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Articles 1 - 30 of 171
Full-Text Articles in Civil Engineering
Perception Of Transportation Challenges And Their Influence On Mode Choice In A Small Us City: A Generalized Structural Equation Modeling Approach, Anindya Kishore Debnath, Suman Kumar Mitra
Perception Of Transportation Challenges And Their Influence On Mode Choice In A Small Us City: A Generalized Structural Equation Modeling Approach, Anindya Kishore Debnath, Suman Kumar Mitra
Civil Engineering Faculty Publications and Presentations
This study profiles individuals encountering transportation challenges by analyzing factors influencing their perceptions and how they affect mode choice decisions in Fort Smith, Arkansas. Using primary travel survey data, we estimated a multinomial logit (MNL) within a Generalized Structural Equation Model (GSEM) that controls for residential self-selection and car ownership endogeneity. We find that individuals from low-income households are more likely to perceive transportation challenges, particularly due to a lack of a car and inadequate public transport. Higher household car ownership generally diminishes perceived challenges, except regarding limited bike lanes. Weekend or late-shift workers are more likely to own cars …
Impact Of Equipment Type On Measured Particle Size Of Civil Engineering Materials, Tanner Turben, Tasnimul R. Ferdous, Andrew Braham, Wen Zhang
Impact Of Equipment Type On Measured Particle Size Of Civil Engineering Materials, Tanner Turben, Tasnimul R. Ferdous, Andrew Braham, Wen Zhang
Civil Engineering Faculty Publications and Presentations
Particle size analysis (PSA) captures the size distribution of finely graded materials with particles generally smaller than 1000 microns. Many civil engineering materials do not leverage PSA for material specifications or acceptance despite the insight into material performance and quality gained through understanding the particle size. The objectives of this study are to compare PSA measurement principles by testing 13 civil engineering materials by laser diffraction, Coulter counter, and microscopy. Asphalt emulsions, cementitious materials, sands, clays, and biological samples were selected to represent a wide set of interests and shapes. It was found that between laser diffraction and Coulter counter …
Cytotoxicity And Genotoxicity Of Glyphosate And Roundup Quickpro On Chinese Hamster Ovary Cells, Tasnimul Ferdous, Qingfang He, Wen Zhang
Cytotoxicity And Genotoxicity Of Glyphosate And Roundup Quickpro On Chinese Hamster Ovary Cells, Tasnimul Ferdous, Qingfang He, Wen Zhang
Civil Engineering Faculty Publications and Presentations
Glyphosate and Roundup products have become the most used herbicide worldwide. However, previous bans in Europe and recent reversal have caused confusion over their safety. This study aims to investigate the cytotoxic and genotoxic effects of Roundup QuickPro and its main ingredient glyphosate using Chinese hamster ovary (CHO) cells. Cytotoxicity was calculated by measuring CHO cell viability with 72 h of exposure to each toxicant. Roundup QuickPro exhibited higher cytotoxicity with LC50 of 511.2 mu g/mL than glyphosate's LC50 of 3389 mu g/mL. The recommended application concentration (11,233.7 mu g/mL) of Roundup QuickPro is much higher than the measured LC50, …
Navigating Transportation Barriers: Older Adults’ Familiarity With New Mobility Options And Perceptions Toward Autonomous Vehicles In Arkansas, Arna Nishita Nithila, Suman Kumar Mitra, Michelle Gray, Alishia Juanelle Ferguson, Jennifer D. Webb
Navigating Transportation Barriers: Older Adults’ Familiarity With New Mobility Options And Perceptions Toward Autonomous Vehicles In Arkansas, Arna Nishita Nithila, Suman Kumar Mitra, Michelle Gray, Alishia Juanelle Ferguson, Jennifer D. Webb
Civil Engineering Faculty Publications and Presentations
The objective of this study is to analyze older adults’ familiarity with new transportation options (ride-hailing services, bike-share services, and shared e-scooter services) and their perception towards autonomous vehicles (fully autonomous cars), as well as how transportation barriers influence their familiarity and perceptions, in Arkansas, a predominantly rural state. Data from 775 older adults aged 60 years or older were collected between October 2021 and October 2022. To fulfill the study objective, the study used Latent Class Cluster Analysis to segment older adults into classes based on their familiarity with new transportation options and their perceptions of autonomous vehicles. The …
