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Articles 1321 - 1350 of 30025
Full-Text Articles in Engineering
Development Of A Homogenized Material Model For Carbon Fiber–Aluminum Transition Joints Using Fea And Optimization, Nicholas M. Couch
Development Of A Homogenized Material Model For Carbon Fiber–Aluminum Transition Joints Using Fea And Optimization, Nicholas M. Couch
All Theses
The integration of metals and composites in automotive structures improves manufacturability and overall structural performance. The proposed Ultrasonic Additive Manufacturing (UAM) joint provides a promising solution for joining aluminum and carbon fiber; however, modeling its behavior across an entire vehicle can be computationally expensive. To address this challenge, a homogenized material card is developed to efficiently capture the joint’s mechanical response while maintaining computational efficiency. A novel characterization method is implemented, employing implicit simulations and optimization techniques to determine the effective material properties of the UAM transition joint. This approach enables rapid iteration of material parameters, facilitating the efficient evaluation …
Hardware And Software Design For A Portable Surgical Training Simulator, Victoria Nelson
Hardware And Software Design For A Portable Surgical Training Simulator, Victoria Nelson
Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research
More than 51 million surgeries are performed on patients annually in the United States. That number grows to 310 million surgeries performed globally each year. Most surgeons go through a minimum of five years of residency – where they train and hone their surgical skills. It is important during this time, and throughout their careers, that they get plenty of practice. Surgical training is time intensive, expensive, and frequently under-resourced. There are finite amounts of surgical training modules for students to share at their facilities. The problem of getting adequate surgical training time continues to exist after surgeons begin their …
A Machine Learning Approach To Detect Pores In Laser Powder Bed Fusion Additive Manufacturing, Jose Galarza, Jose Barron Jr., Luis Jimenez, Tamer Oraby, Jianzhi Li, Farid Ahmed
A Machine Learning Approach To Detect Pores In Laser Powder Bed Fusion Additive Manufacturing, Jose Galarza, Jose Barron Jr., Luis Jimenez, Tamer Oraby, Jianzhi Li, Farid Ahmed
Manufacturing & Industrial Engineering Faculty Publications
Real-time detection of pores in the Laser Powder Bed Fusion (LPBF) metal Additive Manufacturing (AM) process is proposed in this study and can be utilized for in-situ process monitoring and quality control. The average light emission data from the process captured by an optical tomography camera can be integrated into a defect detection module to characterize defects after the deposition of a layer. The light emission contains information on the process zone which could be extracted with the appropriate data techniques. In this paper, we proposed a machine-learning approach that utilizes the mean light intensity data from the melt-pool monitoring …
Modification Of Tini Alloy By Fast Pulse Laser Heat Treatment, Yitao Chen, Mohammad Masud Parvez, Frank Liou
Modification Of Tini Alloy By Fast Pulse Laser Heat Treatment, Yitao Chen, Mohammad Masud Parvez, Frank Liou
Mechanical and Aerospace Engineering Faculty Research & Creative Works
In this study, the effects of local heat treatment with fast pulse laser on thin TiNi shape memory alloy strip materials were investigated. Various materials characterization methods including optical microscope, scanning electron microscope, atomic force microscope, X-ray diffraction, differential scanning calorimetry, and Vickers hardness were used to identify the differences of microstructure, mechanical properties, and functional properties between regions inside and outside the laser-scanned region. The tensile test was also conducted for both the non-laser-scanned specimen and the laser-scanned specimen. The area covered by laser scanning shows great differences by possessing a more homogeneous austenite phase without shear bands and …
Digital Twins, Ai, And Cybersecurity In Additive Manufacturing: A Comprehensive Review Of Current Trends And Challenges, Md Sazol Ahmmed, Laraib Khan, Muhammad Arif Mahmood, Frank Liou
Digital Twins, Ai, And Cybersecurity In Additive Manufacturing: A Comprehensive Review Of Current Trends And Challenges, Md Sazol Ahmmed, Laraib Khan, Muhammad Arif Mahmood, Frank Liou
Mechanical and Aerospace Engineering Faculty Research & Creative Works
The development of Industry 4.0 has accelerated the adoption of sophisticated technologies, including Digital Twins (DTs), Artificial Intelligence (AI), and cybersecurity, within Additive Manufacturing (AM). Enabling real-time monitoring, process optimization, predictive maintenance, and secure data management can redefine conventional manufacturing paradigms. Although their individual importance is increasing, a consistent understanding of how these technologies interact and collectively improve AM procedures is lacking. Focusing on the integration of digital twins (DTs), modular AI, and cybersecurity in AM, this review presents a comprehensive analysis of over 137 research publications from Scopus, Web of Science, Google Scholar, and ResearchGate. The publications are categorized …
