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Vanderbilt University
1.
Schauben, Deanna Nicole.
Mechano-Electrochemistry of Nickel Titanium Alloy.
Degree: MS, Mechanical Engineering, 2017, Vanderbilt University
URL: http://hdl.handle.net/1803/12105 
► MECHANICAL ENGINEERING Mechano-Electrochemistry of Nickel Titanium Alloy Deanna Schauben Thesis under the direction of Professor Cary L. Pint The fields of strain engineering and mechano-electrochemistry…
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▼ MECHANICAL ENGINEERING
Mechano-Electrochemistry of Nickel Titanium Alloy
Deanna Schauben
Thesis under the direction of Professor Cary L. Pint
The fields of strain engineering and mechano-electrochemistry have recently emerged to explore the relationship between strain and electrochemical properties, particularly as they pertain to corrosion. NiTi is an ideal candidate for investigating this relationship due to its superelastic and shape memory properties. Here, an in-situ mechano-electrochemical cell is designed and implemented to obtain the open circuit voltage response of NiTi during straining. Of particular interest is the OCV behavior during the stress-induced martensitic transformation, which is both immediate and dramatic. A survey of OCV response during straining as well as the steady-state response after straining was performed for samples deformed to different percentages of strain at two different strain rates. The steady-state response is permanently changed by up to 44.8 mV only when strain is halted within the SIM plateau, and the magnitude of OCV change increases by a factor of about 2.5-2.9 with a strain rate increase by a factor of 5. These results point to an energetic mechanism of the SIM transformation that is yet to be investigated.
Advisors/Committee Members: Douglas Adams (committee member), Ravindra Duddu (committee member), Cary Pint (Committee Chair).
Subjects/Keywords: martensite; martensitic transformation; austenite; OCV; strain engineering; mechano-electrochemistry; strain; shape memory; NiTi; open circuit voltage; open circuit potential; Nitinol
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APA (6th Edition):
Schauben, D. N. (2017). Mechano-Electrochemistry of Nickel Titanium Alloy. (Thesis). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/12105
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Schauben, Deanna Nicole. “Mechano-Electrochemistry of Nickel Titanium Alloy.” 2017. Thesis, Vanderbilt University. Accessed April 10, 2021.
http://hdl.handle.net/1803/12105.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Schauben, Deanna Nicole. “Mechano-Electrochemistry of Nickel Titanium Alloy.” 2017. Web. 10 Apr 2021.
Vancouver:
Schauben DN. Mechano-Electrochemistry of Nickel Titanium Alloy. [Internet] [Thesis]. Vanderbilt University; 2017. [cited 2021 Apr 10].
Available from: http://hdl.handle.net/1803/12105.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Schauben DN. Mechano-Electrochemistry of Nickel Titanium Alloy. [Thesis]. Vanderbilt University; 2017. Available from: http://hdl.handle.net/1803/12105
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Vanderbilt University
2.
Nath, Paromita.
Uncertainty Quantification and Management in Additive Manufacturing.
Degree: PhD, Civil Engineering, 2020, Vanderbilt University
URL: http://hdl.handle.net/1803/15357
► Additive manufacturing (AM) has shown immense potential in several industries. However, significant variability in the product quality currently hinders widespread use of AM. The focus…
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▼ Additive manufacturing (AM) has shown immense potential in several industries. However, significant variability in the product quality currently hinders widespread use of AM. The focus of this dissertation is on uncertainty quantification (UQ) and uncertainty management (UM) in AM to help solve this challenge by integrating physics-model based prediction with probabilistic sensing and control strategies for the manufacturing process. This research develops a systematic UQ/UM methodology to quantify and control the variability in the AM process. Three objectives are accomplished: (1) formulation of the UQ methodology, (2) process design under uncertainty, and (3) process control under uncertainty. Various sources of uncertainty are considered, such as process and material uncertainty, model discrepancy, and measurement uncertainty. The uncertainty quantification methodology integrates heterogeneous information available from multiple sources and different models. Both forward and inverse problems are addressed. The forward problem (UQ) quantifies the overall uncertainty in the AM process, and the relative contributions of different sources to the overall uncertainty regarding the quality of the AM product. The inverse problem (UM) addresses uncertainty reduction through model calibration, and process design and process control. Efficient surrogate models are constructed to replace the expensive coupled multi-scale multi-physics simulation models for the uncertainty analysis. In particular, a methodology is developed for building surrogate models in the presence of high-dimensional field output. Laboratory experiments are conducted to validate the process parameter optimization results. The proposed methodologies are demonstrated with examples from metal and polymer-based additive manufacturing techniques.