Highway-Transportation-Asset Criticality Estimation Leveraging Stakeholder Input Through An Analytical Hierarchy Process (Ahp), Kwadwo Amankwah, Sarah Hernandez, Suman Kumar Mitra
Highway-Transportation-Asset Criticality Estimation Leveraging Stakeholder Input Through An Analytical Hierarchy Process (Ahp), Kwadwo Amankwah, Sarah Hernandez, Suman Kumar Mitra
Civil Engineering Faculty Publications and Presentations
Transportation agencies face increasing challenges in identifying and prioritizing which infrastructure assets are most critical to maintain and protect, particularly amid aging networks, limited budgets, and growing threats from climate change and extreme events. However, existing prioritization approaches often lack consistency and fail to adequately incorporate diverse stakeholder perspectives. This study develops a systematic, stakeholder-informed method for ranking transportation assets based on their criticality to the overall transportation system. As a novel approach, we use the analytical hierarchy process (AHP) and present a case study of the applied approach. Six criteria were identified for ranking assets: annual average daily traffic …
Establishing Particle Size Recommendations For Cationic Asphalt Emulsions, Tanner Turben, Pedro Diaz-Romero, Andrew Braham
Establishing Particle Size Recommendations For Cationic Asphalt Emulsions, Tanner Turben, Pedro Diaz-Romero, Andrew Braham
Civil Engineering Faculty Publications and Presentations
Asphalt emulsions are used in flexible pavement maintenance and rehabilitation treatments. Emulsion specifications for material characterization are based on testing methodology dating to the 1930s. Newer test methods, including particle size analysis (PSA) of binder droplets in emulsion, have been explored but not implemented into specifications. The objective of this study is to observe the particle size and performance of cationic slow-setting (CSS) emulsions and establish baseline particle size recommendations for cationic emulsions. Four physical property tests (residue, oversize particles, viscosity, and particle size) and two cold mix asphalt performance tests (indirect tensile strength (IDT) and direct shear test (DST)) …
Workforce Forecasting For State Transportation Agencies: A Machine Learning Approach, Adedolapo Ogungbire, Suman Kumar Mitra
Workforce Forecasting For State Transportation Agencies: A Machine Learning Approach, Adedolapo Ogungbire, Suman Kumar Mitra
Civil Engineering Faculty Publications and Presentations
A decline in the number of construction engineers and inspectors at state transportation agencies (STAs) to manage the ever-increasing lane miles has emphasized the importance of workforce planning in these agencies. Forecasting workforce requirements is crucial for effective planning in any industry or agency. This study developed machine learning (ML) models to estimate the person-hour requirements of STAs at the project level. The Arkansas Department of Transportation (ARDOT) was used as a case study, using its employee and project details data between 2012 and 2021. ML regression models ranging from linear, tree ensembles, kernel-based, and neural network-based models were …
Examining The Impact Of The Covid-19 Pandemic On Older Adults' Activity Participation And Mode Usage In A Rural State: A Case Study Of Arkansas, Arna Nishita Nithila, Suman Kumar Mitra, Alishia Juanelle Ferguson, Michelle Gray, Jennifer D. Webb
Examining The Impact Of The Covid-19 Pandemic On Older Adults' Activity Participation And Mode Usage In A Rural State: A Case Study Of Arkansas, Arna Nishita Nithila, Suman Kumar Mitra, Alishia Juanelle Ferguson, Michelle Gray, Jennifer D. Webb
Civil Engineering Faculty Publications and Presentations
