Engineering Commons^™

Localized Multivariate Statistical Assessment Of United States Construction Labor Shortages, Ahmed Shiha, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Craft labor shortage is a persistent challenge facing the construction industry across various markets. The historically low geographic mobility of construction labor exacerbates and localizes labor shortages. Several research efforts relied on subjective evaluations to quantify the existence of labor shortages on a national level. As such, there is a lack of empirical quantification of labor shortages at different geospatial levels. This paper fills this knowledge gap. To this end, the authors adopted a methodology that encompassed: (1) conducting a literature review to identify and collect national-level and subnational indicators that explain the changes in labor supply and demand; (2) …

Coupling Effect Of Abrasion And Erosion On Ultrahigh-Performance Seawater-Sea Sand Concrete, Dawei Ding, Wei Zhang, Lanqin Wang, Hongyan Ma, Biqin Dong, Song Han, Hongjian Xu, Dongshuai Hou

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Preparing ultrahigh-performance seawater-sea sand concrete (UHPSSC) to mitigate the scarcity of freshwater and river sand resources has generated considerable recent research interest. However, the deterioration mechanisms of UHPSSC under the effect of abrasion and erosion remain unstudied. In this paper, the underwater steel ball method was conducted to evaluate the impact of seawater, sea sand, steel fiber, and seawater abrasion on the abrasion resistance of UHPSSC. Then the stress erosion models of calcium-silicate-hydrate (C-S-H) were constructed to investigate the degradation mechanisms of UHPSSC under the effect of external stress and seawater erosion. The results show that the application of seawater …

Ai-Driven Uncertainty Quantification & Multi-Physics Approach To Evaluate Cladding Materials In A Microreactor, Alexander Foutch, Kazuma Kobayashi, Ayodeji Babatunde Alajo, Dinesh Kumar, Syed Bahauddin Alam

Nuclear Engineering and Radiation Science Faculty Research & Creative Works

The pursuit of enhanced nuclear safety has spurred the development of accident-tolerant cladding (ATC) materials for light water reactors (LWRs). This study investigates the potential of repurposing these ATCs in advanced reactor designs, aiming to expedite material development and reduce costs. The research employs a multi-physics approach, encompassing neutronics, heat transfer, thermodynamics, and structural mechanics, to evaluate four candidate materials (Haynes 230, Zircaloy-4, FeCrAl, and SiC–SiC) within the context of a high-temperature, sodium-cooled microreactor, exemplified by the Kilopower design. While neutronic simulations revealed negligible power profile variations among the materials, finite element analyses highlighted the superior thermal stability of SiC–SiC …

Design, Modeling, Control, And Analysis Of A Modular Two-Wheeled Self-Balancing Robotic System, Mishek Jair Musa

Graduate Theses and Dissertations

Two-wheeled self-balancing robots have garnered substantial attention within the realms of research and innovation in academia and industrial settings. In particular, advances in control algorithms, machine learning, reinforcement learning, and sensor technologies have played a pivotal role in their development. Although primarily recognized for their utility in personal transportation in the commercial sector, these robots possess potential applications across various domains, including search and rescue, healthcare, material handling, logistics, etc., due to their active stabilization and exceptional maneuvering capabilities. A particular area of interest lies in the creation of modular self-balancing robots designed for seamless reconfiguration and enhanced human interaction. …

Integration And Testing Of A Quadruped Robot With Ros2, Jeremy S. West

Master's Theses

The Cal Poly Legged Robotics Group has been developing research and teaching platforms for agile legged robotics since 2020. These platforms are expected to provide students with opportunities to develop complete legged-robot systems from low-level control to advanced robotics tasks such as motion planning and decision making. However, the current prototyped quadruped robot lacked the software and sensing capabilities for high-level quadrupedal gaits and advanced robotic research.

To address these challenges, this project developed Switch, a robotic platform that builds upon the previous BRUCE platform with significant hardware and software upgrades. Switch features a modular design that allows individual software …

Development Of A Control System For An 8-Dof Quadrupedal Robotic Research Platform, Jack Butler

Master's Theses

Quadrupedal robots offer a versatile locomotion option that can extend the operating space of a robot into uneven terrains. However, controlling these systems presents significant challenges due to nonlinearities introduced by various factors.

