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Reframing Soil Freezing As An Unsaturated Process, Antai Dong, Xiong Zhang Aug 2026

Reframing Soil Freezing As An Unsaturated Process, Antai Dong, Xiong Zhang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Soil freezing and frost heave are inherently unsaturated soil phenomena. However, most existing numerical models are based on saturated soil mechanics or assume full saturation. This simplification introduces conceptual inconsistencies, requires modifications that violate fundamentals in soil mechanics and fluid mechanics, and often leads to the use of self-conflicting soil properties. To overcome these limitations, this study develops a physically consistent, fully coupled thermohydraulic model for soil freezing grounded in modern unsaturated soil mechanics. A soil freezing characteristic surface (SFCS) is introduced to represent unfrozen water content in partially frozen soils as a function of both suction and temperature. Recognizing …

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Wind Effects Induced By Multivortex Tornadoes On A Low-Rise Building, Yi Zhao, Guirong Yan, Tetsuya Takemi, John Van De Lindt Aug 2026

Wind Effects Induced By Multivortex Tornadoes On A Low-Rise Building, Yi Zhao, Guirong Yan, Tetsuya Takemi, John Van De Lindt

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Multivortex tornadoes contain two or more subvortices that orbit within a parent vortex and can generate highly intermittent and localized near-ground wind fields. This study investigates how tornado flow structure affects wind effects on a low-rise building using large-eddy simulations. One single-vortex tornado and three multivortex tornadoes with different subvortex configurations are examined by systematically varying swirl ratio. Tornado translation is modeled using a relative-motion framework in which the building traverses the vortex field. Aerodynamic force and moment coefficients are evaluated along the traversing path. Additional stationary simulations are conducted to examine repeated load amplification associated with subvortex passages. Compared …

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Non-Uniform Mixing Of Quantum Walks On The Symmetric Group, Avah Banerjee Aug 2026

Non-Uniform Mixing Of Quantum Walks On The Symmetric Group, Avah Banerjee

Computer Science Faculty Research & Creative Works

It is well-known that classical random walks on regular graphs converge to the uniform distribution. Quantum walks, in their various forms, are quantization's of their corresponding classical random walk processes. Gerhardt and Watrous (2003) demonstrated that continuous-time quantum walks do not converge to the uniform distribution on certain Cayley graphs of the Symmetric group, which by definition are all regular. In this paper, we demonstrate that discrete-time quantum walks, in the sense of quantized Markov chains as introduced by Szegedy (2004), also do not converge to the uniform distribution. We analyze the spectra of the Szegedy walk operators using the …

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A Transfer-Learning And Continuous Optimization-Based Framework For Predicting Heat Treatment-Dependent Mechanical Properties Of Ded-Processed Low-Alloy Steels, Atiqur Rahman, Sung Heng Wu, Ranjit Joy, Frank Liou Aug 2026

A Transfer-Learning And Continuous Optimization-Based Framework For Predicting Heat Treatment-Dependent Mechanical Properties Of Ded-Processed Low-Alloy Steels, Atiqur Rahman, Sung Heng Wu, Ranjit Joy, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Directed energy deposition (DED) of low-alloy steels involves strongly coupled effects among alloy composition, solidification behavior, and post-deposition heat treatment, making mechanical property prediction difficult when target-domain data are limited. This study develops a transfer-learning and continuous optimization framework for predicting heat treatment-dependent yield strength (YS), ultimate tensile strength (UTS), hardness (HV), and as-solidified phase fractions of martensite, ferrite, and austenite in DED-processed low-alloy steels. A CALPHAD-based dataset was generated for 125 low-alloy steel compositions. A multilayer perceptron (MLP) surrogate was first trained as a baseline model, then fine-tuned through transfer learning and progressively updated as staged continuous optimization; the …

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Where Do Ai Coding Agents Fail? An Empirical Study Of Failed Agentic Pull Requests In Github, Ramtin Ehsani, Sakshi Pathak, Shriya Rawal, Abdullah Al Mujahid, Mia Mohammad Imran, Preetha Chatterjee Jul 2026

