savings. To further verify the capabilities of the model, a case study was performed on an air handling unit on campus for a three month monitoring period. According to the mechanical model, a total of 63,455 kWh can be potentially saved on the unit by adjusting controls. In addition the mechanical model was able to identify other energy savings opportunities due to set point changes that may result in a total of 77,141 kWh.

Indiana University-Purdue University Indianapolis (IUPUI)

Our ability to engineer materials is limited by our capacity to tailor the material’s microstructure morphology and predict resulting properties. The insufficient knowledge on microstructure-property relationship is due to complexity and randomness in all materials at different scales. The objective of this research is to establish a design optimization methodology for microstructured materials. The material design problem is stated as finding the optimum microstructure to maximize the desired performance satisfying material processing constrains. This problem has been solved in this thesis by means of numerical techniques through four main steps: microstructure characterization, model reconstruction, property evaluation, and optimization. Two methods of microstructure characterizations have been investigated along with the advantages and disadvantages of each method. The first microstructure characterization method is a statistical method which utilizes correlation functions to extract the microstructural information. Algorithms for calculating these correlations functions have been developed and optimized based on their computational cost using MATLAB software. The second microstructure characterization method is physical characterization which works based on evaluation of physical features in microstructured domain. These features have been measured by means of MATLAB codes. Three model reconstruction techniques are proposed based on these characterization methods and employed to generate material models for further evaluation. The first reconstructing algorithm uses statistical functions to reconstruct the statistical equivalent model through simulating annealing optimization method. The second algorithm uses cellular automaton concepts to simulate the grain growth utilizing physical descriptors, and the third one generates elliptical inclusions in a material matrix using physical characteristic of microstructure. The finite element method is used to analysis the mechanical behavior of material models. Several material samples with different microstructural characteristics have been generated to model the micro-scale design domain of AZ31 magnesium alloy and magnesium matrix composite with silicon carbide fibers. Then, surrogate models have been created based on these samples to approximate the entire design domain and demonstrate the sensitivity of the desired mechanical property to two independent microstructural features. Finally, the optimum microstructure characteristics of material samples for fracture strength maximization have been obtained.

Indiana University-Purdue University Indianapolis (IUPUI)

Traumatic Brain Injuries (TBI) are one of the most apprehensive issues today. In recent years a lot of research has been done for reducing the risk of TBI, but no concrete solution exists yet. Helmets are one of the protective devices that are used to prevent human beings from mild TBI. For many years some kind of foam has been used in helmets for energy absorption. But, in recent years non-traditional solutions other than foam are being explored by different groups. Focus of this thesis is to develop a completely new concept of energy absorption for helmet liner by diverting the impact forces in radial directions normal to the direction of impact. This work presents a new design of an advanced layered composite (ALC) for energy dissipation through action of a 3D array of compliant mechanisms. The ALC works by diverting incoming forces in multiple radial directions and also has design provisions for reducing rotational forces. Design of compliant mechanism is optimized using multi-material topology optimization algorithm considering rigid and flexible material phases together with void. The design proposed here needs to be manufactured using the advanced polyjet printing additive manufacturing process. A general and parametric design procedure is explained which can be used to produce variants of the designs for different impact conditions and different applications. Performance of the designed ALC is examined through a benchmark example in which a comparison is made between the ALC and the traditional liner foam. An impact test is carried out in this benchmark example using dynamic Finite Element Analysis in LS DYNA. The comparison parameters under consideration are gradualness of energy absorption and peak linear force transmitted from the ALC to the body in contact with it. The design in this article is done particularly for the use in sports helmets. However, the ALC may find applications in other energy absorbing structures such as vehicle crashworthy components and protective gears. The ultimate goal of this research is to provide a novel design of energy absorbing structure which reduces the risk of head injury when the helmet is worn.

