A Deep Learning Tool For The Assessment Of Pavement Smoothness And Aggregate Segregation During Construction,
2022
Louisiana State University
A Deep Learning Tool For The Assessment Of Pavement Smoothness And Aggregate Segregation During Construction, Mostafa Elseifi, Ramchandra Paudel, Md Tanvir Ahmed Sarkar, Hossam Abohamer, Nirmal Dhakal
Data
Pavement construction monitoring and quality assurance (QA) practices are mostly based on costly, discrete, and destructive methods. Most quality assurance programs are based on pavement construction procedures encompassing in-situ coring for layer thickness determination, density measurements, laboratory testing to measure volumetric properties, and smoothness measurements in case of the availability of a profiler. The main objective of this study was to develop a machine learning-based classifier for predicting pavement roughness and aggregate segregation based on digital image analysis, image recognition, and deep learning machine models. The developed Convolution Neural Networks (CNN) models were trained, tested, and validated using 600-pavement surface …
Using Rice Husk Ash (Rha) As Stabilizing Agent For Problematic Subgrade Soils And Embankments,
2022
Arkansas State University
Using Rice Husk Ash (Rha) As Stabilizing Agent For Problematic Subgrade Soils And Embankments, Zahid Hossain, Rifat Bulut, Fares Tarhuni, Hussein Al-Dakheeli
Data
Arkansas produces the most of the rice in the United States. About 20% of poddy is rice husk (RH), which is burnt under controlled conditions to produce rice rusk ash (RHA). The RHA is considered an environmental hazard and a significant challenge for rice millers. However, RHA is rich in pozzolanic material, which is mainly silica. In this study, RHA is used to stabilize poor soils. Another commonly used stabilizer, hydrated lime (HL), has also been evaluated for comparison purposes. Thus, this study aimed to determine the optimum percentages of RHA, HL, or a combination of these two agents by …
Performance Monitoring Leveraging Advanced Ai Technique With Cnn,
2022
University of Texas at Arlington
Performance Monitoring Leveraging Advanced Ai Technique With Cnn, Suyun Ham Ph.D, Stefan Romanoschi, Yin Chao Wu, Dafnik Saril Kumar David, Sanggoo Kang
Publications
The main goal of this project is to study and develop a reliable nondestructive testing (NDT)-based structural performance prediction model framework leveraging the advanced machine learning convolutional neural network (CNN) technique and rapid crack evaluation system. There are two steps of application CNN technique in this project: 1) the first step is to identify delamination, noise, and the unexpected signal produced by the existing damage identification algorithm to improve the accuracy of NDT results. The input image or training data of NDT data for CNN is comprehensively studied with several features, such as the duration of the signal, the starting …
Increasing Bridge Durability And Service Life With Lidar Enhanced Unmanned Aerial Systems (Uas),
2022
University of New Mexico
Increasing Bridge Durability And Service Life With Lidar Enhanced Unmanned Aerial Systems (Uas), Fernando Moreu, Mahsa Sanei, Chris Lippitt
Data
Bridge construction inspections require quantitative measurements and location information. The conventional approach is visual inspection, which in general, is rather time-consuming, expensive due to traffic closure, subjective, and needs special access. Therefore an automated rebar layout detection algorithm was developed to quickly extract quantitative rebar layout information from the LiDAR data. This systematic method can automatically cluster the bridge elements from a 3D point cloud by using LiDAR-equipped UAS data collection and unsupervised machine learning techniques. A new automated inspection system using a LIDAR-equipped UAS can eventually if developed and tested be more reliable as well as less expensive. In …
Performance Monitoring Leveraging Advanced Ai Technique With Cnn,
2022
University of Texas at Arlington
Performance Monitoring Leveraging Advanced Ai Technique With Cnn, Suyun Ham Ph.D, Stefan Romanoschi, Yin Chao Wu, Dafnik Saril Kumar David, Sanggoo Kang
Data
The main goal of this project is to study and develop a reliable nondestructive testing (NDT)-based structural performance prediction model framework leveraging the advanced machine learning convolutional neural network (CNN) technique and rapid crack evaluation system. There are two steps of application CNN technique in this project: 1) the first step is to identify delamination, noise, and the unexpected signal produced by the existing damage identification algorithm to improve the accuracy of NDT results. The input image or training data of NDT data for CNN is comprehensively studied with several features, such as the duration of the signal, the starting …