The objective of the study was to investigate the impact of the COVID-19 pandemic on the activity participation and mode usage of older adults residing in Arkansas, a predominantly rural state. Leveraging primary data collected from 832 older adult participants, the study employed Latent Class Analysis (LCA) to capture older adults' heterogeneity in travel behavior and found three distinct classes: Pandemic-affected minimal travelers, Unaffected non-commuter car users, and Unaffected commuter car users, showing different levels of their activity participation, mode usage during the pandemic and varying the pandemic's impact on their trips. To understand these variations in light of the …
A Multi-Method Geophysical Approach For Complex Shallow Landslide Characterization, Mohammadyar Rahimi, Clinton Wood, Meersad Fathizadeh, Salman Rahimi
A Multi-Method Geophysical Approach For Complex Shallow Landslide Characterization, Mohammadyar Rahimi, Clinton Wood, Meersad Fathizadeh, Salman Rahimi
Civil Engineering Faculty Publications and Presentations
This case study demonstrates the value of combining multiple non-invasive geophysical methods to characterize a landslide along Highway 7 near Jasper, Arkansas, USA. Geophysical testing was conducted using Multichannel Analysis of Surface Waves (MASW), Horizontal to Vertical Spectral Ratio (HVSR), and Electrical Resistivity Tomography (ERT), supplemented by select soil borings. The geophysical investigation aimed to provide a high-resolution, near-continuous view of subsurface conditions, including bedrock depth and the location of the groundwater table or highly saturated zones within the slide area. These factors are important contributors to slope instability. The MASW results revealed a highly variable depth to weathered bedrock …
Unlocking Telecommuting Patterns Before, During, And After The Covid-19 Pandemic: An Explainable Ai-Driven Study, Adedolapo Ogungbire, Suman Kumar Mitra
Unlocking Telecommuting Patterns Before, During, And After The Covid-19 Pandemic: An Explainable Ai-Driven Study, Adedolapo Ogungbire, Suman Kumar Mitra
Civil Engineering Faculty Publications and Presentations
The COVID-19 pandemic has instigated a global paradigm shift in employment practices, precipitating a widespread transition to telework. While past events had no long-lasting effect on the continued working conditions of the population, it is unclear what a prolonged need for telecommuting on such a nationwide scale would continue to have on the working population. This study uses an explainable artificial intelligence approach to investigate the changes in those telecommuting across three periods: i) pre-pandemic, ii) pandemic, and iii) post-pandemic periods. Machine learning methods, including decision trees, random forest, extreme gradient boost, naïve Bayes, and artificial neural networks, were developed …
Pinn-Chk: Physics-Informed Neural Network For High-Fidelity Prediction Of Early-Age Cement Hydration Kinetics, Md Asif Rahman, Tianjie Zhang, Yang Lu
Pinn-Chk: Physics-Informed Neural Network For High-Fidelity Prediction Of Early-Age Cement Hydration Kinetics, Md Asif Rahman, Tianjie Zhang, Yang Lu
Civil Engineering Faculty Publications and Presentations
Cement hydration kinetics, characterized by heat generation in early-age concrete, poses a modeling challenge. This work proposes a physics-informed neural network (PINN) named PINN-CHK designed for cement hydration kinetics, to predict early-age temperature rises in cement paste. PINN-CHK leverages data-driven solutions to craft a high-fidelity prediction model, encompassing material properties and maturity functions in cement hydration. Trained on heated cement paste data, it simultaneously fits experimental results and underlying physics, yielding a mesh-free simulation. Incorporating governing partial differential equations (PDEs), and initial and boundary conditions into its loss function, PINN-CHK architecture undergoes rigorous benchmark testing, demonstrating unparalleled predictive accuracy compared …
Creating A Bio-Based Circular Economy From Louisiana Sugarcane Byproducts, G. Aita, D. Bhatnagar, G. O. Bruni, M. Deliberto, G. Eggleston, A. Finger, K. Gravois, M. Isied, W. Judice, K. T. Kasson, I. M. Lima, J. L. Purswell, Mena I. Souliman, E. Terrell, B. S. Tubana, H. L. Waguespack Jr., J. J. Wang, P. M. White Jr.
Creating A Bio-Based Circular Economy From Louisiana Sugarcane Byproducts, G. Aita, D. Bhatnagar, G. O. Bruni, M. Deliberto, G. Eggleston, A. Finger, K. Gravois, M. Isied, W. Judice, K. T. Kasson, I. M. Lima, J. L. Purswell, Mena I. Souliman, E. Terrell, B. S. Tubana, H. L. Waguespack Jr., J. J. Wang, P. M. White Jr.