Advisors/Committee Members: Manav Vohra (committee member), Douglas Adams (committee member), Pranav Karve (committee member), Zhen Hu (committee member), Sankaran Mahadevan (Committee Chair).
Subjects/Keywords: Uncertainty quantification; Additive manufacturing; Surrogate modeling; Process design optimization; Process control; Finite element modeling
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APA (6th Edition):
Nath, P. (2020). Uncertainty Quantification and Management in Additive Manufacturing. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/15357
Chicago Manual of Style (16th Edition):
Nath, Paromita. “Uncertainty Quantification and Management in Additive Manufacturing.” 2020. Doctoral Dissertation, Vanderbilt University. Accessed April 10, 2021.
http://hdl.handle.net/1803/15357.
MLA Handbook (7th Edition):
Nath, Paromita. “Uncertainty Quantification and Management in Additive Manufacturing.” 2020. Web. 10 Apr 2021.
Vancouver:
Nath P. Uncertainty Quantification and Management in Additive Manufacturing. [Internet] [Doctoral dissertation]. Vanderbilt University; 2020. [cited 2021 Apr 10].
Available from: http://hdl.handle.net/1803/15357.
Council of Science Editors:
Nath P. Uncertainty Quantification and Management in Additive Manufacturing. [Doctoral Dissertation]. Vanderbilt University; 2020. Available from: http://hdl.handle.net/1803/15357
Vanderbilt University
3.
Absi, Ghina Nakad.
Multi-Fidelity Information Fusion for Structural Dynamics Model Calibration.
Degree: PhD, Civil Engineering, 2019, Vanderbilt University
URL: http://hdl.handle.net/1803/11373
► This dissertation develops a novel approach for fusing information from physics models of different levels of fidelity in the Bayesian estimation of system parameters. In…
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▼ This dissertation develops a novel approach for fusing information from physics models of different levels of fidelity in the Bayesian estimation of system parameters. In order to balance computational effort and accuracy, the proposed method first builds a surrogate model using low-fidelity physics simulations. Then it uses a small number of high-fidelity physics simulations to improve the surrogate model, and uses the improved surrogate for calibration with experimental data. This multi-fidelity strategy facilitates computational efficiency, in surrogate training as well as in Bayesian calibration. Furthermore, the improvement of the surrogate model with high-fidelity results before calibration with experimental data provides stronger, physics-informed priors for the calibration quantities. This is particularly useful when limited experimental data are available, and a reliable, but fast model is needed for calibration.
The multi-fidelity calibration method is extended to the calibration of input-dependent system parameters, where the hyper-parameters of the functional relationships between the input and the parameters are estimated. This extension also takes into consideration the effect of the input on the uncertainty in the sensor measurement.
The multi-fidelity approach is optimized in two ways to maximize the information gain: (1) selecting the high-fidelity simulations to improve the surrogate of the low-fidelity model (simulation optimization); and (2) selecting the experimental sensor configuration (i.e., number and locations of the sensors). The proposed methodology is illustrated for the estimation of damping parameters of a fuselage panel close to the engine in a hypersonic aircraft, which is subjected to acoustic and thermal loading.
Advisors/Committee Members: Douglas Adams (committee member), Prodyot Basu (committee member), Hiba Baroud (committee member), Mark McDonald (committee member), Sankaran Mahadevan (Committee Chair).
Subjects/Keywords: Multi-Fidelity; Information Fusion; Hypersonic Vehicles; Dynamics Models; Bayesian Calibration
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APA (6th Edition):
Absi, G. N. (2019). Multi-Fidelity Information Fusion for Structural Dynamics Model Calibration. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/11373
Chicago Manual of Style (16th Edition):
Absi, Ghina Nakad. “Multi-Fidelity Information Fusion for Structural Dynamics Model Calibration.” 2019. Doctoral Dissertation, Vanderbilt University. Accessed April 10, 2021.
http://hdl.handle.net/1803/11373.
MLA Handbook (7th Edition):
Absi, Ghina Nakad. “Multi-Fidelity Information Fusion for Structural Dynamics Model Calibration.” 2019. Web. 10 Apr 2021.
Vancouver:
Absi GN. Multi-Fidelity Information Fusion for Structural Dynamics Model Calibration. [Internet] [Doctoral dissertation]. Vanderbilt University; 2019. [cited 2021 Apr 10].
Available from: http://hdl.handle.net/1803/11373.
Council of Science Editors:
Absi GN. Multi-Fidelity Information Fusion for Structural Dynamics Model Calibration. [Doctoral Dissertation]. Vanderbilt University; 2019. Available from: http://hdl.handle.net/1803/11373
Vanderbilt University
4.
Douglas, Anna Elisabeth.
