Digital Commons Network^™

Scenario-Based Pareto Analysis For Multi-Objective Optimization Of Process Parameters To Improve Life Cycle Impacts: Case Study Of Ge Production, Dennis Dadzie

Miners Solving for Tomorrow Research Conference

Growing demand for critical minerals increases the need for clear evidence on the environmental burdens of their production. Life‑cycle assessment (LCA) quantifies impacts, but it does not by itself show how to navigate competing environmental performance improvement goals. We examine 63 process configurations for single‑crystal germanium made via chlorinated distillation using five indicators: global warming potential (GWP), water consumption (WC), fine particulate matter (FPM), terrestrial acidification (TA), and cumulative energy demand (CED). Across scenarios, WC is negatively correlated with GWP, weakly related to FPM, TA, and CED, while the other four indicators are strongly positively correlated. Pareto analysis highlights a …

Assessing Radon And Radon Progeny Deposition On Simulated Lung Filter System: Effects Of Cigarette And E-Cigarette Use Based On The Icrp Model, Manuela Isabel Arenas Alvarez

Miners Solving for Tomorrow Research Conference

This project investigates the potential interaction between radon exposure and e-cigarette aerosols, focusing on how radon progeny deposit in the lungs under combined conditions. An experimental system was developed to simulate regional lung deposition based on the International Commission on Radiological Protection (ICRP) model. The setup uses a filter-based design and a custom modular atomizer to generate stable aerosols, with four commercial plastic filters evaluated. Initial results demonstrate reproducible filtration behavior and a total deposition pattern matching ICRP predictions within 21% error. Ongoing work aims to improve agreement with regional deposition curves and enable combined radon–aerosol exposure experiments. This platform …

Preventive Maintenance Scheduling Using Artificial Intelligence And Decision Support Agent, Samiksha Aryal

Miners Solving for Tomorrow Research Conference

Preventive Maintenance models have traditionally relied on a time-based maintenance model, which uses fixed statistical distribution to represent the time-to-failure (TTF). The requirement of data-driven models and automated decision-making systems have become essential for modern manufacturing systems. The use of fixed statistical distribution limits the ability of existing models in producing solutions in real-time. Our model overcomes these limitations by implementing an empirical distribution to represent TTF. The empirical distribution is generated using a neural network which eliminates noise from the raw maintenance log. Renewal Reward Theorem (RRT) is implemented to efficiently provide maintenance threshold in real time. The use …

Robustness Of Fuzzy Artmap To Adversarial Attacks And Progressive Adversarial Training For Streaming Learning, Shane Cairns

Miners Solving for Tomorrow Research Conference

Incremental learners deployed on streaming data must remain robust to evolving adversarial perturbations, yet most adversarial-robustness studies assume offline multi-epoch training with repeated access to historical data. We investigate adversarial robustness in Fuzzy ARTMAP, a prototype-based Adaptive Resonance Theory model that supports single-pass learning without replay. We propose WB-Softmax, a differentiable relaxation that aggregates category-level activations into class-level scores for gradient-based attacks. WB-Softmax PGD achieves 89–100% attack success on vanilla models, exceeding transfer and query-based baselines. We then study adversarial training under true streaming constraints by comparing offline versus online adversarial example generation and standard versus selective updates. Offline adversarial …

Assessing The Effects Of Scale-Dependent Representation Of River Networks On Hydrologic Prediction, Hari Dhital

Miners Solving for Tomorrow Research Conference

Accurate hydrologic prediction at relevant spatial scales is essential for flood risk management. This study explores how spatial scale affects model parameters and simulation outcomes in the Hillslope Link Model (HLM). This was motivated by HLM implementation within the Next Generation Water Resources Modeling (NextGen) framework for the U.S. National Water Model. Since NextGen alters HLM's spatial scale from hillslopes to catchments, we assess how this change affects runoff generation and routing. We implement HLM at both scales using identical, predetermined parameters without calibration to isolate spatial discretization effects. Using approximately ten years of precipitation and streamflow data from watersheds …

Evaluation Of National Water Model Long-Range Streamflow Forecasts In Missouri, Sujan Maharjan

