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Enhancing Operational Efficiency Of Paratransit Services Using Predictive Models, Troyee Saha Jan 2025

Enhancing Operational Efficiency Of Paratransit Services Using Predictive Models, Troyee Saha

Civil Engineering Dissertations - Archive

Paratransit services play a vital role in supporting the mobility of older adults and individuals with disabilities, yet they experienced major disruptions during the COVID-19 pandemic and continue to face ongoing operational issues such as trip cancellations. This dissertation explores these challenges through three distinct analyses using data from Arlington, TX. The first chapter investigates how COVID-19-related factors (policies, cases, and vaccination) and socio-demographics influenced paratransit usage from 2019 to 2021. Applying SARIMAX and Poisson regression models, the study finds a substantial drop in ridership—41% in 2020—and a shift toward essential medical travel. It also reveals that restrictive policies, such …


Development Of Supervised Machine Learning-Based Life-Cycle Cost Estimation And Prediction Models For Comparative Sewer System Rehabilitation Using Open-Cut And Trenchless Cured-In-Place Pipe Methods, Gayatri R. Thakre Jan 2025

Development Of Supervised Machine Learning-Based Life-Cycle Cost Estimation And Prediction Models For Comparative Sewer System Rehabilitation Using Open-Cut And Trenchless Cured-In-Place Pipe Methods, Gayatri R. Thakre

Civil Engineering Dissertations - Archive

Aging wastewater infrastructure in the United States demands renewal strategies that balance cost-effectiveness, sustainability, and minimal social disruption. Conventional open-cut pipeline installation (OCPI) involves extensive excavation and restoration, whereas trenchless alternatives such as Cured-in-Place Pipe (CIPP) Renewal Technology offer reduced surface disturbance and environmental impacts. However, existing studies primarily focus on Construction Costs (CC), neglecting integrated life-cycle evaluations that also account for Environmental Costs (EC) and Social Costs (SC).

The primary objectives of this research are to develop supervised machine-learning (ML) models to estimate and predict CC in 2025 US dollars (USD) per linear foot of OCPI and CIPP Renewal …


Structural Performance Of High-Rise Rc Buildings With Sfrc Columns And Shear Walls Subjected To Seismic Loading, Ali Azzawi Jan 2025

Structural Performance Of High-Rise Rc Buildings With Sfrc Columns And Shear Walls Subjected To Seismic Loading, Ali Azzawi

Civil Engineering Theses - Archive

To investigate the seismic performance of high-rise RC buildings with steel fiber reinforced concrete (SFRC) columns and shear walls, a detailed numerical analysis was established using RISA-3D software on twelve-story RC buildings subjected to earthquakes. The variables included in this research are steel fiber volume fraction (SFVF), number of stories with SFRC columns and shear walls, and concrete strength grade. The mechanical properties of the concrete for each mix are evaluated experimentally. Three types of concrete mix designs were performed in the Civil Engineering Laboratory Building (CELB) using different dosages of steel fibers (0, 25lb/cy, and 70lb/cy). The properties of …


A Design And Analysis Of Computer Experiments Approach To Water Distribution Network Seismic Rehabilitation Optimization, Uthman Abiola Kareem Jan 2025

A Design And Analysis Of Computer Experiments Approach To Water Distribution Network Seismic Rehabilitation Optimization, Uthman Abiola Kareem

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Water is an essential part of human life. However, there are critical infrastructures that enable water availability in communities and homes. One of such is a water distribution network. Water distribution network performance depends on its reliability, which could be threatened by external agents like earthquakes. When earthquakes occur, they cause damages on some pipes within the distribution network and this limits performance of water distribution network. While earthquakes cannot be prevented, effective maintenance intervention may reduce the impact of earthquakes on water distribution networks. In order to develop an effective maintenance plan, researchers approach it in different ways. However, …


Analysis Of Crowd Logistics Networks Using Agent-Based Models, Preetam Kulkarni Jan 2025

