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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: …

Optimalisasi Penerimaan Pajak Hiburan Sebagai Upaya Peningkatan Pendapatan Daerah, Ricky Endrie Saragih

"Dharmasisya” Jurnal Program Magister Hukum FHUI

The Implementation of the regional autonomy implementation has changed the relationship system and interaction scheme among the government institutions, either between the Central Government and Regional Government and horizontal interaction among the executive, legislative and adjudicative or among the regional governments. The existence of regional autonomy gives the regional government the consequence to determine the programs that will be conducted, as well as impacts the increment of funding needed to perform the programs. Entertainment tax is considered as a significant potential regional income besides the hotel and restaurant tax. This should get more concern from the regional government to optimize …

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-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 …

Math And The Mouse: Explorations Of Mathematics And Science In Walt Disney World, Elizabeth L. Bouzarth, John M. Harris, Kevin R. Hutson

The Mathematics Enthusiast

Math and the Mouse is an intensive, collaborative, project-driven, study away course that runs during the three-week May Experience term at Furman University and has many of the attributes of a course-based undergraduate research experience in mathematics. We take twelve students to Orlando, Florida to study the behind-the-scenes mathematics employed to make Walt Disney World operate efficiently. Students learn techniques of mathematical modeling (mostly resource allocation, logistics, and scheduling models), statistical analysis (mostly probability, clustering, data collection, and hypothesis testing), and ow management (queuing theory and some beginning ow dynamics) in an applied setting. Through planned course modules, collaborative activities, …

Optimizing Building Layouts For Proper Self-Shading: A Computational Approach, Amr Mamdoh Ali Youssef

Mansoura Engineering Journal

Self-shaded buildings receive great attentions especially in high-rise building in hot climate zones. This paper introduces a novel optimization approach for reforming high-rise building layout shapes (BLSs) towards better self-shaded alternatives for a given shape, along with the determination of different treatments for optimizing a given shape using shape grammar theory; their performance have been simulated by Autodesk Revit. Variables considered during the generation process include different treatments, range of treatments’ ratios and orientations along with controlling shape area and circumference if required. High-rise buildings in Egypt are used to demonstrate/validate the approach applications. The study results, through many applications, …

Bayesian Models For Spatially Explicit Interactions Between Neighbouring Plants, Cristina Barber, Andrii Zaiats, Cara Applestein, Lisa Rosenthal, T. Trevor Caughlin

Biology Faculty Publications and Presentations

1. Interactions between neighbouring plants drive population and community dynamics in terrestrial ecosystems. Understanding these interactions is critical for both fundamental and applied ecology. Spatial approaches to model neighbour interactions are necessary, as interaction strength depends on the distance between neighbouring plants. Recent Bayesian advancements, including the Hamiltonian Monte Carlo algorithm, offer the flexibility and speed to fit models of spatially explicit neighbour interactions. We present a guide for parameterizing these models in the Stan programming language and demonstrate how Bayesian computation can assist ecological inference on plant–plant interactions.

2. Modelling plant neighbour interactions presents several challenges for ecological modelling. First, nonlinear …

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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 …

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 …

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 …

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 …

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 …

Acrylamide Mitigation By Novel Lactic Acid Bacteria And Bifidobacteria Isolated From Various Food Products: Optimization Of Mitigation, Effect Of Simulated Gastrointestinal Conditions, And Potential Mechanism, Amal Salem Albedwawi

Dissertations

Acrylamide is a toxic compound that is formed in heated carbohydrate-rich food. Scientists have analyzed acrylamide levels before, during, and after processing in order to study the mitigation strategies and, due to the lack of knowledge, this study aimed to: 1) screen 120 newly isolated LAB for their acrylamide removal; 2) optimize the conditions for 6 selected strains of pH, temperature, time and salt, using the Box-Behnken design (BBD), and analyze their acrylamide removal levels; 3) investigate acrylamide removal abilities of the selected LAB isolates under in-vitro digestion conditions, using the INFO-GEST 2.0 model; and 4) examine the mechanism of …

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 …

A Bilevel Optimization Model Based On Edge Computing For Microgrid, Yi Chen, Kadhim Hayawi, Meikai Fan, Shih Yu Chang, Jie Tang, Ling Yang, Rui Zhao, Zhongqi Mao, Hong Wen

All Works

With the continuous progress of renewable energy technology and the large-scale construction of microgrids, the architecture of power systems is becoming increasingly complex and huge. In order to achieve efficient and low-delay data processing and meet the needs of smart grid users, emerging smart energy systems are often deployed at the edge of the power grid, and edge computing modules are integrated into the microgrids system, so as to realize the cost-optimal control decision of the microgrids under the condition of load balancing. Therefore, this paper presents a bilevel optimization control model, which is divided into an upper-level optimal control …

A Bilevel Optimization Model Based On Edge Computing For Microgrid, Yi Chen, Kadhim Hayawi, Meikai Fan, Shih Yu Chang, Jie Tang, Ling Yang, Rui Zhao, Zhongqi Mao, Hong Wen

Faculty Research, Scholarly, and Creative Activity

With the continuous progress of renewable energy technology and the large-scale construction of microgrids, the architecture of power systems is becoming increasingly complex and huge. In order to achieve efficient and low-delay data processing and meet the needs of smart grid users, emerging smart energy systems are often deployed at the edge of the power grid, and edge computing modules are integrated into the microgrids system, so as to realize the cost-optimal control decision of the microgrids under the condition of load balancing. Therefore, this paper presents a bilevel optimization control model, which is divided into an upper-level optimal control …