Indiana University-Purdue University Indianapolis (IUPUI)

Requirements determine the expectations for a new or modified product. Requirements engineering involves defining, documentation and maintenance of requirements. The rapid improving of technologies and changing of market needs require a shorter time to market and more diversified products. As an important and complex task in product development, it is a huge work to develop new requirements for each new product from scratch. The reusability of requirements data becomes more and more important. However, with the current “copy and paste” approach, engineers have to go through the entire set of requirements (sometimes even more than one set of requirements) to identify the ones which need to be reused or updated. It takes a lot of time and highly relies on the engineers’ experiences. Software tools can only make it easier to capture and locate the requirements, but won’t be able to solve the problem of effective reuse of the existing requirement data. The overall goal of this research is to develop a new model to improve the management of requirements and make the reuse and reconfiguration of existing requirements and requirement models more efficient. Considering the requirements data as an important part of the knowledge body of companies, we followed the knowledge categorization method to classify requirements into groups, which were called levels in the study, based on their changing frequency. There are four levels, the regulatory level, the product line level, the product level and the project level. The regulatory level is the most stable level. Requirements in this level were derived from government and industry regulations. The product line level contains the common requirements for a group of products, the product line. The third level, product level, refers to the specific requirements of the product. And the fourth and most dynamic level, the project level, is about the specific configurations of a product for a project. We chose auto-injector as the application to implement the model, since it is a relatively simple product, but its requirements cover many different categories. There are three major steps in our research approach for the project. The first is to develop requirements and classify them for our model. The development of requirements adopts the goal-oriented model to analyze and SysML, a system modeling language, to build requirements model. And the second step is to build requirements template, connecting the solution of the problem to the information system, standalone requirements management tool or information platform. This step is to find a way to realize the multi-level model in an information system. The final step is to implement the model. We chose two software tools for the implementation, Microsoft Office Excel, a commonly used tool for generating requirements documents, and Siemens PLM suite, Teamcenter, a world leading PLM platform with a requirement module. The results in the study include an auto-injector…

Indiana University-Purdue University Indianapolis (IUPUI)

Close range, image based photogrammetry and LIDAR laser scanning technique are commonly utilized methodologies to snap real objects.3D models of already existing model or parts can be reconstructed by laser scanning and photogrammetry. These 3D models can be useful in applications like quality inspection, reverse engineering. With these techniques, they have their merits and limitations. Though laser scanners have higher accuracy, they require higher initial investment. Close-range photogrammetry is known for its simplicity, versatility and e ective detection of complex surfaces and 3D measurement of parts. But photogrammetry techniques can be initiated with comparatively much lower initial cost with acceptable accuracy. Currently, many industries are using photogrammetry for reverse engineering, quality inspection purposes. But, for photogrammetric object reconstruction, they are using di erent softwares. Industrial researchers are using commercial/open source codes for reconstruction and another stand-alone software for reverse engineering and mesh deviation analysis. So the problem statement here for this thesis is to integrate Photogrammetry, reverse engineering and deviation analysis to make one state-of-the-art work ow. xx The objectives of this thesis are as follows: 1. Comparative study between available source codes and identify suitable and stable code for integration; understand the photogrammetry methodology of that particular code. 2. To create a taskpane add-in using API for Integration of selected photogrammetry methodology and facilitate methodology with parameters. 3. To demonstrate the photogrammetric work ow followed by a reverse engineering case studies to showcase the potential of integration. 4. Parametric study for number of images vs accuracy 5. Comparison of Scan results, photogrammetry results with actual CAD data

Indiana University-Purdue University Indianapolis (IUPUI)

Industry is facing the challenge of increasing product complexity while at the same time reducing cost and time in a highly competitive global market. Product Lifecycle Management (PLM) and Systems Engineering have the potential to help companies avoid costly product development and launching, as well as failure during use; these two concepts not only share many common characteristics, but also complement each other. PLM provides an information management system that can seamlessly integrate enterprise data, business processes, business systems and, ultimately, people throughout all phases of the product lifecycle. Systems engineering is an interdisciplinary approach to designing, implementing, evaluating, and managing the complex human-made systems over their life cycle. The same underlying methods that improve management of products and services can be used to organize the framework in which PLM systems are implemented, integrated, and evolved. Though several studies have indicated that adopting Systems Engineering with PLM brings many benefits for industries, implementation of PLM based Systems Engineering with PLM has rarely been conducted. Pattern-Based Systems Engineering (PBSE), a form of Model-Based Systems Engineering (MBSE) based on the use of Systematic Metamodel (S* Metamodel), represents a family of manufacturing system, and is used in the life cycle processes of ISO 15288, was implemented here using TEAMCENTER® PLM software as the platform. More specifically, we have implemented the key portion of the General Production Pattern based on S* Metamodel, and demonstrated the benefit through the manufacturing of oil filter case study. The above implementation have resulted in a powerful systems engineering model in PLM that leverages the capabilities of Teamcenter, to enable an enhanced systems engineering approach. Benefits brought to systems engineering practice include: the ability to capture and reflect stakeholders' requirements and changes in product design process promptly and accurately; the ability of systems engineers to create models quickly and prevent mistakes during modeling; the ability of systems engineers to do their job much easily by using reusable and reconfigurable models; the ability to re-use of previous designs in a new process.