Civil Engineering Faculty Publications and Presentations
Sugarcane (Saccharum officinarum) is Louisiana's number one row crop. Growing and processing sugarcane produces significant amounts of byproducts, including bagasse, crop residue, molasses, filter-press mud, and boiler fly ash. These products represent an important opportunity to generate value-added and specialty products and enhance sugarcane's sustainability by facilitating a circular economy, where agricultural by-products are reused instead of disposing them (linear economy), in order to reduce resource use and energy demand. Examples of value-added products range from biochar, construction materials, animal feed, biofuels, nanoparticles, and fertilizer. Paramount to the success of the bio-based circular economy is creating useful products that are …
Interdependencies Between Wildfire-Induced Alterations In Soil Properties, Near-Surface Processes, And Geohazards, Farshid Vahedifard, Masood Abdollahi, Ben A. Leshchinsky, Timothy D. Stark, Mojtaba Sadegh, Amir Aghakouchak
Interdependencies Between Wildfire-Induced Alterations In Soil Properties, Near-Surface Processes, And Geohazards, Farshid Vahedifard, Masood Abdollahi, Ben A. Leshchinsky, Timothy D. Stark, Mojtaba Sadegh, Amir Aghakouchak
Civil Engineering Faculty Publications and Presentations
The frequency, severity, and spatial extent of destructive wildfires have increased in several regions globally over the past decades. While direct impacts from wildfires are devastating, the hazardous legacy of wildfires affects nearby communities long after the flames have been extinguished. Post-wildfire soil conditions control the persistence, severity, and timing of cascading geohazards in burned landscapes. The interplay and feedback between geohazards and wildfire-induced changes to soil properties, land cover conditions, and near-surface and surface processes are still poorly understood. Here, we synthesize wildfire-induced processes that can affect the critical attributes of burned soils and their conditioning of subsequent geohazards. …
Post-Fire Hydrologic Analysis: A Tale Of Two Severities, Kendra Fallon, Shawn J. Wheelock, Mojtaba Sadegh, Jennifer L. Pierce, James P. Mcnamara, Megan Cattau, Victor R. Baker
Post-Fire Hydrologic Analysis: A Tale Of Two Severities, Kendra Fallon, Shawn J. Wheelock, Mojtaba Sadegh, Jennifer L. Pierce, James P. Mcnamara, Megan Cattau, Victor R. Baker
Civil Engineering Faculty Publications and Presentations
Addressing post-fire impacts largely depends on burn “severity.” A singular severity classification that encompasses the holistic effects of fire on all ecosystem processes does not currently exist. Lumping vegetation burn severity and soil burn severity into one metric, or using them interchangeably, can induce large inaccuracies and uncertainties in the intended ecosystem response to forcing. Often, burn “severity” reflects fire impacts on vegetation, which can be measured through remote sensing. Vegetation burn severity is likely more apropos for ecological research, whereas soil burn severity is more relevant for hydrological analyses. This paper reviews different remotely sensed vegetation severity products currently …
Developing A Model To Predict Bleeding Areas In Asphalt Pavements Using Artificial Neural Network, Rami Khalifah, Mena I. Souliman, Pratik Lama, Omar Elbagalati
Developing A Model To Predict Bleeding Areas In Asphalt Pavements Using Artificial Neural Network, Rami Khalifah, Mena I. Souliman, Pratik Lama, Omar Elbagalati
Civil Engineering Faculty Publications and Presentations
Bleeding can have a negative effect on the performance of a pavement, as the layer of asphalt on the surface can become slippery, reduce skid resistance, and lead to premature wear and tear. Therefore, predicting the bleeding area in asphalt pavements will help in maintaining better pavements, increasing the safety of the drivers, and delivering timely maintenance. The aim of the study is to develop a model using a highly sophisticated analysis tool called an artificial neural network (ANN) to predict the bleeding areas in asphalt pavements as output, with one hidden layer and several neurons and using several independent …