Development Of Distress Index Prediction Models For Rehabilitation Treatments In Louisiana Using Advanced Machine Learning Techniques,
2022
Louisiana State University and Agricultural and Mechanical College
Development Of Distress Index Prediction Models For Rehabilitation Treatments In Louisiana Using Advanced Machine Learning Techniques, Momen R. Mousa, Marwa Hassan
Data
Performance prediction models are used by state agencies to predict future trends in distress indices, hence, determining the required maintenance and/or rehabilitation treatment as well as the deterioration rate and remaining pavement service life. However, most of these models are based on a limited number of parameters and cannot predict the performance distress indices reliably. Such limitation resulted in having, most of the time, a maximum prediction period of five years. As a solution and coping with the ever-increasing size of pavement data, machine learning techniques have become a promising alternative. The objective of this study was to develop a …
Covid-19 And Traffic Safety: Exploring Exposure, Crash Frequency And Severity, And Roadway And Network Design,
2022
University of New Mexico
Covid-19 And Traffic Safety: Exploring Exposure, Crash Frequency And Severity, And Roadway And Network Design, Nicholas N. Ferenchak Ph.D
Publications
Early COVID-19 lockdowns in the first half of 2020 largely kept people at home, thereby reducing motor vehicle traffic levels. Theoretically, reduced traffic exposure should have resulted in reduced motor vehicle crashes. However, a variety of factors may have complicated this relationship. In order to better understand the impact of COVID-19 lockdowns on traffic safety outcomes, we explore fatalities, injuries, and total crashes before and during the lockdowns on both the national and state levels. We provide descriptive statistics and create negative binomial regressions exploring the role of vehicle, user, and built environment factors on traffic safety outcomes. Findings suggest …
Covid-19 And Traffic Safety: Exploring Exposure, Crash Frequency And Severity, And Roadway And Network Design,
2022
University of New Mexico
Covid-19 And Traffic Safety: Exploring Exposure, Crash Frequency And Severity, And Roadway And Network Design, Nicholas N. Ferenchak Ph.D
Data
Early COVID-19 lockdowns in the first half of 2020 largely kept people at home, thereby reducing motor vehicle traffic levels. Theoretically, reduced traffic exposure should have resulted in reduced motor vehicle crashes. However, a variety of factors may have complicated this relationship. In order to better understand the impact of COVID-19 lockdowns on traffic safety outcomes, we explore fatalities, injuries, and total crashes before and during the lockdowns on both the national and state levels. We provide descriptive statistics and create negative binomial regressions exploring the role of vehicle, user, and built environment factors on traffic safety outcomes. Findings suggest …
Increasing Bridge Durability And Service Life With Lidar Enhanced Unmanned Aerial Systems (Uas),
2022
University of New Mexico
Increasing Bridge Durability And Service Life With Lidar Enhanced Unmanned Aerial Systems (Uas), Fernando Moreu, Mahsa Sanei, Chris Lippitt
Publications
Bridge construction inspections require quantitative measurements and location information. The conventional approach is visual inspection, which in general, is rather time-consuming, expensive due to traffic closure, subjective, and needs special access. Therefore an automated rebar layout detection algorithm was developed to quickly extract quantitative rebar layout information from the LiDAR data. This systematic method can automatically cluster the bridge elements from a 3D point cloud by using LiDAR-equipped UAS data collection and unsupervised machine learning techniques. A new automated inspection system using a LIDAR-equipped UAS can eventually if developed and tested be more reliable as well as less expensive. In …
Krs And Kar Review Of Models As A Legal Contract Document,
2022
University of Kentucky
Krs And Kar Review Of Models As A Legal Contract Document, Bryan Gibson, Pam Clay-Young, Rachel Catchings, Chris Van Dyke
Kentucky Transportation Center Research Report
State departments of transportation (DOTs) are expanding the use of electronic engineering data (EED) throughout highway projects — from design and construction through asset management. Included under the umbrella of EED are technologies such as building information modelling (BIM), digital terrain models (DTMs), and 3D models and plan sets. The Kentucky Transportation Cabinet’s (KYTC) Digital Project Delivery (DPD) Initiative is spearheading the transition to EED in the state. While digital delivery promises to streamline project development and management it does not come without hurdles. This report discusses methods for agency wide implementation of EED and highlights best practices for managing, …