Analysis Of Crowd Logistics Networks Using Agent-Based Models, Preetam Kulkarni

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Crowd logistics is a system in which an online platform connects a group of non-professional couriers (crowd/carriers), who use their under-utilized resources to offer delivery service to other individuals or businesses (senders) for a fee. While crowd logistics platforms have the potential to offer more flexible and responsive delivery services for much lower rates than traditional logistics providers, it is difficult for platforms to be successful as it is challenging to meet carriers’ and senders’ expectations. Crowd logistics has been applied in the context of food and grocery delivery, parcel pickup and drop-off services and last-mile delivery, however, it has …


Cnns And Transformers For Visual Understanding: From Feature Alignment To Image Captioning, Xuehao Liu Jan 2025

Cnns And Transformers For Visual Understanding: From Feature Alignment To Image Captioning, Xuehao Liu

Doctoral

Deep learning has developed rapidly since the introduction of Deep Belief Networks during the past decade. As an area of machine learning, it still has many open challenges. Among these open challenges is the issue of transparency, with deep learning models known as black boxes. Both explainability of a model for understanding the decision making process, and the transparency of the relationship between the input and output are crucial for understanding a model. The understanding of models can build trust between AI systems and humans, verify models behavior, and identify potential biases or errors.


Twitter-Based Osint For Cyber Event Analytics, Dakota S. Dale, Kylie Mcclanahan, W. Sky Elder, Qinghua Li Jan 2025

Twitter-Based Osint For Cyber Event Analytics, Dakota S. Dale, Kylie Mcclanahan, W. Sky Elder, Qinghua Li

Electrical Engineering and Computer Science Faculty Publications and Presentations

Open-Source Intelligence (OSINT) is often regarded as a critical component for cybersecurity intelligence gathering to secure cyber infrastructures. As Artificial Intelligence (AI) and social media progress and become more commonplace, we have the unique opportunity to collect and analyze information from social media in real time. In this paper, we propose an AI-based framework for automatically filtering the Twitter stream for cybersecurity information, analyzing the natural language to aggregate the tweets around specific cybersecurity events, and certifying the information. The system's applications range from discovering events security operators may not have been aware of to helping operators investigate on-going events …


Emotion Processing In Adolescents With Epilepsy And Healthy Controls Using Multi-Modal Neuroimaging, Frances Kathryn E. King Jan 2025

Emotion Processing In Adolescents With Epilepsy And Healthy Controls Using Multi-Modal Neuroimaging, Frances Kathryn E. King

Bioengineering Dissertations - Archive

Epilepsy is increasingly recognized as a disorder not only of seizures but also of widespread network dysfunction, impacting cognitive and emotional processing. One critical cognitive process affected in epilepsy is emotional conflict processing, which relies on the interplay of multiple brain networks. However, the spatiotemporal dynamics of emotional conflict processing in epilepsy, particularly in adolescents, have remained poorly understood. This dissertation investigated the neural mechanisms underlying emotional conflict processing in typically developing adolescents and adolescents with epilepsy using magnetoencephalography (MEG). The first study elucidated the spatiotemporal profile of emotional conflict processing in 24 typically developing adolescents using magnetoencephalography (MEG). Cluster-based …


Neurovascular Coupling Impairments In Acute Traumatic Brain Injury: An Eeg-Nirs Analysis, Zachary Armstrong Jan 2025

Neurovascular Coupling Impairments In Acute Traumatic Brain Injury: An Eeg-Nirs Analysis, Zachary Armstrong

Bioengineering Theses - Archive

Traumatic brain injury (TBI) is a major cause of neurological impairment, often leading to variable recovery and uncertain prognosis in the neurocritical care setting. There is a pressing clinical need for robust, physiologically grounded biomarkers to inform prognosis and therapeutic decision-making in acute TBI. This thesis investigates neurovascular coupling (NVC), the physiological coordination between neuronal activity and cerebral blood flow, as a candidate biomarker for brain function and recovery after injury.