Where Do Ai Coding Agents Fail? An Empirical Study Of Failed Agentic Pull Requests In Github, Ramtin Ehsani, Sakshi Pathak, Shriya Rawal, Abdullah Al Mujahid, Mia Mohammad Imran, Preetha Chatterjee

Computer Science Faculty Research & Creative Works

AI coding agents are now submitting pull requests (PRs) to software projects, acting not just as assistants but as autonomous contributors. As these agentic contributions are rapidly increasing across real repositories, little is known about how they behave in practice and why many of them fail to be merged. In this paper, we conduct a large-scale study of 33k agent-authored PRs made by five coding agents across GitHub. (RQ1) We first quantitatively characterize merged and not-merged PRs along four broad dimensions: 1) merge outcomes across task types, 2) code changes, 3) CI build results, and 4) review dynamics. We observe …

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Hybrid Microbial-Enzymatic Electrosynthesis For De Novo Decanoic Acid Production From Co2, Yongze Wang, Wenjin Dong, Meijing Wei, Su Song, Zhiqing Huang, Yaojie Liu, Shelley D. Minteer, Hui Chen Jul 2026

Hybrid Microbial-Enzymatic Electrosynthesis For De Novo Decanoic Acid Production From Co2, Yongze Wang, Wenjin Dong, Meijing Wei, Su Song, Zhiqing Huang, Yaojie Liu, Shelley D. Minteer, Hui Chen

Chemistry Faculty Research & Creative Works

The steady increase in atmospheric CO2 levels is a key driver of anthropogenic climate change, prompting widespread global concern. In this context, the sustainable conversion of CO2 into value-added chemicals represents an attractive route toward carbon-neutral manufacturing and green chemistry. Here, we developed a proof-of-concept hybrid microbial-enzymatic electrosynthesis system that combines microbial electrosynthesis (MES) and enzymatic electrosynthesis (EES) to convert CO2 into decanoic acid under ambient conditions, using electrical energy. In the MES module, CO2 was converted to acetate via the Wood–Ljungdahl pathway of Clostridium ljungdahlii, using H2 produced by electrochemical water splitting as the electron …

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Entity Labels Are Not Entity Signals: A Framework For Observable Relevance In Document Re-Ranking, Utshab Kumar Ghosh, Shubham Chatterjee Jul 2026

Entity Labels Are Not Entity Signals: A Framework For Observable Relevance In Document Re-Ranking, Utshab Kumar Ghosh, Shubham Chatterjee

Computer Science Faculty Research & Creative Works

Entity-aware document retrieval uses query-associated entities as ranking signals, assuming that semantically relevant entities are also useful retrieval signals. We show this assumption is insufficient - and explain why. Unlike terms, which are ground-truth observations, entity links are hypotheses produced by an imperfect linker: an entity can be topically central yet provide no discriminative signal if the linker fires indiscriminately across relevant and non-relevant documents. We formalize this as a distinction between Conceptual Entity Relevance (CER) - whether an entity is topically related to a query - and Observable Entity Relevance (OER) - whether its observed presence in a collection …

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Reproduction Beyond Benchmarks: Constbert And Colbert-V2 Across Backends And Query Distributions, Utshab Kumar Ghosh, Ashish David, Shubham Chatterjee Jul 2026

Reproduction Beyond Benchmarks: Constbert And Colbert-V2 Across Backends And Query Distributions, Utshab Kumar Ghosh, Ashish David, Shubham Chatterjee

Computer Science Faculty Research & Creative Works

Reproducibility must validate architectural robustness, not just numerical accuracy. We evaluate ColBERT-v2 and ConstBERT across five dimensions, finding that while ConstBERT reproduces within 0.05% MRR@10 on MS-MARCO, both models show a drop of 86-97% on long, narrative queries (TREC ToT 2025). Ablations prove this failure is architectural: performance plateaus at 20 words because the MaxSim operator's uniform token weighting cannot distinguish signal from filler noise. Furthermore, undocumented backend parameters create an 8-point gap due to ConstBERT's sparse centroid coverage, and fine-tuning with 3x more data actually degrades performance by up to 29%. We conclude that architectural constraints in multi-vector retrieval …

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Depro: Understanding The Role Of Llms In Debugging Competitive Programming Code, Nabiha Parvez, Md Tanvin Sarkar Pallab, Mia Mohammad Imran, Tarannum Shaila Zaman Jul 2026

