Digital Commons Network^™

Modern Methods Of Self-Monitoring, Diagnostics, And Fault Tolerance In Flow Measurement Systems, Elbek Ortiqov

Chemical Technology, Control and Management

This article investigates various methods and tools for self-monitoring and fault tolerance in flow measurement transducers used in industrial processes. The study focuses on key techniques such as the use of redundancy, generation of reference values, analysis of measurement signals, and control of disturbance variables. These methods allow transducers to detect potential faults, ensure reliable operation, and maintain measurement accuracy even under adverse conditions. The article highlights how self-monitoring contributes to improving system safety, increasing reliability, and reducing downtime. It also discusses the integration of intelligent monitoring systems that support predictive maintenance and real-time diagnostics. Fault-tolerant sensors with self-monitoring capabilities …

Synthesis Of A Control System For Thermal Energy Facilities Using The Quantum Photon Spin Method, Isomiddin Siddikov, N.S Yakubova

Chemical Technology, Control and Management

Increasing energy efficiency and reducing fuel consumption in the process of generating electricity and heat at thermal power plants is one of the urgent tasks. Such systems operate under conditions of random changes in external and internal influences, as well as measurement uncertainties, which reduce the quality of control. In order to overcome this problem, it was proposed to develop an intelligent control system using the quantum photon-spin method to control technological units of thermal power plants. In the proposed approach, a multi-dimensional heating boiler device was taken as a control object, and the simulation modeling of the control system …

Algorithms For The Synthesis Of Adaptive Control Systems Based On The Speed-Gradient Method, Oxunjon Boborayimov

Chemical Technology, Control and Management

This paper discusses the synthesis algorithms for adaptive control systems based on the speed-gradient method. Adaptive control systems with implicit reference and adjustable models are synthesized using speed-gradient techniques, which reduce the requirements for the main control loop structure and the completeness of measurement data. Stable adaptive decentralized control algorithms are developed for a class of interconnected systems with nonlinear local dynamics and uncertainties, ensuring the stability of individual subsystems and the overall system while accounting for their interactions. To incorporate inter-subsystem interactions into the overall control law, an adaptation algorithm based on the speed-gradient method is introduced. A synthesis …

Finding The Shortest And Optimal Path With Metaheuristic And Madm Methods, Narmin Ibrahim Hasanli

Chemical Technology, Control and Management

The article had described a method for finding the shortest and most optimal path among cities. The data had been taken from the TSPLIB library, which had provided standard examples for the Traveling Salesman Problem. This approach had integrated the advantages of the meta-heuristic technique and the Multi Attribute Decision Making method to solve the problem effectively. In the first stage, the population based meta-heuristic method ACO (Ant Colony Optimization) had found optimal solutions in large search spaces. The use of pheromone trails, heuristic information and an iterative search process had given the opportunity to find the best or near-best …

Magnetic Nanoparticles Tethered With Zn–Dpa For The Removal Of Bacteria From Red Blood Cell Suspension, Tochukwu P. Okonkwo, Rajendra P. Gautam, Jacob B. Limburg, Breckin L. Forstrom, Bowen J. Houser, Aaron Rappleyea, Tyler P. Green, Joseph P. Talley, Alexander D. Daum, Stacey J. Smith, Karine Chesnel, William G. Pitt, Roger G. Harrison

Faculty Publications

Bacterial infections continue to drive the need for more effective and rapid methods for bacterial analysis. To address this, magnetic nanoparticles (MNPs) have emerged as promising tools, especially when their surfaces are modified with bacteria binders. The bis-zinc–dipicolylamine (Zn–DPA) complex is known for its broad affinity to bacteria. We have synthesized MNPs via a thermal decomposition method, encapsulated them in silica, modified their surface with Zn–DPA, and tested their ability to remove bacteria. The MNPs retain their superparamagnetic properties and crystallite structure after being encapsulated. The MNPs coated with silica and Zn–DPA effectively bind and remove both Gram-positive and Gram-negative …