Indiana University-Purdue University Indianapolis (IUPUI)

Orthodontics research investigates the methods in which tooth displacement may be directed in the tooth-periodontal ligament-bone-complex. In the biological environment, the periodontal ligament is the soft tissue responsible for the absorption of forces on teeth and has a direct connection to tooth mobility. Current research is limited in that it must be conducted in an in-vivo capacity. A major advancement in orthodontics research would be a testing method that allows for the development and analysis of orthodontic devices without a patient present. This study outlines the development and testing methods for the validation of an artificial periodontal ligament to be used in conjunction with an artificial-tooth-periodontal ligament-bone-complex. The study focused on finding the criteria in which consistent results were produced, the mixture that best simulated the human periodontal ligament’s mechanical behavior, and the robustness of the artificial-periodontal ligament-bone-complex. This study utilized a geometrically accurate denture mold filled with varying compositions of an artificial periodontal ligament for testing. Experiments focused on findings of viscoelasticity, curing times, and instantaneous responses of the teeth under direct orthodontic loading, as well as the changes in response from different teeth within the denture mold. Tests confirmed that a mixture composed of 50% Gasket Sealant No. 2 and 50% RTV 587 Silicone produced a substance that could adequately serve as an artificial periodontal ligament.

Indiana University-Purdue University Indianapolis (IUPUI)

Air handling unit systems are the series of mechanical systems that regulate and circulate the air through the ducts inside the buildings. In a commercial setting, air handling units accounted for more than 50% of the total energy cost of the building in 2013. To make the system more energy efficient and reduce amount of CO₂ gases and energy waste, it is very important for building energy management systems to have an accurate model to help predict and optimize the energy usage and eliminate the energy waste. In this work, two models are described to focus on the energy usage for heating/cooling coils as well as fans for the air handling unit. Enthalpy based effectiveness and Dry Wet coil methods were identified and compared for the system performance. Two different types of control systems were modeled for this research, and the results are shown based on occupancy reflected by the collected CO₂ data. Discrete On/O and fuzzy logic controller techniques were simulated using Simulink MATLAB software and compared based on energy reduction and system performance. Air handling unit located in the basement of one campus building is used for the test case of this study. The data for model inputs is collected wirelessly from the building using fully function device (FFD) and pan coordinator to send/receive the data wirelessly. The air handling unit modeling also is done using Engineering Equation Solver EES Software for the coils and AHU subsystems. Current building management system Metasys software was used to get additional data as model inputs. Moving Average technique was utilized to make the model results more readable and less noisy. Simulation results show that in humid regions where there is more than 45% of relative humidity, the dry wet coil method is the effective way to provide more accurate details of the heat transfer and energy usage of the air handling unit comparing to the other method enthalpy-based effectiveness. Also, fuzzy logic controller results show that 62% of the current return fan energy can be reduced weekly using this method without sacrificing the occupant comfort level comparing to the ON/OFF method. Air quality can be optimized inside the building using fuzzy logic controller. At the same time, system performance can be increased by taking the appropriate steps to prevent the loss of static pressure in the ducts. The implementation of the method developed in this study will improve the energy efficiency of the AHU.