Depro: Understanding The Role Of Llms In Debugging Competitive Programming Code, Nabiha Parvez, Md Tanvin Sarkar Pallab, Mia Mohammad Imran, Tarannum Shaila Zaman

Computer Science Faculty Research & Creative Works

Debugging consumes a substantial portion of the software development lifecycle, yet researchers do not yet understand well the effectiveness of Large Language Models (LLMs) in this task. Competitive programming offers a rich benchmark for such evaluation, given its diverse problem domains and strict efficiency requirements. We present an empirical study of LLM-based debugging on competitive programming problems and introduce DePro, a test-case-driven approach that assists programmers by correcting existing code rather than generating new solutions. DePro combines brute-force reference generation, stress testing, and iterative LLM-guided refinement to efficiently identify and resolve errors. Experiments on 13 faulty user submissions from Codeforces …

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Llm-Enabled Open-Source Systems In The Wild: An Empirical Study Of Vulnerabilities In Github Security Advisories, Fariha Tanjim Shifat, Hariswar Baburaj, Ce Zhou, Jaydeb Sarker, Mia Mohammad Imran Jul 2026

Llm-Enabled Open-Source Systems In The Wild: An Empirical Study Of Vulnerabilities In Github Security Advisories, Fariha Tanjim Shifat, Hariswar Baburaj, Ce Zhou, Jaydeb Sarker, Mia Mohammad Imran

Computer Science Faculty Research & Creative Works

Large language models (LLMs) are increasingly embedded in open-source software (OSS) ecosystems, creating complex interactions among natural language prompts, probabilistic model outputs, and execution-capable components. However, it remains unclear whether traditional vulnerability disclosure frameworks adequately capture these model-mediated risks. To investigate this, we analyze 295 GitHub Security Advisories published between January 2025 and January 2026 that reference LLM-related components, and we manually annotate a sample of 100 advisories using the OWASP Top 10 for LLM Applications 2025.We find no evidence of new implementation-level weakness classes specific to LLM systems. Most advisories map to established CWEs, particularly injection and deserialization weaknesses. …

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“Innocent” Electrolytes Can Influence Organic Electrosynthetic Selectivity, Zachary A. Nguyen, Nhu H. Quach, Mayank Tanwar, Joshua A. Beeler, Kevin Mcfadden, Dylan G. Boucher, Matthew Neurock, Shelley D. Minteer Jul 2026

“Innocent” Electrolytes Can Influence Organic Electrosynthetic Selectivity, Zachary A. Nguyen, Nhu H. Quach, Mayank Tanwar, Joshua A. Beeler, Kevin Mcfadden, Dylan G. Boucher, Matthew Neurock, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Organic electrosynthesis has emerged as a powerful strategy for leveraging electricity in organic synthesis. Despite its growing popularity, the fundamental molecular interactions governing electrochemical systems remain poorly understood. Many electrosynthetic reactions show strong dependence on the identity of the allegedly inert supporting electrolyte, which can significantly impact yields and selectivity, yet the physical origins of these effects are largely unexplored. A mechanistic understanding of electrolyte effects would enable more rational reaction design for applications. Here, we use cyclic voltammetry to investigate cobalt-based metal–carbon bond homolysis and elucidate how common supporting electrolytes influence reaction rates. Bulk electrolysis experiments further reveal how …

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"Todo: Fix The Mess Gemini Created": Towards Understanding Genai-Induced Self-Admitted Technical Debt, Abdullah Al Mujahid, Mia Mohammad Imran Jul 2026

"Todo: Fix The Mess Gemini Created": Towards Understanding Genai-Induced Self-Admitted Technical Debt, Abdullah Al Mujahid, Mia Mohammad Imran

Computer Science Faculty Research & Creative Works

As large language models (LLMs) such as ChatGPT, Copilot, Claude, and Gemini become integrated into software development workflows, developers increasingly leave traces of AI involvement in their code comments. Among these, some comments explicitly acknowledge both the use of generative AI and the presence of technical shortcomings. Analyzing 6,540 LLM-referencing code comments from public Python and JavaScript-based GitHub repositories (November 2022-July 2025), we identified 81 that also self-admit technical debt (SATD). Developers most often describe postponed testing, incomplete adaptation, and limited understanding of AI-generated code, suggesting that AI assistance affects both when and why technical debt emerges. We term GenAI-Induced …

