Engineering Commons^™

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 …

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.

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 …

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 …

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 …

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. …

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 …

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 …

Optimizing Ball‐Milled Composites For Fast Energy Release Under Shock Compression, Siva Valluri, Edward Dreizin, Dana Dlott

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Microparticle additives containing both Al fuel and oxidizer, fabricated by arrested reactive milling (ARM), could potentially increase the power of energetic materials such as HMX because they contain premixed fuel and oxidizer. Optimizing shock reactivity requires exploring a vast parametric space encompassing composition, milling parameters that govern microstructural features such as intraparticle voids and fuel-oxidizer mixing, and the resulting inhomogeneous shock reactivity of individual particles. To present our approach, we used a model composition 8Al⋅3CuO, previously optimized for combustion. We milled powders and prescreened different prepared batches using differential scanning calorimetry (DSC) to rule out batches with significant pre-reaction. Then …

Probe Cytotoxic And Oxidative Stress Effects Of Nanoplastics On Caco-2 Cells: Insights From Raman Spectroscopy And Machine Learning, Bryan Gustafson, Negar Kosari, Emily Brothersen, Morgan Mosher, Anhong Zhou

Biological Engineering Student Research

Nanoplastics and microplastics have become an increasing ecological and health concern due to their widespread presence in the environment and food chain. In this study, Caco-2 cells were used as an in vitro model of the human intestinal epithelium to investigate the cytotoxic effects of polystyrene nanoparticles and microparticles of varying sizes, concentrations, and surface modification. Oxidative stress and apoptosis were evaluated following particle exposure. Raman spectroscopy, combined with machine learning analysis, was employed to detect and characterize biochemical alterations in the cells. Several peak ratios were selected to cluster data depending on size. A correlation between apoptosis and both …

Fabrication Of Photoresist Su-8 Pyrolyzed Carbon Electrodes And Their Integration In A Microfluidic Hematocrit Detection System, Hwi Yong Lee, Jessika A. Rogers, Chito Kendrick, Sanaz Habibi, Adrienne Minerick

Michigan Tech Publications

Carbon microelectrodes are attractive for microfluidic biosensing due to their wide potential window, low overpotentials, chemical stability, and compatibility with low-cost microfabrication. Pyrolysis of photopatterned SU-8 offers a scalable route to carbon electrode fabrication; however, conventional two-step pyrolysis often leads to adhesion issues, geometric distortion, and limited surface area in low-aspect-ratio planar designs. These constraints restrict performance and broader adoption in analytical microdevices. Hematocrit determination, a clinically essential diagnostic measurement, requires electrodes with high reproducibility and robust electrochemical response. A simplified fabrication strategy that improves electrode surface area and performance while maintaining low-aspect-ratio planar geometries remains unresolved. We developed a …

Synergistic Reinforcement Of Lignin–Chitosan Hydrogels Using Vanillin As A Sustainable Green Crosslinker, Moses Ayitey-Adjin Jr., Mohammad Jahid Hasan, Jeremy Erb, Kishore Chand, Garry S. Crosson, Kenya Crosson, Esteban Ureña-Benavides, Erick Salvador Vasquez-Guardado

Chemical and Materials Engineering Faculty Publications

While bio-based hydrogels derived from lignin and chitosan are promising sustainable adsorbents, their practical application is hindered by poor mechanical stability. This study addresses this limitation by synthesizing lignin-chitosan hydrogels using vanillin as a green, bio-derived crosslinker via a facile solution-casting method. The formation of imine (Schiff base) linkages between the aldehyde groups of vanillin and the primary amines of chitosan was confirmed by FTIR spectroscopy (C = N stretching at ~ 1602 cm^− 1). SEM and TGA results demonstrated a reduction in the pore size of the crosslinked hydrogel and an enhanced residual thermal mass. Rheological and …

Percolation-Induced Thermo-Rheological Transitions In Biobased Graphene Nanoplatelet Nanofluids, Abiodun A. Saka, Tobechukwu K. Abor, Anthony C. Okafor, Monday U. Okoronkwo

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Biobased lubricants with thermally responsive rheology are increasingly needed for high-efficiency mechanical systems. Graphene nanoplatelet (GnP) nanofluids in vegetable oils are promising candidates, yet their percolation-driven thermo-rheological transitions remain insufficiently understood. In particular, the coupled concentration–temperature landscape controlling network-mediated flow transitions has not previously been established. Here, surfactant-free GnP nanofluids were prepared in high-oleic soybean oil (HOSO) at concentrations of 0.025–2.15% v/v (ϕ), and their rheological response was mapped between 25°C and 80 °C under steady-shear and oscillatory conditions. Below the percolation threshold (ɸ ≤ 0.1% v/v), the nanofluids exhibit near-Newtonian behavior, moderate reversible viscosity enhancement, and classical Arrhenius-type temperature …

Website: Home, Zhiqu Lu, Likun Zhang, Lei Cao

Gulf Research Program Data Sets

No abstract provided.