Sustainable Manufacturing of Carbon Nanomaterials for Energy Storage Applications.
Degree: PhD, Interdisciplinary Materials Science, 2019, Vanderbilt University
URL: http://hdl.handle.net/1803/11370
► In order to preserve long-term human sustainability on Earth, many researchers have focused significant efforts towards developing technologies that 1) decrease greenhouse gas emissions, and…
(more)
▼ In order to preserve long-term human sustainability on Earth, many researchers have focused significant efforts towards developing technologies that 1) decrease greenhouse gas emissions, and 2) utilize atmospheric carbon dioxide as a feedstock gas for the production of materials, chemicals, and fuels. While Li-ion batteries have emerged as an ideal technology to reduce emissions through electric vehicles and the storage of renewably-generated energy for electricity, the current cost of Li-ion batteries today limits widespread integration. This cost is fueled mainly by the low earth abundance and high processing cost of Li-ion materials. In this dissertation, I focus on the use of low-cost and earth abundant materials for both Li- and Na- ion battery applications. A platform for the capture and conversion of atmospheric CO2 into solid carbon structures is developed, with an emphasis on the catalytic growth of carbon nanotubes (CNTs) through electrochemical routes. Small diameter CNTs are synthesized through the development of an inert anode capable of activating catalytic particles present at the cathode-electrolyte interface, and careful study of dynamic catalytic processes leads to the first mechanistic understandings of electrochemical CNT growth from CO2. Phenomena such as catalyst size dictating the structure of CNTs synthesized and Ostwald ripening of catalysts over time are studied, and electrochemical “pinning” of catalytic particles through the use of high current pulses is demonstrated to drive the formation of small-diameter CNTs with the first observation of single-walled CNTs from CO2 characterized by Raman spectroscopy. Lastly, these CO2-derived CNTs are integrated into Li-ion batteries at both the anode (as the active material) and the cathode (as the conductive additive with Fe-based active materials) and demonstrate a full-cell with a 68% reduction in CO2 emissions associated with Li-ion materials.
Advisors/Committee Members: Douglas Adams (committee member), Greg Walker (committee member), Jason Valentine (committee member), Rizia Bardhan (committee member), Cary Pint (Committee Chair).
Subjects/Keywords: batteries; carbon; carbon dioxide; nanotubes
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APA (6th Edition):
Douglas, A. E. (2019). Sustainable Manufacturing of Carbon Nanomaterials for Energy Storage Applications. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/11370
Chicago Manual of Style (16th Edition):
Douglas, Anna Elisabeth. “Sustainable Manufacturing of Carbon Nanomaterials for Energy Storage Applications.” 2019. Doctoral Dissertation, Vanderbilt University. Accessed April 10, 2021.
http://hdl.handle.net/1803/11370.
MLA Handbook (7th Edition):
Douglas, Anna Elisabeth. “Sustainable Manufacturing of Carbon Nanomaterials for Energy Storage Applications.” 2019. Web. 10 Apr 2021.
Vancouver:
Douglas AE. Sustainable Manufacturing of Carbon Nanomaterials for Energy Storage Applications. [Internet] [Doctoral dissertation]. Vanderbilt University; 2019. [cited 2021 Apr 10].
Available from: http://hdl.handle.net/1803/11370.
Council of Science Editors:
Douglas AE. Sustainable Manufacturing of Carbon Nanomaterials for Energy Storage Applications. [Doctoral Dissertation]. Vanderbilt University; 2019. Available from: http://hdl.handle.net/1803/11370
Vanderbilt University
5.
Pedchenko, Alexander Vadimovich.
The Power Harvesting Ratio: Design and Power Estimation of Vibration Energy Harvesters.
Degree: PhD, Mechanical Engineering, 2015, Vanderbilt University
URL: http://hdl.handle.net/1803/15221
► Due to approximately one quarter of the bridges in the United States being classified as “functionally obsolete” or “structurally deficient”, there is currently a large…
(more)
▼ Due to approximately one quarter of the bridges in the United States being classified as “functionally obsolete” or “structurally deficient”, there is currently a large demand for frequent bridge inspection. This demand can be addressed by remote structural health monitoring. The sensors and data transmission equipment necessary to implement remote monitoring requires electrical power, and wiring sensor networks to bridge power lines is expensive, while batteries require regular maintenance/replacement. By expanding the characteristically narrow operational bandwidth of conventional vibration energy harvesters, these devices can serve as local power sources for structural monitoring networks by harnessing the mechanical energy from vibrations produced during typical bridge use.