Effectiveness Assessment Of E-Ticketing Technology In Construction Of Transportation Projects,
2022
Louisiana State University
Effectiveness Assessment Of E-Ticketing Technology In Construction Of Transportation Projects, Sharareh Kermanshachi, Karthik Subramanya
Publications
The construction of highway infrastructure has devoted significant resources towards e-Construction to reduce the paperwork and automate the tasks in daily operations. Electronic Ticketing (e-Ticketing) is one such component of e-Construction that aids in the digital transfer of material tickets such as asphalt and concrete which accounts for more than fifty per cent of construction costs. Despite the benefits of e-Ticketing, many state departments and agencies are unwilling to transition into this technology. No studies have identified the cause of the delay in the implementation process, developed a framework to comprehend the platform's full potential, quantified savings, and suggested strategies …
Influence Of Specimen Geometry And Anisotropy On Dynamic Modulus Of Asphalt Mixes In South Carolina,
2022
Clemson University
Influence Of Specimen Geometry And Anisotropy On Dynamic Modulus Of Asphalt Mixes In South Carolina, Srinivasan Nagarajan
All Dissertations
The objective of this study was to characterize the variability of dynamic modulus of asphalt mixes in South Carolina on the basis of geometry and anisotropy. High priority mixes Surface Type B, and C; Intermediate Type B and C and Base Type A from three different days of production were collected from seven different contractors each having a different aggregate source and the dynamic modulus was measured using the Asphalt Mixture Performance Tester (AMPT) at temperatures of 40, 70, 100 and 130℉ (4.4, 21.1, 37.8, and 54.4℃) and at frequencies of 25, 10, 5, 1, 0.5, and 0.1 Hz. One-way …
Development Of Distress Index Prediction Models For Rehabilitation Treatments In Louisiana Using Advanced Machine Learning Techniques,
2022
Louisiana State University and Agricultural and Mechanical College
Development Of Distress Index Prediction Models For Rehabilitation Treatments In Louisiana Using Advanced Machine Learning Techniques, Momen R. Mousa, Marwa Hassan
Publications
Performance prediction models are used by state agencies to predict future trends in distress indices, hence, determining the required maintenance and/or rehabilitation treatment as well as the deterioration rate and remaining pavement service life. However, most of these models are based on a limited number of parameters and cannot predict the performance distress indices reliably. Such limitation resulted in having, most of the time, a maximum prediction period of five years. As a solution and coping with the ever-increasing size of pavement data, machine learning techniques have become a promising alternative. The objective of this study was to develop a …
Using Rice Husk Ash (Rha) As Stabilizing Agent For Problematic Subgrade Soils And Embankments,
2022
Arkansas State University
Using Rice Husk Ash (Rha) As Stabilizing Agent For Problematic Subgrade Soils And Embankments, Zahid Hossain, Rifat Bulut, Fares Tarhuni, Hussein Al-Dakheeli
Publications
Arkansas produces the most of the rice in the United States. About 20% of poddy is rice husk (RH), which is burnt under controlled conditions to produce rice rusk ash (RHA). The RHA is considered an environmental hazard and a significant challenge for rice millers. However, RHA is rich in pozzolanic material, which is mainly silica. In this study, RHA is used to stabilize poor soils. Another commonly used stabilizer, hydrated lime (HL), has also been evaluated for comparison purposes. Thus, this study aimed to determine the optimum percentages of RHA, HL, or a combination of these two agents by …
A Deep Learning Tool For The Assessment Of Pavement Smoothness And Aggregate Segregation During Construction,
2022
Louisiana State University
A Deep Learning Tool For The Assessment Of Pavement Smoothness And Aggregate Segregation During Construction, Mostafa Elseifi, Ramchandra Paudel, Md Tanvir Ahmed Sarkar, Hossam Abohamer, Nirmal Dhakal
Publications
Pavement construction monitoring and quality assurance (QA) practices are mostly based on costly, discrete, and destructive methods. Most quality assurance programs are based on pavement construction procedures encompassing in-situ coring for layer thickness determination, density measurements, laboratory testing to measure volumetric properties, and smoothness measurements in case of the availability of a profiler. The main objective of this study was to develop a machine learning-based classifier for predicting pavement roughness and aggregate segregation based on digital image analysis, image recognition, and deep learning machine models. The developed Convolution Neural Networks (CNN) models were trained, tested, and validated using 600-pavement surface …