A prospective cohort study was performed using simultaneous electroencephalography (EEG) and near-infrared spectroscopy (NIRS) recordings in patients with moderate-to-severe TBI and healthy controls. Wavelet transform coherence (WTC) analysis was …


Consumer Preferences And Willingness To Pay For Vertiport Design, Amenities, And Services, David C. Ison Jan 2025

Consumer Preferences And Willingness To Pay For Vertiport Design, Amenities, And Services, David C. Ison

International Journal of Aviation, Aeronautics, and Aerospace

The rise of urban air mobility (UAM) and electric vertical takeoff and landing (eVTOL) aircraft necessitates the development of well-designed vertiports that align with consumer expectations. This study examines consumer preferences and willingness to pay (WTP) for vertiport design, amenities, and services to inform infrastructure planning and investment strategies. Using a survey-based quantitative research design, data were collected from 500 participants to assess key factors influencing WTP, including convenience, security measures, service efficiency, and premium offerings. Findings indicate that location accessibility, affordability, and streamlined security procedures are primary determinants of vertiport adoption. While aesthetic and retail enhancements contribute to passenger …


Learning From Leads: A 1d Dilated Resnet For Ecg Chagas Disease Screening, Somesh Saini, Matheus Lima Diniz Araujo Jan 2025

Learning From Leads: A 1d Dilated Resnet For Ecg Chagas Disease Screening, Somesh Saini, Matheus Lima Diniz Araujo

Student Scholarship

No abstract provided.


Assessing The English Language Needs Of Student Pilots: A Comprehensive Analysis For Effective Aviation English Training, Triyani Rps Dewi, Lilis Kurnianingsih Jan 2025

Assessing The English Language Needs Of Student Pilots: A Comprehensive Analysis For Effective Aviation English Training, Triyani Rps Dewi, Lilis Kurnianingsih

International Journal of Aviation, Aeronautics, and Aerospace

This research aims to identify the English language material needs for pilot students at the Indonesian Civil Aviation Polytechnic in order to improve communication skills that are essential for flight safety and operational effectiveness. In data collection, the researcher distributed questionnaires to students and conducted a Focus Group Discussion (FGD) involving students, flight instructors, English lecturers, and experienced pilots. The research results show that pilot students need two main skills in English learning. First, listening skills, especially in understanding instructions from ATC. Second, speaking skills used to respond to ATC instructions and to make requests or ask for information from …


From Cyclones To Cybersecurity: A Call For Convergence In Risk And Crisis Communications Research, Ann Marie Reinhold, Ross J. Gore, Barry Ezell, Clemente I. Izurieta, Elizabeth A. Shanahan Jan 2025

From Cyclones To Cybersecurity: A Call For Convergence In Risk And Crisis Communications Research, Ann Marie Reinhold, Ross J. Gore, Barry Ezell, Clemente I. Izurieta, Elizabeth A. Shanahan

VMASC Publications

Effective risk and crisis communication can improve health and safety and reduce harmful effects of hazards and disasters. A robust body of literature investigates mechanisms for improving risk and crisis communication. While effective risk and crisis communication strategies are equally desired across different hazard types (e.g., natural hazards, cyber security), the extent to which risk and crisis communication experts utilize the “lessons learned” from scientific domains outside their own is suspect. Therefore, we hypothesized that risk and crisis communication research is siloed according to academic disciplines at the detriment to the advancement of the field of risk communications research writ …


Leveraging Intrinsic Properties For Classification Of Coal Seams Towards Spontaneous Combustion Proclivity And Predicting Susceptibility Using Machine Learning: Smart And Sustainable Mining Approach, Siddhartha Agarwal, Pradeep K. Gautam, Yuhao Zou, Rishabh Dwivedi, Durga C. Panigrahi, Cihan H. Dagli, A. Singh Jan 2025

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

Engineering Management and Systems Engineering Faculty Research & Creative Works

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


Data-Driven Layout Design For Smart Remanufacturing: A Flexible Optimization Model And A Case Study, J. A. Afari, A. Gosavi, J. Hu, R. J. Marley Jan 2025