Technology-Enabled Foreign Object (Fo) Prevention, Christopher Lee Colaw
Technology-Enabled Foreign Object (Fo) Prevention, Christopher Lee Colaw
Open Access Theses & Dissertations
The aviation industry incurs $14 billion per year in cost due to Foreign Object (FO) damage and the prevention and resolution techniques associated with foreign object debris. While aircraft loss, material scrap and rework contribute to that cost impact, a traditional approach to aircraft design and manufacturing which is based on human performance is also a significant driver. Failure modes and effects analysis of human based aircraft manufacturing reveals that two of the largest risks are associated with unknown potential for FO creation and the inability to recall or objectively provide evidence of FO conformity for cases of inquiry, learning, …
Elucidation Of Nano-Mechanical Property Evolution Of 3d-Printed Zirconia, Diana Hazel Leyva Marquez
Elucidation Of Nano-Mechanical Property Evolution Of 3d-Printed Zirconia, Diana Hazel Leyva Marquez
Open Access Theses & Dissertations
This dissertation presents an in-depth look at the mechanical behavior, size changes, and process improvement of ceramic and polymer materials made with additive manufacturing (AM). The work consists of four separate but related studies, each tackling important challenges in fabrication, characterization, and predictive modeling. Chapter 1 examines the nano-mechanical property changes of 3D-printed zirconia made using digital light processing (DLP). By employing nanoindentation and scanning electron microscopy (SEM), the effects of print orientation and sintering on hardness, elastic modulus, and microstructure are revealed. The results indicate that 0°-oriented sintered samples have up to 140% higher hardness compared to preconditioned samples, …
Human Comfort Modeling, Measurement, And Improvement In Human–Robot Collaboration, Yuchen Yan
Human Comfort Modeling, Measurement, And Improvement In Human–Robot Collaboration, Yuchen Yan
All Dissertations
A dissertation is proposed to explore human comfort in human-robot collaboration (HRC) through modeling, prediction, and enhancement methodologies. Human comfort is a crucial yet underexplored factor in HRC, directly influencing task efficiency, trust, and overall collaboration effectiveness. Understanding the influential factors, developing computational models, and refining methods to improve human comfort in HRC are essential steps toward advancing the field of collaborative robotics. To address these challenges, multiple studies have been conducted. A series of experimental studies were performed to investigate how robot motion-based parameters affect human comfort in HRC. These studies examined both analytical comfort modeling approaches and physiological …
Experimental Evaluation And Comparison Of Football-Related Head Impacts Among Ovine, Human, And Hybrid Iii Headforms, Madysn D. Cardinal
Experimental Evaluation And Comparison Of Football-Related Head Impacts Among Ovine, Human, And Hybrid Iii Headforms, Madysn D. Cardinal
All Dissertations
Concussions and traumatic brain injury (TBI) remains a significant public health concern, especially in American football, where repeated head impacts pose long-term risks to athlete health. While current helmet testing standards rely heavily on the Hybrid III surrogate headform to evaluate protective performance, these surrogate models lack anatomical accuracy and exclude the presence of a brain component, limiting their ability to capture the true mechanics of concussion. To address this limitation, this research developed and validated a novel inverted impact testing method that allows the impact testing of a Hybrid III headform and a cadaveric specimen. Additionally, this fixture preserves …
Enhanced Point Cloud Generation From A Novel 360° Underwater Lidar, Olagoke E. Daramola
Enhanced Point Cloud Generation From A Novel 360° Underwater Lidar, Olagoke E. Daramola
Dissertations
This dissertation presents novel algorithms to improve the mapping capabilities of a 360-degree underwater Pulsed Laser Line Scanner LiDAR (PLLS-360°). Due to its 360° field-of-view (FOV), the PLLS-360° is a compact full-waveform omnidirectional imager suitable for seafloor mapping, underwater asset inspection, object detection, ice-sheet mapping, and construction progress monitoring. The proposed methodology includes an improved waveform fitting technique for saturated waveform recovery, detection array response correction, radiometric corrections, and fusion of LiDAR and sonar bathymetric datasets. The first part of this dissertation assesses the LiDAR’s performance and describes how the data for this unique 360° FOV architecture is processed. The …
Mass Effects On Energy Transfer Paths In Nonlinear Vibrating Systems, Manal Mustafa
Mass Effects On Energy Transfer Paths In Nonlinear Vibrating Systems, Manal Mustafa
Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–
This dissertation examines the role of mass in nonlinear systems, uncovering its role in enabling passive energy redistribution and robust vibration control in both idealized and real-world structures. Focusing on a strongly nonlinear two-degree-of-freedom system, it investigates how changes in mass ratio influence the dynamics of energy transfer, nonlinear normal modes (NNMs), and dissipation behavior.
