Engineering Commons^™

Msmgoptimizer: An Open-Source R Package And Web Application For Streamlining Life Cycle Inventory Data Automation In Life Cycle Assessment, Philip Duah, Kwame Awuah-Offei

Mining Engineering Faculty Research & Creative Works

Life Cycle Inventory (LCI) compilation is indispensable in any Life Cycle Assessment (LCA) study, yet the preparation of inventory data for import into LCA software remains one of the most time‑consuming and error‑prone steps in the LCA workflow. LCI datasets frequently originate from multiple data sources and formats, necessitating automation tools that can optimize inventory data for direct use in LCA modeling platforms. SimaPro, the world's leading LCA modeling platform, for example, requires inventory data to be structured according to a proprietary CSV specification that is labour-intensive to prepare manually. Existing tools remain largely inaccessible to most researchers due to …

Thermal And Electrical Properties Of (Cr,Mo,Ta,V,W)C High-Entropy Carbide Ceramics, Ali Sarikhani, Steven M. Smith, Suzana Filipovic, William G. Fahrenholtz, Gregory E. Hilmas

Materials Science and Engineering Faculty Research & Creative Works

The synthesis and characterization along with the resulting properties of fully dense (Cr,Mo,Ta,V,W)C high entropy carbide ceramics were studied. The ceramics were synthesized from metal oxide and carbon powders by carbothermal reduction, followed by spark plasma sintering at various temperatures for densification. Increasing the densification temperature resulted in grain growth and an increase in the lattice parameter. Thermal diffusivity increased linearly with testing temperature, resulting in thermal conductivity values ranging from ∼7 W/m•K at room temperature to ∼12 W/m•K at 200 °C. Measured heat capacity values matched theoretical estimates calculated using the Neumann-Kopp rule. Room temperature electrical resistivity decreased from …

Radiological Safety Assessment Of Gamma Spectroscopy Based Spent Fuel Burnup Analysis At The Itu Triga Mark Ii Reactor, T. Akyurek, Z. Boduroglu, A. Kaya, O. Erbay, I. A. Reyhancan, M. S. Kiziltas, S. Ozcan

Nuclear Engineering and Radiation Science Faculty Research & Creative Works

This study investigates radiological safety and photon attenuation behavior during spent fuel inspection and burnup analysis at the ITU TRIGA Mark II Research Reactor. A lead-shielded fuel inspection system equipped with an HPGe detector was used to perform remote gamma spectroscopy on spent fuel elements, ensuring operator safety. Dose rate measurements were taken using a handheld radiation monitor at both the surface and at a distance of 1 m from the inspection system for each fuel element. The highest contact dose rate was observed for the B4 element (6.68 ± 0.60 μSv/h), while the lowest was for F30 (2.4 ± …

Borders And Bids: Assessing How Competition In Transportation Projects Is Shaped By The Presence Of Out-Of-State Contractors, Mariam Elazhary, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Competitive bidding in transportation construction is vital for securing better value for money and higher-quality proposals. Prior research has attempted to encourage more competition by proposing novel delivery methods, contractual incentives, or alternative bidder profiles. However, one viable bidder profile, which has received limited attention in the literature, is to encourage cross-border participation to expand the pool of qualified firms and thereby increase competition. While, in theory, this may improve economic efficiency, the inclusion of more out-of-state contractors (OSCs) is not costless. The goal of this paper is to assess whether participation by OSCs is associated with strengthening competition in …

Data-Driven Analysis For Managing Causes Of Disputes In Nuclear Power Plant Construction Projects, Mahmoud S. Mansour, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Nuclear energy remains a key element of the energy mix in the United States (US) and other parts of the world, with renewed and increased interest in recent years, driven by rising energy demand across various sectors. This is due to its capabilities of generating a vast amount of reliable and carbon-free electricity, which are crucial advantages as compared to other energy sources. However, nuclear power plant (NPP) projects involve unique risks and complexities that have long hindered their progress and shaped dispute dynamics differently from other construction sectors. Despite extensive research on construction disputes, there is a lack of …