Application Of Machine Learning Models To Predict Driver Left Turn Destination Lane Choice Behavior At Urban Intersections, Mohammed Moinuddin, Logan Proffer, Matthew Vechione, Aaditya Khanal
Application Of Machine Learning Models To Predict Driver Left Turn Destination Lane Choice Behavior At Urban Intersections, Mohammed Moinuddin, Logan Proffer, Matthew Vechione, Aaditya Khanal
Civil Engineering Faculty Publications and Presentations
When there are multiple lanes to choose from downstream of a turning movement, drivers should choose the innermost lane so that drivers at other approaches of the intersection may make concurrent turning movements in the outermost lane(s). However, human drivers do not always choose the innermost lane, which could lead to crashes with other vehicles. Therefore, predicting human driver behaviors is vital in reducing crashes, as the need to share the roadways with automated vehicles (AVs) continues to grow. In this research, various machine learning models have been used to predict the left turn destination lane choice of human-driven vehicles …
Statistical And Deep Learning Models For Reference Evapotranspiration Time Series Forecasting: A Comparison Of Accuracy, Complexity, And Data Efficiency, Arman Ahmadi, Andre Daccache, Mojtaba Sadegh, Richard L. Snyder
Statistical And Deep Learning Models For Reference Evapotranspiration Time Series Forecasting: A Comparison Of Accuracy, Complexity, And Data Efficiency, Arman Ahmadi, Andre Daccache, Mojtaba Sadegh, Richard L. Snyder
Civil Engineering Faculty Publications and Presentations
Reference evapotranspiration (ETo) is an essential variable in agricultural water resources management and irrigation scheduling. An accurate and reliable forecast of ETo facilitates effective decision-making in agriculture. Although numerous studies assessed various methodologies for ETo forecasting, an in-depth multi-dimensional analysis evaluating different aspects of these methodologies is missing. This study systematically evaluates the complexity, computational cost, data efficiency, and accuracy of ten models that have been used or could potentially be used for ETo forecasting. These models range from well-known statistical forecasting models like seasonal autoregressive integrated moving average (SARIMA) to state-of-the-art deep learning (DL) algorithms like temporal fusion transformer …
Social Vulnerability Of The People Exposed To Wildfires In U.S. West Coast States, Arash Modaresi Rad, John T. Abatzoglou, Erica Fleishman, Miranda H. Mockrin, Volker C. Radeloff, Yavar Pourmohamad, Megan Cattau, J. Michael Johnson, Philip Higuera, Nicholas J. Nauslar, Mojtaba Sadegh
Social Vulnerability Of The People Exposed To Wildfires In U.S. West Coast States, Arash Modaresi Rad, John T. Abatzoglou, Erica Fleishman, Miranda H. Mockrin, Volker C. Radeloff, Yavar Pourmohamad, Megan Cattau, J. Michael Johnson, Philip Higuera, Nicholas J. Nauslar, Mojtaba Sadegh
Civil Engineering Faculty Publications and Presentations
Understanding of the vulnerability of populations exposed to wildfires is limited. We used an index from the U.S. Centers for Disease Control and Prevention to assess the social vulnerability of populations exposed to wildfire from 2000–2021 in California, Oregon, and Washington, which accounted for 90% of exposures in the western United States. The number of people exposed to fire from 2000–2010 to 2011–2021 increased substantially, with the largest increase, nearly 250%, for people with high social vulnerability. In Oregon and Washington, a higher percentage of exposed people were highly vulnerable (>40%) than in California (~8%). Increased social vulnerability of …
Shrinkage And Consolidation Characteristics Of Chitosan-Amended Soft Soil: A Sustainable Alternate Landfill Liner Material, Romana Mariyam Rasheed, Arif Ali Baig Moghal, Sai Sampreeth Reddy Jannepally, Ateekh Ur Rehman, Bhaskar C. S. Chittoori
Shrinkage And Consolidation Characteristics Of Chitosan-Amended Soft Soil: A Sustainable Alternate Landfill Liner Material, Romana Mariyam Rasheed, Arif Ali Baig Moghal, Sai Sampreeth Reddy Jannepally, Ateekh Ur Rehman, Bhaskar C. S. Chittoori
Civil Engineering Faculty Publications and Presentations