Indiana University-Purdue University Indianapolis (IUPUI)

In this thesis, a high- fidelity multibody dynamics model of a backhoe for simulating the digging operation is developed using the DIS (Dynamic Interactions Simulator)multibody dynamics software. Sand is used as a sample digging material to illustrate the model. The backhoe components (such as frame, manipulators links,track segments, wheels and sprockets) are modeled as rigid bodies. The geometry of the major moving components of the backhoe is created using the Pro/E solid modeling software. The components of the backhoe are imported to DIS and connected using joints (revolute, cylindrical and prismatic joints). Rotary and linear actuators along with PD (Proportional-Derivative) controllers are used to move and steer the backhoe and to move the backhoes manipulator in the desired trajectory. Sand is modeled using cubic shaped particles that can come into contact with each other, the backhoes bucket and ground. A cubical sand particle contact surface is modeled using eight spheres that are rigidly glued to each other to form a cubical shaped particle, The backhoe and ground surfaces are modeled as polygonal surfaces. A penalty technique is used to impose both joint and normal contact constraints (including track-wheels, track-terrain, bucket-particles and particles-particles contact). An asperity-based friction model is used to model joint and contact friction. A Cartesian Eulerian grid contact search algorithm is used to allow fast contact detection between particles. A recursive bounding box contact search algorithm is used to allow fast contact detection for polygonal contact surfaces and is used to detect contact between: track and ground; track and wheels; bucket and particles; and ground and particles. The governing equations of motion are solved along with joint/constraint equations using a time-accurate explicit solution procedure. The sand model is validated using a conical hopper sand flow experiment in which the sand flow rate during discharge and the angle of repose of the resulting sand pile are experimentally measured. The results of the conical hopper simulation are compared with previously published experimental results. Parameter studies are performed using the sand model to study the e ffects of the particle size and the orifi ces diameter of the hopper on the sand pile angle of repose and sand flow rate. The sand model is integrated with the backhoe model to simulate a typical digging operation. The model is used to predict the manipulators actuator forces needed to dig through a pile of sand. Integrating the sand model and backhoe model can help improving the performance of construction equipment by predicting, for various vehicle design alternatives: the actuator and joint forces, and the vehicle stability during digging.

Indiana University-Purdue University Indianapolis (IUPUI)

There have been many endeavors to design humanoid robots that have human characteristics such as dexterity, autonomy and intelligence. Humanoid robots are intended to cooperate with humans and perform useful work that humans can perform. The main advantage of humanoid robots over other machines is that they are flexible and multi-purpose. In this thesis, a human-like robotic arm is designed and used in a task which is typically performed by humans, namely, catching a ball. The robotic arm was designed to closely resemble a human arm, based on anthropometric studies. A rigid multibody dynamics software was used to create a virtual model of the robotic arm, perform experiments, and collect data. The inverse kinematics of the robotic arm was solved using a Newton-Raphson numerical method with a numerically calculated Jacobian. The system was validated by testing its ability to find a kinematic solution for the catch position and successfully catch the ball within the robot's workspace. The tests were conducted by throwing the ball such that its path intersects different target points within the robot's workspace. The method used for determining the catch location consists of finding the intersection of the ball's trajectory with a virtual catch plane. The hand orientation was set so that the normal vector to the palm of the hand is parallel to the trajectory of the ball at the intersection point and a vector perpendicular to this normal vector remains in a constant orientation during the catch. It was found that this catch orientation approach was reliable within a 0.35 x 0.4 meter window in the robot's workspace. For all tests within this window, the robotic arm successfully caught and dropped the ball in a bin. Also, for the tests within this window, the maximum position and orientation (Euler angle) tracking errors were 13.6 mm and 4.3 degrees, respectively. The average position and orientation tracking errors were 3.5 mm and 0.3 degrees, respectively. The work presented in this study can be applied to humanoid robots in industrial assembly lines and hazardous environment recovery tasks, amongst other applications.

Indiana University-Purdue University Indianapolis (IUPUI)

This work is focused on developing viable self-healing coatings, especially considering the viability of the coating in a commercial context. With this in mind, finding low cost healing agents, with satisfactory healing and mechanical properties as well as adapting the healing system for use in coatings was required. Seven potential healing agents were evaluated and an air-drying triglyceride (linseed oil) was identified as the candidate healing agent. Different encapsulation techniques were evaluated and ureaformaldehyde microcapsules were chosen as the candidate encapsulation technique. Self-healing coatings were fabricated using urea-formaldehyde encapsulated linseed oil. EIS, SEM and TGA technologies were used to evaluate mechanical performance, corrosion resistance, and self-healing performance.