Deployment-Oriented Evaluation Of Temporal And Spatial Forecasting Approaches For Electric Vehicle Charging Demand In Energy Systems, Maher Alaraj, Eyob Solomon Getachew

All Works

Accurate short-term electric vehicle (EV) charging demand forecasting is important for charging infrastructure operation, grid management, and energy-system planning. This study presents a deployment-oriented and reproducible evaluation of temporal, spatial, and unified spatio-temporal forecasting approaches for day-ahead EV charging demand prediction. Using publicly available charging-session data aggregated at hourly resolution across ZIP-code regions, we compare persistence and ARIMA baselines, XGBoost, Long Short-Term Memory (LSTM) networks, Graph Convolutional Networks (GCNs), and a unified GCN+LSTM architecture under a consistent preprocessing pipeline, leakage-free validation protocol, and rolling-origin evaluation framework. For the Boulder ZIP-code dataset considered in this study, temporal information provided the dominant …

Individualized Bayesian Inference Identifies Novel Genetic Variants For Parkinson's Disease, Jin Ren, Yasaman J. Soofi, Md Asad Rahman, Qing Lu, Jinling Liu

Engineering Management and Systems Engineering Faculty Research & Creative Works

Parkinson's disease (PD) is a complex neurodegenerative disorder with a significant genetic component. While genome-wide association studies (GWAS) have been instrumental in identifying genetic variants associated with PD, the reliance on large sample sizes and population-level analyses may overlook variants with lower minor allele frequencies or individual-specific relevance. Individualized Bayesian Inference (IBI) offers a promising method to complement GWAS by identifying and prioritizing candidate genetic markers at both the individual and patients-like-me subgroup levels. This study evaluates the application of IBI to PD genetics, using GWAS as a baseline for comparison. We analyzed genetic data from the Fox Insight online …

Identifying Influential Drivers To The Utilization Of Prefabrication On Student Housing At Cal Poly: A Case Study On The Delivery Method, Dominique Giang

Construction Management

As universities experience increasing enrollment and housing shortages, student housing projects require efficient delivery methods capable of meeting strict occupancy deadlines while minimizing disruption to active campus environments. This research investigates the influential drivers behind the utilization of prefabrication on an ongoing student housing project at California Polytechnic State University, San Luis Obispo. The seven-story project consists of 417 student beds and incorporates repetitive layouts and prefabricated building components. Through qualitative interviews with key project stakeholders involved in early decision-making and field execution, the study examines how project objectives, construction constraints, and delivery considerations influenced the decision to implement prefabrication. …

A Framework For Automated Quantity Extraction From .Ifc Models And Normalized Bid Comparison, Asmaa Mohamed Farouk

Theses and Dissertations

Accurate bid comparison remains a major challenge in construction tendering due to

differences in Bill of Quantities formats, item naming conventions, and pricing methods across

contractor submissions. These variations require time-consuming manual work and often lead to

subjective decisions. This research presents a computational framework that uses Building

Information Modeling through the .ifc file format, combined with text analysis techniques for

automated bid normalization.

The developed system uses a dual-component approach. Phase 1 extracts quantities from .ifc

model files using 3D geometric calculations, automated element classification. Phase 2 uses text

mining with a domain-specific dictionary of construction terms to interpret …

Affordable Thermal Control For Cell Culture Chambers: An Open-Source, Pid-Based Heating Module, Majid Rostami, Sesha Sai Ramineni, Sangyoon J. Han

Michigan Tech Publications

Commercial environmental control systems for live cell imaging chambers frequently cost $10,000–20,000. This paper presents an open-source, PID-controlled heating module built entirely from off-the-shelf components for approximately $500. The system employs four adhesively mounted polyimide heater pads driven at 12 VDC through a closed-loop chain: a K-type thermocouple feeds a Delta DTB4848LV controller, whose analog output is converted to PWM and applied to the heaters via an opto-isolated MOSFET switch. The required heating power was determined through analytical thermal sizing and verified by finite-element simulation (ANSYS Mechanical), confirming that the cell culture region reaches 37°C at steady state. Bench testing …

