Engineering Commons^™

Utilizing Optimization Tools For Passive Flow Control Passage Loss Reduction In Low-Pressure Turbines, Bryant Robert Duane Burton

Browse all Theses and Dissertations

Low-pressure turbines (LPTs) play a crucial role in fuel efficiency and thrust generation of aero-engines. Traditional LPT designs, however, involve multiple stages and numerous blades, resulting in increased weight and manufacturing costs. The challenge of modern- day researchers is to reduce the weight and cost but maintain the high efficiency of LPTs. To address this, one approach is to increase the aerodynamic loading of individual blades, reducing the blade count. However, this can lead to increased secondary losses caused by flow separation, particularly in the endwall regions. This research focuses on optimizing the blade profile at the junction with the …

Analysis And Design Optimization Of Electric Machines With Field Intensifying Configuration, Ali Mohammadi

Theses and Dissertations--Electrical and Computer Engineering

The design and optimization of electric machines face increasing demands for efficiency, improved torque density, manufacturability, and effective utilization of materials. Meeting these demands is particularly vital in for example, electric vehicles (EVs) and renewable energy systems, where performance, reliability, and cost are critical. In this dissertation innovative field-intensifying electric machine configurations have been explored, emphasizing advanced topologies, computational modeling, and optimization techniques to advance the state of the art in electric machine design and analysis.

Electric machines with high torque density are essential for many low-speed direct-drive systems, such as wind turbines, in-wheel traction, and industrial automation. This dissertation …

Application Of Genetic Algorithm In Container Vessel Stowage Planning With Carbon Tax Considerations, Ming-Feng Yang, Wei-Hao Su, Ko-Meng Hu, Yu-Hsuan Li

Journal of Marine Science and Technology–Taiwan

This study developed a method for optimizing stowage planning for container vessels, a crucial aspect of international trade logistics. Over 80% of global trade depends on containerized transportation; thus, effective stowage planning is essential for minimizing transportation costs and enhancing operational efficiency. In the proposed hybrid optimization approach, integer programming is combined with a genetic algorithm to generate optimal stowage plans. The key factors considered in this method include load capacity limits, stacking constraints, and carbon tax regulations. The proposed method involves maximizing space utilization while minimizing logistics costs, with particular emphasis on reducing port dwell times. The findings of …

Autonomous Vehicle Supported Mobility Services For Rural Areas, Alvira Ahmed Tasnim

Graduate Theses, Dissertations, and Problem Reports (ETD)

Autonomous Vehicles (AVs) are emerging as a promising mobility solution to address growing transportation demands, particularly unmet traffic demand in rural areas where conventional transit systems often fall short. Rural areas face unique mobility challenges due to dispersed populations, limited infrastructure, and low/no transit coverage. Existing transit services tend to concentrate around dense urban cores, leaving low-demand areas outside underserved. This spatial undercoverage leads to significant mobility gaps for rural residents. This study examines the potential of AV-based ride-sharing services to address these mobility needs by providing flexible, demand-responsive mobility services where fixed-route transit services are either economically or operationally …

Characterization, Optimization, And Performance Evaluation Of Pcm With Al2o3 And Zno Hybrid Nanoparticles For Photovoltaic Thermal Energy Storage, Md Golam Kibria, Utpol K. Paul, Md Shahriar Mohtasim, Barun K. Das, N. N. Mustafi

Research outputs 2022 to 2026

The electrical efficiency of the photovoltaic (PV) panel is affected significantly with increased cell temperature. Among various approaches, the use of Phase Change Materials (PCMs) with nanoparticles is currently one of the most effective for reducing and managing the temperature of PV panels. In this study, paraffin wax as PCM with different loading levels (0.5 %, 1 %, and 2 %) of hybrid nanoparticles Al2O3 and ZnO were successfully synthesized and their effects on the performance of the Photovoltaic-Thermal (PVT) system were investigated experimentally. Additionally, a prediction model was developed to analyze the interaction between the operating factors (independent variable) …

