Engineering Commons^™

Sustainable Conductive Rpla-Carbon Black Filament For Additive Manufacturing Via Single-Screw Extrusion, Zaidan Faraby Zulkarnain, Shakina Hawapi, Aini Zuhra Abdul Kadir, Muhd Ikmal Isyraf Mohd Maulana, Nor Akmal Fadil, Najlaa Nazihah Mas’Ood, Mohd Rizal Alkahari, Saidin Wahab

ASEAN Journal on Science and Technology for Development

The growing demand for low-cost, sustainable conductive filaments for additive manufacturing motivates the exploration of recycled polymer feedstocks as alternatives to virgin materials. However, the effects of prior thermal reprocessing on both the electrical performance and morphological integrity of recycled PLA (rPLA)–carbon black (CB) composite filaments remain insufficiently characterised, particularly under single-screw extrusion conditions. This study fabricates and characterises conductive filaments from virgin PLA and rPLA, each loaded with CB at 0.2, 0.6, and 1.0 wt%, using a low-cost desktop single-screw extruder. Melt blending was found to be essential for achieving continuous filament extrusion, as ball milling produced insufficient filler …

Dietary Intake Of Micro- And Nanoplastics: Potential Adverse Gi Effects On Microbiome, Inflammation, And Neoplasia, Michael Saadeh, Gordon Hong, Sana Rabeeah, Priyata Dutta, Edward C. Oldfield, Iv, David A. Johnson

Department of Medicine Faculty Publications

Micro- and nanoplastics (MNPs) are pervasive in food-contact environments and the human diet, positioning the gastrointestinal (GI) tract as the primary portal of entry and a plausible site of early biological effects. Human exposure is supported by detection of microplastics in stool and colon tissue, and emerging clinical studies report associations between fecal microplastic burden and GI disease states, including inflammatory bowel disease (IBD) and colorectal cancer (CRC). Preclinical studies provide mechanistic plausibility, reporting that ingested MNPs can modulate microbial ecology, alter mucus membrane integrity, increase intestinal permeability through changes in cellular tight junction biology, and induce inflammatory gene expression. …

Micro- And Nanoplastics: A Paradigm Shift In The Pathogenesis Of Inflammatory Bowel Disease, Michael Saadeh, Priyata Dutta, Gordon Hong, Edward Oldfield, David A. Johnson

Department of Medicine Faculty Publications

Micro- and nanoplastics (MNPs) are pervasive environmental contaminants with growing recognition as potential contributors to human disease. Widespread human exposure occurs primarily through ingestion of contaminated food and water, and MNPs have been detected in multiple human tissues, including the gastrointestinal tract. Experimental evidence provides a plausible biological basis for disease associations, including impairment of intestinal barrier integrity, activation of mucosal immune pathways, and alteration of gut microbial communities caused by MNP exposure. Although human data remain limited, early studies demonstrate MNP detection in stool and suggest potential correlations with inflammatory biomarkers such as fecal calprotectin. These findings, together with …

Microplastics, Nanoplastics, And Obesity: Current Evidence And Biological Mechanisms, Maram Albandak, Sanam Rabeeah, Ahmad Mahdi Zahidi, David A. Johnson

Department of Medicine Faculty Publications

Obesity is a rapidly growing global health concern. The pathogenesis is complex and cannot be fully explained by lifestyle factors alone. The increasing attention towards this concern has finally been directed towards environmental contributors which may influence metabolic regulation. Microplastics and nano-plastics (MNPs) are ubiquitous environmental pollutants that have recently been detected in food, drinking water, air, and human biological samples, raising concerns about their potential role in metabolic disorders, including obesity. Chronic exposure to MNPs may interfere with metabolic homeostasis through multiple biological pathways. Emerging evidence, including both experimental and animal studies, reports alterations in lipid metabolism, body weight, …