Miners Solving for Tomorrow Research Conference

Long-range river stage forecasts are increasingly used to support barge scheduling along the Missouri and Mississippi River navigation corridor. The reliability of these forecasts over extended lead times remains uncertain, particularly in regulated systems influenced by upstream dam operations. This study evaluates the lead-time-dependent performance of National Water Model long-range forecasts at eleven U.S. Geological Survey stations from Rulo to Thebes during 2019–2024. Results show that forecast skill does not decline smoothly with time but exhibits station-specific dips at lead times corresponding to hydraulic travel from major control structures. These periods coincide withstage bias and dispersion, indicating elevated operational uncertainty. …

Evaluation Of Channel Routing Module In The Nextgen National Water Model, Md Saiduzzaman

Miners Solving for Tomorrow Research Conference

The Next Generation Water Resources Modeling (NextGen) framework has a modular structure that enables the integration of multiple hydrologic models with channel routing processes. Within NextGen, the T-Route model performs channel routing using vector-based river networks and supports a hybrid routing approach within a single watershed. This study evaluates the hydraulic diffusive wave routing method implemented in T-Route and compares its performance with the operational Muskingum-Cunge routing used in the National Water Model. The primary objective is to assess the operational capability of streamflow data assimilation across different routing methods using an extensive network of streamflow observations. The routing models …

Controlled Gelation Of Co₂-Resistant Polymer Systems For Improved Conformance In Co₂-Eor, Maryam Sharifi Paroushi

Miners Solving for Tomorrow Research Conference

This presentation introduces a CO₂-resistant hydrogel developed to control fluid movement and improve CO₂ injection performance in subsurface reservoirs for Enhanced Oil Recovery (EOR) and Carbon Capture and Storage (CCS). Conventional polymer gels often lose strength in CO₂-rich environments, resulting in weak plugging, early breakdown, and ineffective flow control. To address this limitation, a sulfonated HPAM-based gel system crosslinked with chromium was developed. The effects of polymer concentration, molecular weight, crosslinker ratio, ionic strength, and pH were investigated to better understand gelation behavior and performance. The formulation exhibited controlled gelation, strong resistance to temperature and CO₂, and minimal shrinkage over …

Empirical Evaluation Of Policy-Based Reinforcement Learning For Dynamic Service Control In An M/M/1 Queue, Joseph Walton

Miners Solving for Tomorrow Research Conference

While reinforcement learning has been increasingly applied to stochastic control, limited work examines policy-based methods in queuing environments modeled as semi-Markov decision processes (SMDP). This study investigates how policy-based reinforcement learning (RL) algorithms perform when applied to service rate control in an M/M/1 queue, a common queuing model for manufacturing and service systems. The problem is formulated as an SMDP in which decisions occur at each new service, allowing an agent to select different service rates from a finite set of speeds, aiming to minimize an objective function that manages system congestion and energy costs. Three policy-based reinforcement learning algorithms, …

Structural Analysis On Iron Phosphate Glasses After Dechlorination Of Mixed Chloride Waste Forms, Lucas Greiner

Miners Solving for Tomorrow Research Conference

Molten salt reactors (MSRs) require durable waste forms for immobilizing halide-rich salts. This study examines iron phosphate glasses derived from a simple salt mixture (SSM), focusing on the effect of Fe₂O₃ additions (2.5–10 wt%) on structure and phase stability. Intermediates were processed at 300–600 °C and vitrified at 1050 °C. Raman spectroscopy and HPLC show that increasing iron content depolymerizes the phosphate network, shifting from Q² toward Q¹ species and reducing chain length. XRD confirms amorphous behavior for ≤7.5 wt% Fe₂O₃, while 10 wt% shows crystallization, with KFeP₂O₇ observed in samples processed at 400 °C. Despite reduced connectivity, iron enhances …

A Method To Accelerate Rock Breakage With Soundless Chemical Demolition Agents, Patrick A. Darko, Hani S. Mitri

Journal of Sustainable Mining

Soundless chemical demolition agents (SCDA) are recognized as a safe and sustainable alternative for rock breakage, with the potential to reduce reliance on explosives in mining. However, their mechanical performance is considerably hampered in the extreme cold climate, with slow or no rock fracturing observed. To overcome this deficiency, two methods were developed in recent studies by 1) electric heating the SCDA borehole with high-temperature wire, and 2) increasing the SCDA mixing water temperature. Good results were obtained with both methods. This paper explores the merits of a hybrid approach combining the two methods to further enhance the SCDA efficiency …

Research Status And Development Trend Of Acidification And Permeability Improvement Technology For Low-Permeability Coal Seam, Shaochuan Chen, Yun Lei, Fuchao Tian, Jie Kang

