Engineering Commons^™

Parametric Structural Optimization Of A Wheel Using The Flex Representation Method, Gregory John Vernon

Theses and Dissertations

The use of the finite element method within an optimization workflow is fraught with challenges that limit the automation of such workflows. These challenges are inherent to the traditional finite element formulations which are heavily dependent on a manual meshing process that introduces variability that is challenging to account for within an automated workflow. The recently developed flex representation method (FRM) provides a salient solution to the manual meshing process without sacrificing solution accuracy. In response to the development of FRM a global automotive company requested a study to explore the applicability of FRM to one of their sizing-optimization problems: …

Applying Hls To Fpga Data Preprocessing In The Advanced Particle-Astrophysics Telescope, Meagan Konst

McKelvey School of Engineering Theses & Dissertations

The Advanced Particle-astrophysics Telescope (APT) and its preliminary iteration the Antarctic Demonstrator for APT (ADAPT) are highly collaborative projects that seek to capture gamma-ray emissions. Along with dark matter and ultra-heavy cosmic ray nuclei measurements, APT will provide sub-degree localization and polarization measurements for gamma-ray transients. This will allow for devices on Earth to point to the direction from which the gamma-ray transients originated in order to collect additional data. The data collection process is as follows. A scintillation occurs and is detected by the wavelength-shifting fibers. This signal is then read by an ASIC and stored in an ADC …

Analyzing The Supply Chain Operation Of A Fast-Food Restaurant Using Simulation Modeling And Developing A Cost Estimation Optimization Model In The Disruption Period, Amit Kumar Saha

Open Access Theses & Dissertations

Supply chain operation performance is a much-discussed topic over the last decade which will lead to optimizing the resources required to provide the necessary level of customer service to a specific segment and improve customer service through increased product availability and reduced order cycle time. During disruption in supply chain, performance parameter changes, and the overall supply chain cost at each stage increases. External factors such as labor shortages, delayed and costly supplies, and decreased demand also contribute to this cost. This thesis work presents a research-focused analysis of a small pizza shop, under circumstances that include the loss of …

Multi-Objective Optimization Of The Fast Neutron Source By Machine Learning, John L. Pevey

Doctoral Dissertations

The design and optimization of nuclear systems can be a difficult task, often with prohibitively large design spaces, as well as both competing and complex objectives and constraints. When faced with such an optimization, the task of designing an algorithm for this optimization falls to engineers who must apply engineering knowledge and experience to reduce the scope of the optimization to a manageable size. When sufficient computational resources are available, unsupervised optimization can be used.

The optimization of the Fast Neutron Source (FNS) at the University of Tennessee is presented as an example for the methodologies developed in this work. …

An Application Of Optimized Bistable Laminates As A Low Velocity, Low Impact Mechanical Deterrent, Graham Lancaster

All Theses

This research considers the problem of using bistable laminates as a mechanical deterrent to the impending impact of a particle. The structure will be controlled through an algorithm that will utilize piezoelectric devices to activate them in unison with the bistable laminate to successfully deter. A novel experimental setup will be constructed to ensure that the bistable laminate stays fixed when acting as a mechanical deterrent. Piezoelectricity is the main driving force of the bistable laminate to morph and this study will use a Macro Fiber Composite (MFC) actuator that contains piezoelectric ceramic rods in a patch to transfer electrical …

Multi-Fidelity Predictions For Control Allocation On The Nasa Ikhana Research Aircraft To Minimize Drag, Justice T. Schoenfeld

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Optimal control settings (camber scheduling) can be used by aircraft to minimize drag at various operating conditions during flight. In this work, camber schedules for minimum drag on the NASA Ikhana are obtained over a range of lift coefficients. A modern numerical lifting-line algorithm is used to predict the lift and drag of the aircraft as a function of operating condition and wing section shape (airfoil camber). The SLSQP optimization algorithm is used to solve for the camber schedule that minimizes drag for a given operating condition. The process is repeated, varying the number of control sections to evaluate the …