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Mxene-Based Optical Fiber Sensors For Chemical And Biosensing: Review And Perspectives, Chen Zhu, Huaijun Guan, Chenxi Huang, Rex E. Gerald, Jie Huang Jul 2026

Mxene-Based Optical Fiber Sensors For Chemical And Biosensing: Review And Perspectives, Chen Zhu, Huaijun Guan, Chenxi Huang, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

No abstract provided.

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Challenges In Scaling R-Tree Spatial Search On Processing-In-Memory, Tasmia Jannat, Michael Gowanlock, Satish Puri Jul 2026

Challenges In Scaling R-Tree Spatial Search On Processing-In-Memory, Tasmia Jannat, Michael Gowanlock, Satish Puri

Computer Science Faculty Research & Creative Works

Spatial query processing is important in scientific, geospatial, and data-intensive applications. R-trees are widely used to index spatial objects, but their query-dependent traversal creates irregular work across different regions. This poster studies the challenges of scaling R-tree spatial search on a commercial Processing-in-Memory (PIM) system. Although PIM reduces CPU to memory data movement by executing search near memory, it does not remove full-pipeline overheads: the host still manages data placement, query batching, kernel launches, result retrieval, and aggregation. Our results show strong DPU-side search acceleration, with PIM kernel speedup ranging from about 20 x to 73 x, but end-to-end speedup …

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Learning Programming In Informal Spaces: Using Emotion As A Lens To Understand Novice Struggles On R/Learnprogramming, Alif Al Hasan, Subarna Saha, Mia Mohammad Imran Jul 2026

Learning Programming In Informal Spaces: Using Emotion As A Lens To Understand Novice Struggles On R/Learnprogramming, Alif Al Hasan, Subarna Saha, Mia Mohammad Imran

Computer Science Faculty Research & Creative Works

Novice programmers experience emotional difficulties in informal online learning environments, where Confusion and Frustration can hinder motivation and learning outcomes. This study investigates novice programmers' emotional experiences in informal settings, identifies causes of emotional struggle, and explores design opportunities for affect-aware support systems. We manually annotated 1,500 posts from r/learnprogramming using the Learning-Centered Emotions framework, applying clustering, and axial coding. Confusion, Curiosity, and Frustration dominated emotional experiences, sometimes co-occurring and linked to early learning stages. Positive emotions were infrequent. The primary emotional triggers included ambiguous errors, unclear learning pathways, and misaligned resources. We identify five key areas where novice programmers …

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Performance Evaluation Of Approximate Nearest Neighbor Search On Nvidia Bluefield-3 Dpu, Sophia Bhoria, Nathan Tibbetts, Arjun Kirubakaran, Alima Subedi, Satish Puri Jul 2026

Performance Evaluation Of Approximate Nearest Neighbor Search On Nvidia Bluefield-3 Dpu, Sophia Bhoria, Nathan Tibbetts, Arjun Kirubakaran, Alima Subedi, Satish Puri

Computer Science Faculty Research & Creative Works

Advanced SmartNICs known as Data Processing Units (DPU) enable in-network data analytics, being equipped with standard processors and accelerators capable of doing custom computation on-NIC. These SmartNICs are advantageous because the host CPU can delegate simpler data analytics tasks, like filtering, to the NIC where the data first arrives. Only data needing further refinement must be passed on to the host CPU. Our benchmarks focus on NVIDIA's commercially available Bluefield-3 DPU. Similarity search, particularly Approximate Nearest Neighbor (ANN) search, is an important domain with wide usage across numerous applications. We explore ANN search on SmartNICs, providing insight into the performance …

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Dynlp: Parallel Dynamic Batch Update For Label Propagation In Graph-Based Semi-Supervised Learning, S. M. Shovan, Arindam Khanda, S. M. Ferdous, Sajal K. Das, Mahantesh Halappanavar Jul 2026