Journal of Sustainable Mining

Low-permeability coal seams in China are often characterized by mineral-clogged pore-fracture systems, severely limiting coalbed methane (CBM) extraction efficiency. Acidification technology, which involves injecting acidic solutions into coal seams to dissolve minerals and enhance permeability, has emerged as a promising approach. This paper systematically reviews the mechanisms, laboratory findings, and field applications of acidification technology for permeability enhancement in low-permeability coal seams. Key findings include significant improvements in pore connectivity, reductions in gas adsorption capacity, and enhanced gas extraction rates post-acidification. Field tests demonstrate that acid fracturing can increase gas extraction volume by 4-7 times. The study also identifies current …

Improving Energy Reliability In Mining Areas Through Modelling And Control Of Resonance Phenomena In Solar-Integrated Power Systems, Yurii Papaika, Gennadiy Pivnyak, Maksim Malyshko, Yuliya Pazynich, Natalia Howaniec, Adam Smolinski

Journal of Sustainable Mining

This study addresses the emergency and operational transient processes that arise when integrating large-scale solar power plants (SPPs) into electrical load nodes, particularly under conditions of limited power system capacity. With the increasing penetration of distributed generation in Ukraine's energy landscape, challenges related to electromagnetic compatibility and harmonic resonance are becoming more prominent. The research builds upon the foundational work of leading Ukrainian scientific schools and focuses on the specific resonance phenomena observed during the operation of solar inverters in medium-voltage networks, especially in regions with high industrial and mining Energy demand. A novel algorithm is proposed for determining the …

Feasibility Study Of Barite Sourcing From Sediments Emerging Due To Treatment Of Waste Water From Coal Mining, Hubert Makuła, Zbigniew Bzowski, Bogusław Michalik

Journal of Sustainable Mining

The accumulation of mine water in settling ponds, which is discharged due to coal mining, allows them to be cleaned out of suspension, and it is the reason for the accumulation of hundreds of thousands of tons of sediments. One interesting mineral enclosed in these sediments is barite, which is considered in the EU as a critical raw material, but it also contains radium originating from formation water.

The effective barite separation and its beneficiation could constitute a win-win solution because then it would be possible to obtain the valuable radium concentrate for further processing, e.g., in nuclear medicine, and …

Wettability Evaluation Via Contact Angle And Data Mining For Enhanced Oil Recovery, Syasya Wadihah Md. Ja’Afar, Bashir Busahmin

Journal of Sustainable Mining

The oil industry has used many enhanced oil recovery (EOR) strategies to increase crude oil production from reservoirs, particularly as production begins to fall. With a significant quantity of hydrocarbon reserves still existing in the reservoirs, improved oil recovery techniques have the potential to increase oil production, with wettability alteration playing a significant role. To date, there has been no comprehensive investigation of wettability in Brunei's sandstone reservoir. The goal of this research is to determine wettability by contact angle measurement and data mining approaches based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm. …

Online Path Planning For Disaster Response In The Presence Of Unknown Road Disruptions: A Comparison Of Research And Practice, Jannatul Shefa, Ashlea Bennett Milburn, Erica Gralla

Industrial Engineering Faculty Publications and Presentations

Purpose This paper aims to illuminate gaps between theory and practice in one crucial area of disaster logistics: transportation management between staging areas and final destinations, on uncertain and disrupted road networks. Relevant current practice in federal, state, nonprofit and private disaster response organizations in the USA is described and compared to pertinent assumptions in the literature on disaster response online path planning under uncertainty. Design/methodology/approach The study uses a qualitative approach. The disaster response routing literature informed the development of an interview guide used for in-depth interviews with disaster response logistics practitioners. Collected data were coded to identify how …

Ais26s: Genai And Llms For Cybersecurity, Political Sciences, Transportation Security, And Resiliency, Latifur Khan

Paul English Applied Artificial Intelligence (AI) Institute Publications

This presentation examines the role of generative artificial intelligence (GenAI) and large language models (LLMs) in addressing complex challenges across cybersecurity, political science, and transportation security. Dr. Latifur Khan discusses how advanced AI methods can be applied to threat detection, data analysis, and decision-making in high-risk and data-intensive environments. The talk highlights interdisciplinary applications of LLMs, emphasizing their ability to extract insights from large-scale data, improve system resilience, and support intelligent infrastructure. Emerging research directions and practical implications for real-world deployment are also discussed.