Indiana University-Purdue University Indianapolis (IUPUI)

In recent years, magnesium alloys, due to their high strength and biocompatibility, have attracted significant interest in medical applications, such as cardiovascular stents, orthopedic implants, and devices. To overcome the high corrosion rate of magnesium alloys, coatings have been developed on the alloy surface. Most coating methods, such as anodic oxidation, polymer coating and chemical conversion coating, cannot produce satisfactory coating to be used in human body environment. Recent studies demonstrate that micro-arc oxidation (MAO) technique can produce hard, dense, wear-resistant and well-adherent oxide coatings for light metals such as aluminum, magnesium, and titanium. Though there are many previous studies, the understanding of processing conditions on coating performance remains elusive. Moreover, previous tests were done in simulated body fluid. No test has been done in a cell culture medium, which is much closer to human body environment than simulated body fluid. In this study, the effect of MAO processing time (1 minute, 5 minutes, 15 minutes, and 20 minutes) on the electrochemical behaviors of the coating in both conventional simulated body fluid and a cell culture medium has been investigated. Additionally a new electrolyte (12 g/L Na2SiO3, 4 g/L NaF and 4 ml/L C3H8O3) has been used in the MAO coating process. Electrochemical behaviors were measured by performing potentiodynamic polarization and electrochemical impedance spectroscopy tests. In addition to the tests in simulated body fluid, the MAO-coated and uncoated samples were immersed in a cell culture medium to investigate the corrosion behaviors and compare the difference in these two kinds of media. The results show that in the immersion tests in conventional simulated body fluid, the 20-minute MAO coated sample has the best resistance to corrosion due to the largest coating thickness. In contrast, in the cell culture medium, all MAO coated samples demonstrate a similar high corrosion resistance behavior, independent of MAO processing time. This is probably due to the organic passive layers formed on the coating surfaces. Additionally, a preliminary finite element model has been developed to simulate the immersion test of magnesium alloy in simulated body fluid. Comparison between the predicted corrosion current density and experimental data is discussed.

Indiana University-Purdue University Indianapolis (IUPUI)

Objective: To evaluate the osseointegration potential of four different surfaces of mini-implants .We hypothesized that mini-implants surface roughness alters the intrinsic biomechanical properties of the bone integrated to titanium. Materials and Methods: Mini implants and circular discs were made from alloy Ti6Al4V grade 5. On the basis of surface treatment study was divided into 4 groups: Group 1: Machined: no surface treatment, Group 2: Acid etched: with hydrochloric acid, Group 3: Grit Blasted with alumina and Group 4: Grit blasted +Acid etched. Surface roughness parameters (mean surface roughness: Ra and Quadratic Average roughness: Rq) of the four discs from each group were measured by the optical profilometer. Contact angle measurement of 3 discs from each group was done with a Goniometer. Contact angle of liquids with different hydrophobicity and hydrophilicity were measured. 128 mini implants, differing in surface treatment, were placed into the tibias and femurs of 8 adult male New Zealand white rabbits. Biomechanical properties (Removal torque and hardness) measurements and histomorphometric observations were measured. Results: Ra and Rq of groups were: Machined (1.17±0.11, 2.59±0.09) Acid etched (1.82±0.04, 3.17±0.13), Grit blasted (4.83±0.23, 7.04±0.08), Grit blasted + Acid etched (3.64±0.03, 4.95±0.04) respectively. Group 4 had significantly (p=0.000) lower Ra and Rq than Group 3. The interaction between the groups and liquid was significant. Group 4 had significantly lower contact angle measurements (40.4°, 26.9°), both for blood and NaCl when compared to other three groups (p≤0.01). Group 4 had significantly higher torque than Group 3 (Tibia: 13.67>9.07N-cm; Femur: 18.21>14.12N-cm), Group 4 (Tibia: 13.67>9.78N-cm; Femur: 18.21>12.87N-cm), and machined (Tibia: 13.67>4.08N-cm; Femur: 18.21>6.49N-cm). SEM analysis reveals significantly more bone implant gap in machined implant surfaces than treated implant surfaces. Bone to implant contact had significantly higher values for treated mini implant surface than machined surface. Hardness of the bone near the implant bone interface is 20 to 25% less hard than bone 1mm away from it in both Femur and Tibia. Conclusion: Surface roughness and wettability of mini implants influences their biological response. Grit blasted and acid etched mini implants had lowest contact angle for different liquids tested and highest removal torques.

