Engineering Commons^™

Optimization Of Pile Construction Sequence Using Cfa Machines, Omar Wael Ammar

Theses and Dissertations

In most construction projects with deep foundations, piling activities are critical to the project schedule and often fall on the critical path. The piling construction process requires a diverse range of resources, including equipment, materials, and skilful labour. Without carefully planning the construction process according to installation standards, there is a significant risk of time and cost overruns. These overruns are caused by inefficiencies such as equipment idle or lost time due to required lags between closely spaced piles. Therefore, it is essential to develop an optimized construction sequence to minimize these risks and enhance overall project efficiency. The primary …

Rotating Scatter Mask System Optimization Study For Determining Optimal Image Recreation, Seth L. Grover

Theses and Dissertations

The Rotating Scatter Mask (RSM) system is a radiation imaging technology currently limited by the mask design and governing identification algorithm parameters. To optimize the RSM design, Dakota—an optimization software—was integrated with a ray tracing code that simulates particle interactions with the RSM detector, and with the Locally Competitive Algorithm (LCA), which reconstructs the source image based on the ray tracing code’s Detector Response Matrix (DRM). Since the original ray tracing code was developed in MATLAB, it was translated into Python to improve compatibility with both Dakota and LCA. The Python version of the ray tracing code was then integrated …

Analog Hardware Implementation Of A Linearly Constrained Quadratic Program Real-Time Solver, Claire E. Tylutki, Claire Tylutki

Master's Theses

This thesis presents the design, implementation, and analysis of a hardware system for solving Linearly Constrained Quadratic Programs (LCQPs) in real time. The architecture follows a generalized feedback structure composed of three key elements: gradient descent on the quadratic cost function, saturation-based nonlinearity to enforce inequality constraints, and an integral controller with an anti-windup mechanism to regulate dynamic behavior and determine steady-state error. This majority analog system converges with equilibria that satisfy the Karush-Kuhn-Tucker (KKT) optimality conditions. Using a representative LCQP, this work presents simulation of the circuit in PLECS and LT Spice to confirm the feasibility of the novel …

Addressing Urban Traffic Congestion: A Deep Reinforcement Learning-Based Approach, Tairan Liu

Mineta Transportation Institute

In an innovative venture, the research team embarked on a mission to redefine urban traffic flow by introducing an automated way to manage traffic light timings. This project integrates two critical technologies, Deep Q-Networks (DQN) and Auto-encoders, into reinforcement learning, with the goal of making traffic smoother and reducing the all-too-common road congestion in simulated city environments. Deep Q-Networks (DQN) are a form of reinforcement learning algorithms that learns the best actions to take in various situations through trial and error. Auto-encoders, on the other hand, are tools that help simplify complex data, making it easier for the DQN to …

Data-Driven Dynamic Decision-Making Using Discrete Optimization And Supervised Machine Learning, Navid Rashedi

Dartmouth College Ph.D Dissertations

In recent years, the operations research community has developed data-driven optimization techniques to solve complex combinatorial problems with the aid of machine learning. This thesis contributes to these efforts by combining machine learning with optimization to expedite online decision-making, with applications in transportation and healthcare.

In the domain of airline operations recovery, the focus is on the aircraft recovery process—repairing disrupted schedules by minimizing overall disruption costs. Traditional exact methods are too time-consuming, while heuristic approaches often yield poor solution quality and lack generalizability across varying formulations. To address these challenges, this research employs supervised machine learning to identify near-optimal …

A Digital Twin Approach To Job Shop Scheduling: Simulation And Optimization In Anylogic, Alan Alejandro Corral Lopez

Open Access Theses & Dissertations

In complex manufacturing environments such as job shops, machine breakdowns and maintenance activities can significantly disrupt production flow, leading to delays, bottlenecks, and reduced throughput. This thesis presents the development of a digital twin for a job shop system using AnyLogic simulation software to evaluate the effectiveness of fallback routing logic, where jobs are dynamically rerouted to alternative machines when primary machines are unavailable due to scheduled and unscheduled events. The digital twin replicates real-world job shop conditions, incorporating variable job sequences, machine-specific processing times, and both preventive and corrective maintenance schedules. Two scenarios were compared: a baseline configuration with …

Cross-Frame Effects And Design Optimization For Skewed Steel I-Girder Bridges, Nisha Sthapit