Scale-Dependent Particle Transport Over Urban-Like Roughness In Turbulent Flow, Rae Riddle

Dissertations and Theses

This study employs direct numerical simulation (DNS) to investigate the dispersion of inertial particles in turbulent flow over three-dimensional urban-like roughness at Reτ = 200. Particles with Stokes numbers St = 5, 25, and 100 are tracked over cubic arrays with spanwise spacings Sy from 2h to 32h, where h = δ/8 and δ is the half-channel height, alongside a smooth-wall reference case. The results reveal scale-dependent particle responses characterized by three distinct regimes. First, high-inertia particles (St = 100) align strongly with mean secondary flows, exhibiting organized plumes above roughness elements. Their vertical transport peaks at intermediate spacing …

Designing Space-Based Architectures To Discover And Track Hazardous Asteroids Using Mo-Mcts, Adam P. Wilmer, Michael J. Klonowski, Marcus J. Holzinger, Robert A. Bettinger

Faculty Publications

The discovery and tracking of near-Earth objects (NEOs), such as asteroids and comets, form the foundation of any effective planetary defense mitigation strategy—that is, the process of reducing or eliminating the threat these objects pose to humanity. Establishing sufficient warning time prior to a potential Earth impact is a critical outcome of this capability, as it enables informed decision-making and the selection of viable mitigation options. This study investigates how to optimally pre-position a fleet of NEO discovery and tracking (D&T) spacecraft within the Sun-Earth system. Candidate architectures—one or more pre-positioned spacecraft—are designed using Multi-Objective Monte Carlo Tree Search (MO-MCTS). …

Triple Active Bridge Implementation And Control, Nehemiah Milton

Miners Solving for Tomorrow Research Conference

The Triple Active Bridge (TAB) is a three-port power converter that allows power flow in both directions with galvanic isolation. This has a wide range of applications, like high-frequency DC-DC conversion, electric vehicles, microgrids and renewable energy systems. To control the TAB during operation, two phase shift parameters between the bridges are adjusted. In this presentation, I will showcase the software and simulation optimizations which extend previous work by reproducing hardware results which align with simulations. I will also go over the knowledge I’ve gained and the skills acquired through this project.

The Stability Study Of Dna-Polymer Hybrids For Nanotechnology Applications, Ethan Kuehn, Milan Jebaraj

Miners Solving for Tomorrow Research Conference

DNA nanostructures have garnered increasing interest in their application as drug delivery vehicles. However, DNA is susceptible to degradation under physiological conditions. To remedy this, we have devised a novel method to coat DNA nanostructures with the polysaccharide chitosan (a natural derivative of chitin). Chitosan binds to DNA electrostatically and inhibits nuclease activity that would normally degrade DNA in a physiological environment. We used both agarose gel electrophoresis (AGE) and atomic force microscopy (AFM) to determine the stability of DNA before and after immersion in a simulated biological environment. Physiological conditions were mimicked by incubating the DNA in cell culture …

Effects Of Pfas On Willow And Poplar Growth, Jamie Koester

Miners Solving for Tomorrow Research Conference

Per- and polyfluoroalkyl substances (PFAS) are being evaluated for uptake and distribution in vascular plants, with unique findings for PFAS concentrations within different plant tissue. This work investigates the effects of PFAS on willow and poplar growth in an attempt to extrapolate findings to other tree species. These findings allow for an understanding of the consequences PFAS has on agriculture and the food chain. As PFAS are persistent the need for sustainable and safe remediation techniques to protect human health and the environment are critically needed.

Analysis Of Autonomous Vehicle Survivability To 5g Communication Errors, Sydney Clark

Miners Solving for Tomorrow Research Conference

Autonomous vehicles rely on low-latency, high-reliability data exchange for real-time perception and control. Disruptions such as packet loss, latency variation, protocol-level errors, and malicious interference can pose significant safety risks to both passengers and surrounding environments. This project aims to evaluate, quantify, and predict the survivability of autonomous vehicle systems to communication errors, with focus on 5G network environments. The impact of these communication impairments on vehicle stability and control will be investigated through high-fidelity cyber-physical simulation of the vehicle and its surrounding environment. Experiments designed to capture varying network conditions will be used to assess a broad range of …

A Wearable Mxene-Based Sweat Sensor For Real-Time Monitoring Of Inflammatory Biomarkers, Ariel Pilger