The presented research contributes to the developing field of multifrequency vibration energy harvesting by introducing two new techniques for linear harvesters. The first is a method for analyzing the effect of an electrical load on the dynamic stability of a harvester. This technique aids the recent research interest in the use of active loading to increase power generation by serving as a means to determine whether the chosen active load results in stable dynamics and, therefore, can actually be utilized.
The second introduced tool is a technique for estimating the average power generation of a vibration energy harvester from the device’s dynamics and the discrete Fourier transform (DFT) of its excitation. This method, termed the power harvesting ratio (PHR), presents the power output of a particular harvester/electrical load combination as a function of frequency and shows the power contribution of each frequency component comprising the excitation.
The stability assessment tool and PHR are experimentally validated using a custom electromagnetic vibration energy harvester. The stability assessment tool is shown to accurately predict whether a certain active load will lead to stable or unstable overall system dynamics. PHR is demonstrated to accurately predict power generation for a variety of excitations (including typical bridge vibrations) and electrical loads (both, passive and active). The PHR technique is also used to investigate potential benefits of active electrical over passive loading, optimization of power yields of different architectures of vibration energy harvesters, and effects of frequency and amplitude variations in the excitation on power yield.
Advisors/Committee Members: Kenneth Pence (committee member), Thomas Withrow (committee member), Douglas Adams (committee member), Michael Goldfarb (committee member), Eric J Barth (Committee Chair).
Subjects/Keywords: electromechanical generation; structural health monitoring; vibration energy harvesting
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APA (6th Edition):
Pedchenko, A. V. (2015). The Power Harvesting Ratio: Design and Power Estimation of Vibration Energy Harvesters. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/15221
Chicago Manual of Style (16th Edition):
Pedchenko, Alexander Vadimovich. “The Power Harvesting Ratio: Design and Power Estimation of Vibration Energy Harvesters.” 2015. Doctoral Dissertation, Vanderbilt University. Accessed April 10, 2021.
http://hdl.handle.net/1803/15221.
MLA Handbook (7th Edition):
Pedchenko, Alexander Vadimovich. “The Power Harvesting Ratio: Design and Power Estimation of Vibration Energy Harvesters.” 2015. Web. 10 Apr 2021.
Vancouver:
Pedchenko AV. The Power Harvesting Ratio: Design and Power Estimation of Vibration Energy Harvesters. [Internet] [Doctoral dissertation]. Vanderbilt University; 2015. [cited 2021 Apr 10].
Available from: http://hdl.handle.net/1803/15221.
Council of Science Editors:
Pedchenko AV. The Power Harvesting Ratio: Design and Power Estimation of Vibration Energy Harvesters. [Doctoral Dissertation]. Vanderbilt University; 2015. Available from: http://hdl.handle.net/1803/15221
Vanderbilt University
6.
Cai, Guowei.
Big Data Analytics in Structural Health Monitoring.
Degree: PhD, Civil Engineering, 2017, Vanderbilt University
URL: http://hdl.handle.net/1803/14239
► This dissertation investigates methods to implement big data analytics in structural health monitoring. Four types of activities are considered: (1) data processing; (2) structural damage…
(more)
▼ This dissertation investigates methods to implement big data analytics in structural health monitoring. Four types of activities are considered: (1) data processing; (2) structural damage diagnosis and prognosis with uncertainty quantification; (3) high-dimensional model parameter calibration; and (4) surrogate model training. First, a methodology is developed to handle the various steps of data processing in structural health monitoring. MapReduce implementation is proposed to process sensor data of high volume, high velocity, and high variety. Then, techniques to parallelize structural damage diagnosis and prognosis with uncertainty quantification are developed. Both forward and inverse problems in uncertainty quantification are investigated with this efficient computational approach. Bayesian methods for the inverse problem of diagnosis, and numerical integration techniques such as Markov chain Monte Carlo (MCMC) simulation and Particle Filter (PF) are parallelized via MapReduce. Thirdly, high-dimensional model parameters calibration is performed efficiently using a three-level parallelization, in which spatial and temporal correlation is handled. Finally, parallelization of surrogate model training is developed, considering both response surrogates and distribution surrogates. Among distribution surrogates, a Gaussian mixture model is able to give analytical solutions for prediction and inference, which greatly reduces the cost of calibration of a high-dimensional model with high-volume data.
Advisors/Committee Members: P. K. Basu, Ph.D. (committee member), Daniel Fabbri, Ph.D. (committee member), Douglas Adams, Ph.D. (committee member), Sankaran Mahadevan, Ph.D. (Committee Chair).