Essays On Perioperative Services Problems In Healthcare, Amogh S. Bhosekar

All Dissertations

One of the critical challenges in healthcare operations management is to efficiently utilize the expensive resources needed while maintaining the quality of care provided. Simulation and optimization methods can be effectively used to provide better healthcare services. This can be achieved by developing models to minimize patient waiting times, minimize healthcare supply chain and logistics costs, and maximize access. In this proposal, we study some of the important problems in healthcare operations management. More specifically, we focus on perioperative services and study scheduling of operating rooms (ORs) and management of necessary resources such as staff, equipment, and surgical instruments. We …

Hybrid Machine Learning And Physics-Based Modeling Approaches For Process Control And Optimization, Junho Park

Theses and Dissertations

Transformer neural networks have made a significant impact on natural language processing. The Transformer network self-attention mechanism effectively addresses the vanishing gradient problem that limits a network learning capability, especially when the time series gets longer or the size of the network gets deeper. This dissertation examines the usage of the Transformer model for time-series forecasting and customizes it for a simultaneous multistep-ahead prediction model in a surrogate model predictive control (MPC) application. The proposed method demonstrates enhanced control performance and computation efficiency compared to the Long-short term memory (LSTM)-based MPC and one-step-ahead prediction model structures for both LSTM and …

Multiple Objective Function Optimization And Trade Space Analysis, Yifan Xu

All Theses

Optimization can assist in obtaining the best possible solution to a design problem by varying related variables under given constraints. It can be applied in many practical applications, including engineering, during the design process. The design time can be further reduced by the application of automated optimization methods. Since the required resource and desired benefit can be translated to a function of variables, optimization can be viewed as the process of finding the variable values to reach the function maxima or minima. A Multiple Objective Optimization (MOO) problem is when there is more than one desired function that needs to …

Mitigating Popularity Bias In Recommendation With Unbalanced Interactions: A Gradient Perspective, Weijieying Ren, Lei Wang, Kunpeng Liu, Ruocheng Guo, Ee-Peng Lim, Yanjie Fu

Research Collection School Of Computing and Information Systems

Recommender systems learn from historical user-item interactions to identify preferred items for target users. These observed interactions are usually unbalanced following a long-tailed distribution. Such long-tailed data lead to popularity bias to recommend popular but not personalized items to users. We present a gradient perspective to understand two negative impacts of popularity bias in recommendation model optimization: (i) the gradient direction of popular item embeddings is closer to that of positive interactions, and (ii) the magnitude of positive gradient for popular items are much greater than that of unpopular items. To address these issues, we propose a simple yet efficient …

Cooperative Wide Area Search Algorithm Analysis Using Sub-Region Techniques, Shawn Whitney

Theses and Dissertations

Recent advances in small Unmmaned Aerial Vehicle (UAV) technology reinvigorates the need for additional research into Wide Area Search (WAS) algorithms for civilian and military applications. But due to the extremely large variability in UAV environments and design, Digital Engineering (DE) is utilized to reduce the time, cost, and energy required to advance this technology. DE also allows rapid design and evaluation of autonomous systems which utilize and support WAS algorithms. Modern WAS algorithms can be broadly classified into decision-based algorithms, statistical algorithms, and Artificial Intelligence (AI)/Machine Learning (ML) algorithms. This research continues on the work by Hatzinger and Gertsman …

Aeroacoustic Analyses For Noise Reduction Application, Mahmoud M. Abdalmola

Mechanical Engineering Theses

In this study, we examine the hypothesis that airflow noise can be reduced by adding metamaterials. The introduction of any obstacle will generate more disturbance in the airflow and therefore add noise. Hence an efficient metamaterial design is required, capable of reducing noise even at higher flow disturbance. In order to examine this hypothesis, we developed a platform to perform isogeometric aeroacoustic analyses to solve Navier stokes equations first. We obtained the velocity fields from fluid-structure analyses and utilized the light-hill analogy to calculate the noise generated as a result of airflow. Then the Helmholtz equation was solved to perform …

Optimizing Transportation Systems With Information Provision, Personalized Incentives And Driver Cooperation, Sayeeda Ayaz

