Engineering Commons^™

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 …

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 …

Comparing The Stiffness Of Cold In-Place Recycled Asphalt Pavement To Hot Mix Asphalt: Determining The Reproducibility Of The Stiffness Rebound Test, Tanner Turben

Civil Engineering Undergraduate Honors Theses

The Stiffness Raveling Mechanism Test (SRMT) was originally developed as an indirect measure of pavement stiffness to determine a pavement’s tendency to ravel, a type of damage. Regarding rehabilitation of existing roadways by Full Depth Reclamation (FDR) Cold In-Place Recycling (CIR), concern of field repeatability was expressed (Hill & Braham, 2016).

An analysis of lab-compacted samples of CIR and Hot Mix Asphalt (HMA) was performed to determine if the results could be reproduced between CIR and HMA. Additionally, the experiment observed the effects of percent air voids, temperature, and moisture conditioning on CIR and HMA. Three samples were prepared for …

Evaluating Fatigue Resistance Of The Fiber-Reinforced 100% Rap Content Asphalt Mixture Rejuvenated With Waste Vegetable Oil, Farshad Haddadi

FIU Electronic Theses and Dissertations

The use of reclaimed asphalt pavement (RAP) in the pavement industry continues to grow as it is an economically and environmentally beneficial proposition. However, a survey conducted by the Federal Highway Administration shows that the average RAP content in the hot mix used in the United States is only 10–20%, even though specifications allow up to 30%. The primary performance drawback of using a high percentage RAP is cracking distresses. This research is an effort to investigate whether basalt fiber and waste vegetable oil (WO) can improve the low and intermediate temperature cracking behavior of a 100% RAP mixture. Bending …