Assessing The Criticality Of Construction Trades: Skilled Labor Shortages And Their Cost And Schedule Impacts, Tamima Elbashbishy, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Skilled labor shortages are a pressing issue in the construction industry. Existing research has primarily focused on the effects of labor shortages at the project or industry level, but there is limited exploration of how these shortages vary across specific trades and their distinct impacts on project outcomes. Evidence indicates that labor shortages vary significantly among trades. This paper addresses this knowledge gap through quantitatively assessing the criticality of key construction trades based on the (1) extent of skilled labor shortages currently witnessed in each trade, (2) impact of these shortages on cost and schedule performance, and (3) degree of …

Environmental Engineers Develop Solutions To Problems Of Planetary Health: The Legacy Of Professor P. Aarne Vesilind, Daniel B. Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The principal ethical obligation of the engineering profession, to "hold paramount the health, safety, and welfare of the public," has been challenged for decades. Professor P. Aarne Vesilind identified two primary deficiencies: an anthropocentric bias that values nature only instrumentally and the use of non-mandatory, aspirational language for environmental protection, which resulted in the exclusion of enforceable environmental canons. This paper argues that two recent developments provide a comprehensive response to Vesilind's recommendations for engineering ethics. First, the United States Bureau of Labor Statistics has redefined environmental engineering as "developing solutions to problems of planetary health." Second, Oerther proposed a …

Impact Of Dispersed Crystalline Domains On Lithium-Ion Conductivity In Amorphous Li2.99ba0.005ocl Electrolytes, Emmanuel Olugbade, Junquan Ou, Leon Shaw, Jonghyun Park

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Solid-state electrolytes promise safer, high-energy batteries, yet ionic transport is limited by structural heterogeneity and interfacial resistance. We combine hydrothermal synthesis and molecular dynamics (MD) to determine how dispersed crystallinity and interfacial orientation govern lithium-ion conduction in barium-doped anti-perovskite Li_2.99Ba_0.005OCl. Structural and thermal analyses identify a largely amorphous matrix with embedded nano crystallites, and MD captures the same short-range order and dispersion seen experimentally. Electrochemical impedance spectroscopy separates high amorphous-phase conductivity from a pellet-scale response dominated by interfacial limitations, consistent with direct-current polarization. Cyclic voltammetry indicates a broad electrochemical stability window. We quantify transport in crystalline …

Distributed Vibration Sensing For Identification Of Loose Connectors In Coaxial Data Transmission Lines, Saidanvar Esanjonovich Valiev, Anthony C. Okafor, Jeremiah J. Rittenhouse, Jie Huang, Daniel S. Stutts

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This study investigates the effect of vibration-induced loose connections on signal reflection (S11) for loose connection identification in aerospace coaxial cables using distributed sensing approach, which is effective in filtering the noise and identifying minor discontinuities. In this approach, a sliding gated window is applied to S11 signal, a fast Fourier transform is performed over the gated windows, cross-correlation is computed between the baseline and vibration-affected signals, and the standard deviation is mapped along the cable length. Sinewave signals from 9 kHz to 5 GHz were swept through cables with vibrating connectors under three conditions: fully tightened, loosened by 180°, …

Tomo-Piv Study Of A Parallel Two-Dimensional Jet In Supersonic Flow, Josiah Mcdermott, Connor Bell, Davide Vigano

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Stabilizing combustion in supersonic flows is a formidable challenge due to the small time scales afforded for air-fuel mixing. Numerous studies in this area have demonstrated the potential of strut-style platforms for fuel injection and mixing enhancement, which remains an active area of research. In the Aerodynamics Research Laboratory at Missouri S&T, a strut-style injector system has recently been installed. In this study, we characterize the flow structures behind this platform in a range of injection pressures and corresponding mass flux ratios. The wake generated by a strut and injection plume, even absent combustion or mixing enhancement geometry, has an …

Corrigendum To “3d Semi-Analytical Thermo-Elasto-Plastic Model For Additive Manufacturing”(Additive Manufacturing, (2026), 127, C, (105308), (S2214860426002344), 10.1016/J.Addma.2026.105308), Tao Liu, Ming C. Leu, Edward C. Kinzel, Chinedum Okwudire