Evolution Of Raman And Photoluminescence Response In Molybdenum Disulfide Thin Films Deposited Via Thermal Atomic Layer Deposition, Wesley Jen, John D. Hues, Icelene Leong, Nolan H. Olaso, Ravindra K. Kanjolia, Mansour Moinpour, Steven M. Hues, Elton Graugnard

Boise State University Publications and Presentations

In order to enable further advances in microelectronics, new processes capable of precisely depositing films are required. This is especially true of processes meant for depositing two-dimensional (2D) transition metal dichalcogenides, such as MoS2, a material of particular interest due to its high potential mobility even at a thickness of a few atoms. In this work, we report industry-compatible processes for depositing crystalline MoS2 with a high degree of precision. We demonstrate the successful conversion of both MoOx and MoSx films deposited via thermal atomic layer deposition using bis(tert-butylimido)bis(dimethylamino)Mo(VI) and H2O or H2S, respectively, into crystalline MoS2 films after an …

Synthesis Of Fe-Doped Porous Carbon Catalyst Derived From Coconut Shell Waste Using Ferric Nitrate Nonahydrate (Fe(No3)3.9h2o) As An Iron Precursor, Ilham Lestadi Putra, Sukarni Sukarni, Heru Suryanto

Journal of Mechanical Engineering Science and Technology (JMEST)

Renewable energy from lignocellulosic biomass is a promising alternative to fossil fuels. Coconut shell (CS) waste is a favorable precursor for porous carbon due to its high carbon content, abundance, and non-food nature. However, conventional biochar often has limited surface area and catalytic active sites, hindering its effectiveness as a catalyst. While Fe-based modifications are promising, the use of ferric nitrate-assisted activation of coconut-shell-derived porous carbon remains underexplored. This research focused on developing an Fe-doped porous carbon catalyst from CS via ultrasound-assisted impregnation, followed by activation in a tube furnace. CS biochar was produced through pyrolysis at 550 °C and …

Dustmambanet: A Hybrid Inceptionv3–State-Space Network For Robust Solar Panel Dust Detection, Kadhim Hayawi, Sakib Shahriar

All Works

To develop a robust, scalable vision-based model for automatic detection and quantification of dust accumulation on solar photovoltaic panels, overcoming limitations of existing convolutional and attention-based methods and supporting proactive maintenance. We propose DustMambaNet, a hybrid model that consists of a pretrained InceptionV3 convolutional neural network as a feature extractor and two selective state space sequence modules. The state space modules use gated depthwise convolutions to represent long-range spatial dependencies that are of linear complexity, after rearranging spatial features to form sequences. The network provides a binary classification of dust with a severity index (DSI) and a continuous one. All …

Spatiotemporal Assessment Of Water Quality Around Western Australian Central Business District Using Satellite Multispectral Imaging, Muhammad Hassnain, Cameron Veal, Muhammad Rizwan Azhar

Research outputs 2022 to 2026

Monitoring urban surface waters requires methods that preserve spatial detail while capturing seasonal and interannual variability. Multispectral satellite remote sensing provides a scalable complement to conventional field and laboratory monitoring across rivers, wetlands, lakes and coastal receiving waters. This study used Sentinel-2 Level-2A imagery processed through the Pixxel Aurora workflow to map a model-based water quality index (WQI) for the Swan-Canning River system, adjacent urban lakes and nearby coastal waters around Perth, Western Australia, from 2018 to 2025. Of 150 candidate images, 96 monthly WQI maps were accepted after software-based cloud correction, area-of-interest coverage checks and visual quality review. Satellite-derived …

Recent Advances In Thermal Performance Improvement Of Parabolic Trough Solar Collectors Using Magnetic Nanofluids And Supercritical Carbon Dioxide Fluid, Taha Baig, Syeda Laraib Tariq, Furqan Jamil, Qamar Abbas, Hassan Bin Shahid, Hafiz Muhammad Ali

Research outputs 2022 to 2026

Among various available types of sustainable energy sources, the role of solar energy is vital due to its safety and low cost. Multiple rigs have been designed to use solar energy to generate steam, where the parabolic trough solar collector (PTSC) is a prominent example. Numerous numerical and experimental studies have been conducted to date to improve the thermal effectiveness of PTSCs. These studies include using hybrid nanofluids, insert types, magnetic nanofluids and supercritical carbon dioxide. The current paper provides a review of these studies, including an in-depth discussion section, an account of remaining challenges, and suggestions for future directions. …

