Engineering Commons^™

Research On Decision-Making Of Autonomous Driving In Highway Environment Based On Knowledge And Large Language Model, Xiang Wang, Guozhen Tan

Journal of System Simulation

Abstract: Aiming at the lack of continuous learning and interpretability of current autonomous driving system, a decision model with cognition, generalization and learning ability is proposed. The model utilizes large language model (LLM) and attention mechanisms to understand and explain driving scenes. the system can accumulate and learn from driving experiences, continuously improving its decisionmaking ability. In a simulation environment, the closed-loop test decision model is applied in high-speed scenarios.The simulation results show that the success rate of the knowledge-driven model is 7% and 4% higher than those of the rule-based and data-driven methods. Additionally, the model exhibits generalization and …

Sustainability In The Cruising Industry: Innovations In Air Quality, Energy Efficiency, And Waste Management, Fikret Durmus, Mi Ran Kim

ICHRIE Research Reports

The cruise industry, a cornerstone of the global hospitality and tourism sector, faces increasing scrutiny over its environmental impact. As passenger numbers grow, so does the industry's responsibility to adopt sustainable practices. This report examines key innovations in air quality management, energy efficiency, and waste management, highlighting the industry's transition from historically high emissions and waste production to advanced sustainability initiatives. Key focus areas include evolving maritime regulations, adopting cleaner propulsion technologies, integrating energy-efficient solutions, and improving waste treatment practices. Findings indicate that industry leaders are investing in liquefied natural gas engines, exhaust gas cleaning systems, and onshore power supply …

Development Of Non-Precious Iron-Cobalt Alloy Catalyst For Electrocatalytic Reaction, Harsh Panchal

Electronic Theses & Dissertations

The development of a FeCo alloy catalyst with tunable Fe/Co ratios is examined to improve electrocatalytic performance in reactions like the oxygen evolution reaction (OER), hydrogen evolution reaction (HER), and oxygen reduction reaction (ORR). Many energy conversion devices, such as fuel cells, metal-air batteries, and water-splitting systems, depend on these interactions to function. These technologies have huge potential to meet the increasing need for hydrogen production and renewable energy sources worldwide, which are critical to attaining a sustainable energy future. When compared with noble metal-based catalysts, the FeCo alloy catalyst shows much higher catalytic activity, according to previous studies. Hydrothermal …

An In Depth Examination Of Educational, Family, Economic, And Personal Determinants On Academic Performance, Engagement, And Stress: A Comprehensive Study Among Engineering Students, Oumaima Larif

Theses and Dissertations

This study explores the effects of family, education, economic, and personal factors on students’ decisions to pursue engineering as a profession and their long-term impact on performance as engineering students. We adopted a mixed-method approach, collecting data through surveys administered to undergraduate and graduate engineering students at Mississippi State University. The study results revealed that family, education, economic, and personal factors profoundly influence students' decisions to study engineering. We found that parental expectations, background information, and socioeconomic status, in conjunction with cultural norms, values, gender expectations, and religious beliefs, affect students. Additionally, this study identified gaps in the existing literature …

Advancing Wood Chip Moisture Content Prediction Using Advanced Generative Ai Techniques, Daniel Esteban Marulanda

Theses and Dissertations

In this study we propose a deep learning method to optimize the classification of wood chip moisture content levels using the Vision Transformer and then ultimately increase the classification performance by creating synthetic images using the diffusion transformer model. In the first chapter of our study, we complete a detailed explanation of how the moisture content levels of 10 different wood chips were gathered ranging from 2 to 50$\%$. This chapter serves as a foundation for subsequent sections, illustrating the challenges associated with the current data collection process, which is both time-consuming and inefficient. Accurately determining moisture content for wood …

The Importance Of Community: An Investigation Of Stress, Coping, And The Value Of Social Support For First Responders, Brian Reid

Theses and Dissertations

People are designed to be in community with others, to work together and share the load and weight of life. First responders are a community that has not emphasized the importance of social support to mitigate and buffer against the stress inherent in their jobs. This study investigates the sources of stress, coping methods, and social support of first responders. Results from the first study show the impact of workplace and family stress on the first responder is impactful from the beginning. The secondary study finds that adaptive coping methods are the preferred method to cope with stress and that …