Kuttanad is a region that lies in the southwest part of Kerala, India, and possesses soft soil, which imposes constraints on many civil engineering applications owing to low shear strength and high compressibility. Chemical stabilizers such as cement and lime have been extensively utilized in the past to address compressibility issues. However, future civilizations will be extremely dependent on the development of sustainable materials and practices such as the use of bio-enzymes, calcite precipitation methods, and biological materials as a result of escalating environmental concerns due to carbon emissions of conventional stabilizers. One such alternative is the utilization of biopolymers. …
Machine Learning-Enabled Regional Multi-Hazards Risk Assessment Considering Social Vulnerability, Tianjie Zhang, Donglei Wang, Yang Lu
Machine Learning-Enabled Regional Multi-Hazards Risk Assessment Considering Social Vulnerability, Tianjie Zhang, Donglei Wang, Yang Lu
Civil Engineering Faculty Publications and Presentations
The regional multi-hazards risk assessment poses difficulties due to data access challenges, and the potential interactions between multi-hazards and social vulnerability. For better natural hazards risk perception and preparedness, it is important to study the nature-hazards risk distribution in different areas, specifically a major priority in the areas of high hazards level and social vulnerability. We propose a multi-hazards risk assessment method which considers social vulnerability into the analyzing and utilize machine learning-enabled models to solve this issue. The proposed methodology integrates three aspects as follows: (1) characterization and mapping of multi-hazards (Flooding, Wildfires, and Seismic) using five machine learning …
Uncovering The Spatio-Temporal Impact Of The Covid-19 Pandemic On Shared E-Scooter Usage: A Spatial Panel Model, Farzana Mehzabin Tuli, Arna Nishita Nithila, Suman Mitra
Uncovering The Spatio-Temporal Impact Of The Covid-19 Pandemic On Shared E-Scooter Usage: A Spatial Panel Model, Farzana Mehzabin Tuli, Arna Nishita Nithila, Suman Mitra
Civil Engineering Faculty Publications and Presentations
This study examines the spatio-temporal effects of the COVID-19 pandemic on shared e-scooter usage by leveraging two years (2019 and 2020) of daily shared micromobility data from Austin, Texas. We employed a series of random effects spatial-autoregressive model with a spatially autocorrelated error (SAC) to examine the differences and similarities in determinants of e-scooter usage during regular and pandemic periods and to identify factors contributing to the changes in e-scooter use during the Pandemic. Model results provided strong evidence of spatial autocorrelation in the e-scooter trip data and found a spatial negative spillover effect in the 2020 model. The key …
Improved Burned Area Mapping Using Monotemporal Landsat-9 Imagery And Convolutional Shift-Transformer, Seyd Teymoor Seydi, Mojtaba Sadegh
Improved Burned Area Mapping Using Monotemporal Landsat-9 Imagery And Convolutional Shift-Transformer, Seyd Teymoor Seydi, Mojtaba Sadegh
Civil Engineering Faculty Publications and Presentations
Satellite imagery, specifically Landsat, have been widely used for mapping and monitoring wildfire burned areas. The new Landsat-9 satellite – with higher radiometric resolution compared to its predecessors, and improved temporal resolution when combined with Landsat-8 (∼8 days) – enables a wide range of applications, particularly burned area mapping (BAM). We propose a novel deep learning BAM model that leverages the strengths of the convolutional layers for deep feature generation from Landsat-9 imagery and shift-transformer block for burned area classification. The performance of the model is evaluated in five large fire case studies across the globe. BAM results are also …
Port-Of-Entry Simulation Model For Potential Wait Time Reduction And Air Quality Improvement: A Case Study At The Gateway International Bridge In Brownsville, Texas, Usa, Benjamin Stewart, Hiram Moya, Amit U. Raysoni, Esmeralda Mendez, Matthew Vechione