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 …

Lemurs Optimizer: A New Metaheuristic Algorithm For Global Optimization, Ammar Kamal Abasi, Sharif Naser Makhadmeh, Mohammed Azmi Al-Betar, Osama Ahmad Alomari, Mohammed A. Awadallah, Zaid Abdi Alkareem Alyasseri, Iyad Abu Doush, Ashraf Elnagar, Eman H. Alkhammash, Myriam Hadjouni

Machine Learning Faculty Publications

The Lemur Optimizer (LO) is a novel nature-inspired algorithm we propose in this paper. This algorithm’s primary inspirations are based on two pillars of lemur behavior: leap up and dance hub. These two principles are mathematically modeled in the optimization context to handle local search, exploitation, and exploration search concepts. The LO is first benchmarked on twenty-three standard optimization functions. Additionally, the LO is used to solve three real-world problems to evaluate its performance and effectiveness. In this direction, LO is compared to six well-known algorithms: Salp Swarm Algorithm (SSA), Artificial Bee Colony (ABC), Sine Cosine Algorithm (SCA), Bat Algorithm …

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 …

Planning System For The Optimization Of Electric Field Delivery Using Implanted Electrodes For Brain Tumor Control, Erin Iredale, Brynn Voigt, Adam Rankin, Kyungho W Kim, Jeff Z Chen, Susanne Schmid, Matthew O Hebb, Terry M Peters, Eugene Wong

Anatomy and Cell Biology Publications

BACKGROUND: The use of non-ionizing electric fields from low-intensity voltage sources (< 10 V) to control malignant tumor growth is showing increasing potential as a cancer treatment modality. A method of applying these low-intensity electric fields using multiple implanted electrodes within or adjacent to tumor volumes has been termed as intratumoral modulation therapy (IMT).

PURPOSE: This study explores advancements in the previously established IMT optimization algorithm, and the development of a custom treatment planning system for patient-specific IMT. The practicality of the treatment planning system is demonstrated by implementing the full optimization pipeline on a brain phantom with robotic electrode implantation, postoperative imaging, and treatment stimulation.

METHODS: The integrated planning pipeline in 3D Slicer begins with importing and segmenting patient magnetic resonance images (MRI) or computed tomography (CT) images. The segmentation process is manual, followed by a semi-automatic smoothing step that allows …

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 …

Reconfigurable Intelligent Surfaces And Capacity Optimization: A Large System Analysis, Aris L. Moustakas, George C. Alexandropoulos, Mérouane Debbah

Machine Learning Faculty Publications

Reconfigurable Intelligent Surfaces (RISs), comprising large numbers of low-cost and almost passive metamaterials with tunable reflection properties, have been recently proposed as an enabling technology for programmable wireless propagation environments. In this paper, we present asymptotic closed-form expressions for the mean and variance of the mutual information metric for a multi-antenna transmitter-receiver pair in the presence of multiple RISs, using methods from statistical physics. While nominally valid in the large system limit, we show that the derived Gaussian approximation for the mutual information can be quite accurate, even for modest-sized antenna arrays and metasurfaces. The above results are particularly useful …

Method Optimization For The Determination Of Cannabinoids In Blood By Liquid Chromatography Tandem Mass Spectrometry (Lc-Ms/Ms), Kevin D. Carrera

Student Theses

Delta-9-tetrahydrocannabinol (THC) continues to be one of the most popular drugs in the USA. Along with THC, other cannabinoids such as cannabidiol (CBD), are on the rise due to an increase in medicinal usage as well as the passage of different legislations removing these products from their current schedule I status. Thus, an urgency exists to develop robust and sensitive analytical methods to determine cannabinoids, especially THC, CBD and metabolites, in biological samples. The purpose of this study was to investigate different analytical procedures to determine the best method to identify and quantify CBD, THC and their metabolites in whole …

Humans Vs. Zombies: Data-Driven Modeling Of Disease Spread, Ognyan Simeonov, Kari Lemelin Fliss, Jennifer Driscoll, Carrie Diaz Eaton

Spora: A Journal of Biomathematics

Disease spread in close-knit communities depends heavily on the natural immunity of the individuals in the community as well as on the individuals’ interactions within the environment. This study uses data from a game of tag called Humans vs. Zombies, played on a small liberal arts campus, to examine how this “human element” can affect the spread of diseases in such communities. We fit five disease models to our data and find the best-fit parameters for each model. We conclude that an SIR model with multiple susceptibility classes and sleep cycles modifications provides the best fit, showing that human behavior …

In-Vitro Validation Of Intratumoral Modulation Therapy For Glioblastoma, Abdulla Elsaleh

Undergraduate Student Research Internships Conference

Intratumoral modulation therapy (IMT) is a novel electrotherapy used to treat brain cancer tumours using electric fields applied directly to the tumours through implanted electrodes. Previous research has validated IMT's effectiveness and provided computer-simulated optimizations for IMT electric fields. This work validates these computer optimizations in-vitro, using a PCB construct to deliver electric fields, and bioluminescence imaging to assess cell viability.

We found electric field strength to correlate with cell viability, and found that rotating (phase-shifted) electric fields did not produce significant improvements in IMT efficacy. Future work will investigate different IMT frequencies and other parameters, while providing biological replicates …