Optimizing Ai Language Models: A Study Of Chatgpt-4 Vs. Chatgpt-4o, Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Md Fayaz Bin Hossen, Muhammad Rezaur Rahman, Md. Shahadat Jaman

Electrical & Computer Engineering Faculty Publications

This paper presents a comparative analysis of OpenAI's GPT-4 and its optimized variant, GPT-4o, focusing on their architectural differences, performance, and real-world applications. GPT-4, built upon the Transformer architecture, has set new standards in natural language processing (NLP) with its capacity to generate coherent and contextually relevant text across a wide range of tasks. However, its computational demands, requiring substantial hardware resources, make it less accessible for smaller organizations and real-time applications. In contrast, GPT-4o addresses these challenges by incorporating optimizations such as model compression, parameter pruning, and memory-efficient computation, allowing it to deliver similar performance with significantly lower computational …

Flux-Weakening Control Methods For Permanent Magnet Synchronous Machines In Electric Vehicles At High Speed, Samer Alwaqfi, Mohamad Alzayed, Hicham Chaoui

Electrical & Computer Engineering Faculty Publications

Permanent magnet synchronous motors (PMSMs) are widely favored by manufacturers for use in electric vehicles (EVs) because of their many benefits, which include high power density at high speeds, ruggedness, potential for high efficiency, and reduced control complexity. However, since the Back Electromotive Force (EMF) increases proportionally with the motor’s rotational speed, it must be carefully controlled at high speeds. Flux-weakening (FW) control is required to avoid excessive electromagnetic flux beyond the power source and inverter’s voltage restrictions. This paper aims to compare various FW control strategies and analyze their effectiveness in maximizing the speed of PMSMs in EV applications …

Swarming Segregation: Leveraging Swarm Intelligence And Regionalization As Instruments For School District Desegregation, Jeffrey Wooten

Theses and Dissertations

Even after Brown led to the South briefly having the most diverse schools in the nation, schools throughout the Northeast have remained the most segregated in the nation for decades. While federal jurisprudence has made compelling desegregation pursuant to the Equal Protection Clause more challenging, New Jersey has a particularly favorable landscape to address severe segregation. With a highly diverse, densely populated public enrollment, favorable state constitutional precedent, and a history of successfully compelling desegregation, New Jersey is fertile ground exploring regional desegregation. Scholars, judges, and even plaintiffs in ongoing litigation (Latino Action Network v. N.J.) have called for New …

Development Of A Hybrid Methodology Of Deep Learning And Machine Learning For Lung Nodule Detection In Medical Computed Tomography Images, Zaed S. Mahdi, Rana M. Zaki, Alaa Kadhim Farhan, Negar Majma

Journal of Soft Computing and Computer Applications

Deep learning and machine learning play an important role in the medical field, helping doctors make accurate, fast and effective diagnosis. Despite the progress achieved in the use of modern technologies in detecting cancerous nodes, current studies still suffer from some challenges and limitations that must be addressed to obtain high efficiency in identifying cancerous nodes. These challenges include using image pre-processing, combining deep learning and machine learning techniques, and constantly adapting to clinical changes, in order to address this. A hybrid methodology has been proposed for detecting cancerous nodules in the lung in medical Computed Tomography (CT) images. It …

Genetic Algorithm-Based Design Solution Of An Area Lighting Scheme - A Case Study, Prabhat Mishra, Arnab Ganguly, Amartya Roy, Mihir Kumar Manna, Abhik Hazra

Manipal Journal of Science and Technology

In this paper, a Genetic Algorithm (GA)-based approach is taken for the lighting design of a specified area. The design of an area lighting scheme primarily depends upon the application of that area and accordingly target values of lighting design parameters are to be decided from relevant BIS (Bureau of Indian Standard) lighting codes. There are several design variables, viz., light distribution, aiming of the luminaire, pole spacing, luminaire mounting height, grid dimension over the field, etc. The task of a lighting designer is to achieve the target design parameters through a suitable combination of set design variables and design …

