Engineering Commons^™

Ce 461 - 104: Professional Practice In Cee, Avinash Prasad

Civil and Environmental Engineering Syllabi

No abstract provided.

Ce 494 - 106, Hm2: Civil Engr Design I, Joseph Baladi

Civil and Environmental Engineering Syllabi

No abstract provided.

Ce 494 - 108: Civil Engr Design I, Joseph Baladi

Civil and Environmental Engineering Syllabi

No abstract provided.

Ce 495 - 102: Civil Engr Design Ii, Babu Veeragowda

Civil and Environmental Engineering Syllabi

No abstract provided.

Ene 262 - 004, Hm2: Intro To Environmental Engr, Paul Schorr

Civil and Environmental Engineering Syllabi

No abstract provided.

Ene 465 - 101: Sustainable Env Infrastructure, William Pennock

Civil and Environmental Engineering Syllabi

No abstract provided.

Mech 235 - 002,004: Eng Mech: Statics, Sunil Saigal

Civil and Environmental Engineering Syllabi

No abstract provided.

Mech 236 - 002, 004, 006, 008, Hm2: Dynamics, Yuan Ding

Civil and Environmental Engineering Syllabi

No abstract provided.

Mech 234 - 002, 004: Engineering Mechanics: Statics, Geraldine Milano

Civil and Environmental Engineering Syllabi

No abstract provided.

Mech 237 - 002, 004, 014, 016, 106, 108: Strength Of Materials, Eduardo Castro

Civil and Environmental Engineering Syllabi

No abstract provided.

Mech 237 - 010, 012, 110, 112: Strength Of Materials, Geraldine Milano

Civil and Environmental Engineering Syllabi

No abstract provided.

Mech 320 - 102: Statics & Mech Of Materl, Mohamad Saadeghvaziri

Civil and Environmental Engineering Syllabi

No abstract provided.

Ce 341 - 002: Soil Mechanics, Andrew Ciancia

Civil and Environmental Engineering Syllabi

No abstract provided.

Ce 350 - Hm2: Transportation Engr - Honors, Branislav Dimitrijevic

Civil and Environmental Engineering Syllabi

No abstract provided.

Ce 320a - 102, 104, 108: Hydraulics Laboratory, Thomas Olenik

Civil and Environmental Engineering Syllabi

No abstract provided.

Ce 431 - 002: Contruction Materials Lab, Walter Konon

Civil and Environmental Engineering Syllabi

No abstract provided.

Exploring Large Language Models For Summarizing And Interpreting An Online Brain Tumor Support Forum, Christy Muasher-Kerwin, M. Courtney Hughes, Michelle L. Foster, Ibrahiim Al Azher, Hamed Alhoori

Faculty Articles, Papers, and Other Scholarship

Objective

Methods

An Improved Machining Temperature Prediction Model For Aerospace Alloys: Effect Of Cutting Edge Radius And Tool Wear, Jonathan Theraroz, Oguzhan Tuysuz, Julius Schoop

Mechanical Engineering Faculty Publications

Temperature rise during machining impacts the workpiece material properties, residual stresses, surface and sub-surface quality. Experimental, numerical, and analytical methods have been used to predict the temperature fields in the tool, workpiece and chip. Each approach has its limitations: experimental techniques are cumbersome with expensive equipment, and numerical modeling is computationally inefficient. Existing analytical models only consider the effect of wear while ignoring the edge radius, though the latter changes with the flank wear in practice. To address this limitation, this article proposes an improved analytical temperature prediction model for orthogonal machining by introducing discrete linear heat sources on the …

Quantifying Multidimensional Effects Of Physicochemical Parameters On Pfas Adsorption Using A Hybrid Response Surface Methodology-Machine Learning Approach, Harsh V. Patel, Jazmin Green, John Park, Stephanie Luster-Teasley Pass, Renzun Zhao

Engineering Management & Systems Engineering Faculty Publications

Per- and polyfluoroalkyl substances (PFAS) contamination has posed a significant environmental and public health challenge due to their ubiquitous nature. Adsorption has emerged as a promising remediation technique, yet optimizing adsorption efficiency remains complex due to the diverse physicochemical properties of PFAS and the wide range of adsorbent materials. Traditional modeling approaches, such as response surface methodology (RSM), struggled to capture nonlinear interactions, while standalone machine learning (ML) models required extensive datasets. This study addressed these limitations by developing hybrid RSM-ML models to improve the prediction and optimization of PFAS adsorption. A comprehensive dataset was constructed using experimental adsorption data, …