Subjects/Keywords: High-dimensional Model Calibration; Bayesian Approaches; MapReduce; Structural Health Monitoring; Big Data Analytics
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APA (6th Edition):
Cai, G. (2017). Big Data Analytics in Structural Health Monitoring. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/14239
Chicago Manual of Style (16th Edition):
Cai, Guowei. “Big Data Analytics in Structural Health Monitoring.” 2017. Doctoral Dissertation, Vanderbilt University. Accessed April 10, 2021.
http://hdl.handle.net/1803/14239.
MLA Handbook (7th Edition):
Cai, Guowei. “Big Data Analytics in Structural Health Monitoring.” 2017. Web. 10 Apr 2021.
Vancouver:
Cai G. Big Data Analytics in Structural Health Monitoring. [Internet] [Doctoral dissertation]. Vanderbilt University; 2017. [cited 2021 Apr 10].
Available from: http://hdl.handle.net/1803/14239.
Council of Science Editors:
Cai G. Big Data Analytics in Structural Health Monitoring. [Doctoral Dissertation]. Vanderbilt University; 2017. Available from: http://hdl.handle.net/1803/14239
Vanderbilt University
7.
Westover, Andrew Scott.
Challenging Conventional Approaches to Energy Storage: Direct Integration of Energy Storage into Solar Cells, the Use of Scrap Metals to Build Batteries, and the Development of Multifunctional Structural Energy Storage Composites.
Degree: PhD, Interdisciplinary Materials Science, 2016, Vanderbilt University
URL: http://hdl.handle.net/1803/14705
► Since the development of batteries by Edison and Volta, energy storage has become an integral part of our technology. As the energy storage devices we…
(more)
▼ Since the development of batteries by Edison and Volta, energy storage has become an integral part of our technology. As the energy storage devices we manufacture, research and develop new energy storage systems has been standardized. This dissertation present three alternative approaches to developing energy storage devices which could completely change the paradigm by which we manufacture and use energy storage. First, I present my work in developing energy storage devices that can be directly integrated into the back of Silicon photovoltaics. This includes initial proof of concept of direct integration of porous Si supercapacitors followed by investigations into high rate faradaic chemical reactions with porous Si and coated porous Si. These faradaic reactions have the possibility of higher energy storage and power matching the performance of silicon photovoltaics. Second, I demonstrate the feasibility of using scrap metals to make high rate batteries that can be paired with photovoltaics by anodizing scrap steel and brass using simple manufacturing methods compatible with do it yourself manufacturing. Third, I will present my work in developing multifunctional structural supercapacitor composites. I demonstrate the ability to measure in-situ the electrochemical response of solid state electrolyte and supercapacitors. I follow this initial work up with the realization of a structural supercapacitor with the mechanical performance approaching that of commercial structural composites and energy storage performance approaching commercial supercapacitors.
Advisors/Committee Members: Jason Valentine (committee member), Shihong Lin (committee member), Amrutur Anilkumar (committee member), Douglas Adams (committee member), Cary L. Pint (Committee Chair).
Subjects/Keywords: Integrated Energy Storage; Scrap Metal Batteries; Photocapacitor; Structural Energy Storage
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APA ·
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Export
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APA (6th Edition):
Westover, A. S. (2016). Challenging Conventional Approaches to Energy Storage: Direct Integration of Energy Storage into Solar Cells, the Use of Scrap Metals to Build Batteries, and the Development of Multifunctional Structural Energy Storage Composites. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/14705
Chicago Manual of Style (16th Edition):
Westover, Andrew Scott. “Challenging Conventional Approaches to Energy Storage: Direct Integration of Energy Storage into Solar Cells, the Use of Scrap Metals to Build Batteries, and the Development of Multifunctional Structural Energy Storage Composites.” 2016. Doctoral Dissertation, Vanderbilt University. Accessed April 10, 2021.
http://hdl.handle.net/1803/14705.
MLA Handbook (7th Edition):
Westover, Andrew Scott. “Challenging Conventional Approaches to Energy Storage: Direct Integration of Energy Storage into Solar Cells, the Use of Scrap Metals to Build Batteries, and the Development of Multifunctional Structural Energy Storage Composites.” 2016. Web. 10 Apr 2021.
Vancouver:
Westover AS. Challenging Conventional Approaches to Energy Storage: Direct Integration of Energy Storage into Solar Cells, the Use of Scrap Metals to Build Batteries, and the Development of Multifunctional Structural Energy Storage Composites. [Internet] [Doctoral dissertation]. Vanderbilt University; 2016. [cited 2021 Apr 10].
Available from: http://hdl.handle.net/1803/14705.
Council of Science Editors:
Westover AS. Challenging Conventional Approaches to Energy Storage: Direct Integration of Energy Storage into Solar Cells, the Use of Scrap Metals to Build Batteries, and the Development of Multifunctional Structural Energy Storage Composites. [Doctoral Dissertation]. Vanderbilt University; 2016. Available from: http://hdl.handle.net/1803/14705
Vanderbilt University
8.