Dynlp: Parallel Dynamic Batch Update For Label Propagation In Graph-Based Semi-Supervised Learning, S. M. Shovan, Arindam Khanda, S. M. Ferdous, Sajal K. Das, Mahantesh Halappanavar

Computer Science Faculty Research & Creative Works

Semi-supervised learning aims to infer class labels using only a small fraction of labeled data. In graph-based semi-supervised learning, this is typically achieved through label propagation to predict labels of unlabeled nodes. However, in real-world applications, new data often arrives in batches, and stale data often becomes irrelevant. Each time a new batch appears, reapplying the traditional label propagation algorithm to recompute all labels is redundant, computationally intensive, and inefficient. To address the absence of an efficient label propagation update method, we propose DynLP, a novel GPU-centric Dynamic Batched Parallel Label Propagation algorithm that performs only the necessary updates, propagating …

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3d Semi-Analytical Thermo-Elasto-Plastic Model For Additive Manufacturing, Tao Liu, Ming C. Leu, Edward C. Kinzel, Chinedum Okwudire Jul 2026

3d Semi-Analytical Thermo-Elasto-Plastic Model For Additive Manufacturing, Tao Liu, Ming C. Leu, Edward C. Kinzel, Chinedum Okwudire

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In additive manufacturing (AM), stress field drives distortion and warping and promotes delamination and cracking. Fast, accurate stress prediction is therefore essential for AM process planning and control, including real-time adaptive control, AM digital twins, data-driven and physics-driven workflows. However, spot-wise thermo-elasto-plastic finite element method (FEM) are often too slow for design iteration or real time use. Existing semi-analytical thermo-elasto-plastic approaches achieve high speed but are largely limited to 2D. In this paper, a full 3D semi-analytical thermo-elasto-plastic model for AM is built. The method uses a spot-wise analytical thermal field as the load and computes displacements and stresses via …

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An Automated Electrochemistry Platform For Accelerating The Characterization Of Enzymatic Electrochemistry, Michael A. Pence, Zachary A. Nguyen, Luke G. Kays, Dylan G. Boucher, Joaquín Rodríguez-López, Shelley D. Minteer Jul 2026

An Automated Electrochemistry Platform For Accelerating The Characterization Of Enzymatic Electrochemistry, Michael A. Pence, Zachary A. Nguyen, Luke G. Kays, Dylan G. Boucher, Joaquín Rodríguez-López, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Enzymatic electrochemistry harnesses the selectivity of enzymes to enable electrochemical applications spanning sensing, synthesis, and energy conversion. However, the sequential nature of electroanalytical experiments limits throughput, restricting the scale at which enzyme-electrode systems can be screened. Here we demonstrate the capabilities of an automated electrochemistry platform, eLab, to increase the throughput of enzymatic electrochemistry investigations. We used the eLab to collect over 10,000 cyclic voltammograms across a large parameter space consisting of two enzyme variants (promiscuous and wild-type glucose oxidase), 20 saccharide substrates, 21 concentrations, and four scan rates, with measurements being made all in triplicate. The expansive dataset enabled …

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Existence And Uniqueness Of Positive Solutions For Hilfer–Hadamard-Type Fractional Differential Equations With Γ-Concave And Sub-Homogeneous Operators, Hasan Rasouli, Hojjat Afshari, Martin Bohner Jul 2026

Existence And Uniqueness Of Positive Solutions For Hilfer–Hadamard-Type Fractional Differential Equations With Γ-Concave And Sub-Homogeneous Operators, Hasan Rasouli, Hojjat Afshari, Martin Bohner

Mathematics and Statistics Faculty Research & Creative Works

In this research, we present necessary and sufficient conditions for the existence and uniqueness of positive solutions for a class of Hilfer–Hadamard-type fractional differential equations with boundary value problems, including those with integral boundary conditions. The obtained results are conditional on a specific set of strong assumptions, which substantially narrow the class of admissible nonlinearities, coefficients, and boundary data. Thus, the present work extends the Hadamard-type framework to the Hilfer–Hadamard setting only within this restrictive regime, rather than providing a full extension to all Hilfer–Hadamard systems. We utilize the properties of (Formula presented.) -concave and sub-homogeneous operators along with two …