Isolating Human Monocytes And Characterizing Human Macrophage Polarization Through Flow Cytometry And Morphological Analysis, Arthur Peter Klujian

Biomedical Engineering

Peripheral Artery Occlusive Disease (PAOD) is a cardiovascular disease that affects more than 200 million people. It is characterized by atherosclerosis, a biologic process where peripheral arteries are restricted due to a buildup in cholesterol and fats. This eventually leads to ischemia, developing complications such as chronic inflammation and possible limb amputation. The current standard of care for patients includes surgical revascularization and exercise therapy. These treatment strategies have had limited success with alleviating symptoms and restoring perfusion, however, many patients still experience ischemia and do not fully restore blood flow. Further exploration in pursuit of treating these shortcomings led …

Review: Advancements In Fibrous Aerosol Filtration Across Experimental Analysis, Numerical Modeling, And Fabrication Technologies, Mirza Muhammad Zaid, Ashish Ranjan Kumar, Ashish Kakoria, Lina Zheng, Guang Xu

Mining Engineering Faculty Research & Creative Works

The increasing incidence of aerosol-related pulmonary diseases has intensified the need for efficient fibrous filtration technologies capable of capturing ultrafine particles with low pressure drop. Although nonwoven fibrous filters are widely used in medical, industrial, and ventilation systems, their complex internal structures and multiscale transport mechanisms remain insufficiently understood. This review examines the theoretical foundations of aerosol filtration, including single-fiber capture mechanisms and the concept of the most penetrating particle size. In addition, electrostatic interactions, including charge generation, transport, and stability, are incorporated to extend conventional mechanical filtration frameworks. Particular attention is given to flow–particle interactions within fibrous media. We …

Sustainable Critical Minerals: Mining, Production, And Legacy, Joel G. Burken, Heileen Hsu-Kim, Mariam Al-Lami, Hunter W. Schroer, Scott Banta, Om Parkash Dhankher, Kwame Awuah-Offei, Lana Alagha

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

No abstract provided.

Manufacturing Routes For Oxide Dispersion Strengthened Alloys, Ertugrul Demir, Seung Min Ha, Alexander Killips, Guan Cheng Chen, Yitian Chi, Dileepa Maddumage, Dalong Zhang, Xiaochun Li, Haiming Wen, Enrique Lavernia

Materials Science and Engineering Faculty Research & Creative Works

Oxide dispersion strengthened alloys are promising structural materials for high temperature, irradiation, and mechanically demanding environments because their performance depends on fine and stable oxide dispersoids distributed within a metallic matrix. However, reliable fabrication remains challenging because precursor oxide nanoparticles or oxide forming species must be transformed into stable oxide dispersoids without excessive agglomeration, coarsening, contamination, or loss during processing. This review critically compares powder metallurgy, additive manufacturing, and liquid metallurgy routes for ODS alloy fabrication, with emphasis on oxide evolution, microstructure control, mechanical performance, scalability, and industrial maturity. Powder metallurgy remains the most reliable route for producing fine and …

The Role Of Mxene In The Process Of Sintering Hpcs To Ceramic, Jianyu Dai, Congjie Wei, Jeremy Watts, Chenglin Wu

Materials Science and Engineering Faculty Research & Creative Works

This work presents a detailed investigation of the pyrolysis and sintering processes of hydridopolycarbosilane (HPCS) polymers, focusing on the formation of β-silicon carbide (β-SiC) and the influence of Ti₃C₂–Ox in this process. Due to the computational limitations of density functional theory (DFT), molecular dynamics methods with appropriate potentials are necessary for simulating large-scale systems, however, the available potentials are limited when the modeling process evolves relatively more element types or complex chemical-mechanical processes are studied. In this work, a machine learning based MACE (Multi-body ACE) model is adopted and trained to accurately capture the polymer's transformation …