Enhancing Profitability In The Air Transport Industry Through Improved Air Passenger Forecasting: A Comparative Analysis Of Arima, Holt-Winters And Lstm Time Series Forecasting Techniques, Megan Skowronek

Theses and Dissertations

Predicting air passenger volumes is crucial for airports and airlines seeking to reduce costs and enhance profitability. Accurate forecasting enables better planning and efficiency improvements within the air transport industry. This study applies LSTM, ARIMA and HW to U.S. air passenger datasets. Each analysis shows a methodology for predicting air passenger volumes across airports, airlines and across airports and airlines simultaneously. ARIMA was found to have limited applicability, since only a subset of the datasets was stationary. LSTM and HW were applicable to all airlines and ARIMA was applicable to no airlines. LSTM had less error compared to HW at …

In-Hand Singulation, Scooping, And Cable Untangling With A 5-Dof Tactile-Reactive Gripper, Yuhao Zhou, Pokuang Zhou, Shaoxiong Wang, Yu She

School of Industrial Engineering Faculty Publications

Manipulation tasks often require a high degree of dexterity, typically necessitating grippers with multiple degrees of freedom (DOF). While a robotic hand equipped with multiple fingers can execute precise and intricate manipulation tasks, the inherent redundancy stemming from its high-DOF often adds complexity that may not be required. In this paper, we introduce the design of a tactile sensor-equipped gripper with two fingers and five-DOF. We present a novel design integrating a GelSight tactile sensor, enhancing sensing capabilities and enabling finer control during specific manipulation tasks. To evaluate the gripper's performance, we conduct experiments involving three challenging tasks: 1) retrieving, …

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 …

Fff Process Parameter Identification With Machine Learning Models, Owen Davis Smith

Honors Theses

Additive manufacturing (AM) has seen increasing popularity in recent times, owing to its efficiency and high speeds, particularly with processes such as Fused Filament Fabrication (FFF). Input process parameters have large impacts on the final part. Incomplete process parameters, which can occur for a variety of reasons, make tasks such as replicating AM studies difficult. A machine learning model can be trained on in-situ layer-wise images collected during a print to combat this issue, predicting process parameters with sufficient data. In this study, two parameters were tested: infill pattern orientation and extrusion width. Twelve parts were produced per parameter and …

A Data Driven Approach To Student Success: Visualizing Engagement And Performance Metrics, Araohat Kokate

2025 Spring Honors Capstone Projects - Archive

Many tutoring centers lack tools to analyze and visualize key performance metrics, limiting data driven decision making. This study develops a data visualization feature for the CSE Student Success Center App at the University of Texas at Arlington, enabling administrators to track student engagement, tutor performance and session trends. Using the data of students and tutors, the feature provides interactive dashboards for real-time insights. Administrators can monitor attendance patterns, tutor workloads and booking trends, optimizing resource allocation. Findings indicate that real-time data visualization enhances decision-making, reducing manual effort while improving operational efficiency. This can further help improve student support services. …

Air And Missile Defense Threat Scenario Variation To Reduce Pretest Sensitization, Video Games As A Case Study, Julie Renee Szekerczes

All-Inclusive List of Electronic Theses and Dissertations

This study uses fixed and variable video game types to measure pretest sensitization as a proxy for repeated and varied threat test scenarios in system performance testing of air and missile defense systems. The pretest sensitization phenomenon exists when repeated exposure to a test condition influences the participant's response. Research shows air and missile defense development correlates with video games, resulting in similar interfaces and computer operating environments. Department of Defense acquisition test and evaluation results must reflect system performance without prior knowledge of the threat scenarios confounding the results. System performance results inform acquisition decisions, such as further funding …