Port-Of-Entry Simulation Model For Potential Wait Time Reduction And Air Quality Improvement: A Case Study At The Gateway International Bridge In Brownsville, Texas, Usa, Benjamin Stewart, Hiram Moya, Amit U. Raysoni, Esmeralda Mendez, Matthew Vechione
Civil Engineering Faculty Publications and Presentations
The mathematical study known as queueing theory has recently become a major point of interest for many government agencies and private companies for increasing efficiency. One such application is vehicle queueing at an international port-of-entry (POE). When queueing, fumes from idling vehicles negatively affect the overall health and well-being of the community, especially the U.S. Customs and Border Protection (CBP) agents that work at the POEs. As such, there is a need to analyze and optimize the border crossing queuing operations to minimize wait times and number of vehicles in the queue and, thus, reduce the vehicle emissions. For this …
Application Of Connected Vehicle Data To Assess Safety On Roadways, Mandar Khanal, Nathaniel Edelmann
Application Of Connected Vehicle Data To Assess Safety On Roadways, Mandar Khanal, Nathaniel Edelmann
Civil Engineering Faculty Publications and Presentations
Using surrogate safety measures is a common method to assess safety on roadways. Surrogate safety measures allow for proactive safety analysis; the analysis is performed prior to crashes occurring. This allows for safety improvements to be implemented proactively to prevent crashes and the associated injuries and property damage. Existing surrogate safety measures primarily rely on data generated by microsimulations, but the advent of connected vehicles has allowed for the incorporation of data from actual cars into safety analysis with surrogate safety measures. In this study, commercially available connected vehicle data are used to develop crash prediction models for crashes at …
Development Of Prediction Model For Rutting Depth Using Artificial Neural Network, Rami Khalifah, Mena I. Souliman, Mawiya Bin Mukarram Bajusair
Development Of Prediction Model For Rutting Depth Using Artificial Neural Network, Rami Khalifah, Mena I. Souliman, Mawiya Bin Mukarram Bajusair
Civil Engineering Faculty Publications and Presentations
One of the most common pavement distresses in flexible pavement is rutting, which is mainly caused by heavy wheel load and various other factors. The prediction of rutting depth is important for safe travel and the long-term performance of pavements. Factors that are considered in this paper for the prediction of rut depth are Temperature, Equivalent Single Axle Load, Resilient modulus, and Thickness of hot mixed asphalt. The input data for all factors are collected from the Long-Term Pavement Performance Information Management System for the state of Texas. Regression analysis is performed for dependent and independent variables to obtain the …
Studying The Compressive, Tensile And Flexural Properties Of Binary And Ternary Fiber-Reinforced Uhpc Using Experimental, Numerical And Multi-Target Digital Image Correlation Methods, Behrooz Dadmand, Hamed Sadaghian, Sahand Khalilzadehtabrizi, Masoud Pourbaba, Milad Shirdel, Amir Mirmiran
Studying The Compressive, Tensile And Flexural Properties Of Binary And Ternary Fiber-Reinforced Uhpc Using Experimental, Numerical And Multi-Target Digital Image Correlation Methods, Behrooz Dadmand, Hamed Sadaghian, Sahand Khalilzadehtabrizi, Masoud Pourbaba, Milad Shirdel, Amir Mirmiran
Civil Engineering Faculty Publications and Presentations
Compressive, tensile, and flexural properties of ultra-high-performance concrete (UHPFRC) specimens were studied in this research. Binary and ternary combinations of micro steel (MS), round crimped (RC), crimped (C), hooked-end (H), and polypropylene (PP) fibers were used in overall ratios of 2% by volume of concrete. For this purpose, 100 x 200 mm cylindrical specimens, dog-bone specimens (length: 330 mm, width: 80 mm, thickness: 40 mm), and prismatic beams with a dimension of 100 x 100 x 500 mm (clear span: 450 mm) were cast and tested under compressive, tensile, and four-point bending tests (4PBT). A digital image correlation (DIC)-based method …
Structural Health Assessment Of Pavement Sections In The Southern Central United States Using Fwd Parameters, Nitish R. Bastola, Mena Souliman, Samer Dessouky, Raja Daoud