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Digital Twin-Assisted Optimization Of 6g Wireless Networks: Ensuring Deterministic Communication, Yingpu Nian, Bo Yi, Xingwei Wang, Sajal K. Das Jul 2026

Digital Twin-Assisted Optimization Of 6g Wireless Networks: Ensuring Deterministic Communication, Yingpu Nian, Bo Yi, Xingwei Wang, Sajal K. Das

Computer Science Faculty Research & Creative Works

With the rapid advancement of 6G technology and the increasing use of smart devices, Deterministic 6G Wireless Networks (D6WN) have emerged to meet the growing network transmission demands. In particular, applications such as autonomous vehicles, remote surgery, and industrial automation require extremely low transmission latency to function effectively, highlighting the critical need for D6WN in supporting these time-sensitive use cases. Yet, the conventional TCP/IP framework lacks effective unified traffic and congestion control scheduling, aggravating latency and uncertainty, posing a challenge to ensuring reliable real-time critical applications. To address the challenges of deterministic transmission in D6WN, this paper integrates Digital Twin …

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Hsv-1 Us3 Hijacks Conserved Actin Regulatory Complexes To Drive F-Actin Remodeling, Md Imran Hossain, Md Arifuzzaman, Md Mehedi Hasan, Seung Jong Park, Leila Rahimian, Ojasvi Dutta, Vladimir Chouljenko, Harikrishnan Mohan, Reza Ghavimi, Konstantin G. Kousoulas Jul 2026

Hsv-1 Us3 Hijacks Conserved Actin Regulatory Complexes To Drive F-Actin Remodeling, Md Imran Hossain, Md Arifuzzaman, Md Mehedi Hasan, Seung Jong Park, Leila Rahimian, Ojasvi Dutta, Vladimir Chouljenko, Harikrishnan Mohan, Reza Ghavimi, Konstantin G. Kousoulas

Computer Science Faculty Research & Creative Works

The herpes simplex virus 1 (HSV-1) US3 is a multifunctional serine/threonine kinase that promotes HSV-1 replication and spread. But its role and the mechanisms by which US3 regulates actin cytoskeletal remodeling remain poorly defined. We combined flow cytometry, confocal microscopy, immunoprecipitation-mass spectrometry (IP-MS), protein complex mapping, and machine learning to characterize US3-mediated F-actin dynamics. Flow cytometry and confocal microscopy showed that wild-type HSV-1 induces significant F-actin remodeling, while the ΔUS3 mutant displays F-actin levels comparable to uninfected cells, identifying US3 as a key regulator. IP-MS identified 47 high-confidence US3 interactors enriched in conserved actin regulatory complexes, including Arp2/3 nucleation machinery, …

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Nb–Zr Interdiffusion In The (Hf,Ta,Ti,Nb)B2–(Hf,Ta,Ti,Zr)B2 High-Entropy Boride System, Ana C. Feltrin, Yue Zhou, Stefano Curtarolo, Gregory E. Hilmas, William G. Fahrenholtz Jul 2026

Nb–Zr Interdiffusion In The (Hf,Ta,Ti,Nb)B2–(Hf,Ta,Ti,Zr)B2 High-Entropy Boride System, Ana C. Feltrin, Yue Zhou, Stefano Curtarolo, Gregory E. Hilmas, William G. Fahrenholtz

Materials Science and Engineering Faculty Research & Creative Works

Niobium (Nb) presents a challenge for achieving homogeneous solid solutions in high-entropy boride and carbide ceramics. In this work, we synthesized (Hf,Ta,Ti,Zr)B2 (Zr-HEB) and (Hf,Ta,Ti,Nb)B2 (Nb-HEB) ceramics by boro/carbothermal reduction, followed by densification via spark plasma sintering (SPS). Diffusion couples were prepared to investigate the interdiffusion behavior of Nb and zirconium (Zr) in these complex systems at temperatures between 2000°C and 2200°C. Aside from Nb and Zr, the other elements exhibited no significant concentration gradient across the diffusion interface. Nb exhibited lower diffusion coefficients ((Formula presented.) Nb = 1.7 x 10−17–1.2 x 10−16 m2 …