Theses and Dissertations

Cross-frames are critical for load distribution and stability in steel I-girder bridges with complex geometry, especially during construction. However, they are often designed with standardized cross-sections that are uniform throughout the bridge. This thesis presents an optimization approach for cross-frame cross-sections for skewed steel I-girder bridges with integral and stub abutments with skews ranging from 15⁰-60⁰. This optimization, using Method of Moving Asymptotes (MMA), minimizes girder flange lateral bending stress while maintaining or reducing the total volume of the cross-frames from the original design. Validated 3D finite element models in CSI Bridge showed that the optimization achieved around 20% decrease …

Optimization-Based Distributed Controller For Multi-Agents System In Microgrid Secondary Control, Fahad S. Alshammari, Ayman El-Refaie, Saleh Alyahya, Sheroz Khan

Electrical and Computer Engineering Faculty Research and Publications

Micro-grids function to connect to power system power produced by the renewable energy resources. In islanded micro-grids, grid-forming units collaborate to maintain the micro-grids voltage and frequency by utilizing droop control technique that includes primary, secondary and tertiary levels. Secondary control intervenes to improve power sharing and restore voltage and frequency to their nominal levels. However, the conventional droop control applied to a grid with mismatched line parameters experiences a trade-off between reactive power sharing and voltage regulations. This paper applies real-time trajectory tracking convex optimization to ensure by communicating power sharing between units in a consensus topology. The optimization …

Artificial Intelligence Applications For Grid-Connected Solar Inverters, Utkirjon Ubaydullaev, Sarvinoz Mirzaeva, Hasan Mustafoev

Chemical Technology, Control and Management

The increasing global demand for renewable energy has highlighted the importance of grid-connected solar inverters in ensuring efficient and stable power conversion. However, challenges such as fluctuations in solar energy generation, grid disturbances, and power quality issues necessitate advanced control strategies. The integration of artificial intelligence (AI) into solar inverters presents a transformative solution, enhancing performance, adaptability, and reliability in real-world applications.

This review explores the role of AI techniques, including machine learning (ML), deep learning (DL), fuzzy logic, and reinforcement learning (RL), in optimizing key inverter functionalities such as maximum power point tracking (MPPT), fault detection, power quality enhancement, …

Bio-Inspired Highest Lift-To-Drag-Ratio Fin Shape And Angle For Maximum Surfboard Stability: Flow Around Fish Fins, Megan S. Macneill, Brian Barkdoll

Michigan Tech Publications

Wave surfing is a multi-billion dollar industry involving both maneuverability and speed, yet little research has been performed regarding the highest lift-to-drag-ratio fin shape for these competing qualities. Numerical modeling and laboratory experiments were performed here to identify a bio-inspired fin shape that maximized lateral stability and minimized drag forces, in order to increase surfing maneuverability. Nine fins based on dorsal fins of real fish were tested. Both the CFD and laboratory experiments confirmed that the fin of the same shape as that of the Short-Finned Pilot Whale at an angle of attack of 10° had the greatest lift-to-drag ratios. …

Analytical Dispatch Strategies For Pumped Storage Hydro: A Conditional Dynamic Programming Approach To Discontinuous Multi-Period Optimization Problems, Jian Liu, Jianwen Zhang, Zaiwu Gong, Donald C. Wunsch, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

The increasing integration of renewable energy sources like wind and solar poses significant challenges to secure and stable grid operation. Energy storage systems, particularly pumped storage hydro (PSH), play a crucial role in balancing power supply and demand. Traditional analytical studies of PSH economic dispatch problems often assume zero lower bounds for generating and pumping rates to simplify analysis and derive analytical solutions for multi-period optimization problems. However, the inherent mechanical design constraints of PSH require non-zero minimum flow rates for efficient operation. We analyze two scenarios, merchants having PSH only and merchants having both PSH and wind farms. In …

Hybrid Renewable Multi-Generation System Optimization: Attaining Sustainable Development Goals, Md Shahriar Mohtasim, Barun K. Das, Utpol K. Paul, Md Golam Kibria, Md Sanowar Hossain

Research outputs 2022 to 2026

The optimization of hybrid renewable multi-generation systems is crucial for enhancing energy efficiency, reducing costs, and ensuring sustainable power generation. These factors can be significantly affected by system designs, optimization methods, climate changes, and varying energy demands. The optimization of a stand-alone hybrid renewable energy system (HRES) that integrates various combinations of electricity, heating, cooling, hydrogen, and freshwater needs has not been reported in a single comprehensive study. Additionally, there has been insufficient attention given to the impact of temporal resolution, the recovery of excess energy usage, and aligning these efforts with the sustainable development goals (SDGs). This study reviews …

Long-Term Techno-Economic Analysis Considering System Strength And Reliability Shortfalls Of Electric Vehicle-To-Grid-Systems Installations Integrated With Renewable Energy Generators Using Hybrid Gru-Classical Optimization Method, Md Ohirul Qays, Iftekhar Ahmad, Daryoush Habibi, Paul Moses