A number of significant contributions are introduced in this work beginning with the introduction of the frequency-energy-peaks (FE-pks) plot, a novel tool that visualizes how energy flows through the system, revealing transient resonance orbits, internal resonance effects, and effectively capturing the different nonlinear phenomena with …
The Advancement Of Automation In Beef Packaging Pack-Off Systems, Matthew Newman
The Advancement Of Automation In Beef Packaging Pack-Off Systems, Matthew Newman
Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–
Marble Technologies has developed a new system for beef, pork, and lamb producers that improves quality and worker experience in the packing of products. This work explores the augmentation of this system with the introduction of robotic packing to further reduce labor, increasing worker availability for value-added tasks.
Experimentation conducted to date has explored handling delicate meat products in the standard Marble system and the proposed robotic systems. These mechanical subsystems are critical intermediaries in safely and reliably delivering products to robots and from robots to boxes. Two case studies are presented to walk through the process and challenges of …
Decoding Anisotropic Porous Medium: A Synergy Of Lattice Boltzmann Modelling And Operator Learning To Predict Permeability As A Function Of Orientation, Soumya Shouvik Bhattacharjee
Decoding Anisotropic Porous Medium: A Synergy Of Lattice Boltzmann Modelling And Operator Learning To Predict Permeability As A Function Of Orientation, Soumya Shouvik Bhattacharjee
Open Access Theses & Dissertations
Understanding the directional properties of porous media is essential for accurately predicting flow behavior, reactive transport, and fluid-solid interactions in systems ranging from geothermal reservoirs to energy storage devices and biological tissues. Directional variations in permeability - reflecting a medium's response to flow at different angular orientations - are particularly important for complex, inherently anisotropic geometries. In this study, we employ a Lattice Boltzmann (LBM) model to calculate directional permeabilities from porous media images subjected to varying flow inlet angles. Three classes of porous media were investigated: (1) synthetic media with circular grains, serving as isotropic baselines; (2) synthetic media …
Modeling And Characterization Of Additively Manufactured Barium Titanate Ceramic, Luz Irene Bugarin
Modeling And Characterization Of Additively Manufactured Barium Titanate Ceramic, Luz Irene Bugarin
Open Access Theses & Dissertations
This dissertation investigates the influence of geometric design on the mechanical properties of BTO structures fabricated via 3D printing. Using finite element modeling (FEM), we simulate mechanical stress responses across a range of architected designs. Results reveal that specific design strategies can significantly enhance performance by promoting favorable stress distributions. This work highlights the critical role of structural design in optimizing functional ceramics and provides a computational framework for the design of next-generation piezoelectric devices.
A Digital Engineering Framework For Ai-Driven Trade-Off Evaluation And Predictive Component Classification, Alejandro Silva Au
A Digital Engineering Framework For Ai-Driven Trade-Off Evaluation And Predictive Component Classification, Alejandro Silva Au
Open Access Theses & Dissertations
This thesis introduces a digital engineering tool designed to help engineers make smarter decisions when choosing actuators. At its core, the system brings together machine learning (specifically XGBoost) and a decision-making method called Multi-Utility Attribute Theory (MUAT). The goal is to support engineers in picking components based on what really matters for their designs, whether that's speed, cost, durability, or any other performance factor. What makes this tool stand out is its user-friendly interface that lets people interact with the system directly. It takes a set of actuator performance data, classifies each one into a relevant use category, and then …
Shape Memory Behavior In Medium To High Entropy Shape Memory Alloys: Design, Prediction, And Experimental Analysis, Hatim Raji
Theses and Dissertations
This dissertation provides a data-driven system integrating synthetic data generation and machine learning (ML) techniques to create multicomponent SMA compositions with specific transformation temperatures (TTs). Models were trained to represent the nonlinear dependencies influencing martensitic transformation behavior by using elemental, thermodynamic, and process-related aspects. The capacity of the ML models on medium entropy NiTiHfPd and high entropy NiTiHfZrCu systems accuracy was confirmed by experimental validation showing TTs closely matched with model outputs.