An Integrated Decision-Making Framework For A Closed-Loop Supply Chain Network Redesign Problem, Amir M. Fathollahi-Fard

AUIQ Technical Engineering Science

The rapid growth in demand and environmental concerns in industries like glass manufacturing necessitate the redesign of closed-loop supply chain (CLSC) networks to address both operational inefficiencies and sustainability challenges. Unlike conventional supply chain design, redesigning CLSC networks involves strategic decisions such as opening new facilities, closing existing ones, and managing the cost trade-offs associated with these transitions. Motivated by these challenges, this paper proposes an integrated decision-making framework to tackle the closed-loop supply chain network redesign (CLSCNR) problem. The proposed framework is formulated as a mixed-integer programming (MIP) model, specifically tailored for the glass industry. The forward supply chain …

Lignin Cationization For The Removal Of Phosphates And Nitrates From Effluents Of Wastewater Treatment Plants, Fannyuy V. Kewir

LSU Master's Theses

The removal of phosphates and nitrates from wastewater treatment plant (WWTP) effluents is important for preventing pollution of receiving waters. In this study, we chemically modified alkaline lignin (aLN) with quaternary ammonium groups to obtain biodegradable cationic lignin (cLN). We characterized the cLN and tested its efficacy for removing phosphates and nitrates in a lab setting and on field-collected WWTP samples. Adsorption isotherm and kinetic studies were performed in aqueous media, and the effects of several variables (contact time, pH, initial concentration, and adsorbent dose) were investigated. The Langmuir isotherm described phosphate and nitrate adsorption well, with R2 values of …

Physics-Informed Transfer Learning For Process Control, Samuel Arce Munoz

Theses and Dissertations

In the realm of process control, managing complex systems with limited prior knowledge presents significant challenges, particularly in environments where traditional mechanistic models are either unavailable or computationally prohibitive. This work explores the integration of deep transfer learning with system identification and Model Predictive Control (MPC) to develop control strategies that are both data-efficient and computationally streamlined. Initially, Long Short-Term Memory (LSTM) networks are employed to create approximate MPC controllers by leveraging transfer learning from a source system to a target system, demonstrating that transfer learning can achieve comparable performance to traditional MPC methods with reduced training data. Building upon …

Ohmic Contacts For Fabrication Of Sic Cmos Devices, Anthony Di Mauro

Graduate Theses and Dissertations

Today’s world of electronics is dominated by semiconductor devices which utilize silicon as their substrate material. Though, silicon is not ideal for semiconductor devices in high-voltage or high-temperature applications. Additionally, the efficiency of silicon devices becomes drastically reduced in nonideal operating conditions. Therefore, finding alternatives to silicon?based devices has been a topic for decades now. A few great candidates to replace silicon devices for said applications include Silicon Carbide (SiC), Gallium Nitride (GaN), and Aluminum Arsenide (AlAs). SiC has grown its reputation as the best candidate, when compared to other potential alternatives, due to its wide bandgap, high operating frequency, …

A Techno-Economic Perspective On Efficient Hybrid Renewable Energy Solutions In Douala, Cameroon’S Grid-Connected Systems, Reagan Jean Jacques Molu, Serge Raoul Dzonde Naoussi, Mohit Bajaj, Patrice Wira, Wulfran Fendzi Mbasso, Barun K. Das, Milkias Berhanu Tuka, Arvind R. Singh

Research outputs 2022 to 2026

Cameroon is currently grappling with a significant energy crisis, which is adversely affecting its economy due to cost, reliability, and availability constraints within the power infrastructure. While electrochemical storage presents a potential remedy, its implementation faces hurdles like high costs and technical limitations. Conversely, generator-based systems, although a viable alternative, bring their own set of issues such as noise pollution and demanding maintenance requirements. This paper meticulously assesses a novel hybrid energy system specifically engineered to meet the diverse energy needs of Douala, Cameroon. By employing advanced simulation techniques, especially the Hybrid Optimization Model for Electric Renewable (HOMER) Pro program, …