In this thesis, model-predictive control (MPC) is applied to an 8-DOF legged robot developed by Cal Poly’s Legged Robotics group. The MPC framework employs a lumped rigid-body model that treats the robot as a single rigid body with forces applied directly at the foot contact points. The controller is developed within the ROS2 environment, with integration of state estimation and gait-pattern generation, to provide maximum modularity and …

Machine Learning And Clinical Eeg Data For Multiple Sclerosis: A Systematic Review, Badr Mouazen, Ahmed Bendaouia, El Hassan Abdelwahed, Giovanni De Marco

Manufacturing & Industrial Engineering Faculty Publications

Multiple Sclerosis (MS) is a chronic neuroinflammatory disease of the Central Nervous System (CNS) in which the body’s immune system attacks and destroys the myelin sheath that protects nerve fibers, leading to a wide range of debilitating symptoms and causing disruption of axonal signal transmission. Accurate prediction, diagnosis, monitoring and treatment (PDMT) of MS are essential to improve patient outcomes. Recent advances in neuroimaging technologies, particularly electroencephalography (EEG), combined with machine learning (ML) techniques — including Deep Learning (DL) models — offer promising avenues for enhancing MS management. This systematic review synthesizes existing research on the application of ML and …

Reinforcement Learning And Virtual Human Animation: A Novel Approach To Data-Driven Animation, Portraying Dynamic, Flexible Human-Like Behaviours, Vihanga Gamage

Dissertations

Virtual characters require animation capable of portraying dynamic, context-sensitive human-like behaviours. Several approaches to generating such animation have been developed, but each carries limitations. Motion capture can produce high-fidelity animation but is expensive and ill-suited to systems that must respond in real time. Physics-based reinforcement learning (RL) enables flexible, dynamic behaviour portrayal, yet relies on simulation feedback signals that are unavailable for social gestures. Supervised approaches can learn social behaviours from motion capture data but yield agents with limited flexibility and generalisation.

This thesis presents RLAnimate, a model-based, data-driven RL framework for character animation that enables a single agent to …

Evaluating (Bio)Degradation Of Carbon Tetrachloride In Fe(Iii)-Reducing Environments, Adam Rogers

All Theses

Understanding degradation of carbon tetrachloride in-situ is vital for many remediation projects across the world, yet conclusive evidence of its feasibility is lacking in previous studies.

The main objective of this research is to assess the potential for carbon tetrachloride attenuation by biological, abiotic, and combined processes in a Fe(III)-reducing aquifer. In doing so, it assesses the effect of pH and stoichiometric ratio on abiotic degradation of carbon tetrachloride using various reducing agents, evaluates iron-mediated versus direct biotic degradation of carbon tetrachloride using pure cultures under resting and growth conditions, and characterizes the effects of culture strain, electron acceptors and …

Bike/Ped Data Collection And Model Calibration, Eirini Stavropoulou, Dionysios Tzamakos, Nikiforos Stamatiadis, Reginald Souleyrette, Teng Wang

Kentucky Transportation Center Research Report

Motivated by an uptick in pedestrian and bicycle traffic, as well as the inclusion of pedestrian and bicyclist weights in the Strategic Highway Investment Formula For Tomorrow, the Kentucky Transportation Cabinet (KYTC) has made significant investments in transportation facilities for nonmotorized users. Despite an intensified focus on the needs of nonmotorized users, KYTC has not yet established a formal program to track the number of people walking, biking, skateboarding, and using micromobility devices statewide. Based on a review of methods and technologies for counting nonmotorized users; analysis of counting programs established by local, state, and regional transportation agencies; and a …

Congestion And Travel Time Reliability Performance Measures For Shift 2026, Mei Chen, Eugene Antwi, Xu Zhang

Kentucky Transportation Center Research Report

Researchers obtained and processed probe speed data from HERE Technologies and integrated them with the Kentucky Transportation Cabinet’s highway inventory to develop congestion and travel time reliability performance metrics. This report summarizes analyses conducted using HERE speed data for 2022 – 2023. HERE data were processed using an established methodology, after which they were aligned with Kentucky’s highway inventory network. Analysis found that 2022 – 2023 HERE data offer significant improvements in coverage and quality over previous years. For locations that lacked sufficient data, researchers used HERE’s speed model to estimate hourly speeds. Data were used to calculate congestion and …

Traffic Prediction For Research And Education Networks: Anomaly-Aware Deep Learning And Benchmarking, Mohammad Arafath Uddin Shariff

School of Computing: Dissertations, Theses, and Student Research

Research and Education Networks (RENs) and High-Performance Computing (HPC) environments are critical infrastructures for modern scientific discovery, demanding sustained high-throughput and low-latency data transfers. Unlike commercial networks, RENs exhibit unique traffic characteristics, including predominant “elephant flows,” inherent burstiness, and complex temporal-spatial dynamics often decoupled from human-driven cycles. Traditional traffic forecasting methods, tailored for commercial Wide Area Networks (WANs), consistently fail to capture these distinct REN dynamics, leading to inefficient resource management and potential impediments to scientific progress.