Website: Latest Results, Zhiqu Lu, Likun Zhang, Lei Cao

Gulf Research Program Data Sets

No abstract provided.

Website: News And Events, Zhiqu Lu, Likun Zhang, Lei Cao

Gulf Research Program Data Sets

No abstract provided.

The Self-Aware Room: A Framework For Operational Self-Awareness In Evolvable Blended Environments, David B. Smith

Publications and Research

The Self-Aware Room (SAR) is a room-scale research environment developed within the larger Balanced Blended Space and Blended Reality Performance System research trajectory. Rather than treating the room as a conventional “smart” environment composed of fixed automation technologies, SAR approaches it as an evolvable blended environment made from physical, virtual, conceptual, sensory, computational, and performative relationships. Its defining feature is not any particular sensor, model, or output device, but the set of transformations through which physical activity becomes structured observation, bounded representation, interpreted state, governed decision, and mediated response.

This paper develops the conceptual and methodological foundations of SAR as …

Mineral Composition-Driven Competitive Adsorption Behavior Of Superplasticizer In Recycled Concrete Powder-Cement Pastes: Quantification And Validation, Junpeng Du, Tongsheng Zhang, Hongyan Ma, Peiliang Shen, Yiqun Guo, Siqing Zeng, Jiangxiong Wei, Qijun Yu

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Recycled concrete powder (RCP) exhibits pronounced variability in mineral component contents, which leads to competitive adsorption of superplasticizers in RCP-Portland cement (PC) pastes and consequently to mineral composition-dependent deviations in rheological properties. In this study, limestone powder (LSP), quartz powder (QZP), and hardened paste powder (HPP) were used to simulate the main components of RCP. Effects of RCPs with target components on the rheological properties of blended cement paste were investigated, and a competitive-adsorption coefficient (CC) was proposed to quantify the competitive adsorption of superplasticizer. Results showed that increasing LSP-enriched RCP content reduced the yield stress of cement paste, primarily …

Enhancing Algae Biofilm Quantity And Value Through Controlled Light Intensity For Treatment Of Municipal Anaerobic Digestor Effluent, Joshua D. Wintch, Ronald C. Sims

Biological Engineering Student Research

Rotating algae biofilm reactors (RABRs) have been shown to remove nutrients from wastewater and to cultivate algae for bioproducts. Another key variable in RABR technology for cultivating microalgae biomass is light intensity. The goal of this study was to address a gap in the design and operation of algae biofilm reactors by analyzing the effects of light intensity on biomass quality and quantity, chemical precipitation of phosphorus, and phosphorus uptake into biomass. This study utilized a triplicate laboratory-scale experiment with PAR intensities from 10 to 2000 µmol m⁻²·s⁻¹. Municipal wastewater anaerobic digester effluent (ADE) was utilized …

Bc-Xaia: A Blockchain-Based Recruitment Framework With Explainable Ai And Smart Contract Integration, Heba Allah Adel, Sayed Abdelgaber, Wessam H. El-Behaidy

Computer Science

Ensuring transparency and security in digital recruitment systems remains a critical challenge. This study proposes BC-XAIA, a unified framework that integrates blockchain, smart contracts, explainable artificial intelligence (XAI), and agile methodology to enable consistent, secure, and traceable recruitment decision-making. Smart contracts, implemented in Solidity and deployed using the Remix Ethereum IDE, automate key processes such as identity verification, data access control, and behavior monitoring, reducing reliance on centralized intermediaries. To support intelligent decision-making, multiple machine learning models, including Random Forest, Logistic Regression, and Support Vector Machine (SVM), were trained and evaluated on a recruitment dataset, with Random Forest achieving the …

Sensitivity Study Regarding Abs Formulation On Hybrid Rocket Performance, Ava T. Wilkey, Ryan J. Thibaudeau, Stephen A. Whitmore