Indiana University-Purdue University Indianapolis (IUPUI)

Predictability of tooth displacement in response to specific orthodontic load system directly links to the quality and effectiveness of the treatment. The key questions are how the tooth’s environment changes in response to the orthodontic load and how the biological tissues respond clinically. The objectives of this study are to determine the mechanical environment (ME) changes and to quantify the biological tissues’ response. Eighteen (18) patients who needed maxillary bilateral canine retractions were involved in the study. A method was developed to quantify the 3D load systems on the canine, which allowed the treatment strategies to be customized in terms of orthodontic loading systems to meet either translation (TR) or controlled tipping (CT) requirement. Dental casts were made before and after each treatment interval, and the Cone Beam Computed Tomography (CBCT) scans were taken prior to and following the entire treatment for control of treatment strategy and post treatment evaluations. Finite element method (FEM) was applied to calculate the location of center of resistance (CRes) for tooth movement control. The location and variation of CRes were recorded and compared with previous studies. A quick CRes assessment method that locates CRes by calculating the centroid of the contact surface (CCS) and the centroid of the projection of root surface (CPCS) in certain direction was also tested and compared with the results from FEM. Customized T-loop spring, a kind of orthodontic appliance, was designed, fabricated, and calibrated on a load measuring system to ensure that the load met the clinician’s prescription. The treatment outcomes in terms of tooth displacement and root resorption characterized by the changes of tooth length and volume as well as the bone mineral density (BMD) represented by the Hounsfield units (HU) change were recorded and analyzed. The ME in terms of stress were also calculated by using FEM. Paired t-test and mixed model ANOVA methods were used to analyze the relationships between the mechanical inputs (quantified and customized load, and corresponding stress) and clinical outcomes (root resorption and BMD change). It was found that the overall root resorption is not significant for canine retraction, but apical root resorption does occur, meaning that orthodontic load is not a sufficient factor. Also, it was observed that HU distribution changed significantly in both root and alveolar bone. The maximum reduction was on the coronal level in the direction perpendicular to the direction of movement in root, and in the direction of the tooth movement at the coronal level in bone. In addition, it was determined that the locations of the CRes in the MD and BL directions were significantly different. The locations of the CRes of a human canine in MD and BL directions can be estimated by finding the CPCSs in the two directions. Finally, it was shown that the stress invariants can be used to characterize how the osteocytes feel when ME…

Indiana University-Purdue University Indianapolis (IUPUI)

The first part of the study describes the development of a microCT based engineering model to study orthodontic responses. The second part investigated the relationship between orthodontic stimulus, root resorption and bone modeling. It was hypothesized that stress magnitudes are insufficient to portray the mechanical environment and explain the clinical response; directions also play a role. An idealized tooth model was constructed for finite element analysis. The principal stress magnitudes and directions were calculated in tipping and translation. It was concluded that within the same region of root, PDL and bone, there can be compression in one structure, tension in another. At a given point in a structure, compression and tension can coexist in different directions. Magnitudes of compression or tension are typically different in different directions. Previously published data presenting only stress magnitude plots can be confusing, perhaps impossible to understand and/or correlate with biological responses. To avoid ambiguities, a reference to a principal stress should include its predominant direction. Combined stress magnitude/direction results suggest that the PDL is the initiator of mechanotransduction. The third part of this project tested the role of the P2X7 receptor in the dentoalveolar morphology of C57B/6 mice. P2X7R KO (knockout) mice were compared to C57B/6 WT to identify differences in a maxillary molar and bone. Tooth dimensions were measured and 3D bone morphometry was conducted. No statistically significant differences were found between the two mouse types. P2X7R does not have a major effect on alveolar bone or tooth morphology. The final part examines the role of the P2X7 receptor in a controlled biomechanical model. Orthodontic mechanotransduction was compared in wild-type (WT) and P2X7R knock-out (KO) mice. Using Finite Element Analysis, mouse mechanics were scaled to produce typical human stress levels. Relationships between the biological responses and the calculated stresses were statistically tested and compared. There were direct relationships between certain stress magnitudes and root resorption and bone formation. Hyalinization and root and bone resorption were different in WT and KO. Orthodontic responses are related to the principal stress patterns in the PDL and the P2X7 receptor plays a significant role in their mechanotransduction.