Learning To Accelerate Globally Optimal Solutions: Applications In The Ac Optimal Power Flow Problem, Muhammet Fatih Cengil

Graduate Theses and Dissertations

The Alternating Current Optimal Power Flow (AC-OPF) problem is a fundamental optimization challenge critical to ensuring the economical and reliable operation of power grids. While fast heuristic methods provide upper-bound solutions, assessing their quality requires lower bounds obtained from relaxations of the AC-OPF problem. This dissertation focuses on finding globally optimal solutions to the AC-OPF problem by enhancing the effectiveness and efficiency of Quadratic Convex (QC) relaxations. Leveraging machine learning techniques, we aim to achieve tighter relaxations faster and improve computational performance, enabling practical scalability for real-time applications.

In Chapter 2, we propose a machine learning-based method to accelerate the …

Hybrid Energy Systems: Synergy Margin And Control Co-Design, Mario Garcia Sanz

Faculty Scholarship

Extraordinary properties emerge from subsystems' interactions. Hybrid energy systems (HESs) are a promising concept that could change the renewable energy landscape. By co-designing generation, storage, and conversion technologies, HESs can provide new electrical power services, increase grid stability and control authority, and generate energy and/or nonenergy products such as electricity, hydrogen, ammonia, heat, digital data, or fresh water. This article discusses some conditions the co-design of HESs should follow to optimize the combined system (synergy), avoiding deterioration (dysfunction). It introduces some technoeconomic synergy conditions, develops a synergy margin, and analyses several case studies, exploring also the control co-design methodology to …

Novel Nanocomposite Of Carbonized Chitosan-Zinc Oxide-Magnetite For Adsorption Of Toxic Elements From Aqueous Solutions, Dalia A. Ali Eng, Ganna Gaber Ismail Eng.

Chemical Engineering

Herein, a novel nanocomposite (carbonized chitosan-zinc oxide-magnetite, CCZF) was developed to effectively remove toxic elements in water remediation. Combining the high adsorption capacities of chitosan with the magnetic properties of magnetite and the chemical stability of zinc oxide, the combination of these unique properties makes it an efficient and versatile material that offers a sustainable solution for water purification. The (CCZF) nanocomposite was synthesized through the coprecipitation method and characterized using various techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), Brunauer–Emmett–Teller (BET) analysis, X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, and zeta potential analysis. The results showed …

Machine Learning-Driven Process Analysis And Optimization In Solid-State Welding And Fusion-Based Additive Manufacturing, Radif Uddin Ahmed

Master's Theses

In the modern era of advanced manufacturing, optimizing process parameters is pivotal in ensuring the quality and reliability of sophisticated component fabrication. This study presents a novel, data-driven approach to parameter optimization in two cutting-edge manufacturing techniques: Friction Stir Welding (FSW) and Laser Powder Bed Fusion (LPBF). By leveraging machine learning methodologies, this research addresses the critical challenge of efficiently determining optimal process parameters, a task traditionally relying on time-consuming and resource-intensive trial-and-error methods. This study will lead to a robust data-driven framework for process analysis of more advanced manufacturing techniques like the Additive Friction Stir Deposition (AFSD) process. Friction …

Robust Data-Driven Run-To-Run Control Via One-Step Constrained Optimization For Automated Serial Sectioning, Rhianna M. Oakley

Mechanical Engineering ETDs

This Thesis develops a one-step predictive run-to-run controller (R2R-MPC) for automating a mechanical serial sectioning (MSS) system. MSS is a destructive material analysis process that iteratively removes slices of material and captures 2D images, reconstructing them into 3D representations. Commonly used in material science for characterizing materials and failure analysis, MSS typically operates in an open-loop fashion, which experiences high variability in material removal due to system disturbances. To address this, a robust closed-loop R2R-MPC is presented, modeling MSS process uncertainty using a linear differential inclusion identified from operational historical data. The R2R-MPC is posed as an optimization problem that …