Bilateral Leading Edges With Tubercle Modifications: An Experimental Study, Roberto Sanchez
Bilateral Leading Edges With Tubercle Modifications: An Experimental Study, Roberto Sanchez
Theses and Dissertations
The increasing demand for better performance and maneuverability from airfoils to sustain superior performance over a wide range of platforms, including vehicles, propellers, and wing designs, continues to grow. Researchers have drawn inspiration from nature, looking at birds of prey, dragonflies, and humpback whales for aerodynamic improvements. Among these, tubercle airfoils, inspired by the humpback whale’s flipper, have gained increasing interest. This experimental study presents the results of bilateral tubercle leading-edge airfoils based on a modified NACA 0018 design with a chord length of 1.82 inches, a span width of 7.5 inches, and an amplitude of 6.3c%. Five configurations were …
Primary And Parametric Resonances Of Angled Mems And Nems Cantilever Resonators, Benjamin Matthew Huerta
Primary And Parametric Resonances Of Angled Mems And Nems Cantilever Resonators, Benjamin Matthew Huerta
Theses and Dissertations
This work investigates the resonances of electrostatically actuated micro- and nano-electromechanical systems (MEMS/NEMS) uniform cantilever resonators positioned at an angle relative to a ground plate. The resonances considered in this work include primary and parametric resonance. For each resonance, the amplitude-frequency and amplitude-voltage responses are presented. The model is constructed using Euler-Bernoulli beam theory. Results are obtained by construction of a Reduced Order Model considering up to the first five modes of vibration. The Method of Multiple Scales is used when considering only the first mode shape, and the software AUTO 07p is used for higher terms. Two models are …
3d Printing Of Short Fiber Reinforced Polypropylene: Novel Lattice Architecture And Material Characterization, Mohammad Ghazi Alshneeqat
3d Printing Of Short Fiber Reinforced Polypropylene: Novel Lattice Architecture And Material Characterization, Mohammad Ghazi Alshneeqat
Theses
This study explores the enhanced compressive behavior of 3D-printed single and double gyroid solid-networks lattices. Where the double gyroids are constructed from two intertwined single gyroid structures. These structures were designed by nTop implicit modeling tool and then fabricated by material extrusion additive manufacturing method at optimized printing parameters, including optimized nozzle temperature and raster angle. The main objective of this study is to reveal the compressive behavior of the novel double gyroid lattice structure and then to tailor its response through variable gyroid heights. Standard polymer tests were performed, considering thermogravimetric analysis, to confirm the thermal stability of the …
Decision Field Theory For Human-Multi-Robot Collaboration: Human-Centric Decision-Making For Multi-Robot Systems, Ryan Mbagna Nanko
Decision Field Theory For Human-Multi-Robot Collaboration: Human-Centric Decision-Making For Multi-Robot Systems, Ryan Mbagna Nanko
All Theses
At first glance, choosing between an apple and an orange appears to be a straightforward matter of personal taste; however, this seemingly simple preference opens a window into the multifaceted world of decision-making, revealing the complex interplay of cognitive processes, psychological, and behavioral-economic principles that guide our choices \cite{bandyopadhyayRoleAffectDecision2013}. By unpacking these nuanced perspectives, we uncover insights that can drive more effective human-robot interaction and collaboration.
Modeling human cognition requires understanding the evolution of choice utility and the influence of emotions. Decision Field Theory (DFT) stands out by capturing the fluctuating nature in human preferences over time, explaining why choices …
Advancing Multi-Physics Modeling For Microwave Heating: Application In Micro-Reactor Design And Optimization, Raghav Adhikari
Advancing Multi-Physics Modeling For Microwave Heating: Application In Micro-Reactor Design And Optimization, Raghav Adhikari
All Theses
Microreactors are a type of small-scale chemical reactors for achieving reduced volume, improved product selectivity and higher reaction rate. It allows precise temperature control, which is crucial for sensitive chemical processes. Microreactors can be employed as key components of conducting small-scale reactions with improved reactor configuration and process efficiency. It is important to identify a localized and precise heating mechanism to trigger and control the corresponding chemical reactions.