Data-Driven Layout Design For Smart Remanufacturing: A Flexible Optimization Model And A Case Study, J. A. Afari, A. Gosavi, J. Hu, R. J. Marley

Engineering Management and Systems Engineering Faculty Research & Creative Works

Abstract: In remanufacturing, a vital segment of the sustainable, low-carbon circular economy, existing versions of the traditional unequal-areas facility layout problem (UA-FLP) model face significant limitations in designing layouts. To be specific, in the process of minimizing the material-handling cost (MHC), these models also alter departmental dimensions, often diverging from construction specifications. This poses a difficulty, as critical equipment required for remanufacturing, e.g., sorting and cleaning machines, have unalterable dimensions, which implies that departmental dimensions cannot be changed from specifications provided. To address this, a novel Flexible Envelope UA-FLP (FE-UA-FLP) model is proposed in this work for designing layouts wherein …


Transplant Surgeon Fuzzy Associative Memory (Tsfam): Model For Capturing Surgeon Perspective, Rachel Dzieran, Cihan H. Dagli, Robert J. Marley Jan 2025

Transplant Surgeon Fuzzy Associative Memory (Tsfam): Model For Capturing Surgeon Perspective, Rachel Dzieran, Cihan H. Dagli, Robert J. Marley

Engineering Management and Systems Engineering Faculty Research & Creative Works

AI-driven healthcare decision-making is multi-faceted, requiring complex logic to adapt to evolving policies and societal demands. Effective change implementation by healthcare providers and multidisciplinary organ transplant teams depends on adaptive decision-making. The proposed Transplant Surgeon Fuzzy Associative Memory (TSFAM) model introduces a novel approach to Human-AI Teaming, keeping human expertise central while dynamically adjusting to changing requirements. TSFAM employs fuzzy logic to manage imperfect data and human ambiguity, integrating the transplant surgeon perspective with the AI deep learning decision-making tool, creating a resilient solution in this critical domain. By embedding adaptive capabilities into the architecture, TSFAM exemplifies the adaptability of …


Electricity Theft Detection With An Adaptive Deep Learning Architecture, Mohammed Sleiman, Cihan Dagli, Rui Bo Jan 2025

Electricity Theft Detection With An Adaptive Deep Learning Architecture, Mohammed Sleiman, Cihan Dagli, Rui Bo

Engineering Management and Systems Engineering Faculty Research & Creative Works

Electricity theft presents a significant challenge to the power industry. This paper demonstrates an adaptive deep framework integrating dimensionality reduction, graph modeling, attention mechanisms, and dynamic feature refinement for improving theft detection. Principal Component Analysis squeezes consumption data while an Autoencoder extracts latent representations and denoises the input. A Gated Graph Convolutional Neural Network uses k-Nearest Neighbors to model local relationships, while Transformers capture long range global dependencies. Neural Ordinary Differential Equations then refine features over continuous time, improving adaptability to complex patterns. The framework achieves 94.01% accuracy with stratified 5-fold cross validation. However, class imbalance challenges the minority class …


Cyber Forensics With Deep Learning Recurrent Neural Networks, Pfautch Ric, Dagli Cihan, Ashiku Lirim Jan 2025

Cyber Forensics With Deep Learning Recurrent Neural Networks, Pfautch Ric, Dagli Cihan, Ashiku Lirim

Engineering Management and Systems Engineering Faculty Research & Creative Works

Detection of anomalies and anti-patterns is essential for adaptive systems with the ability to perform without foreknowledge. Some problems require both classification and regression along with sensitivity tuning and explainability. Some have highly dimensional datasets that are time dependent. This research offers results for Long-Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) algorithms using the BETH dataset. It unpacks metadata attributes and stages a unique approach via Abstract-Feature Analysis (AFA), hyper parameter tuning, and Principal Component Analysis (PCA) within the RNN model. By removing foreknowledge, this research offers insights into RNN anomaly detection performance when an event absent in training …


