The fatigue behavior, indirect tensile strength （ITS） and resilient modulus test results for warm mix asphalt （WMA） as well as hot mix asphalt （HMA） at different ageing levels were evaluated. Laboratory-prepared...The fatigue behavior, indirect tensile strength （ITS） and resilient modulus test results for warm mix asphalt （WMA） as well as hot mix asphalt （HMA） at different ageing levels were evaluated. Laboratory-prepared samples were aged artificially in the oven to simulate short-term and long term ageing in accordance with AASHTO R30 and then compared with unaged specimens. Beam fatigue testing was performed using beam specimens at 25 ℃ based on AASHTO T321 standard. Fatigue life, bending stiffness and dissipated energy for both unaged and aged mixtures were calculated using four-point beam fatigue test results. Three-point bending tests were performed using semi-circular bend （SCB） specimens at -10 ℃ and the critical mode I stress intensity factor K1 was then calculated using the peak load obtained from the load-displacement curve. It is observed that Sasobit and Rheofalt warm mix asphalt additives have a significant effect on indirect tensile strength, resilient modulus, fatigue behavior and stress intensity factor of aged and unaged mixtures.展开更多
Nano silica due to its spherical shape, tiny size and higher density compared to bitumen, may have an inherent potential to improve hot mix asphalt(HMA) self-healing. In this research scanning electron microscopy(SEM)...Nano silica due to its spherical shape, tiny size and higher density compared to bitumen, may have an inherent potential to improve hot mix asphalt(HMA) self-healing. In this research scanning electron microscopy(SEM) images were used to investigate size, morphology and dispersion of nano silica particles. Additionally, HMA self-healing mechanism was also examined by SEM. Furthermore, dynamic indirect tensile test(IDT) was used to evaluate HMA self-healing index. The SEM results indicated that bitumen mortar flowing into micro cracks may be one of the most important mechanisms of HMA self-healing. The experiment results also showed that modification of bitumen by nano silica promotes the ability of the HMA self-healing.展开更多
While various kinds of fibers are used to improve the hot mix asphalt(HMA) performance, a few works have been undertaken on the hybrid fiber-reinforced HMA. Therefore, the fatigue life of modified HMA samples using po...While various kinds of fibers are used to improve the hot mix asphalt(HMA) performance, a few works have been undertaken on the hybrid fiber-reinforced HMA. Therefore, the fatigue life of modified HMA samples using polypropylene and polyester fibers was evaluated and two models namely regression and artificial neural network(ANN) were used to predict the fatigue life based on the fibers parameters. As ANN contains many parameters such as the number of hidden layers which directly influence the prediction accuracy, genetic algorithm(GA) was used to solve optimization problem for ANN. Moreover, the trial and error method was used to optimize the GA parameters such as the population size. The comparison of the results obtained from regression and optimized ANN with GA shows that the two-hidden-layer ANN with two and five neurons in the first and second hidden layers, respectively, can predict the fatigue life of fiber-reinforced HMA with high accuracy(correlation coefficient of 0.96).展开更多
文摘The fatigue behavior, indirect tensile strength （ITS） and resilient modulus test results for warm mix asphalt （WMA） as well as hot mix asphalt （HMA） at different ageing levels were evaluated. Laboratory-prepared samples were aged artificially in the oven to simulate short-term and long term ageing in accordance with AASHTO R30 and then compared with unaged specimens. Beam fatigue testing was performed using beam specimens at 25 ℃ based on AASHTO T321 standard. Fatigue life, bending stiffness and dissipated energy for both unaged and aged mixtures were calculated using four-point beam fatigue test results. Three-point bending tests were performed using semi-circular bend （SCB） specimens at -10 ℃ and the critical mode I stress intensity factor K1 was then calculated using the peak load obtained from the load-displacement curve. It is observed that Sasobit and Rheofalt warm mix asphalt additives have a significant effect on indirect tensile strength, resilient modulus, fatigue behavior and stress intensity factor of aged and unaged mixtures.
文摘Nano silica due to its spherical shape, tiny size and higher density compared to bitumen, may have an inherent potential to improve hot mix asphalt(HMA) self-healing. In this research scanning electron microscopy(SEM) images were used to investigate size, morphology and dispersion of nano silica particles. Additionally, HMA self-healing mechanism was also examined by SEM. Furthermore, dynamic indirect tensile test(IDT) was used to evaluate HMA self-healing index. The SEM results indicated that bitumen mortar flowing into micro cracks may be one of the most important mechanisms of HMA self-healing. The experiment results also showed that modification of bitumen by nano silica promotes the ability of the HMA self-healing.
文摘While various kinds of fibers are used to improve the hot mix asphalt(HMA) performance, a few works have been undertaken on the hybrid fiber-reinforced HMA. Therefore, the fatigue life of modified HMA samples using polypropylene and polyester fibers was evaluated and two models namely regression and artificial neural network(ANN) were used to predict the fatigue life based on the fibers parameters. As ANN contains many parameters such as the number of hidden layers which directly influence the prediction accuracy, genetic algorithm(GA) was used to solve optimization problem for ANN. Moreover, the trial and error method was used to optimize the GA parameters such as the population size. The comparison of the results obtained from regression and optimized ANN with GA shows that the two-hidden-layer ANN with two and five neurons in the first and second hidden layers, respectively, can predict the fatigue life of fiber-reinforced HMA with high accuracy(correlation coefficient of 0.96).
