Author: sshao45

THE EFFECT OF CLUSTERING OF RECLAIMED ASPHALT PAVEMENT (RAP) PARTICLES ON RUTTING PERFORMANCE OF ASPHALT MIXTURES CONTAINING RAP

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PI: Junan Shen

Co-PI(s): Myung Jeong, Sungun Kim, and Xiaoming Yang

Institution(s): Georgia Southern University

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Abstract

Reclaimed asphalt pavement (RAP) mixtures consists of clusters of aggregates bonded together by the aged asphalt. Declustering of RAP particles during new asphalt mixing changes the gradation of the mixture, which affects the performance of the new asphalt mixtures containing the RAP. In this study, RAP materials with different degrees of clustering were used to make new Superpave mixtures. The degree of clustering in each RAP material was associated to its gradation change before and after the asphalt extraction. The Hamburg wheel tracking device (HWTD) was used to evaluate the rutting and striping performance of the asphalt mixtures at regular and elevated temperatures. Finally, statistical analyses were performed to evaluate the relationship between the HWTD test performance and the degree of clustering in the original RAP material. The research results showed that clusters is the original RAP material has a negative impact on rutting and striping performance of asphalt mixtures with a nominal maximum size of 9.5 to 25 mm. The impact is the most evident under the HWTD test at elevated test temperatures.

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STRUCTURAL TESTING OF NON-PROPRIETARY UHPC FOR CLOSURE POURS BETWEEN PRECAST BRDIGE DECK PANELS

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PI: Lixrine Ngeme

Co-PI(s): 

Institution(s): Georgia Institute of Technology

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Abstract

Ultra-high-performance concrete (UHPC), is an innovative material that may be used in tandem with prefabricated bridge elements and systems (PBES). The material is characterized by an extremely high compressive strength and a usable tensile strength that allows for more optimized structural elements. However, the prohibitively high cost of proprietary UHPC mixes has slowed the adoption of the material to be widely used throughout the state of Georgia. The Georgia Department of Transportation (GDOT) seeks to solve this issue by investigating the feasibility of using locally and more affordable cementitious materials in developing a non-proprietary UHPC. In response, researchers at the Georgia Institute of Technology have developed a non-proprietary mix that replaces expensive cementitious materials with more available and affordable constituents.

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FULL DEPTH PAVEMENT RECLAMATION: PERFORMANCE ASSESSMENT AND RECOMMENDATIONS FOR BEST PERFORMANCE

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PI: Jayhyun Kwon

Co-PI(s): Youngguk Seo, Adam Kaplan, and Jidong Yang

Institution(s): Kennesaw State University

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Abstract

This study investigates the influence of the variability in the FDR base layer stiffness on pavement performance. A series of field and laboratory tests were performed on a pavement reconstruction project in Georgia to assess variability. Tests included Unconfined Compressive Strength (UCS) tests and deflection tests with a Light Weight Deflectometer (LWD) and Falling Weight Deflectometer (FWD). Mechanistic sensitivity analyses were performed based on the field and laboratory test results to investigate the effect of variability in FDR properties on pavement performance. The results indicate both the FDR base thickness and strength have a significant influence on the predicted pavement responses. Findings presented here will be of interest to pavement engineers involved in the design and performance modeling of FDR pavement.

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EVALUATION OF BRINE IMPACT ON PORTLAND CEMENT CONCRETE (TASK 4)

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PI: Youngguk Seo

Co-PI(s): 

Institution(s): Kennesaw State University

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Abstract

This study presents a series of laboratory tests illustrating a long-term damage evolution in concrete saturated with brine at air temperatures. Six brine blends of CaCl2 and NaCl are formulated to test different chloride concentration levels. Multiple concrete batches are prepared to fabricate samples (4-in by 8-in cylinders) with two fly ash types (C and F) and a wide range of air contents (2.0% to 15.0%). The damage potential of concrete samples is tracked with surface resistivity measurements and compared with the results (relative dynamic modulus and weight loss of concrete) of the standard F-T tests to propose a range of optimum chloride concentrations that are less damaging to concrete pavements while offering the best melting performance.