Interfacial Shear Transfer Between Steel H-Piles And Concrete Encased In Cfrp, Mohanad M. Abdulazeez, Binod Shrestha, Mohamed A. Elgawady

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Numerous in-service steel H-piles, a common structural element in the bridge industry, suffer severe corrosion. One of the adopted solutions is to use concrete jackets to encase the corroded sections. Therefore, interfacial shear strength between the uncorroded section and the jacket is crucial. This paper presents an experimental investigation of the interfacial shear stresses of 18 full-scale H-piles encased in concrete jackets and subjected to push-out static testing. The concrete jackets are confined using different carbon fiber-reinforced polymer (CFRP) confinement ratios. Different cross-sectional areas and distributions of shear studs are investigated. The average and maximum bond stresses are evaluated and …

Enabling Carbon Dioxide Mineralization And Active Set Control In Portlandite-Based Cementitious Suspensions, Xiaodi Dai, Sharu Bhagavathi Kandy, Rui Xiao, Manas Sarkar, Shubham Wani, Thiyagarajan Ranganathan, Narayanan Neithalath, Aditya Kumar, Mathieu Bauchy, Edward Garboczi, Torben Gädt, Samanvaya Srivastava, Gaurav Sant

Materials Science and Engineering Faculty Research & Creative Works

The real-time control of concrete's stiffening allows users to better control pumping and extrusion during 3D-printing processes. Here, a portlandite-based cementitious formulation (i.e., slurry or suspension) that features the potential for rapid CO₂ uptake is adapted for 3D-printing applications. In particular, we showcase a portlandite-fly ash binder system combined with a thermo responsive polymer, wherein precise control via thermal activation allows set control and rapid solidification. Through the thermally induced polymerization of polyacrylamide, the hybrid binder system rapidly undergoes stiffening at trigger onset temperatures ranging from 60 °C to 80 °C, exhibiting average stiffening rates of up to 2600 …

2025 Safety Belt Usage Survey In Kentucky, Erin Lammers-Staats, Derek Young, Kenneth Agent

Kentucky Transportation Center Research Report

No abstract provided.

Physics-Based Machine Learning Framework For Predicting Structure-Property Relationships In Ded-Fabricated Low-Alloy Steels †, Atiqur Rahman, Md Hazrat Ali, Asad Waqar Malik, Muhammad Arif Mahmood, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The Directed Energy Deposition (DED) process has demonstrated high efficiency in manufacturing steel parts with complex geometries and superior capabilities. Understanding the complex interplays of alloy compositions, cooling rates, grain sizes, thermal histories, and mechanical properties remains a significant challenge during DED processing. Interpretable and data-driven modeling has proven effective in tackling this challenge, as machine learning (ML) algorithms continue to advance in capturing complex property structural relationships. However, accurately predicting the prime mechanical properties, including ultimate tensile strength (UTS), yield strength (YS), and hardness value (HV), remains a challenging task due to the complex and non-linear relationships among process …

Navigating Barriers: Examining Social Equality Through Transportation Disadvantages And Perceived Healthcare Accessibility In South Carolina, Yihong Ning, Songyuan Deng, Yuche Chen

Faculty Publications

Transportation inequities significantly contribute to health disparities, particularly in socially and geographically diverse regions like South Carolina. Prior research predominantly relied on objective measurements, like travel time or distance, to assess healthcare accessibility. However, limited attention has been given to the subjective perceptions of transportation barriers. To address this gap, we designed a comprehensive survey consisting of 61 questions (including 32 five-point Likert-scale items) capturing demographic, socioeconomic, and travel behavior data from a diverse sample of South Carolina residents. Urban and rural contexts were distinguished using county categorization and built environment measures. Exploratory Factor Analysis (EFA) was employed to identify …