Community Wastewater Treatment Resilience Assessment, Tristan Veal

All Theses

With the rising threat of climate change and cascading impacts from infrastructure failure there is a growing need to strengthen community resilience. Theoretical and practical resilience frameworks are available, but they vary in aim and scope; there is no standard tool to assess resilience. This research expands on the resilience matrix (RM) application methods of previous research completed by the United States Army Corps of Engineers (USACE) and Clemson University. That work focused on drinking water treatment systems and developed a few dozen specific indicators, or metrics, to quantify resilience. This research adds wastewater infrastructure with the aim of identifying …

Minimizing Uncovered Triples: An Integer Programming Approach To College Football Conference Scheduling, Caleb Mallett

Industrial Engineering Undergraduate Honors Theses

Collegiate football teams often compete in groups of 8-20 teams known as conferences. One such conference, the Atlantic Coastal Conference (ACC), added three new schools for the 2024-25 season, bringing their total to 17 teams. Currently, each ACC team plays eight games against others within the ACC. At the season’s conclusion, the two ACC teams with the best intraconference record compete in a conference championship game. With 17 total teams each playing eight games, the ACC could have a three-way tie for the best record where none of top the three teams play one another. To avoid this situation, we …

Developing 3d-Printed Packaging To Protect Biodegradable Sensors Used For Large-Scale, Efficient Water Quality Monitoring, Han L. Siew

Industrial Engineering Undergraduate Honors Theses

Freshwater degradation due to human activities costs the United States over $2.2 billion annually, highlighting the urgent need for improved water quality monitoring methods. Traditional water sampling techniques are labor-intensive, time-consuming, and reliant on single-use plastics that contribute to environmental pollution. This research aims to address these issues by developing 3D-printed biodegradable sensor packaging for unmanned aerial vehicle (UAV)-assisted water sampling. By utilizing biodegradable materials, the research seeks to create an eco-friendly solution that ensures sensor durability while reducing negative environmental impact. The study will involve adjusting the packaging design to withstand UAV deployment by testing and improving the resistance …

Tradespace Exploration With Statistical Modeling Techniques And Immersive Visual Representation In Virtual Environments, Nikhil Raj

All Theses

Statistical modeling techniques combined with virtual reality (VR) visualization offer powerful new approaches to tradespace exploration in engineering design. The research presented addresses the challenge of analyzing and communicating insights from complex multidimensional datasets, particularly for autonomous ground vehicle systems.

Beginning with a review of statistical methods—including Principal Component Analysis (PCA), Analysis of Variance (ANOVA), and correlation analysis—the study examines their applications in tradespace exploration. Building on this foundation, three distinct visualization pathways connecting MATLAB data to virtual environments are developed and evaluated: VRML representation, STL conversion, and Blender integration. Each approach is assessed for its ability to maintain data …

Survival Signature Estimation Using Optimization And Monte-Carlo Simulation For K ≥ 3 Classes Of Nodes On Two-Terminal Networks, Md Sazid Rahman

Graduate Theses and Dissertations

This research develops an efficient approach to estimating survival signatures for two-terminal networks with more than two classes of components. Recently, the survival signature has gained substantial attention in the literature on network reliability estimation due to its unique separability property, which enables passing the network topology information independent of the failure distribution of the components. Following recent results from the literature, estimating the two-terminal survival signature by Monte Carlo simulation entails solving a multi-objective maximum capacity path problem on a two-terminal network in each replication. We adapt a multi-objective Dijkstra’s algorithm from the literature to construct the set of …

Life Cycle Analysis Of Cosmetic Products -- Assessing Environmental Sustainability And Potential Impacts, Karina Magro Machado

Theses, Dissertations and Culminating Projects

The cosmetic industry has a significant environmental footprint due to its reliance on water, energy, petrochemical-derived ingredients, and plastic-based packaging. This study performs a cradle-to-grave Life Cycle Analysis (LCA) to evaluate the environmental impacts of three cosmetic products: CeraVe Daily Moisturizing Lotion, bareMinerals Gen Nude Powder Blush, and Gillette Foamy Regular Shave Cream. The analysis was conducted using OpenLCA software and free databases, modeling each product across raw materials, packaging, manufacturing, transportation, use and end-of-life phases. The results showed that the shave cream had the highest environmental burden to three out of the four categories, especially in consumption and carbon …