Metal Additive Manufacturing Of Damage-Controlled Elements For Structural Protection Of Steel Members, Hamdy Farhoud, Islam Mantawy

Henry M. Rowan College of Engineering Departmental Research

This paper develops hybrid steel members by integrating additively manufactured, ultra-lightweight, damage-controlled elements (DCEs) into hot-rolled structural steel members. This approach relies on segmenting a structural member into distinct sections; one or two segments are enlarged to be capacity protected; however, another end or middle DCE segment is optimized to emulate the conventional member’s strength and stiffness. A small-scale DCE was topologically optimized and then additively manufactured using a powder bed fusion technique through a direct metal laser sintering process of 17-4PH stainless steel and then was experimentally tested to study the buckling behavior under compression. The experimental testing of …

Optimal Control Of Nonlinear, Nonautonomous, Energy Harvesting Systems Applied To Point Absorber Wave Energy Converters, Houssein Yassin, Tania Demonte Gonzalez, Kevin Nelson, Gordon Parker, Wayne Weaver

Michigan Tech Publications

Pursuing sustainable energy solutions has prompted researchers to focus on optimizing energy extraction from renewable sources. Control laws that optimize energy extraction require accurate modeling, often resulting in time-varying, nonlinear differential equations. An energy-maximizing optimal control law is derived for time-varying, nonlinear, second-order, energy harvesting systems. We demonstrate that sustaining periodic motion under this control law when subjected to periodic disturbances necessitates identifying appropriate initial conditions, inducing the system to follow a limit cycle. The general optimal solution is applied to two point absorber wave energy converter models: a linear model where the analytical derivation of initial conditions suffices and …

Performance Analysis Of C++ Parallel Algorithms In Hpx, Srinivas Yadav Singanaboina

LSU Master's Theses

The exponential growth in computational power and the increasing demand for high-performance applications have driven the need for greater parallel efficiency. Over the years, the number of cores in consumer-level CPUs and high-performance computing (HPC) systems has grown significantly. In response, numerous parallel programming li- braries have been developed. Each of these libraries offers unique mechanisms to enhance parallel performance. In this paper, we investigate the performance of five such paral- lel programming backends: C++ std::execution::par, OpenMP, TBB, Taskflow, and HPX. We evaluate these libraries using two sets of benchmarks. The first set focuses on standard C++ STL algorithms, including …

System Of Monitoring And Control Of Thermal Regime In Gas-Fired Furnaces, U.U. Kholmanov

Chemical Technology, Control and Management

The system of monitoring and control of thermal regime in gas furnaces is considered, the description of which includes temperature sensors, control systems and optimization algorithms. Attention is paid to monitoring, which allows to ensure stability and efficiency of furnace operation. The existing approaches to thermal regime control are analyzed. Examples of implementation of these systems are given, as well as the prospects for their development with regard to modern trends in automation and digitalization.

Nonlinear Model Predictive Control Of Heaving Wave Energy Converter With Nonlinear Froude–Krylov Forces, Tania Demonte Gonzalez, Enrico Anderlini, Houssein Yassin, Gordon Parker

Michigan Tech Publications

Wave energy holds significant promise as a renewable energy source due to the consistent and predictable nature of ocean waves. However, optimizing wave energy devices is essential for achieving competitive viability in the energy market. This paper presents the application of a nonlinear model predictive controller (MPC) to enhance the energy extraction of a heaving point absorber. The wave energy converter (WEC) model accounts for the nonlinear dynamics and static Froude–Krylov forces, which are essential in accurately representing the system’s behavior. The nonlinear MPC is tested under irregular wave conditions within the power production region, where constraints on displacement and …