Crack Control And Bond Performance Of Alternative Coated Reinforcements In Concrete,
2022
Clemson University
Crack Control And Bond Performance Of Alternative Coated Reinforcements In Concrete, Sachin Sreedhara
All Dissertations
Concrete cracking in structures is a ubiquitous problem which can lead to the deterioration of the structure. Other than affecting the strength aspect of a structure, cracking impacts the serviceability criteria as well. Although cracking phenomenon in any structure is highly inevitable, it has to be minimized in order to maintain a structure’s life effectively. Cracking in reinforced concrete structures is related to the bond strength developed between the bar and the concrete. It also depends on an ability of the bar to resist the stresses due to shrinkage to minimize the crack. Another important aspect is the resistance offered …
Optimal Scheduling Of Connected And Autonomous Vehicles At A Reservation-Based Intersection.,
2022
University of Louisville
Optimal Scheduling Of Connected And Autonomous Vehicles At A Reservation-Based Intersection., Muting Ma
Electronic Theses and Dissertations
Reservation-based intersection control has been evaluated with better performance over traditional signal controls in terms of intersection safety, efficiency, and emission. Controlling connected and autonomous vehicles (CAVs) at a reservation-based intersection in terms of improving intersection efficiency is performed via two factors: trajectory (speed profile) and arrival time of CAVs at the intersection. In an early stage of the reservation-based intersection control, an intersection controller at the intersection may fail to find a feasible solution for both the trajectory and arrival time for a CAV at a certain planning horizon. Leveraging a deeper understanding of the control problem, reservation-based intersection …
Autonomous Vehicles On The Smart Roads: Challenges And Potentials,
2022
Kennesaw State University
Autonomous Vehicles On The Smart Roads: Challenges And Potentials, Laura Cristancho, Baleki Campbell, Mahyar Amirgholy
The Kennesaw Journal of Undergraduate Research
Self-driving vehicles and smart roads are not new concepts. These ideas have been discussed for many years but for much of this time, the required technology was not available to make them a reality. Just recently has our technology caught up to our ideas and we are beginning to see progress towards the realization of the automated highway system. As the transition to a complete automated system is still in progress, this leaves many questions that still need to be answered as well as allowing for novel solutions to be presented. Using modern research papers to formulate a sound basis …
Causes Of Cement Concrete Pavement Diseases In High-Cold And High-Altitude Areas And Progress In Repairing Techniques,
2022
Qinghai Communications Technical College
Causes Of Cement Concrete Pavement Diseases In High-Cold And High-Altitude Areas And Progress In Repairing Techniques, Tiejun Hou
International Conference on Durability of Concrete Structures
The climatic characteristics of high-cold and high-altitude areas are low temperature, large temperature differences, and strong ultraviolet radiation. This paper analyzes the causes of cement concrete pavement diseases in high-cold and high-altitude areas and summarizes the common disease types of cement concrete pavements in high-cold and high-altitude areas. Moreover, new repair techniques to improve the maintenance quality of cement concrete pavements in high-cold and high-altitude areas are introduced.
Wastewater-Derived Ammonia For A Green Transportation Fuel,
2022
California State University, Fresno
Wastewater-Derived Ammonia For A Green Transportation Fuel, Joseph Kalman, Maryam Haddad
Mineta Transportation Institute
The energy-water nexus (i.e., availability of potable water and clean energy) is among the most important problems currently facing society. Ammonia is a carbon-free fuel that has the potential to reduce the carbon footprint in combustion related vehicles. However, ammonia production processes typically have their own carbon footprint and do not necessarily come from sustainable sources. This research examines wastewater filtration processes to harvest ammonia for transportation processes. The research team studied mock wastewater solutions and was able to achieve ammonia concentrations above 80%(nanofiltration) and 90% (reverse osmosis). The research team also investigated the influence of transmembrane pressure and flow …
