@article{wang_ghanbari_underwood_kim_2021, title={Development of framework of the predictive performance-engineered mix design procedure for asphalt mixtures}, volume={23}, ISSN={1029-8436 1477-268X}, url={http://dx.doi.org/10.1080/10298436.2021.1938044}, DOI={10.1080/10298436.2021.1938044}, abstractNote={ABSTRACT This paper presents a new asphalt mixture design framework for predictive performance-engineered mix design (PEMD) and the theory and procedures that underlie the proposed design method. This method allows pavement engineers to determine an optimized mix design based on the predicted pavement/mixture performance for all possible combinations of a given set of component materials (i.e. aggregate and binder) in the design space. The proposed PEMD process is based on the ‘performance-volumetrics relationship’ (PVR) concept. The calibration of the PVR is based on the mixture performance predicted from FlexPAVETM, a three-dimensional finite element program that performs viscoelastic analysis under moving loads, using the material properties of the asphalt mixture in question at widely spaced volumetric conditions. Three mixtures of different nominal maximum aggregate sizes and binder types are used to demonstrate the proposed PEMD process. Finally, the predicted performance results obtained from different design approaches are compared.}, number={12}, journal={International Journal of Pavement Engineering}, publisher={Informa UK Limited}, author={Wang, Yizhuang David and Ghanbari, Amir and Underwood, Benjamin Shane and Kim, Youngsoo Richard}, year={2021}, month={Jun}, pages={4190–4205} } @article{ghanbari_underwood_kim_2020, title={Development of a rutting index parameter based on the stress sweep rutting test and permanent deformation shift model}, volume={23}, ISSN={1029-8436 1477-268X}, url={http://dx.doi.org/10.1080/10298436.2020.1748190}, DOI={10.1080/10298436.2020.1748190}, abstractNote={ABSTRACT The use of index parameters to evaluate the performance of asphalt mixtures has become an important process for making informed pavement material decisions. These index parameters are indicators of asphalt mixture performance and thus are widely used in the asphalt paving industry. This paper presents a new rutting index parameter to assess the rutting resistance of asphalt mixtures using the stress sweep rutting test and the permanent deformation shift model. The proposed parameter, referred to as the Rutting Strain Index (RSI), is novel in that it integrates material testing and structural simulations. To develop the RSI index parameter, more than 70 mixtures from different geographical locations that exhibit a wide variety of performance were evaluated. The results show that the RSI is able to capture the effects of mix design factors, such as RAP content, binder content, and volumetric properties. Furthermore, a set of RSI threshold values are proposed for different allowable traffic levels in terms of rutting. The RSI can be employed by agencies as a tool for performance engineered mix design and quality assurance purposes whereby agencies will be able to accept or reject a mixture based on RSI thresholds.}, number={2}, journal={International Journal of Pavement Engineering}, publisher={Informa UK Limited}, author={Ghanbari, Amir and Underwood, Benjamin Shane and Kim, Youngsoo Richard}, year={2020}, month={Apr}, pages={387–399} } @article{wang_ghanbari_underwood_kim_2021, title={Development of preliminary transfer functions for performance predictions in FlexPAVE™}, volume={266}, ISSN={0950-0618}, url={http://dx.doi.org/10.1016/j.conbuildmat.2020.121182}, DOI={10.1016/j.conbuildmat.2020.121182}, abstractNote={Mechanistic-empirical design and performance-related specifications are state-of-the-art tools for designing pavements and determining incentives/disincentives for paving contracts. These methods require the reliable prediction of pavement performance throughout the pavement's design life. One such prediction program is FlexPAVE™, which applies three-dimensional viscoelastic finite element analysis with moving loads to calculate the pavement's mechanical responses under traffic loading and given climate data. The simplified viscoelastic continuum damage model and shift model are used to calculate the fatigue damage in the pavement's cross-section and the rut depths, respectively. With regard to fatigue damage, a fatigue transfer function is needed to convert the computed cross-sectional damaged area (i.e., the damage level) to the cracked area on the pavement surface. With regard to rut depth, a rutting transfer function is needed to calibrate the predicted rut depths. In this study, preliminary transfer functions for the predicted fatigue damage and rut depths were developed using four sets of field measurement data obtained from test sections in the United States, Canada, and South Korea that include interstate highways and an accelerated testing facility. Good agreement between the predicted performance and field observations was found after calibration of FlexPAVE™.}, journal={Construction and Building Materials}, publisher={Elsevier BV}, author={Wang, Yizhuang David and Ghanbari, Amir and Underwood, Benjamin Shane and Kim, Youngsoo Richard}, year={2021}, month={Jan}, pages={121182} } @article{jeong_wang_ghanbari_nash_nener-plante_underwood_kim_2020, title={Pavement performance predictions using performance-volumetric relationship and evaluation of construction variability: Example of MaineDOT shadow project for the development of performance-related specifications}, volume={263}, ISSN={0950-0618}, url={http://dx.doi.org/10.1016/j.conbuildmat.2020.120150}, DOI={10.1016/j.conbuildmat.2020.120150}, abstractNote={This paper describes the process chain for a shadow project of the Federal Highway Administration’s Asphalt Mixture Performance-Related Specifications (PRS) by the MaineDOT. Eleven mixture samples were acquired from a field project selected by MaineDOT and were performance-tested for calibration (a ‘four corners’ procedure) and verification to develop the performance-volumetric relationship (PVR) for the selected mixture. The PVR function for the selected mixture worked reasonably well to predict pavement performance at the volumetric conditions that were not included in the PVR development and reflected reasonable trends with regard to various field densities.}, journal={Construction and Building Materials}, publisher={Elsevier BV}, author={Jeong, Jaehoon and Wang, Yizhuang David and Ghanbari, Amir and Nash, Casey and Nener-Plante, Derek and Underwood, Benjamin Shane and Kim, Y. Richard}, year={2020}, month={Dec}, pages={120150} } @article{wang_ghanbari_underwood_kim_2019, title={Development of a Performance-Volumetric Relationship for Asphalt Mixtures}, volume={2673}, ISSN={0361-1981 2169-4052}, url={http://dx.doi.org/10.1177/0361198119845364}, DOI={10.1177/0361198119845364}, abstractNote={ This paper aims to establish the relationship between the volumetric performance of asphalt mixtures and their performance in relation to pavement fatigue cracking and rutting. A good performance-volumetric relationship (PVR) can dramatically improve the working efficiency of mixtures and can be used in future performance-engineered mixture design and performance-related specifications. For this study, three asphalt mixtures were first designed to incorporate systematic changes in volumetric conditions, then fatigue cracking and rutting performance tests were conducted at each condition. Statistical analyses of the results suggest that a first-order (linear) model and power model would be an appropriate form of the PVR function. The number of volumetric conditions required to calibrate the PVR function is also investigated. Finally, a rule of thumb for selecting the volumetric conditions for the model calibrations is provided. The verification results show that the proposed PVR function is able to capture the response of mixture performance to changes in volumetric conditions. }, number={6}, journal={Transportation Research Record: Journal of the Transportation Research Board}, publisher={SAGE Publications}, author={Wang, Yizhuang David and Ghanbari, Amir and Underwood, Benjamin Shane and Kim, Youngsoo Richard}, year={2019}, month={May}, pages={416–430} }