Doctoral Dissertations

Poor performance of the transportation systems has many detrimental effects such as higher travel times, increased travel costs, higher energy consumption, and greenhouse gas emissions, etc. This thesis optimizes the transportation systems by addressing the traffic congestion problem and climate change impact resulting from the inefficient operation of these systems. I first focus on the key player of the transportation systems e.g., human being/traveler, and model travelers' route choice behavior with real-time information. In this study, I define looking-ahead behavior in route choice as a traveler's taking into account future diversion possibilities enabled by real-time information in a network with …

Optimal Synthesis Of Crank-Rocker Mechanisms With Optimum Transmission Angle For Desired Stroke And Time-Ratio Using Genetic Programming, Bahman Ahmadi, Behnam Ahmadi

Michigan Tech Publications

Dimensional synthesis of crank-rocker mechanisms applied to provide some desired values of stroke and time ratio, is of utmost importance for designing an efficient mechanism. In the synthesis and manufacturing of crank-rocker mechanisms, the designers are further challenged by other design criteria, such as quality of motion. In this study, a novel approach based on genetic programming (GP) is proposed for dimensional synthesis of planar crank-rocker mechanisms with optimum transmission angle over the desired stroke and time-ratio. An analytical approach is elaborated which leads to an interesting relationship of length of the coupler and rocker links. It is, therefore, advised …

A Comparative Performance Analysis Of The Novel Turboaux Engine With A Turbojet Engine, And A Low-Bypass Ratio Turbofan Engine With An Afterburner, Kaleab Fetahi, Sharanabasaweshwara A. Asundi, Arthur C. Taylor

Mechanical & Aerospace Engineering Faculty Publications

Presented herein is a comparative performance analysis of a novel turbofan engine with an auxiliary combustion chamber, nicknamed the TurboAux engine, against a turbojet engine, and a low bypass ratio turbofan engine with an afterburner is presented. The TurboAux engine is an adaption of the low-bypass ratio turbofan engine, but with secondary combustion in an auxiliary bypass annular combustion chamber for thrust augmentation. The TurboAux engine is envisioned with the desire to facilitate clean secondary burning of fuel at temperatures higher than in the main combustion chamber with air exiting the low-pressure compressor. The comparative study starts by analyzing the …

Design Of Solvent-Assisted Plastics Recycling: Integrated Economics And Environmental Impacts Analysis, Austin L. Lehr, Kayla L. Heider, Emmanuel A. Aboagye, John D. Chea, Jake P. Stengel, Pahola Thathiana Benavides, Kirti M. Yenkie

Henry M. Rowan College of Engineering Faculty Scholarship

In 2018, the United States generated over 35. 7 million tons of plastic waste, with only 8.4% being recycled and the other 91.6% incinerated or disposed of in a landfill. The continued growth of the polymer market has raised concerns over the end of life of plastics. Currently, the waste management system is faced with issues of inefficient sorting methods and low-efficiency recycling methods when it comes to plastics recycling. Mechanical recycling is the commonest recycling method but presents a lower-valued recycled material due to the material incompatibilities introduced via the inefficient sorting methods. Chemical recycling offers a promising alternative …

Low-Reynolds-Number Locomotion Via Reinforcement Learning, Yuexin Liu

Dissertations

This dissertation summarizes computational results from applying reinforcement learning and deep neural network to the designs of artificial microswimmers in the inertialess regime, where the viscous dissipation in the surrounding fluid environment dominates and the swimmer’s inertia is completely negligible. In particular, works in this dissertation consist of four interrelated studies of the design of microswimmers for different tasks: (1) a one-dimensional microswimmer in free-space that moves towards the target via translation, (2) a one-dimensional microswimmer in a periodic domain that rotates to reach the target, (3) a two-dimensional microswimmer that switches gaits to navigate to the designated targets in …

Model-Based Deep Learning For Computational Imaging, Xiaojian Xu

McKelvey School of Engineering Theses & Dissertations

This dissertation addresses model-based deep learning for computational imaging. The motivation of our work is driven by the increasing interests in the combination of imaging model, which provides data-consistency guarantees to the observed measurements, and deep learning, which provides advanced prior modeling driven by data. Following this idea, we develop multiple algorithms by integrating the classical model-based optimization and modern deep learning to enable efficient and reliable imaging. We demonstrate the performance of our algorithms by validating their performance on various imaging applications and providing rigorous theoretical analysis.