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STRATEGIES AND RESOURCES FOR STRENGTHENING THE IMPLEMENTATION OF THE CONSTRUCTION QUALITY ACCEPTANCE FIRM (CQAF) MODEL IN THE INNOVATIVE PROJECT DELIVERY ENVIRONMENT

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PI: Jung Hyun Lee

Co-PI(s): Baabak Ashuri, Lier Liu, Evan Mistur, and Gordon Kingsley

Institution(s): Georgia Institute of Technology

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Abstract

Considering the social and economic values of high-quality transportation infrastructure in the U.S., major projects delivered using innovative project delivery require a new model to ensure effective quality management. Several State Departments of Transportation (DOTs) have adopted a new quality management system requiring the use of the developers’ construction quality acceptance firm (CQAF), also known as an independent quality firm (IQF). A better understanding is needed to develop innovative methods of conducting quality assurance (QA) in the construction engineering and inspection (CEI) industry. Therefore, this research aims to provide guidance on strengthening the QA process in the innovative project delivery environment. To identify the current state of understanding in the CQAF model compared to traditional quality management, this study conducted a combination of content analysis, survey, and follow-up interviews. The content analysis identified the major differences in the approach taken by different state DOTs and compiled the primary similarities and differences in QA between design-build (DB) and public-private partnership (P3) projects. A survey of the CEI industry provided valuable lessons for future improvement in quality management services in federal-aid design-build projects. We further consolidated our interpretation of QA topics and investigated strategies for QA at GDOT through in-depth interviews with 15 survey participants. Our findings offer a better understanding of the roles and responsibilities of the CQAF model and contribute to adopting the new quality assurance program and enhancing the CQAF model for current and future projects in the DB and P3 environments.

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ASSESSING THE APPLICABILITY OF OPEN-FORMAT VIDEO IN PAVEMENT CONDITION DATA QUALITY CONTROL PROCEDURES

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PI: James (Yichang) Tsai

Co-PI(s): 

Institution(s): Georgia Institute of Technology

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Abstract

Data-driven pavement quality management, including QA and QC procedures, is mandated by HPMS and required for the GDOT. Unfortunately, the previous lack of an open format for pavement condition data made this difficult. The newly-developed standard specification of ?2-Dimensional and 3-Dimensional (2D/3D) Pavement Image Data File Format? is an open-format 2D/3D pavement data standard that could potentially be used by GDOT to independently validate pavement condition data quality. Thus, the objectives of this project are 1) to assess the feasibility of using this open-format standard in support of GDOT?s independent validation of the quality of the pavement condition data, and 2) to recommend the work for implementing this open-format data standard. The test outcomes from the pixel-by-pixel range data comparison show the conversion steps are lossless for different pavement surface types and different pavement conditions, and so it is feasible to convert 3D data into the open-format standard data in support of GDOT?s pavement data quality control.

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DEVELOPMENT OF HIGHWAY MOWING OPERATIONS, MONITORING, AND VERIFICATION USING UAVS

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PI: Javier Irizarry

Co-PI(s): Yong Kwon Cho

Institution(s): Georgia Institute of Technology

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Abstract

Vegetation control and roadside mowing on highway is a repetitive task conducted several times per year. Especially, verification of mowing work is labor-intensive, time-consuming and presents safety issues. This study focuses on a development of UAV-based automatic mowing inspection framework using computer vision and Artificial Intelligence. This work also presents a workflow analysis to optimize for the right-of-way mowing activities. The goal of this project is to develop an automated performance verification framework for highway grass condition monitoring tasks. The proposed method uses real highway image data captured by the UAV to process the grass classification and height estimation algorithms. The results from the proposed approaches are evaluated in terms of accuracy of detected grass regions and heights by comparing ground truth data. The outcome of this research will enhance and automate the roadway mowing inspection and monitoring process.

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[20-10] DEVELOPMENT OF DRONE-ASSISTED PAVEMENT PROFILE MAPPING: NEAR-SURFACE VOID DETECTION APPLICATION.

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PI: Javier Irizarry

Co-PI(s): Tarek Rakha

Institution(s): Georgia Institute of Technology

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Abstract

Near-surface voids can develop into potholes and spalling causing potential driving hazards. A UAS with dual camera sensors can efficiently collect infrared (IR) and visual (RGB) images. This research studied the application of Computer Vision and Deep Learning to analyze UAV-collected multi-spectrum images to detect areas with voids beneath pavement surfaces.

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