Efficient Phosphate Removal From Water Using Ductile Cast Iron Waste: A Response Surface Methodology Approach, Mai Hassan Dr., Nada Alkhashab Eng., Ahmed Osman Dr., Dalia A. Ali Eng

Chemical Engineering

Water scarcity is a critical issue worldwide. This study explores a novel method for addressing this issue by using ductile cast iron (DCI) solid waste as an adsorbent for phosphate ions, supporting the circular economy in water remediation. The solid waste was characterized using XRD, XRF, FTIR, and particle size distribution. Wastewater samples of different phosphate ion concentrations are prepared, and the solid waste is used as an adsorbent to adsorb phosphate ions using different adsorbent doses and process time. The removal percentage is attained through spectrophotometer analysis and experimental results are optimized to get the optimum conditions using Design …

Efficient Phosphate Removal From Water Using Ductile Cast Iron Waste: A Response Surface Methodology Approach, Mai Hassan Roushdy Dr., Nada Amr El-Khashab Eng,, Ahmed Ibrahim Osman Dr., Dalia Amer Ali Dr.

Chemical Engineering

Water scarcity is a critical issue worldwide. This study explores a novel method for addressing this issue by using ductile cast iron (DCI) solid waste as an adsorbent for phosphate ions, supporting the circular economy in water remediation. The solid waste was characterized using XRD, XRF, FTIR, and particle size distribution. Wastewater samples of different phosphate ion concentrations are prepared, and the solid waste is used as an adsorbent to adsorb phosphate ions using different adsorbent doses and process time. The removal percentage is attained through spectrophotometer analysis and experimental results are optimized to get the optimum conditions using Design …

Burn Cost Modeling For Surface Grinding Optimization, Taiwo Fasae

Dissertations (1934 -)

Surface grinding plays a pivotal role in the machining industry, constituting roughly 25% of all machining operations worldwide. Its precision and efficiency are crucial, particularly in sectors requiring high-quality surface finishes, such as aerospace and semiconductor manufacturing. For thermal damage prevention, traditional approaches to parameter selection use thresholds to exclude burn-prone parameters. However, by omitting the cost of burn, the threshold-exclusion strategy yields outcomes that fail to reflect the true costs of grinding. This dissertation introduces a novel burn cost model that transcends these limitations, offering a more nuanced and cost-effective approach to managing grinding burn. The burn cost model …

Two-Level Design Optimization Of Ac Machines With Dc Stator Excitation And Minimal Torque Ripple Using Reluctance Rotor Profile Shaping, Ali Mohammadi, Oluwaseun A. Badewa, Yaser Chulaee, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Torque ripple mitigation in electric machines is important for a smooth and stable operation, minimize mechanical vibrations, and enhance the overall performance. In this paper, a novel two-level optimization method is proposed for the design of synchronous flux-switching and hybrid excitation machines with an innovative multi-point spline shaping method to minimize the torque ripple. This study uses models that are validated by experimental tests from a prototype with similar topology, and exemplifies the aforementioned optimization process on a 28 pole machine. The analysis results indicate that the torque ripple can be substantially reduced with improved electromagnetic torque of the electric …

A Micromagnetic Study Of Skyrmions In Thin-Film Multilayered Ferromagnetic Materials, Nicholas J. Dubicki

Dissertations

Magnetic skyrmions are topologically protected, localized, nanoscale spin textures in non-centrosymmetric thin ferromagnetic materials and heterostructures. At present they are of great interest to physicists for potential applications in information technology due to their particle-like properties and stability. In a system of multiple thin ferromagnetic layers, the stray field interaction was typically treated with various simplifications and approximations. It is shown that extensive analysis of the micromagnetic equations leads to an exact representation of the stray field interaction energy in the form of layer interaction kernels, a so-called 'finite thickness' representation. This formulation reveals the competition between perpendicular magnetic anisotropy …