The dissertation evaluates and extends three general frameworks, plug-and-play priors (PnP), regularized …

Developing Novel Optimization And Machine Learning Frameworks To Improve And Assess The Safety Of Workplaces, Amin Aghalari

Theses and Dissertations

This study proposes several decision-making tools utilizing optimization and machine learning frameworks to assess and improve the safety of the workplaces. The first chapter of this study presents a novel mathematical model to optimally locate a set of detectors to minimize the expected number of casualties in a given threat area. The problem is formulated as a nonlinear binary integer programming model and then solved as a linearized branch-and-bound algorithm. Several sensitivity analyses illustrate the model's robustness and draw key managerial insights. One of the prevailing threats in the last decades, Active Shooting (AS) violence, poses a serious threat to …

Power Market Cybersecurity And Profit-Targeting Cyberattacks, Qiwei Zhang

Doctoral Dissertations

The COVID-19 pandemic has forced many companies and business to operate through remote platforms, which has made everyday life and everyone more digitally connected than ever before. The cybersecurity has become a bigger priority in all aspects of life. A few real-world cases have demonstrated the current capability of cyberattacks as in [1], [2], and [3]. These cases invalidate the traditional belief that cyberattacks are unable to penetrate real-world industrial systems. Beyond the physical damage, some attackers target financial arbitrage advantages brought by false data injection attacks (FDIAs) [4]. Malicious breaches into power market operations could induce catastrophic consequences on …

Optimization Of Lattice Structure Using Machine Learning Approach, Tanzila Bint Minhaj

Open Access Theses & Dissertations

The goal line of designing any structure is to get maximum performance at minimum cost. Therefore, optimization is the only method to achieve that objective. Engineers have been practicing different formats of optimization. Topological optimization is one of the well-known long-practiced methods. But it is always desired to find the most helpful design method that considers every relevant parameter associated with the structure. In the continuation of this search to enhance the efficacy of design through optimization, a new approach was explored in the following work. The motivation was to enable a model to be capable of finding out the …

Optimal Global Supply Chain And Warehouse Planning Under Uncertainty, Avnish Kishor Malde

All Dissertations

A manufacturing company's inbound supply chain consists of various processes such as procurement, consolidation, and warehousing. Each of these processes is the focus of a different chapter in this dissertation.

The manufacturer depends on its suppliers to provide the raw materials and parts required to manufacture a finished product. These suppliers can be located locally or overseas with respect to the manufacturer's geographic location. The ordering and transportation lead times are shorter if the supplier is located locally. Just In Time (JIT) or Just In Sequence (JIS) inventory management methods could be practiced by the manufacturer to procure the raw …

Control Mapping Methodology For Tailless Morphing-Wing Aircraft, Zachary S. Montgomery

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Advanced aircraft designs tend to have several control surfaces or devices that affect the flight of the aircraft. It is difficult or even impossible for a pilot to directly control each of these devices and fly the aircraft well. Therefore, a control mapping logic is needed to take typical pilot commands and map them to what the control devices should do to achieve the pilot’s commands. This work presents a methodology for determining this control mapping logic using two different approaches. The first uses a theoretical approach based on lifting-line theory, while the second leverages computational methods. The methodology consists …

Hierarchical And Distributed Architecture For Large-Scale Residential Demand Response Management, Pramod Herath Mudiyanselage

All Dissertations

The implementation of smart grid brings several challenges to the power system. The ‘prosumer’ concept, proposed by the smart grid, allows small-scale ‘nano-grids’ to buy or sell electric power at their own discretion. One major problem in integrating prosumers is that they tend to follow the same pattern of generation and consumption, which is un-optimal for grid operations. One tool to optimize grid operations is demand response (DR). DR attempts to optimize by altering the power consumption patterns. DR is an integrated tool of the smart grid. FERC Order No. 2222 caters for distributed energy resources, including demand response resources, …

Data-Driven Passivity-Based Control Of Underactuated Robotic Systems, Wankun Sirichotiyakul