How Do Governments Combat Jihad Online?, Noah Cook

Honors College Theses

Since the September 11th, 2001 attacks, jihadist groups like ISIS, al-Qaeda, and al-Shabaab have used the internet as a tool for recruitment, radicalization, and propaganda dissemination. Since then, governments, non-governmental organizations, and private companies have developed strategies to combat jihadism on the internet. This paper examines how these actors have worked to mitigate the digital jihadist footprint and its effects by analyzing three main approaches to countering violent Islamist extremism on the internet: counter narrative initiatives, awareness-raising programs, and content removals. This paper finds that each of these methods has its own strengths and weaknesses. Counter narrative campaigns show the …

Using Clustering Techniques And Mitre Att&Ck Threat Interpretation To Detect Anomalies In Modbus/Tcp For Industrial Control Systems, Shivanjali Khare, Tirthankar Ghosh, Jhansi Sreya Jagarapu, Atharva Haridas Sagare

Journal of Cybersecurity Education, Research and Practice

Recent attacks on America's critical infrastructure have drawn increased attention on securing industrial control systems and operational technology in power plants, utility companies, and other sectors providing public services. Attack detection and mitigation strategies on these systems have shown promising results using machine learning and other statistical baselining techniques, mostly using supervised learning and classification. Unsupervised learning using cluster analysis and other techniques remain mostly unexplored. In this paper, we propose multi-layered feature extraction and hybrid clustering framework to detect fine-grained nested attack patterns in Modbus-over-TCP traffic. Operating under the assumption of known number of distinct network categories, our approach …

Engineered Porous Structures For Propellants Using Additive Manufacturing, Elbert Caravaca

Dissertations

Foamed polymers are widely used today for shock absorption and packaging materials to prevent damage to their contents. Typical foamed densities vary from 0.1 g/cm³ to 0.4 g/cm³ depending on the polymeric materials used. There is a need to explore foaming densities above 0.4 g/cm³ for propellants with highly engineered surface area progression for increased combustion performance. One way to achieve this is through highly controlled and engineered graded foam structures. To further exploit this approach, additive manufacturing coupled with a tunable means to generate foamed structures is the target of this work. To generate foam structures …

The Sliding Aperture Transform: A Mathematical Method Applied To Radiation-Induced Dlts Capacitance Transients, Md Abu Bakkar Siddique

Graduate Masters Theses

This thesis presents the Sliding Aperture Transform (SLAPt), a novel mathematical technique for extracting exponential argument and pre-factor  from experimental data. The method transforms measured waveforms into an inverse-domain representation where exponential decay processes appear as distinct peaks, simplifying data analysis and reducing the effects of baseline offsets and noise. The technique is here applied to time dependent capacitance transients associated with irradiated and non-irradiated silicon pn junction diodes. The technique is further developed and applied to positive argument exponentials using an axillary function. This allows forward bias  current-voltage measurements, and forward pulse-bias current transient measurements to be SLAP analyzed, …

Motor Imagery Eeg Decoding For Brain-Computer Interfaces: Structured Representation, Transfer, And Drift, Yiming Shen

Graduate Doctoral Dissertations

Motor imagery EEG decoding is often summarized by the accuracy of a final classifier, but the classifier is only the last stage of the pipeline. Before classification, the signal has already been shaped by preprocessing, feature extraction, source-session organization, and adaptation. This dissertation studies how feature representation, source-session transfer, and drift shape reliable MI-EEG decoding for brain-computer interfaces.

It first studies within-session decoding on public MI-EEG datasets using nested validation that keeps preprocessing, feature fitting, and model selection inside the training folds. This analysis separates gains from feature representation from gains due to nonlinear classification, and relates both comparisons to …

One Size Does Not Fit All: Revisitingworld Models And Neurosymbolic Ai, Amit P. Sheth, Madhur Thareja, Anushka Pawar, Niyati Rawal

Publications

World models are being built twice, from opposite ends, without a shared theory of how the two halves should meet. One lineage grounds the world model in perception: a self-supervised, latent-predictive encoder – exemplified by Joint Embedding Predictive Architectures (JEPA) – that learns the structure of sensory experi-ence. A second, older lineage grounds the world model in cognition: an explicit, inspectable structure of entities, rules, and constraints, ranging from knowledge graphs to formal logic to physical law. Neither lineage alone has produced a world model that is simultane-ously adaptive and auditable. We argue this is not solved by picking a …