Ibi-Dt: A Novel Approach Combining Individualized Bayesian Inference And Decision Tree For Identifying Cancer Drivers And Their Interactions, Md Asad Rahman, Gregory F. Cooper, Jinying Zhao, Xinghua Lu, Jinling Liu

Engineering Management and Systems Engineering Faculty Research & Creative Works

Cancer is mainly caused by a relatively small portion of somatic genome alterations (SGAs), called cancer drivers. Despite success in identifying a good number of cancer drivers, many more remain to be discovered to explain various cancers. Moreover, limited tools are available to identify potential interactions among cancer drivers for a better understanding of oncogenesis. To tackle these challenges, we have developed a novel approach called individualized Bayesian inference using a decision tree (IBI-DT). IBI-DT recognizes the genetic heterogeneity among cancer patients, where different individuals or patient subgroups of distinct genomic makeup may have different drivers. IBI-DT works by constructing …

Enhancing Non-Player Character Dialogue In Video Gages: An Evaluation Of Large Language Model-Generated Responses, Lam P. Quach

Master's Theses

As video games increasingly emphasize narrative depth and player immersion, the quality of Non-Player Character (NPC) dialogue has become crucial for creating engaging gaming experiences. This thesis investigates the potential of Large Language Models (LLMs) to generate high-quality NPC dialogue by comprehensively evaluating four state-of-the-art models: Gemma 3 27B, Mistral 7B, QWEN 2.5, and LLAMA 3.1. The study employs a mixed-methods approach, combining human evaluation (N=50 participants) with AI-based assessment across five key benchmarks: coherence, personality expression, engagement, style/tone appropriateness, and overall quality. Participants evaluated 32 dialogue samples (8 per model) generated for a fantasy game context featuring two distinct …

Sainik Vol 1 Issue 1, Sastra Deemed To Be University

SAINIK

No abstract provided.

Low-Resource Ecoacoustic Audio Classification, Enis Berk Coban

Dissertations, Theses, and Capstone Projects

Ecoacoustic monitoring via machine learning enables scalable analysis but is often constrained by labeled data scarcity, particularly in remote regions like the Arctic. This thesis confronts low-resource ecoacoustic audio classification by developing and evaluating complementary machine learning methodologies. We introduce EDANSA, the first publicly available, expert- labeled Arctic dataset of its kind, curated via novel active learning, alongside a baseline CNN. We systematically evaluate transfer learning, showing general audio embeddings effectively bootstrap classifiers for challenging Arctic sounds, significantly outperforming direct label mapping. Optimizing label utility, we investigate standard data augmentation and introduce novel audio data valuation via Shapley values, revealing …

The Floodnet Community Engagement Guide, Véronëque Ignace, Sofia Mariyamis, Kendra Krueger, Polly Pierone, Hayley Elszasz, Hannah Eisler Burnett

The Science and Resilience Institute at Jamaica Bay, SRIJB

"At the Intersection of Science, Policy, and Community: The FloodNet NYC Community Engagement Strategy” is a public-facing community engagement guide that documents the strategies, tools, and lessons developed through FloodNet NYC, a cross-sector partnership among researchers at NYU and CUNY and New York City agencies. Designed as a practical resource, this guide shares our approach to community engagement and dissemination so that researchers, practitioners, community organizations, and public agencies can adapt these methods to their own urban climate science projects and other community-centered efforts that address climate challenges.

Grounded in community-based participatory research (CBPR) principles, the guide presents community engagement …

Multi-Modal Depth Estimation Using Camera And Mmwave Sensors, Alston D. Devero-Belfon

Student Theses

For accurately estimating the depth of environments with varying lighting conditions, reliable methods are limited. By utilizing wireless sensor technology in conjunction with cameras, a wide range of environments can be visualized, and objects within these environments can be tracked and monitored. Such methods offer cost-effective alternatives and provide a more secure, data-at-rest option for individuals with low vision, while also enhancing machine perception. In this work, we develop such a prototype that utilizes wireless sensors and cameras, which act in sync, enabling us to estimate the depth of objects within varying lighting environments to a level that is recognizable …