In fact, microwave heating has gathered significant attention in recent years due to its ability to deliver efficient, rapid, and localized heating, which can accelerate reaction rates and enhances the reaction selectivity. …
Advancing Life Cycle Assessment For Environmental Sustainability Of Carbon Fiber-Reinforced Polymer Composites (Cfrps)), Hao Chen
All Dissertations
Carbon fiber-reinforced polymer composites (CFRPs) have emerged as promising materials, particularly for lightweight applications, with the potential to reduce environmental impacts across multiple sectors, including automotive, aerospace, and renewable energy. However, fully realizing their sustainability potential requires a more comprehensive and context-specific understanding of their environmental performance throughout the entire life cycle—from raw material production to end-of-life management.
This dissertation advances life cycle assessment (LCA) practices for CFRPs by addressing key challenges across multiple phases of the CFRP life cycle. First, I conducted a critical review and meta-analysis of carbon fiber manufacturing, revealing substantial variability in reported data on energy …
Synergistic Enhancement Of Tribological Behavior And Colloidal Stability In Cuo Nanolubricants Via Ligand Tuning, Sherif Elsoudy, Sayed Akl Akl Dr, Sayed Akl A. Akl Dr, Esm Lane, Abas Hadawey, Philip D. Howes
Synergistic Enhancement Of Tribological Behavior And Colloidal Stability In Cuo Nanolubricants Via Ligand Tuning, Sherif Elsoudy, Sayed Akl Akl Dr, Sayed Akl A. Akl Dr, Esm Lane, Abas Hadawey, Philip D. Howes
Mechanical Engineering
Nanoparticle-based lubricants, or nanolubricants, can exhibit superior tribological properties compared to unmodified base oils. However, these performance gains are highly dependent on the nanoparticle surface chemistry, particularly in maintaining stable colloidal dispersions. This study explores the influence of oleic acid (OA) and oleylamine (OAm) functionalization on the tribological and colloidal properties of CuO nanoparticles dispersed in an SAE 20W50 base oil. We present a hybrid optimization framework combining Response Surface Methodology (RSM) with Bayesian Optimization (BO) to identify the optimal OA to OAm ratio (OA–OAm) for CuO nanolubricants. Unlike prior studies that employed either RSM alone or trial-and-error approaches, this …
Inter-Cellular Forces Modulate Cell-Ecm Traction Forces, Zaria Booth
Inter-Cellular Forces Modulate Cell-Ecm Traction Forces, Zaria Booth
Mechanical & Aerospace Engineering Theses & Dissertations
Epithelial cells are among the most abundant cell types in the human body, making up sheets of epithelial tissues that cover the linings of organs and body cavities. Cellular adhesion and force transmission across epithelial tissues are crucial in maintaining tissue integrity and ensuring proper tissue regeneration. Defects in cellular force transmission have been found in various diseases, including cancer. Force transmission at cell-cell and cell-ECM junctions drive cell survival and development. It has been previously shown that changes in cell-ECM traction directly modulates forces at cell-cell contacts. In this study, we aim to determine the effects of perturbations in …
Towards Improving Computational Modeling Of The Lumbar Spine - Impact Of Material Properties And Laminotomy On Spinal Biomechanics, Isaac K. Kumi
Towards Improving Computational Modeling Of The Lumbar Spine - Impact Of Material Properties And Laminotomy On Spinal Biomechanics, Isaac K. Kumi
Mechanical & Aerospace Engineering Theses & Dissertations
Spinal ligaments play a crucial role in maintaining the mechanical stability of the lumbar spine. These dense, collagenous tissues not only resist excessive motion but also distribute loads between spinal components to protect neural structures. Traditionally, the mechanical response of ligaments has been modeled using linear elastic assumptions, which treat the tissue as having a constant stiffness regardless of loading history. While this simplifies analysis, it fails to capture the time-dependent behaviors, such as creep, stress relaxation, and hysteresis, that are characteristic of biological tissues.