Traffic Safety In Tacoma: A Dual Study On Community Perceptions Of Vision Zero And The Application Of The Safe System Framework, Janeroza W. Matyenyi Jan 2025

Traffic Safety In Tacoma: A Dual Study On Community Perceptions Of Vision Zero And The Application Of The Safe System Framework, Janeroza W. Matyenyi

UNF Graduate Theses and Dissertations

The city of Tacoma adopted Vision Zero in 2020 and is planning to achieve zero traffic deaths and severe injuries by 2035. As part of its outreach plan to engage the local community, the city of Tacoma’s Vision Zero team surveyed the critical issues affecting traffic safety as perceived by road users. One of the Vision Zero strategies is to implement safer speeds across streets by reducing speed limits that are too high. This study aims to analyze the factors influencing the perceptions of speeding and high-speed limits as safety concerns, analyze narratives from respondents on issues affecting traffic safety, …


Rodcast Interaction: A Novel Technique For Dense Virtual Reality Environments, Nevzat U. Demirseren Jan 2025

Rodcast Interaction: A Novel Technique For Dense Virtual Reality Environments, Nevzat U. Demirseren

UNF Graduate Theses and Dissertations

Virtual Reality (VR) technologies continue to grow in popularity and application versatility, yet effective interaction within complex dense environments remains as a critical challenge. In particular, users with low level of VR experience often face decreased accuracy and dissatisfaction selecting occluded objects. A variety of interaction techniques to select and manipulate objects exist, but there is a research gap in understanding what kinds of techniques support users in dense environments. This study evaluates the user performance and preference in such environments. Three interaction techniques are examined in this study: Go-Go Hand, Flower Cone, and a proposed technique called RodCast Interaction. …


Numeric Simulation Of A Realistic Hydrokinetic Turbine In Exposed Ocean Environments, Anneke Neber Jan 2025

Numeric Simulation Of A Realistic Hydrokinetic Turbine In Exposed Ocean Environments, Anneke Neber

Open Access Master's Theses

As renewable energies become increasingly more important, it becomes necessary to tap into new resources, such as energy from tidal or ocean currents. A recent development is the use of hydrokinetic turbines, deployed on floating plat- forms. Numerical modeling can be an important tool to determine the forces acting on the floating platform and the turbine.

In this thesis, a realistic floating hydrokinetic turbine was simulated in OpenFAST. Experimental data and hand calculations, were used to partially verify the simulation. Environmental data at a site was analyzed to determine conditions to run the simulations for different tidal current speeds and …


Emulsion Liquid Membrane (Elm) Technique For Efficient Separation Of Heavy Metals From Acidic Solutions Including Phosphoric Acid: A Review, O. Karai, N. Y. Selem, K. Benabderazak, J. Mendil, H. Mazouz, M. H. Al-Dahhan Jan 2025

Emulsion Liquid Membrane (Elm) Technique For Efficient Separation Of Heavy Metals From Acidic Solutions Including Phosphoric Acid: A Review, O. Karai, N. Y. Selem, K. Benabderazak, J. Mendil, H. Mazouz, M. H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Heavy metal ions in aqueous and acidic solutions pose serious threats to ecosystems. Their effective removal is crucial, and emulsion liquid membrane (ELM) technology offers a promising solution. This review delves into ELM's principles, mechanisms, components, and performance indicators including stability for extracting heavy metals from acidic solutions including phosphoric acid., ELM's stability issues, such as internal phase coalescence, membrane leakage, and swelling, limit its efficiency. Thus, this review paper discusses previous research that analyzed ELM stability and heavy metal extraction efficiency from these acidic solutions. Furthermore, it assesses other techniques like Emulsion Ionic Liquid Membrane (EILM) and Pickering Emulsion …


Enhanced Cholesterol Efflux And Atherosclerosis Regression Via Ceh Gene Delivery Using Galactose-Functionalized Dendrimeric Nanoparticles, Huari Kou, Jing Wang, Paul J. Yannie, Da Huang, William J. Korzun, Genta Kakiyama, Siddhartha S. Ghosh, Hu Yang Jan 2025