Mechanical and Aerospace Engineering Student Publications and Presentations

Acrylonitrile butadiene styrene (ABS) has emerged as a widely adopted solid fuel for hybrid rocket propulsion due to its compatibility with fused deposition modeling and favorable regression characteristics. As a terpolymer, however, ABS monomer mass fractions vary across commercial sources, introducing thermochemical variability that is rarely accounted for in propulsion modeling. This study presents a sensitivity analysis examining how compositional variability among ten commercially available ABS feedstock propagates into hybrid rocket performance predictions. Each source was characterized using bomb calorimetry and Fourier-transform infrared spectroscopy to derive source-specific constituent mass fractions and enthalpies of formation, which were supplied to NASA’s Chemical …

Multidimensional Total Quality Management And Its Effects On Sustainability And Performance In Industrialized Building System Projects, Felix Delmonte

Mechanical and Civil Engineering Faculty Publications

This study develops and tests a multidimensional total quality management (TQM) framework to explain how distinct quality practices influence environmental sustainability, construction quality, cost and schedule performance, waste reduction, energy efficiency, stakeholder satisfaction, and overall project performance in industrialized building system (IBS) projects. Soft and hard TQM dimensions such as leadership commitment, customer focus, employee involvement, training and continuous improvement, process management, supplier quality, and data driven decision making are operationalised and linked to eight outcome constructs. Partial least squares structural equation modelling (PLS SEM) is used to estimate direct effects and to examine mediation by waste reduction and energy …

Ai Cyber First Responders: Bottleneck Analysis Of Heterogeneous Cpu–Gpu Pipelines For Security Operations Center Triage, Christine Pierce

Harrisburg University Other Works

Abstract — Modern Security Operations Centers (SOCs) must continuously process massive volumes of heterogeneous security telemetry while meeting stringent throughput, latency, and operational continuity requirements. Although transformer-based artificial intelligence has significantly improved threat detection and alert prioritization, most cybersecurity research evaluates model accuracy rather than the end-to-end behavior of AI-enabled operational pipelines. Consequently, relatively little is known about how heterogeneous CPU–GPU coordination, scheduling overhead, memory movement, and synchronization collectively influence operational SOC performance. This paper presents the AI Cyber First Responder, a heterogeneous SOC triage architecture that integrates GPU-accelerated transformer inference with CPU-based doctrine-driven reasoning to investigate end-to-end pipeline behavior …

The Use Of Machine Learning Models For Predicting The Dielectric Strength Of Gases, Matthew Mileski, Paul W. Groth, Timothy S. Wolfe, Adib J. Samin

Faculty Publications

Technological advancements in high voltage systems have pushed sulfur hexafluoride (SF6) to its operational limits. Furthermore, this gas has other drawbacks including a high liquefaction temperature and a high global warming potential. Therefore, there has been an urgent need to find alternative gases with high dielectric strength (DS). In this work, density functional theory (DFT) is used to calculate molecular descriptors that are fed into an artificial neural network (ANN) and a random forest (RF). These machine learning (ML) models are then used to predict the DS for hundreds of molecules. A finite element model (FEM) is also used to …

The Business Next Door: Ev Construction: Back To The Future, Steve Vanderveen

University Faculty Publications and Creative Works

The genesis of the company dates to 1945 when two young men, Peter Elzinga and John Volkers, formed a partnership to construct homes in Fremont, Michigan. But its story begins before that.

Mountain Development In Nepal: Settlements, Infrastructure, And Economic Transformation, Keshav Bhattarai, Ambika P. Adhikari

Himalayan Research Papers Archive

As Nepal urbanizes, expands infrastructure, strengthens local governments, and explores deeper connectivity with India and China, climate change is increasing floods, landslides, heat, and water insecurity. Rapid internal migration, rising disaster risks, youth outmigration, and dependence on remittances are also revealing the limits of conventional urban development, especially in the mountainous region. The central challenge for Nepal is no longer just to accommodate growing towns and cities, but to build settlements that are safe, productive, environmentally resilient, and capable of sustaining long-term prosperity.

This paper argues that Nepal's urban future must be guided by a new development paradigm centered on …

Enhancing A Mid-Wave Infrared Fourier Transform Hyperspectral Imager For Explosions, James T. Stofel, Kody A. Wilson, Martin Larivière-Bastien, Anthony L. Franz, Michael L. Dexter

Faculty Publications

Capturing reliable hyperspectral imager data at a meaningful frame rate for explosions and other fast-changing scenes is not possible in the mid-wave infrared region under traditional sensor operating configurations and processing techniques, which typically have frame rates on the order of 0.5–2.0 Hz. To combat these shortcomings, the scene acquisition parameters were tailored for explosions and a new method for processing optical signatures of fast transient scenes with Fourier-transform infrared hyperspectral imagers was developed. For this technique, the instrument was first configured to collect asymmetric interferograms while optimizing the number of measurement points on the short side of the interferogram. …