This thesis addresses this critical gap by developing and validating a robust, scalable, and anomaly-aware traffic forecasting framework specifically tailored for REN/HPC networks. …

Hardware And Software Design For A Portable Surgical Training Simulator, Victoria Nelson

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

More than 51 million surgeries are performed on patients annually in the United States. That number grows to 310 million surgeries performed globally each year. Most surgeons go through a minimum of five years of residency – where they train and hone their surgical skills. It is important during this time, and throughout their careers, that they get plenty of practice. Surgical training is time intensive, expensive, and frequently under-resourced. There are finite amounts of surgical training modules for students to share at their facilities. The problem of getting adequate surgical training time continues to exist after surgeons begin their …

Owl Solar-Powered Link: Duck Radio Mesh For Autonomous Monitoring, Jaden Tran, Shane Williams

Electrical Engineering

The Solar Duck Sensor Node transforms a standard DuckLink into a fully self-sustaining environmental monitor. A compact solar panel / power bank module plugs into the power ports of both the DuckLink and the Raspberry Pi Zero 2 W, keeping them charged through day-night cycles. The Pi Zero 2 W will perform local processing of sensor data. Sensor output will come from the Raspberry Pi AI Camera and its object detection capabilities. This output will be distilled into metadata and advertised over BLE. The DuckLink captures these packets, encapsulates them into LoRa payloads, and forwards them across the ClusterDuck mesh …

Simulation Of Photochemical Effects On Air Quality, Grace Li

Chemical Engineering Undergraduate Honors Theses

Nitrogen dioxide (NO₂) and ozone (O₃) are both EPA criteria air pollutants in the troposphere, largely generated by combustion and therefore present in significant concentrations in urban areas. Sunlight facilitates chemical reactions between pollutants and ambient air. Aerosols modulate the amount of available energy required to drive such photochemical reactions, ultimately impacting air quality. Simulating photolysis rates with FastJX software is a resource-efficient strategy to study how these aerosols can affect air quality.

A Machine Learning Approach To Detect Pores In Laser Powder Bed Fusion Additive Manufacturing, Jose Galarza, Jose Barron Jr., Luis Jimenez, Tamer Oraby, Jianzhi Li, Farid Ahmed

Manufacturing & Industrial Engineering Faculty Publications

Real-time detection of pores in the Laser Powder Bed Fusion (LPBF) metal Additive Manufacturing (AM) process is proposed in this study and can be utilized for in-situ process monitoring and quality control. The average light emission data from the process captured by an optical tomography camera can be integrated into a defect detection module to characterize defects after the deposition of a layer. The light emission contains information on the process zone which could be extracted with the appropriate data techniques. In this paper, we proposed a machine-learning approach that utilizes the mean light intensity data from the melt-pool monitoring …

Navigating Transportation Barriers: Older Adults’ Familiarity With New Mobility Options And Perceptions Toward Autonomous Vehicles In Arkansas, Arna Nishita Nithila, Suman Kumar Mitra, Michelle Gray, Alishia Juanelle Ferguson, Jennifer D. Webb

Civil Engineering Faculty Publications and Presentations

The objective of this study is to analyze older adults’ familiarity with new transportation options (ride-hailing services, bike-share services, and shared e-scooter services) and their perception towards autonomous vehicles (fully autonomous cars), as well as how transportation barriers influence their familiarity and perceptions, in Arkansas, a predominantly rural state. Data from 775 older adults aged 60 years or older were collected between October 2021 and October 2022. To fulfill the study objective, the study used Latent Class Cluster Analysis to segment older adults into classes based on their familiarity with new transportation options and their perceptions of autonomous vehicles. The …

An Injectable, Dual-Curing Hydrogel For Controlled Bioactive Release In Regenerative Endodontics, Meisam Omidi, Daniela S. Masson-Meyers, Jeffrey M. Toth