Single-Molecule Orientation And Localization Microscopy, Sophie Brasselet, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Single-molecule localization microscopy (SMLM) offers enhanced spatial resolution in optical microscopy, providing detailed insights into the spatial organization of proteins in cells at the nanoscale. Over the past decade, SMLM has progressively incorporated the capability to retrieve the orientations of single molecules using their polarized dipolar emission pattern. Here we explore recent advancements in single-molecule orientation and localization microscopy (SMOLM), which yields super-resolved images of molecular three-dimensional (3D) orientations, wobble and 3D positions. This advancement opens possibilities to explore the nanoscale organization and conformation of biological molecules as well as to monitor and design local 3D optical fields in nanophotonics. …

Effect Of Short-Chain Polymer Binders On The Mechanical And Electrochemical Performance Of Silicon Anodes, Fei Sun, L. Zurita-Garcia, Dean R. Wheeler

Faculty Publications

Polymer binders are crucial components in providing both mechanical support and chemical stability to the structure of porous Li-ion electrodes. Particularly in silicon anodes, the active material undergoes substantial volume expansion of up to 275%. Due to the mechanical constraint of the current collector, these silicon materials tend to expand in the normal direction while exhibiting substantial particle rearrangement and plastic deformation. Conventional rigid binders such as polyacrylic acid (PAA) and polyimide (PI), while providing satisfactory initial capacity, do not eliminate diminished long-term performance. Our research attempts to develop binder formulations that can accommodate sufficient flexibility for the substantial volume …

Storage Location Optimization In Automated Storage And Retrieval Systems: A Deep Reinforcement Learning Approach, Lingjun Wang, Aldy Gunawan, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

This study investigates the optimization of storage location in automated storage and retrieval systems (AS/RS). We introduce an optimization approach based on the Deep Q-Network (DQN) algorithm to enhance warehouse task efficiency and minimize stacker travel during storage and retrieval. To accelerate the algorithm training process, we integrate a prioritized experience replay mechanism. Furthermore, we decouple action selection from value estimation within the DQN framework to address the issue of value overestimation. The proposed model is evaluated against three heuristic methods. The experimental results demonstrate that our approach significantly outperforms these baselines.

Large Lithium-Ion Battery Model For Secure Shared E-Bike Battery In Smart Cities, Donghui Ding, Zhao Li, Linhao Luo, Ming Jin, Bin Zhu, Yichen Zhong, Junhao Hu, Peng Cai, Huiqi Hu

Research Collection School Of Computing and Information Systems

Electric bikes powered by lithium-ion batteries are increasingly used in smart cities to promote sustainable mobility and efficient delivery services. However, limited battery range and slow plug-in charging remain key challenges. Shared electric bike battery systems, facilitated by battery swapping stations, offer a promising solution by enabling quick and efficient battery replacements. However, their success hinges on accurate anomaly detection, battery health estimation and remain range prediction. These tasks remain challenging due to data scarcity, battery diversity and environmental variability. Here we show that a large-scale lithium-ion battery model trained on over ten million battery time series data enables robust …

Synergetic Adsorptive Mechanisms, Reusability And Cost Evaluations Of Green Fabricated Hybrid Barium Cobalt Nanocomposites For Methylene Blue And Lead Removal From Wastewater, Titus Chinedu Egbosiuba, Chibuike Christogonus Njoku, Ijeoma Jacinta Ani, Godwin Ifeanyi Ogbuehi, Abdulkareem Omeiza Yusuf, Abiodun Azeez Saka, Ugochukwu Ewuzie, Ebuka Emmanuel Ezennajiego, Blessing Onyinye Okafor, Walter Chibuike Anene, Cecilia Chika Unegbu, Florence Acha, Monday Uchenna Okoronkwo