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The author regret about the correction in the Equation B(1) in original article. The corrected version of the Equation B(1) is given below,(1.1)∂uxxx,ξ∂x=116πμ1−ν4ν−1x−ξxR3−3x−ξx3R5−8ν−5x−ξxR13+34ν−3x−ξx3R15−18x−ξxzξzR15+30x−ξx3zξzR17−12ν−12ν−1x−ξxR1R1+z+ξz2+4ν−12ν−1x−ξx3R13R1+z+ξz2+8ν−12ν−1x−ξx3R12R1+z+ξz3 The authors would like to apologise for any inconvenience caused. DOI of original article: < 10.1016/j.addma.2026.105308>

Proactive Safety Reasoning In Human-Robot Collaboration In Disassembly Through Llm-Augmented Stpa And Fmea, Morteza Jalali Alenjareghi, Fardin Ghorbani, Samira Keivanpour, Yuvin Adnarain Chinniah, Sabrina Jocelyn

Études primaires

Disassembly tasks in human–robot collaboration (HRC) environments present safety challenges due to hazardous materials, control system variability, and physically demanding operator tasks. To address these challenges, we propose an AI-augmented risk assessment framework integrating System-Theoretic Process Analysis (STPA) and Failure Mode and Effects Analysis (FMEA). This framework is implemented in four configurations: Term Frequency– Inverse Document Frequency (TF-IDF), Fine-tuned Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and RAG with a structured Knowledge Graph (KG) built from safety standards. The system supports real-time, standards-compliant safety reasoning by generating interpretable, context-specific recommendations. We evaluate these configurations across GPT-3.5 TURBO, GPT-4o, GPT-4.1, and …

Computer Vision-Based Collision Prevention In Construction: Bridging Academic Advances And Industrial Requirements, Marwa Ziadia, François Gauthier, Damien Burlet-Vienney

Études primaires

Computer vision (CV) technologies have emerged as promising tools for real-time collision risk management. This paper examines CV-based collision-prevention systems from academic and industrial perspectives with a focus on identifying technical and implementation challenges affecting their deployment on construction sites. A scoping review of 158 publications was conducted, alongside an assessment of commercial CV-based collision-prevention systems currently used in construction. The analysis focused on five key functions: object detection, distance measurement and proximity estimation, tracking, worker re-identification (ReID), and deployment robustness. Academic studies demonstrate substantial progress in detection accuracy, real-time processing, trajectory tracking, and predictive risk assessment through deep learning …

Workshop Outcomes Report: 2nd International Workshop On Seismic Resilience Of Arctic Infrastructure And Social Systems, Majid Ghayoomi, Daniela Morganti

Faculty Publications

The report provides an overview of the second international workshop on Seismic Resilience of Arctic Infrastructure and Social Systems. The report discusses agenda, workshop activities, interdisciplinary working groups, and results. It ends with several strategic questions and investigation plans that were developed as part of the workshop activities.

Development And Validation Of A Multi-Output Neural Network-Based Virtual Temperature Sensor For Electric Vehicle Thermal Management, Dalton Michael Wiggins

Graduate Theses, Dissertations, and Problem Reports (ETD)

Battery electric vehicles (BEVs) rely on accurate thermal management to ensure component performance, efficiency, safety, and long-term durability. Critical propulsion system components, including electric motors and high-voltage battery packs, are commonly monitored using physical temperature sensors. However, these sensors increase system cost, introduce additional hardware complexity, and may be impractical for directly measuring temperatures at critical internal locations. Virtual temperature sensors (VTSs) provide a software-based alternative by estimating component temperatures using readily available vehicle operating data.

This research presents the development and validation of a long short-term memory (LSTM) neural network-based virtual temperature sensor capable of simultaneously estimating the motor …

Assessment Of Emissions Factors For Produced Water And Other Atmospheric Liquid Storage Tanks On Natural Gas Sites, David Glenn Childs

Graduate Theses, Dissertations, and Problem Reports (ETD)

As the US natural gas (NG) sector continues to grow, concerns have increased regarding the effects and increasing volume of greenhouse gases emitted into the atmosphere. While NG is a cleaner burning fuel than diesel and gasoline, unburned methane (CH₄) has a global warming potential (GWP) 27-30 times that of carbon dioxide (CO₂). To better quantify CH₄ emissions on NG sites, the US Department of Energy (DOE) granted West Virginia University (WVU) funding to collect direct measurements at well sites and compressor stations.