Biomedical Engineering Faculty Research and Publications

Regenerative endodontics seeks to restore the vascularized pulp–dentin complex following conventional root canal therapy, yet reliable neovascularization within the constrained root canal remains a key challenge. This study investigates the development of an injectable, dual-curing hydrogel based on methacrylated decellularized amniotic membrane (dAM-MA) and compares its performance to a conventional gelatin methacryloyl (GelMA). The dAM-MA platform was designed for biphasic release, incorporating both free vascular endothelial growth factor (VEGF) for an initial burst and matrix-metalloproteinase-cleavable VEGF conjugates for sustained delivery. The dAM-MA hydrogel achieved shape-fidelity via thermal gelation at 37 °C and possessed tunable stiffness (0.5–7.8 kPa) after visible-light irradiation. …

Advancing Multi-Physics Modeling For Microwave Heating: Application In Micro-Reactor Design And Optimization, Raghav Adhikari

All Theses

Microreactors are a type of small-scale chemical reactors for achieving reduced volume, improved product selectivity and higher reaction rate. It allows precise temperature control, which is crucial for sensitive chemical processes. Microreactors can be employed as key components of conducting small-scale reactions with improved reactor configuration and process efficiency. It is important to identify a localized and precise heating mechanism to trigger and control the corresponding chemical reactions.

In fact, microwave heating has gathered significant attention in recent years due to its ability to deliver efficient, rapid, and localized heating, which can accelerate reaction rates and enhances the reaction selectivity. …

The Development And Application Of A Method To Simulate Commotio Cordis Inducing Impacts For The Evaluation Of Football Chest Protective Equipment, Bianca J. Henline

All Theses

As one of the most widely played and watched contact sports in the United States, football presents a significant risk of blunt chest trauma. Thus, effective chest protection is essential to prevent rare but fatal injuries like commotio cordis. Despite this, current test methods for certifying chest protective equipment fail to account for injury metrics relevant to commotio cordis events. Recent literature identifies rib deformation and viscous criterion as critical predictors of commotio cordis, yet these metrics are not adequately addressed in the existing testing standard. Furthermore, this standard exclusively assesses chest gear specific to baseball and lacrosse through projectile …

Polyphenols For The Mitigation Of Vascular Calcification; In Vitro And In Vivo Studies, Abdullah Altuhami

All Theses

Globally, cardiovascular diseases, in most cases associated with calcification, are the main cause of death. However, currently, the only effective cure is to undergo surgery to augment or receive a healthy donor heart, which could be very difficult due to the long waiting list and the associated risks. The possibility of body rejection of the foreign organs is attributed to immunoreaction or the risk of infection, since the donor must be on immunosuppressant drugs that lower the body's immunity and facilitate the body's acceptance of the new organ as one of its own. Taking that into consideration, using tissue-engineered vascular …

Effect Of Cigarette Smoke Extract And Nutrient Deficiency On Energy Metabolism And Biosynthesis: An In Vitro Intervertebral Disc Explant Culture Study, Avery E. Madden

All Theses

Low back pain consistently ranks among the leading causes of disability worldwide, with degenerative changes in spinal intervertebral discs (IVDs) recognized as a key contributor. Degeneration arises from the disruption of mechanical and biological cues within the disc’s cartilaginous tissue, often exacerbated by aging or injury. In recent decades, cigarette smoking has also been identified as a significant risk factor, as IVD degeneration is more prevalent among individuals with a history of smoking. Smoke inhalation is thought to promote degeneration both directly, by exposing cells to water-soluble toxic chemicals in smoke; and indirectly, through nutrient deficiency resulting from vasoconstriction and …

Mission-To-Designs: Automating Uav Conceptual Design Generation, Nana A. Adjei

All Theses

The conceptual design stage of Unmanned Aerial Vehicles (UAVs) is an exploratory phase where designers are tasked with developing and evaluating a wide range of viable design concepts, considering different geometries and configurations based on mission requirements. The goal is to identify the most suitable design after the exploration for further development and progression to the next phase. Several tools and frameworks have been developed to assist designers in this stage, each offering unique capabilities, but all with the common aim of aiding in the efficient development and evaluation of conceptual designs. This is important in the UAV design process …

A Three-Stage Matheuristic For The Blood Stochastic Inventory Routing Problem, Vincent F. Yu, Nabila Salsabila, Aldy Gunawan, Aldy Gunawan, Nurhadi Siswanto

Research Collection School Of Computing and Information Systems

This research introduces a blood distribution system under vendor-managed inventory that considers uncertain supply and demand. We present it as the Blood Stochastic Inventory Routing Problem, formulating it as a two-stage stochastic programming model. To solve this problem, this study proposes a three-stage matheuristic that combines a perturbation heuristic, Adaptive Large Neighborhood Search, and an exact approach. From historical data of Surabaya Blood Center in Indonesia, six sets of new instances are generated under different settings. Computational results show that our proposed three-stage matheuristic outperforms CPLEX and a two-stage matheuristic by gaining optimal or better solutions within a significantly shorter …