Neural Network Driven By Electrochemical Performance Data For Predicting The Discharge Termination Time Of Seawater Electrolyte-Based Metal-Air Batteries, Peng-Peng Shen, Yi-Chi Pan, Yu-Rong Liu, Lu-Dan Zhang, Ning Niu, Guan-Jun Wang, De-Kun Yang, Xin-Long Tian, Peng Rao

Journal of Electrochemistry

Seawater electrolyte-based metal-air batteries exhibit great promise for marine energy supply systems. However, conventional statistical analysis methods, though applicable to seawater metal-air battery lifetime prediction, have inherent limitations of insufficient prediction accuracy and large error. Herein, a deep time-series regression framework based on InceptionTime and incorporating prior-biased attention pooling is proposed to construct a nonlinear mapping between electrochemical performance sequences and the discharge termination time of catalysts. Specifically, chronoamperometric profiles are employed to extract long-term stability features, while prior knowledge derived from linear sweep voltammetry is introduced to strengthen the attention weighting over critical potential regions. Under a nested leave-one-catalyst-out …

Microwave-Assisted Synthesis Of Core-Shell Structured Pd@Pdptcufe Recessed Truncated Octahedral Nanocrystals For Multifunctional Electrocatalysis, De-Zhong Hu, Wen-Dan Jiang, Wei Keat Ng, Jun Yang, Xiong-Wu Kang

Journal of Electrochemistry

Developing cost-efficient and durable multifunctional electrocatalysts of hydrogen evolution reaction, oxygen reduction reaction and oxygen evolution reaction is crucial for improving energy conversion efficiency in electrolytic water splitting electrolyzer and advancing rechargeable zinc-air batteries. Polyhedral shaped nanocrystals with well-defined crystal facets represent a type of model catalysts that enables the exploration of structure-activity relationships. However, it is still very challenging to prepare alloy nanocrystals with multiple metal components due to their complicated redox potentials and mixing enthalpy. Herein, we report a rapid microwave-assisted polyol reduction method for syntheses of core-shell Pd@PdPtCu, Pd@PdPtCuNi, Pd@PdPtCuCo and Pd@PdPtCuZn octahedral nanocrystals, and recessed truncated-octahedral …

In Situ Electrochemical Characterization Techniques For Active Hydrogen In Electrocatalytic Nitrate Reduction To Ammonia, Hong-Mei Li, Mei Yi, Zhao-Yu Jin, Ming-Hao Xie, Khalid M. Omer, Yong Guo, Pan-Pan Li

Journal of Electrochemistry

Electrocatalytic nitrate reduction to ammonia (NitRR) represents a sustainable pathway that integrates environmental remediation with the production of high-value ammonia. However, the activity and selectivity of this process are limited by the generation, consumption, and dynamic equilibrium of the key transient intermediate—active hydrogen (*H). Precise modulation of *H necessitates a comprehensive understanding of its behavior, which relies fundamentally on advanced in situ electrochemical characterization techniques. However, a systematic review dedicated to the rational selection and application of in situ electrochemical techniques for the specific characterization of *H in NitRR, with clear definitions of each technique's "detectable targets, quantitative accuracy, and …

Dynamic Flood Risk Assessment For Transportation Infrastructure In Fresno, Ca, Yushin Ahn, Fayzul Pasha

Mineta Transportation Institute

Urban roadway flooding in flat metropolitan environments often shows up as small areas of standing water rather than large, flowing floods. In low-gradient urban environments, subtle micro-topographic features—such as pavement crowns, curbs, and localized depressions—often control where surface water accumulates following rainfall. Accurately identifying these localized ponding areas is important for roadway flood screening and infrastructure management. This study develops a LiDAR-based depression mapping framework to identify roadway segments susceptible to surface ponding in flat urban environments. High-resolution airborne LiDAR datasets were used to generate detailed elevation maps (down to less than a foot in resolution) from ground-classified point clouds …