Engineering Commons^™

Exploring Scms And Fibers For Structural Build-Up In 3d Printing Using Penetration Test, Shiva Kumar Goud Kasani

Miners Solving for Tomorrow Research Conference

Additive manufacturing with cementitious materials advances rapidly, but predicting structural build-up is critical for 3D printed structure buildability. Various supplementary cementitious materials (SCMs) and fibers are commonly used to enhance structural build-up in 3D printing. Evaluating their effects is necessary for successful printing. In this research, this effect is studied for common SCMs, including fly ash and silica fume, and fibers including polypropylene (0.375% and 0.75% by volume), steel (0.75% and 1.5% by volume), and hemp fibers (0.375% and 0.75% by volume). The Structural build-up was quantified through continuous static yield stress measurements (via vane rheometer, penetration, and slump) during …

Synthesis And Hydrothermal Evaluation Of Poly(Styrene Phosphonate) For Conformance Control In Geothermal Reservoirs, Sara Mccauley

Miners Solving for Tomorrow Research Conference

As atmospheric carbon dioxide levels continue to rise, geothermal energy has emerged as a promising energy alternative to fossil fuels. A barrier to widespread implementation and energy production efficiency is macro-heterogeneity of the rock matrix. Cracks, void spaces, and flow conduits divert fluid flow away from unswept portions of the geothermal reservoir and can cause cooling of the reservoir. Flow heterogeneity has been treated in oil reservoirs by injecting hydrogel particles that travel preferentially to ultra-high permeability zones and selectively block fluid flow in these regions. We are applying polymer hydrogels that withstand hydrothermal conditions of 225 up to 275°C …

Challenges And Best Practices Of Regional Innovation Ecosystems, Mahnaz Asgari Sooran

Miners Solving for Tomorrow Research Conference

Many places around the world are developing regional innovation ecosystems to spur regional economic. Many innovation ecosystems fail or barely maintain their initial momentum after a few years. In this paper, we identified challenges and best practices facing innovation ecosystems interviews with the innovation ecosystem stakeholders. We employed the MIT REAP (Regional Entrepreneurship Acceleration Program) model to categorize the five main stakeholders of the innovation ecosystem: entrepreneurs, universities, industry, risk capital, and government. Our initial results indicated the following: (a) Access to capital and talented workforce; (b) Stakeholder discovery process is one of the critical areas to understand the basic …

Simulating Thermal Diffusion Through Image-Derived Microstructures Of Ceramic Matrix Composites, Matik Heskin

Miners Solving for Tomorrow Research Conference

Thermal energy transport in materials can be effectively modeled using finite element software such as COMSOL. Experimentally measured or NIST–JANAF thermal conductivity data can be used to represent material behavior within these simulations. For heterogeneous or composite materials, effective properties are often approximated using rule-of-mixtures calculations. However, this overlooks the nuanced effects caused by complex microstructural geometry. To address this limitation, imaging and coding tools such as MATLAB can be used to process scanning electron microscopy (SEM) images. By thresholding the images to distinguish constituent materials, a representative mesh can be generated and imported into an FEM program. This approach …

Human Intention Prediction Using Cnn And Lstm Networks In Physical Human–Robot Interactions, Khosro Ghorbani Zadeh

Miners Solving for Tomorrow Research Conference

Advances in robotics and artificial intelligence have increased expectations for interactive robots in eldercare and assistive applications. A key challenge in creating safe and effective systems is accurately recognizing human intent and translating it into meaningful commands for robots to follow. Traditional physics-based models often fail to fully represent human force interactions due to their dynamic nature, while neural networks provide a promising alternative for predicting force-movement intentions. Multi-layer perceptrons (MLPs) show potential, however, they struggle with temporal dependencies and generalization. Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNNs) help address these limitations. This study compares these architectures …

Ai-Driven Frameworks For Mitigating Rockfall Hazards, Unstable Ground Condition And Improving Safety In Underground Mine Through Thermal Imaging, Akhrorbek Narmatov

Miners Solving for Tomorrow Research Conference

Scaling, the removal of loose rocks from excavation walls to prevent rockfalls is a critical safety procedure in underground mining operations. Approximately a quarter of fatal mining accidents are due to rockfalls. Detecting unstable rocks during scaling and assessing ground stability remain challenging due to limited visibility, dust, and environmental conditions.

Excavation disturbs the in-situ stress state, causing stress redistribution, fracture propagation, and the formation of discontinuities that lead to loose rock blocks. Ventilation airflow affects heat transfer at exposed surfaces, amplifying temperature contrasts between intact rock and fractured blocks associated with instability.