Decomposition And Coordination For Multiobjective Optimization: A Framework And Methodology, Philip J. De Castro

All Dissertations

In this work, we consider finding Pareto efficient solutions for complex multiobjective optimization problems (MOPs). Complex MOPs are unique in the literature because they have many more objective functions than is typically considered. In fact, such complex MOPs will have 30+ objective functions. This large problem size presents computational and coginitive difficulties. Computationally, standard techniques for solving MOPs are often ineffective and cognitively it is difficult for a decision maker (DM) to handle all of the information provided in such a large problem. To address these challenges, we develop a decomposition and coordination framework. This framework will allow us to …

Extending Simulation-Enhanced Bayesian Optimization Of System Designs: A Computational Study, Luke Kim

Data Science Undergraduate Honors Theses

This honors thesis builds off work initially accepted for publication in the Proceedings of the 2025 IISE Annual Conference & Expo, which introduced “Simulation-Enhanced Bayesian Optimization” (SEBO)—a hybrid testing optimization approach that combined the usage of unbiased but costly physical experiments with the usage of cheaper but potentially biased computer experiments to optimize engineered systems. The original study established the SEBO methodology and demonstrated its effectiveness on a multimodal, two-dimensional benchmark function. Expanding on the work performed, we conduct a broader evaluation of the SEBO framework through parameter testing and experimentation under a variety of additional benchmark functions. This investigation …

A Causal Model Of Performance Shaping Factors For Human Reliability Analysis In Manufacturing., Prameet Ranjan Jha

Electronic Theses and Dissertations

Human reliability analysis is a critical component of probabilistic risk assessment, aimed at predicting and mitigating human errors in complex systems. This dissertation develops a novel approach to human reliability analysis in manufacturing by integrating structural equation modeling and Bayesian networks to improve the estimation of human error probabilities. Traditional human reliability assessment methods, such as the Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) and the Technique for Human Error Rate Prediction (THERP), provide structured techniques for estimating human error probabilities. However, these methods often fail to capture the complex interdependencies among performance shaping factors (PSFs), limiting their applicability in …

Engineering Solutions For The Transplant Supply Gap: Social Network Analysis, Artificial Intelligence, And Optimization In Living Kidney Donation., Joshua Nielsen

Electronic Theses and Dissertations

Kidney transplantation is the gold standard for treating end-stage renal disease, yet over 90,000 patients remain on the transplant waitlist. This dissertation introduces engineering-driven solutions to help reduce the transplant supply gap by addressing three challenges: illicit trafficking, donor recruitment, and evaluation inefficiencies. First, we model illicit organ trafficking networks using social network analysis. We demonstrate that targeting transplant clinics alone is insufficient to disrupt operations. Instead, disrupting the network requires detaining brokers who organize behind-the-scenes logistics—offering a more effective strategy for intervention. Second, we seek to identify a latent population of potential living donors who face barriers such as …

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 …

A Systems Engineering Approach For Mitigating Space Debris In Earth's Orbital Regimes, Manuel Soto

Open Access Theses & Dissertations

Space debris in Earth's orbital regimes is a complex threat that originates with human space activity and is maintained by Earth's gravitational force. Space debris poses the risk of colliding with and destroying operational space assets. These collisions, in turn, pose the risk of compounding space debris fragments by turning operational space entities involved in collisions into additional space debris. In other words, the space debris impact does not end with a fragment colliding with a space entity. Instead, the collision is a new space-debris birth since the entities colliding are likely to become multiple fragments. Depending on the collision's …

Multistage Random Key Genetic Algortihm Optimization For Scheduling Flexible Flow Lines With Sequence Depenedent Setup Times, Aadithan Anbuvanan

All Theses

This thesis proposes a new variation to the Random Key Genetic Algorithm (RKGA) for scheduling optimization in flexible flow line manufacturing with sequence dependent setup times. The proposed RKGA representation decodes scheduling information independently at each stage, unlike the traditional RKGA, which is only sequenced based on the first stage, limiting flexibility. The proposed method's performance is compared to the traditional method with varying numbers of jobs and stages. It is compared regarding performance ratio and statistical significance of differences through the Wilcoxon Signed Rank Test. Results show that the proposed RKGA outperformed traditional RKGA in high complexity (8 Stage …