The Association Between The Multidimensional Evaluation Of Attitudes Toward Security Recommendations And The Intention Of Following Those Recommendations, Miguel A. Toro-Jarrin, Pilar Pazos, Miguel A. Padilla

Engineering Management & Systems Engineering Faculty Publications

This study focused on the attitudes toward security recommendations as determinants of compliance with these recommendations in the workplace. It aimed to determine whether attitudes toward an overall concept (security recommendations in organizations) are associated with Information Security (IS) actions. We also examined the relationship between various dimensions of attitudes toward security recommendations and IS actions that follow these recommendations. We conducted a national survey of American workers. Six hundred and eighty-two responses were retained. We also collected demographic data to explore their moderating role in the relation between predictors and IS action-intention. The survey included four workplace scenarios and …

Individual Design Task Final Report Security Design, Ciarrah Bell

Honors Academy

"The Environmental Services Campus project is a comprehensive development designed to support the City of Springfield’s Environmental Services operations, with a focus on functionality, sustainability, and safety. The campus includes administrative office space, staff parking, a maintenance vehicle garage, and educational facilities aimed at community outreach. A component of the project is establishing site-wide security that not only protects personnel and assets but also integrates seamlessly with the architectural and environmental goals of the facility.

The primary focus of the Security IDT is the development and implementation of a comprehensive security strategy for the entire site. This includes designing and …

Leveraging Intrinsic Properties For Classification Of Coal Seams Towards Spontaneous Combustion Proclivity And Predicting Susceptibility Using Machine Learning: Smart And Sustainable Mining Approach, Siddhartha Agarwal, Pradeep K. Gautam, Yuhao Zou, Rishabh Dwivedi, Durga C. Panigrahi, Cihan H. Dagli, A. Singh

Engineering Management and Systems Engineering Faculty Research & Creative Works

Mine fires and other hazards caused by spontaneous coal combustion are a pervasive and longstanding issue in Jharia coalfields, India. This study proposes a novel approach to classify coal seams based on their propensity to spontaneous combustion using the intrinsic properties of 30 coal samples from different seams. This method eliminates the need for expensive and time-consuming experimental determinations of susceptibility indices (SI) such as crossing point temperature (CPT), critical air blast (CAB), and differential thermal analysis (DTA). All clustering models, viz. hierarchical, k-means, and multidimensional scaling, aptly classify coal seams into three categories: highly risky, medium risky, and low …

Using Telemetry To Assess Operator Effects On Hydraulic Shovel Energy Efficiency. Part Ii: Assessing Operator Effects, Noah Adekunle Aluko, Kwame Awuah-Offei

Mining Engineering Faculty Research & Creative Works

In this second part of a two-part series, this study investigates whether operator practices significantly affect the energy efficiency of hydraulic shovels, using detailed telemetry data. Rather than assuming this relationship, the research systematically tests it through a combination of statistical and regression analyses. First, Welch's and Kruskal–Wallis ANOVA confirm that operators differ significantly in their energy efficiency (p = 0.0000). Next, correlation analysis links parameters identified in Part I to energy per unit loading rate, and difference regression analysis determines which parameters most strongly influence efficiency variations. The results show that differences in payloads are the primary driver of …

Understanding The Usefulness Of Self-Escape Technologies In Underground Mining: Perspectives Of Metal/Nonmetal Miners, Eugene A. Gyawu, Kwame Awuah-Offei, D. A. Baker

Mining Engineering Faculty Research & Creative Works

Research on mine self-escape often focuses on coal mining, while perspectives from underground metal/nonmetal miners remain understudied despite their distinct emergency response challenges and unique operating environments. Using a scenario-based survey approach, this study evaluated underground metal/nonmetal miners' perceptions of the usefulness of 18 hypothetical self-escape interventions and how these perceptions are influenced by worker characteristics. Employment type was the strongest predictor of usefulness ratings, with hourly employees rating several self-escape interventions significantly higher than salaried employees, including those related to improving self-contained self-rescuers (SCSRs) and tethered guidance systems. The data suggested potential trends where perceived usefulness increased with more …

Evaluating Feasibility Of Incorporating Fuel Cell Drive Trains Into Existing Haul Trucks, Ayorinde Akinrinlola, Kwame Awuah-Offei, Abdullah Al Moinee