Current practices rely on manual inspection, requiring …

Toward Sustainable 3d Printable Cementitious Materials: Low-Carbon Design With Fiber Reinforcement, Nima Mahmoudzadeh Vaziri

Miners Solving for Tomorrow Research Conference

3D printing of cementitious materials, as an emerging construction technology, faces challenges in both mechanical performance and sustainability. Conventional mixture designs rely on high cement contents, leading to increased CO2 emissions, while printed elements often exhibit brittle behavior with limited crack resistance and reduced post-cracking performance. This study investigates the development of low-carbon 3D printed cementitious composites using environmentally friendly supplementary cementitious materials (SCMs) and fillers, combined with fiber reinforcement to enhance mechanical performance. Locally available SCMs and fillers were incorporated to significantly reduce cement content (>40%) and improve sustainability. Fiber reinforcement was introduced to mitigate brittleness and enhance …

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 …

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) …

Corrigendum To “Advanced Techniques In Quartz Wafer Precision Processing: Stealth Dicing Based On Filament-Induced Laser Machining” [Opt. Laser Technol. 171 (2024) 110474] (Optics And Laser Technology (2024) 171, (S0030399223013671), (10.1016/J.Optlastec.2023.110474)), Yun Wang, Yutang Dai, Farhan Mumtaz, Kaiyan Luo

Electrical and Computer Engineering Faculty Research & Creative Works

The authors regret, that the affiliation for author Yun Wang was incomplete. To accurately reflect both the author's academic affiliation and the research platform where the work was conducted. The correct affiliation for Yun Wang is updated as above. The authors would like to apologize for any inconvenience caused.

Graphene Synthesis: A Reactor-Oriented Review Of Conventional And Emerging Production Methods, Paul C. Ani, Zeyad Zeitoun, Hasan J. Al-Abedi, Joseph D. Smith

Chemical and Biochemical Engineering Faculty Research & Creative Works

Graphene's unparalleled electrical, mechanical, and thermal properties have positioned it as a transformative material across diverse sectors, including electronics, energy storage, biomedicine, and environmental remediation. However, scalable, cost-effective, and high-quality production remains a critical challenge. This review presents a comprehensive, reactor-oriented analysis of both conventional and emerging graphene synthesis methods, categorized into top-down and bottom-up approaches. Special emphasis is placed on the role of reactor configurations in determining product quality, layer control, scalability, and economic viability. Key synthesis techniques explored include chemical vapor deposition (CVD), epitaxial growth, electrochemical exfoliation, ultrasonic-assisted methods, microwave reactors, combustion synthesis, and plasma-enhanced processes. By evaluating …

Additive Manufacturing Of Ti-Ni Based Ternary Shape Memory Alloys, Yitao Chen, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Metal additive manufacturing has become a powerful tool to develop customized metal alloys and to discover more advanced properties for novel extended applications. Ti-Ni based shape memory alloy is a group of intriguing smart functional materials, and adding a small amount of a third element can promote and induce more attractive functions. Due to the difficulty in traditional processing and the unique feature of material flexibility of in-situ alloying in additive manufacturing processes, not only Ti-Ni binary shape memory alloys but also Ti-Ni-X ternary shape memory alloys can be developed, manufactured, and investigated in-depth by additive manufacturing. This paper provides …

Dendrimer Nanogels With Built-In Free Radical Scavenging Enable Efficient Topical Delivery Of A Hydrophilic Antioxidant To Restore Lens Redox Balance For Cataract Treatment, Lin Qi, Huari Kou, Anna Chernatynskaya, Da Huang, Vimalin Jeyalatha Mani, Humeyra Karacal, Nuran Ercal, Hu Yang

Chemistry Faculty Research & Creative Works

Cataract is a leading cause of vision impairment worldwide and are primarily caused by oxidative stress that damages and aggregates lens proteins, leading to lens opacification. However, the eye's anatomical barriers limit the penetration and bioavailability of antioxidant therapies. To address this challenge, a dendrimer-based nanogel with a built-in reactive oxygen species (ROS)-scavenging capability developed by us was employed to deliver the antioxidant N-acetylcysteine (NAC) to the lens. NAC was loaded into a generation-5 PEGylated poly(amidoamine) dendrimer (G5-PEG-TK, termed the GPT) nanogel. The resulting NAC-GPT was characterized for its ROS-scavenging activity, bioavailability, and corneal permeability. The efficacy of NAC-GPT was …