Viscoelastic modeling may provide a more physiologically accurate representation by incorporating both elastic and viscous …
Microstructural Investigation Of Graphene Reinforced Nickel Aluminum Bronze Prepared Via Laser Powder Bed Fusion, Wen Qian, Maxwyll Mcconnell, Jazmin Ley, Luke Schwaninger, Xin Chen, Bai Cui, Joseph A. Turner
Microstructural Investigation Of Graphene Reinforced Nickel Aluminum Bronze Prepared Via Laser Powder Bed Fusion, Wen Qian, Maxwyll Mcconnell, Jazmin Ley, Luke Schwaninger, Xin Chen, Bai Cui, Joseph A. Turner
Mechanical Engineering Faculty Publications
Nickel aluminum bronze (NAB) powders coated with reduced graphene oxide (RGO) were successfully fabricated using additive manufacturing (AM) via laser powder bed fusion. The resulting samples were characterized using a suite of complementary techniques, including x-ray diffraction, scanning electron microscopy, energy-dispersive x-ray spectroscopy, nanoindentation, x-ray computed tomography, and electron backscatter diffraction. These methods were employed to reveal the micro- and nanoscale features within the fine dendritic microstructure. The as-fabricated microstructures were observed to deviate significantly from typical as-cast configurations. In the AM RGO-coated NAB specimens, the formation of the κI phase was notably suppressed and is attributed to the …
Impact Of Humidity From Shrink (Wrap) Tunnels On Refrigeration Systems: Comparing Economic And Environmental Impact Of Natural Gas And Electric, Segun Samuel Oladipo
Impact Of Humidity From Shrink (Wrap) Tunnels On Refrigeration Systems: Comparing Economic And Environmental Impact Of Natural Gas And Electric, Segun Samuel Oladipo
Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research
This thesis examines the economic and environmental effects of electric and steam shrink-wrapping tunnels used in beef packaging processes, paying particular attention to the indirect refrigeration loads caused by the heat and humidity that each system releases. Traditional sustainability evaluations frequently ignore these indirect impacts, which are especially important in meat processing facilities where 45–55% of electricity use is attributed to refrigeration. Life cycle assessment (LCA), field measurements, and thermodynamic modeling are all used in this work to offer a thorough analysis of both tunnel types.
The case study facility in Nebraska operates both steam and electric shrink tunnels to …
Advancing Real-World Implementation Of The Well Optimized Linear Finder (Wolf) High-Speed Atmospheric Turbulence Compensation Method, Timothy Evan Coon
Advancing Real-World Implementation Of The Well Optimized Linear Finder (Wolf) High-Speed Atmospheric Turbulence Compensation Method, Timothy Evan Coon
Theses and Dissertations
This dissertation advances the real-world implementation of the Well Optimized Linear Finder (WOLF) method for high-speed Atmospheric Turbulence Compensation (ATC). Atmospheric turbulence introduces phase aberrations into optical wavefronts and degrades image quality in terrestrial imaging systems. Traditional phase diversity methods are computationally intensive and poorly suited to real-time operation. The WOLF method addresses these limitations through a novel, point-wise formulation of the optical transfer function (OTF) as a structured autocorrelation of the generalized pupil function (GPF). This formulation enables the estimation of phase aberrations at individual spatial coordinates with distributed computational complexity.
The research begins by developing a MATLAB-based simulation …
Exploring Methods For Quantifying Uncertainty In Neural Network-Based Turbulence Closures, Cody Grogan
Exploring Methods For Quantifying Uncertainty In Neural Network-Based Turbulence Closures, Cody Grogan
All Graduate Theses and Dissertations, Fall 2023 to Present
Machine Learning (ML) is a very promising field for data-driven modeling of different phenomena. In the field of Computational Fluid Dynamics (CFD), ML is an enticing alternative to traditional methods to improve the accuracy and computational efficiency of simulations. However, many ML models, like Neural Networks, don’t quantify their uncertainty or indicate their confidence in a prediction to those who wish to use them. This is especially important because the use of inaccurate ML predictions in a CFD simulation can greatly impact the validity of a simulation. However, with uncertainty quantification, an ML model can indicate to a modeler the …
A Provable Semi-Infinite Programming Approach For Solving Dynamic Nash Games, Tyler C. Gardner
A Provable Semi-Infinite Programming Approach For Solving Dynamic Nash Games, Tyler C. Gardner
All Graduate Theses and Dissertations, Fall 2023 to Present
Many engineering problems must account for the non-cooperative decisions and actions of multiple players. These problems can be modeled within a game-theoretic framework. The approach herein is to model problems as Nash games, convert them to semi-infinite programs, and leverage provable semi-infinite algorithms to solve the original problem. A particular algorithm that leverages off-the-shelf solvers is used to solve four low-dimensional benchmark problems successfully. Two types of linear quadratic dynamic games are then investigated: ones where each player’s problem is convex and ones where at least one player’s problem is nonconvex. Within each type, variations based on information structure, communication …