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Nascent Titanium-/Silicon-Containing Particle Formation In Corona-Discharge-Assisted Combustion, Chanakya Bagya Ramesh, Frank Daoru Han, Yang Wang Jul 2026

Nascent Titanium-/Silicon-Containing Particle Formation In Corona-Discharge-Assisted Combustion, Chanakya Bagya Ramesh, Frank Daoru Han, Yang Wang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Adding plasmas to a flame has been shown to introduce high concentrations of charges, ions, and radicals to the said flame. This technique of adding plasma to a flame is called plasma-assisted combustion (PAC), and this addition has been shown to make a flame more stable and efficient. At the same time, PAC has also been shown to alter particle formation during combustion. Here, we investigate the effect of a high-frequency (∼21 kHz) alternating current (AC) corona discharge on particle formation and growth in a premixed flame, especially at the initial stages (with particle sizes below 10 nm). We first …

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Finite-Temperature Grain-Boundary Segregation In High-Entropy Carbides, Marium M. Mou, Tarek Md Anamul Haque, Samuel E. Daigle, Josiah Roberts, William G. Fahrenholtz, Jon Paul Maria, Douglas E. Wolfe, Eva Zurek, Stefano Curtarolo, Donald W. Brenner Jul 2026

Finite-Temperature Grain-Boundary Segregation In High-Entropy Carbides, Marium M. Mou, Tarek Md Anamul Haque, Samuel E. Daigle, Josiah Roberts, William G. Fahrenholtz, Jon Paul Maria, Douglas E. Wolfe, Eva Zurek, Stefano Curtarolo, Donald W. Brenner

Materials Science and Engineering Faculty Research & Creative Works

High-entropy carbides are promising candidates for extreme-temperature environments, but their grain-boundary chemistry remains difficult to resolve because segregation involves both chemical disorder and finite-temperature configurational sampling. Here, we quantify temperature-dependent grain-boundary segregation in high-entropy carbides using a universal message-passing atomic cluster expansion (MACE) machine learning interatomic potential combined with a hybrid Monte Carlo–molecular dynamics workflow. A 53.1 (Formula presented.) (Formula presented.) symmetric tilt grain boundary was sampled for six representative high-entropy carbide compositions containing group IV, V, and VI transition metals at 300 and 2000 K. Element-resolved metal-sublattice composition profiles reveal composition-dependent segregation modes. Several chemistries exhibit selective near-boundary enrichment …

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Vehicle Autonomy To Ecosystem Intelligence: A Systematic Review Of Dynamic Vision Architectures In Surface Mining Operations, Nana Yaa Damtewaa Anti, Samuel Frimpong, Muhammad Azeem Raza Jul 2026

Vehicle Autonomy To Ecosystem Intelligence: A Systematic Review Of Dynamic Vision Architectures In Surface Mining Operations, Nana Yaa Damtewaa Anti, Samuel Frimpong, Muhammad Azeem Raza

Mining Engineering Faculty Research & Creative Works

Autonomous Haulage Systems (AHS) have significantly transformed surface mining operations by improving safety, productivity, and operational consistency. Currently, AHS predominantly rely on vehicle-centric perception architectures. Onboard LiDAR, radar, cameras, and Global Navigation Satellite Systems (GNSS) perform sensing, interpretation, and decision-making within individual systems. These processes enable collision avoidance and path tracking. However, they are limited in their ability to consider the broader, dynamic mining environment characterized by dust, terrain degradation, geotechnical instability, heterogeneous traffic, and rapidly evolving operational conditions. This paper presents a systematic review of dynamic vision systems of AHS in surface mining. It critically analyzes the transition from …

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Higher-Order Statistical Analysis Of Inter-Arrival Times For Radiation Detector Deadtime Characterization And Paralysis Factor Determination, Abdallah Wazzan, Shoaib Usman, Tayfun Akyurek Jul 2026

Higher-Order Statistical Analysis Of Inter-Arrival Times For Radiation Detector Deadtime Characterization And Paralysis Factor Determination, Abdallah Wazzan, Shoaib Usman, Tayfun Akyurek