In this work, a total of 18 sites, including controlled and uncontrolled …

Architecture And Mechanistic Engineering Of Nanocomposite Steam Electrodes For High-Performance Metal-Supported Protonic Ceramic Cells, Xuemei Li

Graduate Theses, Dissertations, and Problem Reports (ETD)

The advancement of proton-conducting ceramic cells (PCCs) is crucial for efficient energy conversion in hydrogen- and/or ammonia-based energy carrier systems. However, a bigger success requires significant progress in cell fabrication, interfacial stability, fast electrode kinetics, and high Faradaic efficiency. This study investigates the rational design, fabrication, and performance breakthroughs of PCCs, with a focus on electrode architecture engineering, material interfacial coupling, and mechanistic understanding of electrochemical processes.

The metal-supported fuel electrode structure of PCFCs was systematically optimized, revealing the significant influence of Ni diffusion on cell performance and durability. High power density and stable ammonia-fueled operation were achieved. A heterointerface-rich …

Innovative Strategies For Stabilizing Zinc Anodes: From Molecular Design To Practical Zinc-Ion Batteries, Nhat Anh Thi Thieu

Graduate Theses, Dissertations, and Problem Reports (ETD)

Aqueous zinc-ion batteries (AZIBs) have become increasingly attractive as grid-scale energy storage solutions due to their safety, low cost, and environmental friendliness. However, the anode-electrolyte interface in AZIBs is prone to instability due to severe dendrite growth, self-corrosion, parasitic water-induced side reactions, and hydrogen evolution reactions (HER), which collectively lead to poor cyclability. To date, various interfacial engineering strategies have been investigated to address these challenges and improve the stability of Zn metal anodes. This dissertation presents a unified strategy for regulating Zn deposition through synergistic electrode and electrolyte design in laboratory-scale coin cells and then applies these concepts to …

Multiphysics Modeling Of Microwave-Assisted Calcination Of Soec Perovskite Precursors, Hongwei Liu

Graduate Theses, Dissertations, and Problem Reports (ETD)

The calcination of precursor powders is a critical step in the synthesis of solid oxide electrolysis cells (SOECs), where phase purity and microstructural control directly influence electrochemical performance. Conventional calcination methods are energy-intensive and time-consuming, often requiring prolonged high-temperature processing. In this thesis, microwave-assisted calcination is investigated as an alternative approach to enable rapid, energy-efficient processing of SOEC per- ovskite precursor powders. Microwave heating offers distinct advantages, including volumetric and selective heating, reduced processing times, and improved energy utilization compared to con- ventional thermal methods. A multiphysics modeling framework is developed, which integrates electromagnetic wave propagation, governed by Maxwell’s equations, …

Evaluation Of Engineering Controls In Mitigation Of Fecal And Chloride Contamination To An Urban Stream, Gabriel J. Zenny

Graduate Theses, Dissertations, and Problem Reports (ETD)

Fecal coliform contamination is a major contributor to surface water pollution in the United States’ (U.S.) waterways, whether from combined sewer overflows (CSOs) (point source pollution), runoff from precipitation and snowmelt (nonpoint source pollution), or exfiltration from aging and failing infrastructure. In addition to fecal bacteria, chloride contamination is also a major, prevalent surface water contaminant impacting U.S. waterways. Chloride contamination is predominantly released into U.S. waterways as nonpoint source pollution, endemic to northern areas that use industrial brine and salt as a form of mitigation for ice accumulation on roadways. The purpose of this research was to investigate impairment …

Plant-Wide Process Modeling, Techno-Economic Optimization, And Bayesian Uncertainty Quantification For Manufacturing Value-Added Products From Lignocellulosic Biomass, Poulomi Das

Graduate Theses, Dissertations, and Problem Reports (ETD)

For decades, many chemicals have been produced from fossil resources, contributing to resource depletion, pollution from extraction and refining, and hazardous byproducts. Growing environmental concerns and declining fossil reserves have intensified the search for sustainable sources of fuels, energy, and chemicals. Lignocellulosic biomass, the only abundant renewable carbon source, is therefore being explored as a feedstock for second-generation biofuels and high-value chemicals.