Enhanced Cholesterol Efflux And Atherosclerosis Regression Via Ceh Gene Delivery Using Galactose-Functionalized Dendrimeric Nanoparticles, Huari Kou, Jing Wang, Paul J. Yannie, Da Huang, William J. Korzun, Genta Kakiyama, Siddhartha S. Ghosh, Hu Yang

Chemical and Biochemical Engineering Faculty Research & Creative Works

Cholesteryl ester hydrolase (CEH) is a critical enzyme in cholesterol ester hydrolysis, influencing cholesterol metabolism and efflux. This study demonstrates that CEH overexpression promotes free cholesterol efflux from macrophages, thereby reducing the lipid burden in existing atherosclerotic plaques. To enable targeted delivery, galactose-functionalized polyamidoamine (PAMAM) dendrimeric nanoparticles were utilized as nanocarriers for hepatic delivery of the CEH expression vector. The therapeutic potential of CEH plasmid-loaded dendrimeric nanoparticles was evaluated in Ldlr-/- mice. Results showed a significant reduction in total lesion area (21%) and aortic arch lesion area (23%) compared to baseline. Lesion component analysis revealed marked decreases in total cholesterol …


Innovative Air Convection Embankment For Cold/Arctic Region Low-Volume Roads, Hanli Wu, Jenny Liu, Xiong Zhang, Steve Saboundjian Jan 2025

Innovative Air Convection Embankment For Cold/Arctic Region Low-Volume Roads, Hanli Wu, Jenny Liu, Xiong Zhang, Steve Saboundjian

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Roadbed thaw settlement is a unique challenge for the durability of low-volume roads (LVRs) in permafrost regions. Air convection embankment (ACE) is an effective technique that acts as a semi-heat-transfer system to control temperature variation and reduce the thaw depth of subsoil. However, limited by the shortage of the necessary crushed rocks within a short distance, building an ACE in Alaska, U.S., is prohibitively expensive. Previous studies identified the feasibility of using cellular concrete for ACE and determined the optimized thickness of the cellular concrete aggregate interlayer for ACE. However, the economic efficiency and thermal and mechanical performance of the …


Identifying Early Warning Signs Of Construction Labor Shortages, Ahmed Shiha, Islam H. El-Adaway Jan 2025

Identifying Early Warning Signs Of Construction Labor Shortages, Ahmed Shiha, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Construction labor shortages constrain project-level objectives and national development plans. The goal of this study is to utilize the lagged effects of macroeconomic conditions as early warning signs of construction labor shortages. To this end, the authors adopted a methodology, encompassing (1) retrieval of publicly available data and preprocessing of construction labor shortage as the target variable and macroeconomic measures as the explanatory variables, (2) identification of short-term associations between shortages and economic cycles using the Granger causality test, (3) examination of long-term relationships between labor shortages and economic conditions using the Johansen cointegration test, and (4) estimation of the …


Forecasting State-Level Construction Labor Earnings For Enhanced Project Cost Control: An Econometric And Deep-Learning Analysis Of The Leading Economic Indicators, Ahmed Shiha, Islam H. El-Adaway Jan 2025

Forecasting State-Level Construction Labor Earnings For Enhanced Project Cost Control: An Econometric And Deep-Learning Analysis Of The Leading Economic Indicators, Ahmed Shiha, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

As a major input to several work packages, the labor element constitutes a critical component for successful performance of construction projects. Localized labor shortages, fundamental changes in prevailing wage laws, and historical shifts in the unionization rates of construction workers impair the adequate estimation of construction labor costs in diverse labor market dynamics. Meanwhile, existing studies have utilized national-level indicators to study the trends of construction labor costs, but the relationship between the multifaceted local economic factors and state-level construction labor costs remains understudied. This paper fills such a knowledge gap. A three-stage methodology is adopted: (1) data collection of …