Remaining Life Analysis Of Pipeline Gas With Extreme Value Theory, Rony Prayitno Simeon, Eddy Sumarno Siradj, Tedi Kurniawan

Journal of Materials Exploration and Findings

Energy and chemical companies use pipelines to transfer oil, gas, and other materials from one place to another, within and between their plants. Pipeline integrity is an important concern because pipeline leakage could result in serious economic or environmental losses. Some research has applied to understand the effect of extrapolation value of the minimum thickness of pipeline by using the Extreme Value Theory. In this research, both statistical models and Extreme Value methods were applied and developed for the reliability of the pipeline by assuming the constant corrosion rate and deviation due to measuring devices were neglected. The research obtained …

Integrity Assessment Of Shipping Line Pipelines Using Risk-Based Analysis To Determine Risk And Maintenance Strategies, Ade Ratih Anggraini, Dwi Marta Nurjaya

Journal of Materials Exploration and Findings

Pipeline Shipping Lines X, Y & Z are classified as critical infrastructure, being the only transportation through the crude oil lifting from P and R location to the transfer station in NM Area. To maintain the workflow of the Shipping Line, integrity assessments and risk evaluation are required to ensure the operational and safety. Anomalies were found by analysing inspection, monitoring, and repair data, while the pipelines' future integrity was assessed by calculating the remaining life. Risk-Based Analysis (RBA), which is a modification of Kent Muhlbaeur's method, is employed to conduct the risk assessment using the Probability of Failure (POF) …

Assessment Of H2s-Induced Cracking Susceptibility In Steam Line Pipes And Weld Zones During Geothermal Well Construction, Riene Kaelamanda Pragitta, Yudha Pratesa

Journal of Materials Exploration and Findings

The susceptibility of steam line pipes, especially in the HAZ (heat-affected zone) and weldment areas, to hydrogen sulfide in the geothermal industry is crucial to understand from the early stages, particularly during construction. The combination of tensile stress from residual stresses after welding and metallurgical phase transformation makes the joint areas vulnerable to sulfide stress cracking. This condition becomes even more extreme when the equipment operates during the well stimulation phase. This research assesses the severity of H₂S-induced cracking using NACE MR0175 and ISO 15156-1 standards, focusing on the effects of pH and partial pressure of H₂S (p_{H₂S …}

Survival Signature Estimation For All-Terminal Networks By Solving The Multi-Objective Bottleneck Spanning Tree Problem, Dewan Maisha Zaman

Graduate Theses and Dissertations

This research examines the problem of estimating the survival signature of all-terminal networks using Monte Carlo (MC) simulation. Following a recent similar result for twoterminal networks, we show that the work required within each MC replication corresponds to solving a multi-objective bottleneck spanning tree (MOBST) problem. We implement the resulting MC procedure using a “Blocks” algorithm from the literature to solve the MOBST in each replication by identifying its minimal set of non-dominated points. We compare this implementation against intuitive benchmark procedures for completing the work within an MC replication. We conduct numerical experiments to assess the efficacy of multi-objective …

The Food Truck: A Multi-Product Newsvendor With Trans-Shipment Cost, Samuel Ajibola

Electronic Theses and Dissertations

The Newsvendor Problem is a key model in supply chain management that focuses on determining the optimal order quantity to minimize costs under uncertain demand. This thesis introduces the Food Truck Problem, an extension of the Newsvendor model that incorporates nonlinear transshipment costs for inventory transportation. In this context, a Food Truck must determine the optimal stock levels for multiple products while minimizing costs related to stock shortages, excess inventory, and transportation. Unlike traditional Newsvendor models, our approach explicitly considers a quadratic transshipment cost, which necessitates the use of Lagrangian duality and Karush-Kuhn-Tucker (KKT) conditions for analysis. Moreover, we apply …