Brubaker, Cole Dylan.
Functionalized Composites for 3D-Printing and Additive Manufacturing Applications.
Degree: PhD, Civil Engineering, 2019, Vanderbilt University
URL: http://hdl.handle.net/1803/15358
► With the ability to shorten production times, while simultaneously minimizing material waste, additive manufacturing technologies and techniques, including 3D printing, have emerged with the potential…
(more)
▼ With the ability to shorten production times, while simultaneously minimizing material waste, additive manufacturing technologies and techniques, including 3D printing, have emerged with the potential to revolutionize the way various materials are produced, utilized and repaired across a growing number of fields and applications. The relative ease and speed at which new parts and prototypes with complicated geometries can be designed and fabricated has driven the need, and continued demand, for 3D printing. In fact, many industry experts have dubbed additive manufacturing and 3D printing related technologies as the fourth industrial revolution – Industry 4.0 – due to its highly disruptive nature in the manufacturing sector. Building upon the recent progress in 3D-printed material systems, the focus of this dissertation revolves around the design, development, characterization, inspection, and implementation of optically enhanced composites through the use of various nano- and micron-scale additives. Specifically, I explore the incorporation of cadmium-based quantum dots, gold nanoparticles, and zinc-based phosphor materials within a polylactic acid (PLA) polymer host matrix to evaluate their compatibility with additive manufacturing applications. Various materials characterizations are performed to study the impact of filament functionalization on the selected additive and polymer host matrix following printing. Additionally, relevant applications and potential end uses for the three material systems are developed, including passive and active devices, to demonstrate the versatility of this approach for designing and developing functionalized materials for additive manufacturing and 3D printing related applications.
Advisors/Committee Members: Sandra Rosenthal (committee member), Sankaran Mahadevan (committee member), Florence Sanchez (committee member), Kane Jennings (Committee Chair), Douglas Adams (Committee Chair).
Subjects/Keywords: Quantum Dots; Gold Nanoparticles; Phosphors; Additive Manufacturing; 3D Printing; Nanotechnology
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APA (6th Edition):
Brubaker, C. D. (2019). Functionalized Composites for 3D-Printing and Additive Manufacturing Applications. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/15358
Chicago Manual of Style (16th Edition):
Brubaker, Cole Dylan. “Functionalized Composites for 3D-Printing and Additive Manufacturing Applications.” 2019. Doctoral Dissertation, Vanderbilt University. Accessed April 10, 2021.
http://hdl.handle.net/1803/15358.
MLA Handbook (7th Edition):
Brubaker, Cole Dylan. “Functionalized Composites for 3D-Printing and Additive Manufacturing Applications.” 2019. Web. 10 Apr 2021.
Vancouver:
Brubaker CD. Functionalized Composites for 3D-Printing and Additive Manufacturing Applications. [Internet] [Doctoral dissertation]. Vanderbilt University; 2019. [cited 2021 Apr 10].
Available from: http://hdl.handle.net/1803/15358.
Council of Science Editors:
Brubaker CD. Functionalized Composites for 3D-Printing and Additive Manufacturing Applications. [Doctoral Dissertation]. Vanderbilt University; 2019. Available from: http://hdl.handle.net/1803/15358
Vanderbilt University
9.
Li, Chenzhao.
Sensitivity Analysis and Uncertainty Integration for System Diagnosis and Prognosis.
Degree: PhD, Civil Engineering, 2016, Vanderbilt University
URL: http://hdl.handle.net/1803/14238
► A system of interest usually consists of some unknown model parameters that affect its output. System diagnosis estimates these model parameters and track their evolution…
(more)
▼ A system of interest usually consists of some unknown model parameters that affect its output. System diagnosis estimates these model parameters and track their evolution if the system is time-dependent. Subsequently, the prognosis predicts the system output at future inputs. An important challenge in diagnosis and prognosis is the presence of various uncertainty sources, such as natural variability, inadequate data, and approximate models. The first challenge is how to integrate the contributions of the different uncertainty sources towards the overall prediction uncertainty; dimension reduction is another challenge in the case of a large number of uncertainty sources; other challenges includes test design, computational efficiency, etc. This dissertation uses the Bayesian network and variance sensitivity analysis as major mathematical tools and develops multiple innovations to solve the aforementioned challenges in system diagnosis and prognosis. Regarding sensitivity analysis, this dissertation proposes a framework to incorporate both aleatory and epistemic uncertainty, and a new sample-based algorithm to significantly improve the computational efficiency. This leads to sensitivity analysis of the Bayesian network for dimension reduction. Regarding uncertainty integration, this dissertation proposes a roll-up method to incorporate the results from multiple uncertainty quantification activities, and a sensitivity-based optimization approach for test design. A dynamic Bayesian network is utilized for the diagnosis and prognosis of time-dependent systems, and illustrated with an aircraft wing digital model to monitor the health status of the wing. A fast Bayesian inference algorithm is also proposed to improve the computational efficiency, thus enabling real-time diagnosis and prognosis for decision support. In sum, this dissertation covers multiple topics in uncertainty quantification and system health monitoring, and the proposed methodologies/algorithms provide valuable breakthroughs for comprehensive uncertainty integration and higher computational efficiency without compromising accuracy.