Mining Engineering Faculty Research & Creative Works

Hydrogen, as a fuel source in material handling, has become a viable option for achieving carbon reduction targets. The objective of this work was to apply vehicle drive train and energy simulation in MATLAB/Simulink to guide a discussion of the challenges and opportunities of incorporating hydrogen fuel cell drive trains into the current form factors of mine haul trucks. We built and validated a model based on the Komatsu 830-E truck and used it to estimate the hydrogen requirements for typical short-haul, medium-haul, and long-haul cycles; in the short-haul case (cycle time = 852 s) the truck consumed 23.6 L …

Cracking The Code: Harnessing Serpentinization-Driven Micro-Crack Networks For Hydrogen Generation And Subsurface Resource Recovery, U. Mutlu, G. Boitnott, A. Lisjak, J. Ha, O. Mahabadi, P. Connolly, B. N. Tunnell, T. Sherizadeh, S. Nowak, J. E. Olson

Mining Engineering Faculty Research & Creative Works

This study focuses on simulating volume-increasing processes caused by natural hydrogen-generating serpentinization, a reaction in which olivine and pyroxene typically transform into serpentine minerals. The volume increase leads to crack propagation along grain interfaces and new crack generation within unreacted crystals (aka grains). The interplay between thermo-hydro-mechanicalchemical (THMC) conditions plays a critical role in the initiation, propagation, and coalescence of various fracture surfaces, which enhances permeability and can accelerate serpentinization and hydrogen production rates. In the scenarios considered, chemical reactions between formation brine and reactive minerals result in volumetric expansion, generating stress and promoting the propagation of micro-cracks. Our results …

Aperiodically Intermittent Dynamic Event-Triggered Control For Predefined-Time Synchronization Of Stochastic Complex Networks, Lei Xue, Haoyu Zhou, Yongbao Wu, Jian Liu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, the problem of practical predefined-time synchronization in mean square (PTSMS) of stochastic complex networks (SCNs) is investigated through dynamic event-triggered control (E-TC). Different from the existing literature, this paper considers the dynamic E-TC in an a periodically intermittent control framework and employs the average control rate, which makes it easier to satisfy the conditions of the theorem. In comparison to existing finite-time and fixed-time synchronization, by introducing the time-varying function, it can be guaranteed that all states of SCNs achieve the practical PTSMS within a preset time without calculating the convergence time. Combined with stochastic analysis theory, …

Optimal Tissue Clearing Of Gastric Cancerous Organoids Imaged Via High Resolution Light Sheet Microscopy, Lauren D. Lieu

2025 Fall Honors Capstones Projects - Archive

While the rate of surviving a myocardial infarction has increased in the past 60 years from 60% to 90%, the rate of Americans developing chronic heart disease such as heart failure, arrhythmias, and hypertensive heart disease has risen. This has led to the development of imaging technology such as Light Sheet Microscopy (LSM) and Light Field Microscopy (LFM) to study heart contractility and congenital heart disease via models such as cancerous organoids or Zebrafish. However, LSM and LFM results are highly dependent on the quality of the staining and cleared samples. This study looks to add to the growing field …

Signal Analysis Of Calcium Dynamics In Pancreatic Cells, Abhidha Kunwar

2025 Fall Honors Capstones Projects - Archive

Calcium (Ca²⁺) signaling plays a critical role in insulin secretion from pancreatic βcells. Photo-biomodulation (PBM) of red or near-infrared wavelengths is applied to enhance cellular metabolism and Ca²⁺ activity in pancreatic cells. This study aims to rigorously analyze how PBM influences calcium dynamics in pancreatic cells by applying the Fast Fourier Transform (FFT), converting Ca²⁺ spiking patterns to the frequency domain to determine dominant oscillatory behaviors. Using a calcium-binding fluorophore, Ca²⁺ activity was acquired before and after PBM at 810 nm, processed with a machine learning algorithm, and further analyzed in MATLAB using FFT to assess changes in calcium signal …

Excitation And Polarization Of Isolated Neurons By High-Frequency Sine Waves For Temporal Interference Stimulation, Iurii Semenov, Vitalii Kim, Giedre Silkuniene, Andrei G. Pakhomov

Bioelectrics Publications

The capacity of temporal interference (TI) stimulation to target deep brain regions without affecting nearby surface electrodes remains uncertain. Using artifact-free optical recording, we compare excitation patterns and thresholds in hippocampal neurons stimulated by “pure” and amplitude-modulated sine waves, representing TI waveforms near electrodes and at the target, respectively. We show that pure 2- and 20-kHz sine waves induce repetitive firing at rates that increase up to 60–90 Hz with stronger electric fields. Beyond this limit, action potentials merge into sustained depolarization, resulting in an excitation block. Modulating the sine waves at 20 Hz aligns firing with amplitude “beats” and …