Development Of A Homogenized Material Model For Carbon Fiber–Aluminum Transition Joints Using Fea And Optimization, Nicholas M. Couch

All Theses

The integration of metals and composites in automotive structures improves manufacturability and overall structural performance. The proposed Ultrasonic Additive Manufacturing (UAM) joint provides a promising solution for joining aluminum and carbon fiber; however, modeling its behavior across an entire vehicle can be computationally expensive. To address this challenge, a homogenized material card is developed to efficiently capture the joint’s mechanical response while maintaining computational efficiency. A novel characterization method is implemented, employing implicit simulations and optimization techniques to determine the effective material properties of the UAM transition joint. This approach enables rapid iteration of material parameters, facilitating the efficient evaluation …

Computational Study Of Nonlinear Electrokinetic Phenomena In Shear-Thinning Fluids, Wai Yuen Leung

All Theses

Electrokinetic phenomena have been widely used for fluid pumping and particle manipulation in micro/nanofluidic systems. They refer to the motion of fluids or particles in response to an electric field because of the spontaneous formation of an electric double layer at the fluid-solid interface. Understanding electrokinetic phenomena in micro/nanochannels is critical for a wide range of applications across various engineering fields, such as disease diagnostics, contaminant treatment and cell analysis. To date, numerous studies have been reported on electrokinetic phenomena in Newtonian fluids, where the classical Helmholtz-Smoluchowski theory indicates a linear relationship between fluid electroosmosis/particle electrophoresis and electric field. However, …

Life Cycle Assessment Of The Cultivation Of Lettuce In A Hydroponic System Using The Nutrient Film Technique, Raquel Jordan

All Theses

Hydroponic systems are an emerging method of soilless crop cultivation typically done inside a greenhouse where nutrients are delivered dissolved in water rather than being supplied from the soil. Potential benefits of hydroponic systems include reduced irrigation requirements, higher crop yield per area, and the ability to grow crops year-round in nontraditional areas such as urban settings, cold climates, and sites with contaminated soil. However, hydroponic systems tend to have high energy requirements for lighting and climate control, which can yield significant environmental impacts. To explore the environmental impacts of cultivating lettuce in a nutrient film technique (NFT) hydroponic system, …

Machine Learning Based Medical Ultrasound Image Classification And Grad-Cam Interpretation, Victoria C. Hemphill

All Theses

This work takes a step in creating a diagnostic tool for the classification decision process of Achilles tendinopathy using ultrasound images. An attention-based multiple instance learning model is developed to classify the images. Typically, doctors capture multiple ultrasound images of the Achilles tendon during a study to determine a complete diagnosis. Multiple instance models adopt this behavior by providing a single label for a set of instances (images). The images are grouped into ”bags” at the study level and passed into the model. The MIL model then uses its attention property to assign an importance score to each image to …

Visor-Zt: A Visibility, Simulation, And Operational Resilience Framework For Zero Trust Security In Ros 2, Noah Tinker

All Theses

Robotic systems are becoming more and more prevalent in modern society, with Robot Operating System 2 (ROS 2) being the dominant operating system for these implementations. Its popularity can be attributed to its design, which is purpose-built for distributed systems and asynchronous communications. However, ROS 2 security is static and therefore less capable of responding to contemporary threats and network behavior. This becomes a greater issue when considering its applications in the military and defense sectors, where security is of the highest importance. In recent years, the U.S. Department of Defense (DoD) has implemented zero trust (ZT) security based on …

A Generalizable And Privacy-Preserving Framework For Anomaly Detection In Heterogeneous Iot Environments, Mahshid Rezakhani

All Theses

With the rapid growth of Internet of Things (IoT) devices across various sectors, detecting anomalies in such systems has become increasingly challenging. IoT environments produce diverse and evolving data streams, often lacking labeled examples, which limits the effectiveness of traditional machine learning models. These models typically require frequent retraining and struggle to adapt to new deployment conditions. This thesis proposes a flexible, privacy-aware framework for anomaly detection in multivariate time series data generated by heterogeneous IoT systems. The approach integrates a long short-term memory variational autoencoder (LSTM-VAE) with contrastive learning and adversarial adaptation, enabling the model to generalize across domains, …