Miners Solving for Tomorrow Research Conference

Many conventional biosensing approaches rely on invasive sampling or bulky benchtop instrumentation, limiting their use in continuous and portable applications. This project focuses on the development of wearable sweat-based biosensors that enable non-invasive, continuous, and portable monitoring of physical, chemical, and biological markers. The system will be designed to target markers present in sweat and transduce the biochemical interactions into measurable electrical signals. These signals will be processed through integrated electronics to produce clear, interpretable outputs for users and medical professionals. Supporting circuitry including filters, amplifiers, and an independent power supply will be implemented as necessary to ensure signal accuracy, …

A Speed-Adjusted Centipawn Metric For Chess Cheating Detection, Benjamin Sullins, Benjamin Biehl

Miners Solving for Tomorrow Research Conference

The proliferation of chess engines has compromised the integrity of online play through both manual assistance and automated bots. This research proposes Si, a novel metric designed to quantify unnatural play by integrating move latency, the relative strength of the selected move, and the density of high-quality alternatives available in a given position. By fitting Si  values to theoretical probability distributions across specific Elo ratings and time controls, we establish a statistical baseline for human performance. Discrepancies between an individual's Si  profile and these established distributions provide a robust framework for identifying artificially inflated play, offering a potential method for …

Biosensors For Biomedicine, Drake O'Leary

Miners Solving for Tomorrow Research Conference

This project investigated the use of engineered bacterial reporter systems to detect cellular stress responses associated with antibiotic activity. While constructs were successfully introduced and tested against known antibiotics, the reporter consistently produced a blue signal across conditions, limiting the ability to distinguish specific stress responses. This suggests issues such as leaky expression, insufficient regulatory control, or lack of specificity in the reporter design. Although results were inconclusive, this work highlights key challenges in developing reliable biosensors and provides a foundation for future optimization. Improving signal specificity and reducing background expression will be critical for enabling accurate characterization of antibiotic …

Ballistic Trajectories From Triangular Libration Points To Moon, Collin Gentry

Miners Solving for Tomorrow Research Conference

As stable points in the Earth-Moon system, the triangular libration points, L4 and L5, have many advantageous properties for space exploration. Ballistic trajectories at varying delta-Vs and impulse angles are computed and propagated from the libration points, and trajectories that arrive at the lunar surface are investigated. Preliminary conclusions are drawn about the accessibility of the lunar surface from the triangular libration points, and the implications for mission design are discussed. These trajectories present an alternative means of accessing the Moon, expanding the viability of the triangular points for missions and offering additional options for the use of cisular space.

Ai Adoption Tensions For Organ Procurement Organizations, Joely Grace Hall

Miners Solving for Tomorrow Research Conference

Artificial intelligence (AI) has the potential to improve efficiency in healthcare, yet its adoption remains limited, with only 22% of healthcare organizations having implemented domain-specific AI tools. Adoption may be especially complex in specialized domains such as organ transplantation, where ethical, legal, and operational challenges are dominant. This study examined factors influencing AI acceptance within Organ Procurement Organizations (OPOs), focusing on technological, organizational, and environmental contexts.

Semi-structured interviews with 16 OPO executives from 10 OPOs revealed key tensions shaping AI adoption. We identified five tensions that are holding back OPO leaders from AI adoption, (1) misconceptions, (2) training approach, (3) …

Construction Of A Deffi Sprayer: Using 3d Printer Methodology And Techniques For Cost-Effective Analysis Using Desi Mass Spectrometry Imaging, Ryan Karst, Savvy Stevens, Luke Amos, Logan Koester, Ethan Newbold, Karson Whitaker

Symposium Projects

Using 3D Printer Methodology and Techniques for Cost-Effective Analysis using DESI Mass Spectrometry Imaging

Visual Pattern Mining With Similarity Metrics For Model-Free Trading In The Korean Futures Market, Juhyeon Jang, Jaeyun Kim, David Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

The fractal market hypothesis highlights multi-scale dynamics in financial time series and provides a theoretical foundation for pattern-based analysis. This study proposes a model-free visual pattern mining framework that transforms high-frequency market data into image representations to support intelligent decision-making. By converting 1-minute KOSPI200 futures data into candlestick chart and Bollinger band images, the method effectively captures structural patterns and volatility dynamics. The framework applies similarity metrics and Intersection over Union (IoU)-based visual comparison to identify historically similar patterns and generate intelligent trading signals without model training or complex parameter tuning. Experimental results demonstrate that combining visual features of candlestick …