Advisors/Committee Members: Douglas Adams (committee member), Prodyot Basu (committee member), Caglar Oskay (committee member), Liping Wang (committee member), Sankaran Mahadevan (Committee Chair).
Subjects/Keywords: Sensitivity analysis; Uncertainty integration; diagnosis; prognosis; Bayesian network
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APA (6th Edition):
Li, C. (2016). Sensitivity Analysis and Uncertainty Integration for System Diagnosis and Prognosis. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/14238
Chicago Manual of Style (16th Edition):
Li, Chenzhao. “Sensitivity Analysis and Uncertainty Integration for System Diagnosis and Prognosis.” 2016. Doctoral Dissertation, Vanderbilt University. Accessed April 10, 2021.
http://hdl.handle.net/1803/14238.
MLA Handbook (7th Edition):
Li, Chenzhao. “Sensitivity Analysis and Uncertainty Integration for System Diagnosis and Prognosis.” 2016. Web. 10 Apr 2021.
Vancouver:
Li C. Sensitivity Analysis and Uncertainty Integration for System Diagnosis and Prognosis. [Internet] [Doctoral dissertation]. Vanderbilt University; 2016. [cited 2021 Apr 10].
Available from: http://hdl.handle.net/1803/14238.
Council of Science Editors:
Li C. Sensitivity Analysis and Uncertainty Integration for System Diagnosis and Prognosis. [Doctoral Dissertation]. Vanderbilt University; 2016. Available from: http://hdl.handle.net/1803/14238
Vanderbilt University
10.
Muralidharan, Nitin.
Mechano-Electrochemistry for Advanced Energy Storage and Harvesting Devices.
Degree: PhD, Interdisciplinary Materials Science, 2018, Vanderbilt University
URL: http://hdl.handle.net/1803/12573
► A fundamental perception in the energy storage community is that mechanical processes accompanying electrochemical processes are an unavoidable by-product. However, the coupling between mechanics and…
(more)
▼ A fundamental perception in the energy storage community is that mechanical processes accompanying electrochemical processes are an unavoidable by-product. However, the coupling between mechanics and electrochemistry termed as the ‘mechano-electrochemical coupling’ is a powerful yet unexplored tool. Using principles of elastic strain engineering, we demonstrate controllable modulation of electrochemical parameters governing energy storage systems. Leveraging the shape memory properties of NiTi alloys, redox potentials and diffusion coefficient modulations for energy storage materials were achieved as a function of applied strain. Building off these principles, we developed electrochemical-mechanical energy harvesters for harnessing ambient mechanical energy at very low frequencies (<5 Hz), a regime where the conventional state-of the art piezoelectric and triboelectric energy harvesters have drastically reduced performances. We also highlight frequency tuning capabilities in this class of energy harvesters owing to the inherent differences in various battery electrode chemistries for use in human motion harvesting and sensing applications and multifunctional transient energy harvesting and storage devices. Additionally, to further illustrate the relationship between mechanical and electrochemical properties, we developed multifunctional structural supercapacitor and battery composites for use in load-bearing applications. Overall, these approaches provide paradigm shifting fundamental insights as well as create a framework for developing such multifunctional energy storage/harvesting architectures for a multitude of applications.
Advisors/Committee Members: Dr. Greg Walker (committee member), Dr. Rizia Bardhan (committee member), Dr. Leon Bellan (committee member), Dr. Piran Kidambi (committee member), Dr. Cary Pint (Committee Chair), Dr. Douglas Adams (Committee Chair).