Nuclear Engineering and Radiation Science Faculty Research & Creative Works

All real detectors exhibit hybrid behavior that combines both paralyzable and non-paralyzable which requires improved characterization techniques. This study investigates the relationship between detector deadtime parameters and higher-order statistical for inter-arrival time distributions to develop advanced detector characterization. Two comprehensive Monte Carlo simulation approaches were employed using MATLAB: a full radioactive decay curve analysis spanning approximately 4.5 half-lives of Cobalt-60 and Vanadium-52 sources, and a fixed count rate analysis covering practically achievable laboratory conditions (440 to 1,000,000 counts per second). The hybrid deadtime model was implemented with deadtimes ranging from 2.5 to 50 μs for the full simulation and from …

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Multi-Parametric Nonlinear Programming For Lossy Lmp Sensitivity Analysis Using Outer Progressive Cuts, Yuhan Huang, Tao Ding, Chenggang Mu, Rui Bo, Pengwei Du Jul 2026

Multi-Parametric Nonlinear Programming For Lossy Lmp Sensitivity Analysis Using Outer Progressive Cuts, Yuhan Huang, Tao Ding, Chenggang Mu, Rui Bo, Pengwei Du

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate sensitivity analysis of locational marginal price (LMP) is crucial for risk hedging and market management. This paper proposes multiparametric nonlinear programming for sensitivity analysis of LMP with nonlinear network loss, also known as lossy LMP. Global analytical solutions for lossy LMP and the corresponding critical regions are derived. An outer progressive cut algorithm is developed to constrain the network loss error within a specific range for the whole parametric domain. Case studies show the improved accuracy over methods with lossless or fixed loss factors, and a two-order-of-magnitude online speedup over Monte Carlo methods while maintaining lower total computational time.

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Coupled Multiphysics Transport-Reaction Modeling Framework For Combustion Synthesis Of Cement Phases: Insights Into Β-C2s Formation And Wavefront Dynamics, Sayee Srikarah Volaity, Shubham Agrawal, Aditya Kumar, Narayanan Neithalath Jun 2026

Coupled Multiphysics Transport-Reaction Modeling Framework For Combustion Synthesis Of Cement Phases: Insights Into Β-C2s Formation And Wavefront Dynamics, Sayee Srikarah Volaity, Shubham Agrawal, Aditya Kumar, Narayanan Neithalath

Materials Science and Engineering Faculty Research & Creative Works

Biofuel-based combustion synthesis (BCS) processes offer low-temperature, low-carbon routes to lime and clinker production. However, they involve tightly coupled interactions between heat transfer, gas flow, and sequential solid-state reactions within reactive pellets. Experiments typically provide surface temperature evolution and final phase assemblages but give limited insight into the conversion process and the interaction between composition and process conditions. A coupled transport-reaction framework is developed here to resolve this limitation─the synthesis of β-C2S (belite), a major cementing phase, serving as an example. Transient conservation equations for energy, momentum, and species are solved for a porous pellet exchanging heat and mass with …

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Characteristics And Microscopic Mechanisms Of Nsep-Modified Asphalt With Reduced Fume Emission And Enhanced Environmental Benefits, Yiliang Li, Jianguo Wei, Anmin Zou, Jinming Li, Jenny Liu, Di Wang, Xuan Xiao, Yuming Zhou Jun 2026

Characteristics And Microscopic Mechanisms Of Nsep-Modified Asphalt With Reduced Fume Emission And Enhanced Environmental Benefits, Yiliang Li, Jianguo Wei, Anmin Zou, Jinming Li, Jenny Liu, Di Wang, Xuan Xiao, Yuming Zhou

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Toxic fumes emitted during the construction and maintenance of hot-mix asphalt mixtures represent a significant challenge for both the environment and construction workers. To reduce the generation of these toxic fumes, nano-sepiolite (NSEP, a natural mineral) powder was incorporated into base asphalt (BA), styrene-butadiene-styrene (SBS) -modified asphalt (SBSA), and crumb rubber-modified asphalt (CRA) to formulate sepiolite-modified asphalt binders. The rheological properties of these NSEP-modified asphalts were evaluated using dynamic shear rheometer (DSR) and bending beam rheometer (BBR) tests. Subsequently, smoke density tests and gas chromatography-mass spectrometry (GC-MS) were utilized to analyze the quantity and composition of the volatile organic compounds …

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