Research outputs 2022 to 2026

Higher penetration of Electric Vehicle-to-Grid charging stations (EV2GCSs) in power grids integrated with renewable energy generators (REGs) result in system-instabilities raising the risk of blackout issues. Although techno-economic feasibility of EV2GCSs has been identified within the literature addressing power outage and financial concerns as a contemporary solution, no long-term techno-economic analysis has been investigated considering system strength and reliability shortfalls before the EV2GCSs installation. Therefore, this research aims to evaluate the long-term (2025–2045) techno-economic analysis of EV2GCSs into REGs-integrated grid systems by accounting for system strength and reliability factors. A novel optimization framework is developed, combining Gated Recurrent Units (GRU) …

Scalable Mxene-Based Textile Supercapacitors, Abaigeal Aydt

Honors Program: Senior Projects (Public)

The demand for flexible and wearable energy storage devices for portable applications has led to the exploration of textile-based supercapacitors (TSCs). TSCs will allow for the creation of a new class of energy harvesting and storing technology directly into our clothing and will require using non-toxic and/or biocompatible materials. This will result in a greener and more sustainable path to address the challenges at the nexus of energy, mobility, and sustainability. To fabricate a TSC, a yarn made of fibers, such as wool or cotton, is coated with MXene flakes; MXenes are composed of transition metal carbides, nitrides, or carbonitrides …

Lifting-Line Predictions For The Ideal Twist Effectiveness Of Spanwise Continuous And Discrete Control Surfaces, Zachary S. Montgomery, Douglas F. Hunsaker, James J. Joo

Mechanical and Aerospace Engineering Faculty Publications

Modern materials and manufacturing technologies have allowed the construction of morphing wings that are able to continuously vary certain airfoil parameters such as twist, camber, or control surface deflection as a function of span. This work presents a twist effectiveness parameter as a means of comparing the ideal aerodynamic efficiency of spanwise continuous control surfaces (morphing wings) and spanwise discrete control surfaces (standard wings). A numerical algorithm is used to compute the twist effectiveness of both continuous and discrete control-surface designs over a wide range of planform shapes with evenly spaced actuation for inviscid, incompressible flow. Results included here show …

Quantifying The Impact Of Highly Corrosive Environments On Fsrm Budgets And Infrastructure Condition At Air Force Bases, Justin M. Weber

Theses and Dissertations

The Department of Defense (DoD) faces significant challenges in maintaining mission-critical infrastructure within highly corrosive environments, with annual costs exceeding $22.5 billion to combat corrosion. This thesis investigated the interplay between environmental severity, sustainment funding, and infrastructure performance. This research utilized Facility Sustainment, Restoration, and Modernization (FSRM) funding data, statistical analyses, and regression modeling, to evaluate how Environmental Severity Index (ESI) categories influence Base Condition Index (BCI) trends and the efficacy of the Facility Sustainment Model (FSM). The analysis revealed that installations in higher ESI categories required significantly greater investment per square foot to achieve comparable improvements in BCI. The …

Enhancing Reliability Of A 3d Cargo Scanning System, Gabriel F. Bartolomei

Theses and Dissertations

Recent advancements in 3D cargo scanning and machine learning offer solutions to improve cargo processing reliability. This study enhances a 3D cargo scanning system by addressing software crashes, connectivity failures, and image accuracy issues limiting its operational effectiveness. A systematic approach identified the primary causes of system failures. System updates were implemented, followed by 30 pre- and post-update trials to evaluate reliability improvements. Statistical t-tests showed a significant reduction in failures, although processing time slightly increased. Results indicated that targeted hardware and software updates enhanced cargo scanning efficiency and dependability. Future work will focus on refining sensor calibration, optimizing network …

Best Estimate Reconstruction Of The Control Profile For A Maneuvering Reentry Vehicle, Justin R. Evans

Theses and Dissertations

Astrodynamic reentry is an increasingly important flight regime as countries around the world develop new spacecraft and weapons. A design of interest is that of hypersonic glide vehicles with the ability to maneuver in the atmosphere. As these vehicles become more common across the world, it has become advantageous to track foreign reentry tests in order to determine capabilities. While current observation techniques may allow position and velocity to be tracked across the trajectory, orientation of the vehicle is not always observable. The ability to find vehicle orientation across time gives insight into the performance characteristics of the vehicle. This …

Methodology Of Automated Control Of Situations In Structurally Complex Systems With Recycled Flows, Khusan Zokirovich Igamberdiev Academician, Madina Mirxalilovma Fozilova

Chemical Technology, Control and Management

This article discusses the methodology of automated management of situations in structurally complex systems with recycled flows. The need to develop a correct model for effectively controlling such systems based on scientific principles of analysis and decision-making is substantiated. Particular attention is paid to modeling, optimizing, and using digital technologies, including artificial intelligence, to improve the accuracy and efficiency of management decisions. The principles of decomposition, multi-criteria optimization, and linguistic models of fuzzy correspondence are described, which can be used in conditions of uncertainty and complexity of industrial facilities.