Structural Health Assessment Of Pavement Sections In The Southern Central United States Using Fwd Parameters, Nitish R. Bastola, Mena Souliman, Samer Dessouky, Raja Daoud
Civil Engineering Faculty Publications and Presentations
Various Departments of Transportation in the South-Central States and elsewhere have made extensive use of the Non-Destructive Testing (NDT) surface deflection bowl data. The falling weight deflectometer (FWD) test is a popular NDT-based test used by transportation authorities to evaluate the performance of flexible pavement. Nevertheless, it is rare to develop a method for evaluating pavement sections using FWD data from all sensors. There is a constant demand for DOTs and highway agencies to have a streamlined approach that can be applied directly to their databases. This research focuses on extending and verifying the concept of previously published area ratio …
The Impact Of Biofilms And Dissolved Organic Matter On The Transport Of Nanoparticles In Field-Scale Streams, Junyeol Kim, Kevin R. Roche, Diogo Bolster, Kyle Doudrick
The Impact Of Biofilms And Dissolved Organic Matter On The Transport Of Nanoparticles In Field-Scale Streams, Junyeol Kim, Kevin R. Roche, Diogo Bolster, Kyle Doudrick
Civil Engineering Faculty Publications and Presentations
The fate and transport of nanoparticles (NPs) in streams is critical for understanding their overall environmental impact. Using a unique field-scale stream at the Notre Dame-Linked Experimental Ecosystem Facility, we investigated the impact of biofilms and the presence of dissolved organic matter (DOM) on the transport of titanium dioxide (TiO2) NPs. Experimental breakthrough curves were analyzed using temporal moments and fit using a mobile-immobile model. The presence of biofilms in the stream severely reduced the transport of the TiO2 NPs, but this was mitigated by the presence of DOM. Under minimal biofilm conditions, the presence of DOM …
Maximum Grid Spacing Effect On Peak Pressure Computation Using Inflow Turbulence Generators, Zahra Mansouri, Rathinam Panneer Selvam, Arindam Gan Chowdhury
Maximum Grid Spacing Effect On Peak Pressure Computation Using Inflow Turbulence Generators, Zahra Mansouri, Rathinam Panneer Selvam, Arindam Gan Chowdhury
Civil Engineering Faculty Publications and Presentations
The peak pressures are computed using computational fluid dynamics (CFD) with the synthetic inflow turbulence generator and compared with 1:6 scale Texas Tech University (TTU) wind tunnel measurements. The inflow turbulence is calculated using the Consistent Discrete Random Flow Generation Method (CDRFG) method. The maximum and minimum frequencies from the field or experimental measurements as input to the inflow turbulence generator without considering the largest grid spacing used in the CFD model leads to high pressure error. For one case, more than 100% error in peak pressure results is observed. In addition, spurious pressures are observed at the building location …
Anthropogenic Stressors Compound Climate Impacts On Inland Lake Dynamics: The Case Of Hamun Lakes, Arash Modaresi Rad, Jason Kreitler, John T. Abatzoglou, Kendra Fallon, Kevin R. Roche, Mojtaba Sadegh
Anthropogenic Stressors Compound Climate Impacts On Inland Lake Dynamics: The Case Of Hamun Lakes, Arash Modaresi Rad, Jason Kreitler, John T. Abatzoglou, Kendra Fallon, Kevin R. Roche, Mojtaba Sadegh
Civil Engineering Faculty Publications and Presentations
Inland lakes face unprecedented pressures from climatic and anthropogenic stresses, causing their recession and desiccation globally. Climate change is increasingly blamed for such environmental degradation, but in many regions, direct anthropogenic pressures compound, and sometimes supersede, climatic factors. This study examined a human-environmental system – the terminal Hamun Lakes on the Iran-Afghanistan border – that embodies amplified challenges of inland waters. Satellite and climatic data from 1984 to 2019 were fused, which documented that the Hamun Lakes lost 89% of their surface area between 1999 and 2001 (3809 km2 versus 410 km2), coincident with a basin-wide, multi-year …