Reevaluating The Van’T Hoff And Arrhenius Equations: How Temperature And Pressure Affect Chemical Reaction Thermodynamics, Equilibrium, And Kinetics, Jianmin Wang Jan 2025

Reevaluating The Van’T Hoff And Arrhenius Equations: How Temperature And Pressure Affect Chemical Reaction Thermodynamics, Equilibrium, And Kinetics, Jianmin Wang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The van’t Hoff equation, which is used to calculate the effect of temperature on equilibrium constants, was derived from the Gibbs – Helmholtz equation that relates the molar Gibbs free energy to the molar enthalpy of a chemical reaction. However, the Gibbs – Helmholtz equation was developed for systems that do not consider contributions of Gibbs free energy from chemical species. Consequently, the van’t Hoff equation and the Arrhenius equation derived from it are technically incomplete.

By employing Hess’s law and the appropriate Gibbs free energy equation for chemical reaction systems, this investigation develops theoretical equations to calculate the effects …


Active Phytoextraction Of Toluene Shifts The Microbiome And Enhances Degradation Capacity In Hybrid Poplar, Michael Benisrael, Dasiel Obregon, Philipp Wanner, Jeremy Fernandes, Joel G. Burken, Ramon Aravena, Beth L. Parker, Elizabeth A. Haack, David T. Tsao, Kari E. Dunfield Jan 2025

Active Phytoextraction Of Toluene Shifts The Microbiome And Enhances Degradation Capacity In Hybrid Poplar, Michael Benisrael, Dasiel Obregon, Philipp Wanner, Jeremy Fernandes, Joel G. Burken, Ramon Aravena, Beth L. Parker, Elizabeth A. Haack, David T. Tsao, Kari E. Dunfield

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Hybrid poplars are widely recognized for their effectiveness in remediating subsurface aromatic hydrocarbon contaminants, including benzene, toluene, ethylbenzene, and xylene isomers (BTEX). While BTEX compounds are frequently found in the transpiration streams of poplars at contaminated sites, the microbial dynamics within these trees, particularly in response to hydrocarbon exposure, remain underexplored. This study utilized high-throughput amplicon sequencing to investigate the trunk microbiome in hybrid poplars at a field-scale toluene phytoremediation site. Across the plant growth season (spring to late summer), we observed a significant seasonal increase in bacterial diversity and richness, particularly in trees located in areas with the highest …


Performance And Economic Evaluation Of Asphalt-Based High Friction Surface Treatment (Hfst) Applications, Alireza Roshan, Magdy Abdelrahman Jan 2025

Performance And Economic Evaluation Of Asphalt-Based High Friction Surface Treatment (Hfst) Applications, Alireza Roshan, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

High Friction Surface Treatments (HFSTs) are recognized for enhancing friction between tires and road surfaces, with reduced road accidents being a key benefit. Epoxy-based HFSTs, though widely used, come with challenges like compatibility issues with existing pavements, higher installation and removal costs, and reduced durability tied to substrate quality. Recently, state agencies have increasingly focused on developing asphalt-based alternative binders for HFST applications as highlighted in the National Cooperative Highway Research Program (NCHRP) RFP #NCHRP 10-145. This study introduces asphalt-based HFSTs as an alternative to traditional epoxy-based treatments. Various aggregate types were examined for friction performance and the effect of …


Challenges In Numerical Simulation Of Frost Heave, Antai Dong, Xiong Zhang Jan 2025

Challenges In Numerical Simulation Of Frost Heave, Antai Dong, Xiong Zhang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Frost heave of soil extensively exists in northern regions and poses a significant threat to infrastructure in cold regions. Despite over a century of research, challenges persist in numerically simulating frost heave. This study addresses two key issues: (1) What is the primary driving force for liquid water transfer during the freezing process? (2) How can we correctly represent unfrozen water content? Critical insights are derived from the theoretical analysis of coupled hydrothermal migration during soil freezing processes, followed by a case simulation using COMSOL Multiphysics. It concludes that of the water content gradient, suction gradient, and hydraulic gradient, only …