Chemical and Biochemical Engineering Faculty Research & Creative Works

Barium nanoparticles (BaNPs), cobalt nanoparticles (CoNPs), and hybrid barium-cobalt nanocomposites (BaCoNCs) were synthesized using an eco-friendly green technique with Anacardium occidentale leaf extract for sequestration of methylene blue (MB) dye and lead (Pb (II)) ions from industrial wastewater. The nanoparticles and nanocomposites were characterized using Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), high-resolution scanning electron microscopy (HRSEM), and Brunauer-Emmett-Teller (BET) analysis to assess their functional groups, crystalline structure, morphology, and surface properties, confirming successful synthesis. Batch adsorption studies showed that optimal pollutant removal occurred at pH values of 8 for MB and 5 for Pb(II), with a contact time …

Systematic Hazard Analysis Of Flare System Nodes In Chemical Process Safety, Hayder A. Alhameedi, Athmar A. Alzubaidi, Joseph D. Smith, Doug Allen, Saud Aldawood, Paul Ani

Chemical and Biochemical Engineering Faculty Research & Creative Works

Multidimensional consequences may arise from an accident in the flare system of any chemical or petrochemical plant due to the improperly managed flare system, which can lead to the presence of the toxic and flammable gases. The Hazard and Operability Study (HAZOP) is a systematic method used to assess and identify risks that can occur during operation, ensuring risk reduction and the safety of using equipment or units. This study aims to apply the HAZOP technique to identify the hazards associated with the gas flaring process in an air-assisted flare. The air-assisted flare system was subdivided into four sections (nodes), …

Neuro-Ins: A Learning-Based One-Shot Node Insertion For Dynamic Routing Problems, Zhiqin Zhang, Jingfeng Yang, Zhiguang Cao, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

The rise in instant delivery services necessitates efficient route planning in last-mile delivery scenarios, where new orders arrive dynamically and need to be integrated into existing routes. In such contexts, complete re-optimization of routes are not permitted, and node insertion to existing route sequences is the only viable option. However, many existing heuristics for node insertion, such as the Cheapest Insertion (CI) method, are myopic and often result in suboptimal solutions retrospectively. This paper presents Neuro-Ins, an initial yet novel attempt at harnessing a learning-based framework to handle the insertion of new orders for the Pickup and Delivery Problem (PDP). …

Exploring The Adoption Of Construction Technologies In Infrastructure Projects: Bridging Perceptions Of Experts With Real Project Data, Fareed Salih, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Infrastructure projects have progressively adopted construction technologies, yet previous studies have not fully explored technology utilization by comparing the perceptions of experts with actual project data. This research fills this knowledge gap. The authors (1) developed, distributed, and collected a survey completed by 52 construction practitioners to investigate the use of these technologies and their associated benefits; (2) checked the survey reliability and validity using Cronbach's alpha test; (3) investigated the perceptions of utilizing construction technologies across industry sectors; (4) explored the perceptions of benefits across industry sectors; (5) analyzed the impact of construction technologies on project objectives and phases …

Experimental And Theoretical Studies Of Novel Resilient Smart Shear Keys For Speedy Functional Recovery Of Highway Bridges After Extreme Events, Xinzhe Yuan, Jun Han, Jian Zhong, Haibin Zhang, Genda Chen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Sacrificial shear keys in small-to-medium-span highway bridges mainly provide lateral support to the bridge superstructure under extreme events such as earthquake and/or tsunami. However, such support could lead to irreparable harm to important bridge elements like abutments and bent caps (base), delaying the functional recovery of bridges in the aftermath. In addition, existing designs of the shear key primarily emphasize resistant capacity but overlook resilience. This study introduces a new sliding, modular, adaptive, replaceable, and two-dimensional (SMART) shear key designed to enhance the resilience of I-girder highway bridges. The SMART shear key has three primary goals: 1) enabling the rapid …

Positive Effects Of Sulfates On Performance Of Cement Paste Incorporating Low-Grade, High-Aluminum Steel Slag, Nannan Zhang, Gao Deng, Wenyu Liao, Chuanlin Hu, Hongyan Ma