Subjects/Keywords: electrochemical mechanical coupling; energy harvesting; in-situ; strain; stress; mechanical processes; elastic strain engineering; strain setting; substrate strains; shapememory alloy; superelastic; multifunctional energy storage; transient energy harvesters; transient energy storage; pseudocapacitors; supercapacitors; load-bearing; structural; human motion harvesting; modulating electrochemistry; mechano-electrochemistry; advanced energy storage; advanced energy harvesting; low frequency energy harvesting; ambient energy harvesting; electrochemical-mechanical energy harvesting; Nitinol; battery mechanics; strain engineering; energy storage
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APA (6th Edition):
Muralidharan, N. (2018). Mechano-Electrochemistry for Advanced Energy Storage and Harvesting Devices. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/12573
Chicago Manual of Style (16th Edition):
Muralidharan, Nitin. “Mechano-Electrochemistry for Advanced Energy Storage and Harvesting Devices.” 2018. Doctoral Dissertation, Vanderbilt University. Accessed April 10, 2021.
http://hdl.handle.net/1803/12573.
MLA Handbook (7th Edition):
Muralidharan, Nitin. “Mechano-Electrochemistry for Advanced Energy Storage and Harvesting Devices.” 2018. Web. 10 Apr 2021.
Vancouver:
Muralidharan N. Mechano-Electrochemistry for Advanced Energy Storage and Harvesting Devices. [Internet] [Doctoral dissertation]. Vanderbilt University; 2018. [cited 2021 Apr 10].
Available from: http://hdl.handle.net/1803/12573.
Council of Science Editors:
Muralidharan N. Mechano-Electrochemistry for Advanced Energy Storage and Harvesting Devices. [Doctoral Dissertation]. Vanderbilt University; 2018. Available from: http://hdl.handle.net/1803/12573
Vanderbilt University
11.
Bogdanor, Michael James.
Failure Prediction of Fiber Reinforced Composites Using
Reduced Order Multiscale Models.
Degree: PhD, Civil Engineering, 2015, Vanderbilt University
URL: http://hdl.handle.net/1803/14575
► Fiber reinforced polymer (FRP) composites present a significant opportunity for increas- ing performance and energy efficiency in a number of technology sectors, most notably the…
(more)
▼ Fiber reinforced polymer (FRP) composites present a significant opportunity for increas-
ing performance and energy efficiency in a number of technology sectors, most notably the
automotive and aerospace industries. In order to reduce the development costs for FRP ma-
terials, accurate and efficient predictive methods are required which capture the evolution
of damage at the heterogeneous microscale. The goal of this dissertation is to advance the
state of the art in the failure prediction of FRP composites through new multiscale methods
both for the mechanical response and propagation of uncertainty in the material. The contin-
ued development of the eigen-deformation based homogenization method with reduced order
models (EHM) is presented, including a new approach to address the tension-compression
stiffness anisotropy in the fiber direction and a novel parameter weighting method to capture
the disparate damage evolution under uniaxial and shear loading. A blind prediction study
of laminated IM7/977-3 composites using the improved EHM approach is presented for three
composite layups ([0,45,90,-45]2S, [30,60,90,-60,-30]2S, and [60,0,-60]3S) under static tension
and compression and tension-tension fatigue with open hole and unnotched configurations.
Additionally, Bayesian parameter calibration is implemented within the EHM framework to
quantify uncertainty in the composite and is utilized to predict the probabilistic behavior of
laminated composite specimens subject to strain rate-dependent effects.
Advisors/Committee Members: Douglas Adams (committee member), P.K. Basu (committee member), Stephen Clay (committee member), Haoxiang Luo (committee member), Sankaran Mahadevan (committee member), Caglar Oskay (Committee Chair).
Subjects/Keywords: multiscale mechanics; composites; uncertainty quantification; progressive damage; blind prediction
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Bogdanor, M. J. (2015). Failure Prediction of Fiber Reinforced Composites Using
Reduced Order Multiscale Models. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/14575
Chicago Manual of Style (16th Edition):
Bogdanor, Michael James. “Failure Prediction of Fiber Reinforced Composites Using
Reduced Order Multiscale Models.” 2015. Doctoral Dissertation, Vanderbilt University. Accessed April 10, 2021.
http://hdl.handle.net/1803/14575.
MLA Handbook (7th Edition):
Bogdanor, Michael James. “Failure Prediction of Fiber Reinforced Composites Using
Reduced Order Multiscale Models.” 2015. Web. 10 Apr 2021.
Vancouver:
Bogdanor MJ. Failure Prediction of Fiber Reinforced Composites Using
Reduced Order Multiscale Models. [Internet] [Doctoral dissertation]. Vanderbilt University; 2015. [cited 2021 Apr 10].
Available from: http://hdl.handle.net/1803/14575.
Council of Science Editors:
Bogdanor MJ. Failure Prediction of Fiber Reinforced Composites Using
Reduced Order Multiscale Models. [Doctoral Dissertation]. Vanderbilt University; 2015. Available from: http://hdl.handle.net/1803/14575
. 
Open Access Theses and Dissertations