Rutting Prediction of Flexible Pavements Using Finite Element Modeling

During the past two decades, Finite Element (FE) techniques were successfully used to simulate different pavement problems that could not be modelled using the simpler multi-layer elastic theory. In this study, a two-dimensional finite element model was developed, using ABAQUS software, in order to investigate the impact of static repeated wheel load on rutting formation and pavement response. The procedures of building a model and performing static analysis are introduced. In that model, pavement materials were presented as linear-elastic–plastic based on Drucker-Prager model. In addition, the asphalt layer was assumed to follow a viscoelastic behavior using Pellinen and Witczak model, which was adopted by NCHRP. The Falling Weight Deflectometer FWD was also proposed as an effective and practical tool for on-site pavement evaluation and field measurements, other than the laboratory tests. After insuring the model validation, the study investigated the impact of temperature, tire pressure and subgrade strength on the rut depth as a pavement response. The sensitivity analysis indicated that the rut depth increases with increasing the temperature and the tire pressure and with decreasing the subgrade strength

Development of Indiana\u27s SPS9-A Site

The Superpave system for hot mix asphalt (HMA) design was introduced in 1995 and adopted throughout most of the USA by 2000. This system uses performance-oriented approach to materials selection and mix design, and takes into account the local environmental and traffic conditions. It recognizes that the behavior of HMA depends on the temperature, loading and aging conditions and provides tools (in the form of materials selection and performance-related tests) that should help to protect pavements against low-temperature cracking, rutting and fatigue cracking. This report summarizes the field and laboratory studies conducted to investigate the influence of asphalt binder grade on the field performance of HMA pavements. In particular, the effect of binder grade on low temperature cracking and on permanent deformation (rutting) of pavement was investigated. In addition, the validity of some of the existing low-temperature models for assessing the susceptibility of a given binder to low temperature cracking is also analyzed. The study involved construction and field evaluation of six test sections on the interstate I-70, east of Indianapolis, Indiana. Four of the six sections contained various SUPERPAVE binder grades, one of the sections was constructed using traditional Marshal mix design, and one of the sections contained 15% of recycled asphalt concrete (RAP). The monitoring of performance of the test sections involved periodical distress surveys and collection of field cores for laboratory testing of volumetric, binder and aggregate properties. In addition, the original binders and plant mix samples were also evaluated. The results of this test program indicate that, in general, the binder grade does influence the field performance of HMA and that susceptibility to failure of a given material can (in many cases) be predicted from the laboratory test results. Particularly good correlation between the laboratory-based data and field performance was observed for low-temperature binder tests, indicating that these tests can reliably predict the critical cracking temperature of the pavement. On the other hand, the test results also confirmed that low-temperature prediction algorithms proposed in the original Superpave specifications were too conservative, for the environmental conditions present at the test site

OpenMP aware MHP Analysis for Improved Static Data-Race Detection

Data races, a major source of bugs in concurrent programs, can result in loss of manpower and time as well as data loss due to system failures. OpenMP, the de facto shared memory parallelism framework used in the HPC community, also suffers from data races. To detect race conditions in OpenMP programs and improve turnaround time and/or developer productivity, we present a data flow analysis based, fast, static data race checker in the LLVM compiler framework. Our tool can detect races in the presence or absence of explicit barriers, with implicit or explicit synchronization. In addition, our tool effectively works for the OpenMP target offloading constructs and also supports the frequently used OpenMP constructs.We formalize and provide a data flow analysis framework to perform Phase Interval Analysis (PIA) of OpenMP programs. Phase intervals are then used to compute the MHP (and its complement NHP) sets for the programs, which, in turn, are used to detect data races statically.We evaluate our work using multiple OpenMP race detection benchmarks and real world applications. Our experiments show that the checker is comparable to the state-of-The-Art in various performance metrics with around 90% accuracy, almost perfect recall, and significantly lower runtime and memory footprint. © 2021 IEEE

OpenMP aware MHP Analysis for Improved Static Data-Race Detection

Data races, a major source of bugs in concurrent programs, can result in loss of manpower and time as well as data loss due to system failures. OpenMP, the de facto shared memory parallelism framework used in the HPC community, also suffers from data races. To detect race conditions in OpenMP programs and improve turnaround time and/or developer productivity, we present a data flow analysis based, fast, static data race checker in the LLVM compiler framework. Our tool can detect races in the presence or absence of explicit barriers, with implicit or explicit synchronization. In addition, our tool effectively works for the OpenMP target offloading constructs and also supports the frequently used OpenMP constructs.We formalize and provide a data flow analysis framework to perform Phase Interval Analysis (PIA) of OpenMP programs. Phase intervals are then used to compute the MHP (and its complement NHP) sets for the programs, which, in turn, are used to detect data races statically.We evaluate our work using multiple OpenMP race detection benchmarks and real world applications. Our experiments show that the checker is comparable to the state-of-The-Art in various performance metrics with around 90% accuracy, almost perfect recall, and significantly lower runtime and memory footprint. © 2021 IEEE

Dynamic response analysis of rutting resistance performance of high modulus asphalt concrete pavement

In order to systematically study the rutting resistance performance of High-Modulus Asphalt Concrete (HMAC) pavements, a finite element method model of HMAC pavement was established using ABAQUS software. Based on the viscoelasticity theory of asphalt, the stress and deformation distribution characteristics of HMAC pavement were studied and compared to conventional asphalt pavement under moving loads. Then, the pavement temperature field model was established to study the temperature variation and the thermal stress in HMAC pavement. Finally, under the condition of continuous temperature variation, the creep behavior and permanent deformation of HMAC pavement were investigated. The results showed that under the action of moving loads, the strain and displacement generated in HMAC pavement were lower than those in conventional asphalt pavement. The upper surface layer was most obviously affected by outside air temperature, resulting in maximum thermal stress. Lastly, under the condition of continuous temperature change, HMAC pavement could greatly reduce the deformation of asphalt material in each surface layer compared to conventional asphalt pavement