Currently, global wood-panel industry heavily depends on petroleum-derived commercial adhesives like phenol-formaldehyde, urea-formaldehyde, etc. These formaldehyde-based chemicals cause hazards to both human health and environment through emission of toxic volatile organic compounds. Typically, lignin is considered as one …

Semantic-Weighted Lidar–Camera Slam For Robust Mapping In Vegetation-Rich Environments, David Aigbovboise Akhihiero

Graduate Theses, Dissertations, and Problem Reports (ETD)

Many LiDAR odometry and SLAM methods are lightweight and effective, but they assume that all LiDAR point returns are equally reliable. In practice, this assumption is often violated in vegetation rich or semi transparent environments, where in a single beam footprint, LiDAR beams may intersect multiple scattering surfaces like leaves, branches or glass. These ambiguities in returns produces probabilistic or biased range measurements that violate the assumptions of most geometric registration frameworks and can lead to drift and inconsistency.

To address this challenge, this dissertation proposes a semantic-weighted LiDAR-camera SLAM framework that integrates class dependent weights into a front-end LiDAR …

Multi-Timescale Monitoring And Modeling For Resilient Smart Grids: Pmu Anomaly Detection And Battery Digital Twins, Muhammad Imran Hossain

Graduate Theses, Dissertations, and Problem Reports (ETD)

Modern power systems face failures at very different timescales. Cyber-physical disturbances may emerge within seconds, while battery degradation develops over hundreds of operating cycles. Both monitoring problems share the same underlying difficulty: power systems produce measurement data in abundance, but reliably labeled examples of abnormal or degraded operation are scarce. Rare grid events are difficult to label, and battery degradation data are heterogeneous across cells, cycling protocols, and chemistries. This thesis addresses these challenges through two complementary domain-informed learning frameworks that constrain representation learning using information specific to each physical problem.

First, at the system level, T-BiGAN, a Transformer-augmented bidirectional …

Cell-To-Pack Modeling Of Lithium-Ion Batteries: From Bayesian Parameterization To Pack-Level Optimization, Derek Slack

Graduate Theses, Dissertations, and Problem Reports (ETD)

One of the major hurdles for electric or hybrid aviation is the comparative energy density between lithium-ion batteries and jet fuel. To help obtain maximal power-to-weight ratio in electric or hybrid powertrains the battery pack design should be optimized to be as light as possible while meeting thermal safety and power requirements. The proposed solution is an optimization routine beginning with a cell-level parameter estimation of lithium-ion battery cells, where data driven Bayesian Gaussian Processes replace empirically or analytically derived parameters in a first principles electrochemical model in PyBaMM, as functions of the transient state of the cell. The resulting …

Physics-Informed Machine Learning Methods To Predict Heavy-Duty Diesel Engine Performance And Emissions, Sandeep Guguloth

Graduate Theses, Dissertations, and Problem Reports (ETD)

The development of internal combustion engines for increased efficiency and reduced emissions demands improved design tools that are cost-effective, fast, and easy to integrate into existing engineering workflows. Low-dimensional physically based engine models serve this role by reducing the need for iterative experimental prototyping but historically rely on empirical correlations that sacrifice fidelity compared to CFD. Machine learning (ML) approaches, conversely, achieve high predictive accuracy but lack interpretability and generalize poorly beyond their training data. Physics-informed machine learning (PIML) bridges this gap by constraining the solution space to physically feasible predictions, offering a more reliable way to model in-cylinder phenomena. …

Dataless Neural Networks For Boolean Satisfiability And Network Optimization, Andrew Evan Gautier

Graduate Theses, Dissertations, and Problem Reports (ETD)