Lagrange Multipliers As A Metric For Early-Stage Shipboard Power System Design, Magdalen A. Barnes

Theses and Dissertations--Electrical and Computer Engineering

Integrated power systems are essential in the operation of electric ships and must function under a diverse range of conditions. In addition to routine operation, ships should be prepared to respond to challenging events that require significant amounts of power. Demanding scenarios, coupled with complex and interconnected power systems, present challenging issues. The power and energy ratings of equipment are crucial factors in the operational success of the ship; however, to meet economic constraints, balance between performance and cost must be upheld. Details regarding equipment models and specifications are typically unavailable during early-stage design. Power system modeling and simulation can …

Multi-Objective Design Optimization Of Hypoid Geared Rotor Systems, Xinqi Wei

Mechanical and Aerospace Engineering Dissertations - Archive

Hypoid gears represent one of the most generalized and complex forms of gearing, widely used for power transmission of skew shafts in vehicles, aviation, and marine transmission applications. Optimizing their performance remains challenging due to the complex tooth surface and contact behavior. Specifically, the design parameters of the tooth surface are multi-scale, interdependent, and subject to strong constraints, leading to strong nonlinearity and an ill-conditioned Jacobian matrix in the parameter identification model. Moreover, feasible and insensitive contact conditions are difficult to constrain due to the inherent complexity of local conjugate contact between the meshing surfaces. These challenges significantly increase optimization …

Data-Driven Layout Design For Smart Remanufacturing: A Flexible Optimization Model And A Case Study, J. A. Afari, A. Gosavi, J. Hu, R. J. Marley

Engineering Management and Systems Engineering Faculty Research & Creative Works

Abstract: In remanufacturing, a vital segment of the sustainable, low-carbon circular economy, existing versions of the traditional unequal-areas facility layout problem (UA-FLP) model face significant limitations in designing layouts. To be specific, in the process of minimizing the material-handling cost (MHC), these models also alter departmental dimensions, often diverging from construction specifications. This poses a difficulty, as critical equipment required for remanufacturing, e.g., sorting and cleaning machines, have unalterable dimensions, which implies that departmental dimensions cannot be changed from specifications provided. To address this, a novel Flexible Envelope UA-FLP (FE-UA-FLP) model is proposed in this work for designing layouts wherein …

Two-Level Multi-Objective Design Optimization Including Torque Ripple Minimization For Stator Excited Synchronous And Flux Switching Machines, Ali Mohammadi, Oluwaseun A. Badewa, Yaser Chulaee, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Electric machine performance can be enhanced through torque ripple mitigation, which reduces mechanical vibrations and improves system stability and operation. This paper proposes a novel two-level optimization method for synchronous flux-switching and hybrid excitation machines, featuring an innovative multi-point spline shaping approach for torque ripple minimization. The study employs experimentally validated models based on a prototype with a similar topology. The optimization process is implemented on two distinct designs: a 20-pole inner rotor PM-excited stator machine and a 28-pole outer rotor DC-excited stator machine. Analysis results demonstrate that the proposed innovative method significantly reduces torque ripple in both configurations. Force …

Powersynth 2: Automated Power Electronics Physical Design Synthesis With Custom And Heterogeneous Components, Mehran Sanjabiasasi, Alan H. Mantooth, Yarui Peng

Electrical Engineering and Computer Science Faculty Publications and Presentations

Electronics Design Automation (EDA) has shown significant importance in the power electronics industry. As power electronic circuits become more complex, the traditional trial-and-error approach in physical design becomes less effective and time-consuming. Novel packaging technologies and intelligent physical design automation solutions are crucial to overcome these challenges and produce reliable solutions. PowerSynth 2 is an EDA tool for generating and optimizing power module layouts. To extend the layout synthesis capability beyond power modules, the layout engine needs to consider various custom components such as capacitors, inductors, and gate drivers. This research presents a novel framework for the layout synthesis process …

Minimizing Cpu Utilization For Job Scheduling Problems By The Advanced Round Robin Method: A Pragmatic Perspective, Haribhau R Bhapkar, Pankaj R Chandre, Parikshit Mahalle