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Steel slag with high aluminum (Al) content significantly delays the early hydration of cement when used as a supplementary cementitious material (SCM). To address this challenge, this study investigates the effects of gypsum (Gy) and sodium sulfate (SS) additions on the performance of cement pastes with 30 % high-Al ladle metallurgy furnace (LMF) slag. The mechanical properties, hydration kinetics, phase evolution, as well as the early-age hydration mechanism were explored. The results indicate that C3S hydration is substantially inhibited under high-Al conditions, mainly attributed to the rapid dissolution and reaction of reactive aluminates (particularly mayenite) in the slag. Both Gy …

Development Of A Balanced Mix Design Approach For Stone Matrix Asphalt Mixtures, Bo Lin, Yizhuang David Wang, Jenny Liu

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Stone Matrix Asphalt (SMA) has been widely used as a durable, high-quality mixture for primary roads. With the growing interest in incorporating innovative materials into SMA designs, developing effective and reliable mix design methodologies has become essential to ensure durability, sustainability, and cost-effectiveness. While performance tests have gained national acceptance for asphalt mix design and balanced mix design (BMD) methods have been adopted in many states for hot mix asphalt (HMA), SMA has not been fully considered with the BMD implementation. This study aimed to develop a BMD approach for SMA, incorporating both SMA-specific volumetric parameters and performance requirements. To …

Data-Driven Shear Capacity Prediction Of Studs Embedded In Uhpc For Steel-Uhpc Composite Structures, Yanping Zhu, Woubishet Zewdu Taffese, Genda Chen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study employs ensemble learning algorithms to accurately predict the shear capacity of studs embedded in ultrahigh performance concrete (UHPC), a critical aspect of structural engineering. Using a comprehensive data set featuring six UHPC slab features, seven stud features, and one shear pocket feature, 35 ensemble models are developed across five cases and seven algorithms (bagging, random forest, AdaBoost, gradient boosting, XGBoost, CatBoost, and LightGBM). The Shapley additive explanations (SHAP) analysis is conducted on the top-performing models to gain insights into their decision-making mechanisms. Results indicate that transforming UHPC slab geometry parameters into a volume, alongside different diameter ratios, proves …

Amorphous Sio2-Stabilized High-Valent Iron-Oxo Complexes Derived From Fe- And Si-Rich Solid Wastes For Efficient Tetracycline Hydrochloride Degradation, Cuirong Yan, Hongyan Ma, Xiunan Cai, Zhongqiu Luo, Jinyu Shi, Wenhao Li, Xintao Zhou

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

High-valent iron-oxo complexes show promise as green oxidants for water remediation but suffer from critical limitations in stability and pH adaptability. Herein, we report a facile method to synthesize amorphous SiO₂-stabilized high-valent iron-oxo complexes via Na⁺ diffusion activation of iron/silicon-rich copper smelting slag. In the complex, the synergistic coexistence of two distinct silica‑oxygen tetrahedral configurations-basic Na₂SiO₃ and acidic SiO2 oxides establishes a self-regulating pH buffering system that stabilizes solution neutrality. This unique structural design ensures sustained oxidative activity of the complex, representing a significant advancement over conventional silica-supported catalysts due to its intrinsic acid-base …

Guiding State-Specific Studies On Highway Disasters: Examining Differences In Postdisaster Funding, Mariam Elazhary, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The highway sector is frequently and severely impacted by natural disasters. To mitigate these effects and reduce the need for large relief budgets or emergency funds, it is crucial to study the resilience of the transportation network. As such, defining resilience in absolute terms is not enough; instead, it is equally important to analyze specific case studies and build a lessons-learned rapport. This is critical because it helps identify unique vulnerabilities and strengths that might be overlooked in broader analyses. However, current research on highway resilience often lacks empirical evidence to support the selection of these unique and significant case …