Boise State University Theses and Dissertations

Classical control strategies for robotic systems are based on the idea that feedback control can be used to override the natural dynamics of the machines. Passivity-based control (Pbc) is a branch of nonlinear control theory that follows a similar approach, where the natural dynamics is modified based on the overall energy of the system. This method involves transforming a nonlinear control system, through a suitable control input, into another fictitious system that has desirable stability characteristics. The majority of Pbc techniques require the discovery of a reasonable storage function, which acts as a Lyapunov function candidate that can be …

Development Of A Reverse Engineered, Parameterized, And Structurally Validated Computational Model To Identify Design Parameters That Influence American Football Faceguard Performance, William Ferriell

All Dissertations

Traumatic brain injury (TBI) continues to have the greatest incidence among athletes participating in American football. The headgear design research community has focused on developing accurate computational and experimental analysis techniques to better assess the ability of headgear technology to attenuate impacts and protect athletes from TBI. Despite efforts to innovate the headgear system, minimal progress has been made to innovate the faceguard. Although the faceguard is not the primary component of the headgear system that contributes to impact attenuation, faceguard performance metrics, such as weight, structural stiffness, and visual field occlusions, have been linked to athlete safety. To improve …

Warp-Aware Adaptive Energy Efficiency Calibration For Multi-Gpu Systems, Zhuowei Wang, Xiaoyu Song, Lianglun Cheng, Hai Wan, Wuqing Zhao, Tao Wang

Electrical and Computer Engineering Faculty Publications and Presentations

Massive GPU acceleration processors have been used in high-performance computing systems. The Dennard-scaling has led to power and thermal constraints limiting the performance of such systems. The demand for both increased performance and energy-efficiency is highly desired. This paper presents a multi-layer low-power optimisation method for warps and tasks parallelisms. We present a dynamic frequency regulation scheme for performance parameters in terms of load balance and load imbalance. The method monitors the energy parameters in runtime and adjusts adaptively the voltage level to ensure the performance efficiency with energy reduction. The experimental results show that the multi-layer low-power optimisation with …

Enhancements To Nuclear Thermal Propulsion Rockets, Kimberly Gonzalez

UNLV Theses, Dissertations, Professional Papers, and Capstones

Nuclear thermal rocket propulsion has been proposed as a highly efficient technology for space vehicles traveling from earth orbit to the moon, Mars, and other locations in the solar system. With twice the performance of a chemical rocket, nuclear thermal propulsion (NTP) uses the thrust produced by heating hydrogen gas within a thermal nuclear reactor where the exhaust is then passed through a de Laval nozzle to produce supersonic flow. NTP engines were the subject ofthe NERVA experiments at the Nevada Test Site in the 1970’s, and they produced a specific impulse of up to 900 seconds which is almost …

Employing Boundary Element Approach With Genetic Algorithm To Increase Travel Range Of Repulsive Actuators, Yu Tian, Ronald N. Miles, Shahrzad Towfighian

Mechanical Engineering Faculty Scholarship

The design of repulsive electrostatic actuators having enlarged travel range is achieved by combining the boundary element approach and a genetic algorithm. The boundary element method enables calculating the electrostatic forces without time consuming finite element simulations. Once a static equation that uses a model of effective lumped mass solves the travel ranges, the GA maximizes travel ranges by optimizing the dimensional parameters. The effectiveness of the scheme is demonstrated with extensive experimental results showing the travel ranges of a micro out-of-plane actuator are increased by up to 190%. The developed platform can improve the signal-to-noise ratios and the performance …

Persistent Mapping Of Sensor Data For Medium-Term Autonomy, Kevin Nickels, Jason Gassaway, Matthew Bries, David Anthony, Graham W. Fiorani

Engineering Faculty Research

For vehicles to operate in unmapped areas with some degree of autonomy, it would be useful to aggregate and store processed sensor data so that it can be used later. In this paper, a tool that records and optimizes the placement of costmap data on a persistent map is presented. The optimization takes several factors into account, including local vehicle odometry, GPS signals when available, local map consistency, deformation of map regions, and proprioceptive GPS offset error. Results illustrating the creation of maps from previously unseen regions (a 100 m × 880 m test track and a 1.2 km dirt …