Combinatorial optimization problems (COPs) require searching over a finite solution space subject to constraints, with the goal of satisfying an objective function. They arise in operations research, scheduling, resource allocation, circuit design, and many other fields. Many problems in combinatorial optimization (including satisfiability and network design) are NP-hard. Traditionally, researchers have built approximate solvers that return near- optimal solutions efficiently by developing increasingly sophisticated heuristics and meta- heuristics. Deep learning has provided new opportunities for improving combinatorial solvers by leveraging neural guidance to prune the search space. Traditional neural networks have distinct drawbacks in this context: separate training and …

Data Augmentation And The Reliability Of Conformal Prediction For Uncertainty Quantification In Medical Imaging, Rizwan Ahamed

Graduate Theses, Dissertations, and Problem Reports (ETD)

The safe clinical deployment of deep learning models for high-stakes medical imaging tasks requires more than high average accuracy; it requires demonstrable, per-case reliability. Uncertainty quantification (UQ) provides the missing signal that tells a clinician when a model prediction can be trusted and when a case should be escalated for expert review. Among UQ approaches, conformal prediction (CP) is especially attractive because it produces prediction sets that are guaranteed, under the assumption of exchangeability, to contain the true label with a user chosen probability, and it does so without assumptions about the model or the data distribution. This report first …

Student Support In Civil And Environmental Engineering, Heather Marie Rice

Graduate Theses, Dissertations, and Problem Reports (ETD)

Many student support services target first-year engineering students to help improve their transition from high school to college and to reach first-year retention goals. These opportunities are communicated to students through a variety of ways. The objectives of this work are to evaluate student perspectives of student services support factors in a civil and environmental engineering program and investigate how student support services and opportunities are communicated to students in a civil and environmental engineering program. The media identified for student support service outreach were the fundamentals of engineering program newsletters, academic advising newsletters, Statler eNews newsletters, and the bulletin …

Dielectrophoretic Biomarkers For Cancer Detection And Cell Analysis: Integrating Microfluidics And Ai, Raphael Olumide Oladokun

Graduate Theses, Dissertations, and Problem Reports (ETD)

Pancreatic ductal adenocarcinoma (PDAC) carries a five-year survival rate of 13%, driven largely by late-stage diagnosis and the absence of sensitive noninvasive screening tools. Current diagnostic methods lack the sensitivity to detect disease-associated systemic changes at early and precancerous stages, representing a critical clinical gap. This dissertation addresses the central hypothesis that PDAC and its pathological subtypes induce measurable, disease-associated electrophysiological changes in circulating PBMCs that can serve as correlative liquid-biopsy biomarkers. To test this hypothesis, this work asks: can dielectrophoresis (DEP), impedance and zeta potential analysis with AI-assisted classification distinguish benign pancreatic conditions (non-malignant control), precancerous lesions (primarily IPMNs), …

Multi-Sensor Fusion For Manual Wheelchair State Estimation, Kathylee Pinnock Branford

Graduate Theses, Dissertations, and Problem Reports (ETD)

Kathylee Pinnock Branford Manual wheelchairs are essential to mobility and independence, yet accurately characterizing wheelchair motion in real-world environments remains challenging. Inertial measurement units (IMUs) provide a practical means of estimating wheelchair kinematics, but existing trajectory-reconstruction studies have largely been limited to short, controlled trials. This report developed and evaluated a four-IMU framework comprising one sensor on each rear wheel and two sensors on the wheelchair frame. Three orientation algorithms (VQF, Mahony AHRS, and Madgwick AHRS), two accelerometer ranges (±2 g and ± 4 g), and calibrated and uncalibrated sensor data were evaluated during indoor motion-capture trials and a outdoor …

Process Optimization And Quality Control In Manufacturing Of Frp Composites By Vartm, Mohamed Emadeldin Omar Abdelhadi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Railroad tank cars, being one of the most used means of transportation of hazardous material across the country, have not been structurally upgraded for a long time. Thus, the Pipeline and Hazardous Materials Safety Administration (PHMSA), a United States Department of Transportation (USDOT) agency, released a rule for safer transportation of highly hazardous and flammable liquids by railroad to enhance the design specifications of both the new and existing tank cars in May 2015. A multifunctional composite jacket is proposed as a new material to structurally enhance the railroad tank cars to withstand any accidents that could happen en route. …