ASEAN Journal on Science and Technology for Development

CPU scheduling issues include minimizing waiting time for processes, ensuring fairness in resource allocation, and optimizing throughput. Balancing these objectives can be challenging, as improving one aspect may negatively impact another, making it essential to design efficient scheduling algorithms. This work presents an innovative approach to enhance CPU utilization through the development of a Result-Based Round Robin Scheduling Algorithm. Traditional Round Robin Scheduling methods often face challenges in efficiently allocating CPU time, leading to suboptimal system performance. In response to these limitations, the proposed method introduces a result-oriented strategy that dynamically adjusts time quantum allocations based on the execution progress …

A Design And Analysis Of Computer Experiments Approach To Water Distribution Network Seismic Rehabilitation Optimization, Uthman Abiola Kareem

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Water is an essential part of human life. However, there are critical infrastructures that enable water availability in communities and homes. One of such is a water distribution network. Water distribution network performance depends on its reliability, which could be threatened by external agents like earthquakes. When earthquakes occur, they cause damages on some pipes within the distribution network and this limits performance of water distribution network. While earthquakes cannot be prevented, effective maintenance intervention may reduce the impact of earthquakes on water distribution networks. In order to develop an effective maintenance plan, researchers approach it in different ways. However, …

How Many Passes Does It Take? An Investigation To Determine The Optimal Number Of Liposome Extrusion Cycles, Kasey Piper

Honors Theses

Liposomes are lipid-based nanoparticles with significant applications in drug delivery and membrane research. One of the most common methods for fabricating liposomes of specific sizes is membrane extrusion, where liposomes are passed through porous membranes to reduce their size. The precise number of passes needed and the factors influencing this process remain unclear. This thesis investigates the relationship between the number of passes through a track-etched polycarbonate membrane and size and lamellarity of extruded liposomes with a focus on lipid type (DOPC, DMPC, Soy PC), membrane pore size (50, 100, 200, 400 nm), and the effect of freeze-thaw cycling. To …

Optimization Of A Vertical-Axis Wind Turbine Airfoils Using Machine Learning, Numerical And Experimental Methodologies, Leovigildo Torres Angel

CGU Theses & Dissertations

This study aimed to enhance the aerodynamic performance of a Vertical-Axis Wind Turbine (VAWT) airfoil through a multidisciplinary approach that combines Machine Learning (ML), Computational Fluid Dynamics (CFD), and experimental validation. The focus was on enhancing the lift-to-drag coefficients ratio (퐶 푙 /퐶 퐷 ), particularly at higher Angles of Attack (AoA ≥ 20°), a critical operational regime for VAWTs. A baseline airfoil of 12-inch chord length and 10-inch wingspan was analyzed using ANSYS Fluent across a range of AoA (0°–90°) at a constant freestream velocity of 10 m/s (Re ≈ 2.0 × 10 5 ). This served as a …

Multi-Dimensional Iot-Based Energy Management Approach For Smart Homes: A Unified Model For Comfort And Energy Efficiency, Muhammad Ans, Teodoro Montanaro, Ilaria Sergi, Ahmad Alsharoa, Miriam Pezzuto, Luigi Patrono

Electrical and Computer Engineering Faculty Research & Creative Works

As smart home technologies evolve, achieving energy-efficient indoor climate management while maintaining comfort and air quality is a growing priority. This paper introduces a novel optimization framework for smart buildings that minimizes energy costs and dynamically manages indoor environmental conditions, specifically temperature, CO₂ concentration, and illuminance. Unlike conventional systems, our model incorporates dynamic constraints that respond to day-night comfort requirements and leverage real-time variations in electricity prices and environmental conditions. By optimally controlling the power levels of air conditioning, air purification, and lighting systems, the framework ensures indoor comfort while significantly reducing operational costs.A nonlinear optimization approach with dynamic …

High-Frequency Accurate Dual-Side Equivalent Circuit Model For Transformers, Reza Vahdani, Junyong Park, Manish Kizhakkeveettil Mathew, Zhekun Peng, Chiuk Song, Hyucksu Kweon, Jiang Lijun, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This study delves into the modeling of a transformer in the frequency range of 100 KHz to 30 MHZ. The coupling coefficient was considered as a function of leakage and self-inductance and incorporated in the optimization process of transformer modeling in the proposed method. The equivalent circuit focused on the critical aspects of leakage inductance, parasitic capacitance, and winding effects. At first, the winding effect of an air-core inductor over wide frequency range with both single-layer and double-layer windings was shown. Then an equivalent circuit was proposed to model a transformer over this frequency range. The comparison between the measured …