Investigation of Strength and Fatigue Life of Rubber Asphalt Mixture
Strength and fatigue life are essential parameters of pavement structure design. To accurately determine the pavement structure resistance of rubber asphalt mixture, the strength tests at various temperatures, loading rate, and fatigue tests at different stress levels were conducted in this research...
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doaj-19b7b4e9bac64b09b2cecebd332b03892020-11-25T02:48:05ZengMDPI AGMaterials1996-19442020-07-01133325332510.3390/ma13153325Investigation of Strength and Fatigue Life of Rubber Asphalt MixtureJiang Yuan0Songtao Lv1Xinghai Peng2Lingyun You3Milkos Borges Cabrera4National Engineering Laboratory of Highway Maintenance Technology, Changsha University of Science and Technology, Changsha 410004, Hunan, ChinaNational Engineering Laboratory of Highway Maintenance Technology, Changsha University of Science and Technology, Changsha 410004, Hunan, ChinaNational Engineering Laboratory of Highway Maintenance Technology, Changsha University of Science and Technology, Changsha 410004, Hunan, ChinaDepartment of Civil and Environmental Engineering, Michigan Technological University, Houghton, MI 49931-1295, USANational Engineering Laboratory of Highway Maintenance Technology, Changsha University of Science and Technology, Changsha 410004, Hunan, ChinaStrength and fatigue life are essential parameters of pavement structure design. To accurately determine the pavement structure resistance of rubber asphalt mixture, the strength tests at various temperatures, loading rate, and fatigue tests at different stress levels were conducted in this research. Based on the proposed experiments, the change law of rubber asphalt mixture strength with different temperatures and loading rates was revealed. The phenomenological fatigue equation of rubber asphalt mixture was established. The genetic algorithm optimized backpropagation neural network (GA-BPNN) is highly reliable for optimizing production processes in civil engineering, and it has a remarkable application effect. A GA-BPNN strength and fatigue life prediction model was created in this study. The reliability of the prediction model was verified through experiments. The results showed that the rubber asphalt mixture strength decreases and increases with the increase of temperature and loading rate, respectively. The goodness of fit of the rubber asphalt mixture strength and fatigue life prediction model based on the GA-BPNN could reach 0.989 and 0.998, respectively. The indicators of the fatigue life prediction model are superior to the conventional phenomenological fatigue equation model. The GA-BPNN provides an effective method for predicting the rubber asphalt mixture strength and fatigue life, which significantly improves the accuracy of the resistance design of the rubber asphalt pavement structure.https://www.mdpi.com/1996-1944/13/15/3325rubber asphalt mixturestrengthfatigue lifegenetic algorithmback propagation neural network |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jiang Yuan Songtao Lv Xinghai Peng Lingyun You Milkos Borges Cabrera |
spellingShingle |
Jiang Yuan Songtao Lv Xinghai Peng Lingyun You Milkos Borges Cabrera Investigation of Strength and Fatigue Life of Rubber Asphalt Mixture Materials rubber asphalt mixture strength fatigue life genetic algorithm back propagation neural network |
author_facet |
Jiang Yuan Songtao Lv Xinghai Peng Lingyun You Milkos Borges Cabrera |
author_sort |
Jiang Yuan |
title |
Investigation of Strength and Fatigue Life of Rubber Asphalt Mixture |
title_short |
Investigation of Strength and Fatigue Life of Rubber Asphalt Mixture |
title_full |
Investigation of Strength and Fatigue Life of Rubber Asphalt Mixture |
title_fullStr |
Investigation of Strength and Fatigue Life of Rubber Asphalt Mixture |
title_full_unstemmed |
Investigation of Strength and Fatigue Life of Rubber Asphalt Mixture |
title_sort |
investigation of strength and fatigue life of rubber asphalt mixture |
publisher |
MDPI AG |
series |
Materials |
issn |
1996-1944 |
publishDate |
2020-07-01 |
description |
Strength and fatigue life are essential parameters of pavement structure design. To accurately determine the pavement structure resistance of rubber asphalt mixture, the strength tests at various temperatures, loading rate, and fatigue tests at different stress levels were conducted in this research. Based on the proposed experiments, the change law of rubber asphalt mixture strength with different temperatures and loading rates was revealed. The phenomenological fatigue equation of rubber asphalt mixture was established. The genetic algorithm optimized backpropagation neural network (GA-BPNN) is highly reliable for optimizing production processes in civil engineering, and it has a remarkable application effect. A GA-BPNN strength and fatigue life prediction model was created in this study. The reliability of the prediction model was verified through experiments. The results showed that the rubber asphalt mixture strength decreases and increases with the increase of temperature and loading rate, respectively. The goodness of fit of the rubber asphalt mixture strength and fatigue life prediction model based on the GA-BPNN could reach 0.989 and 0.998, respectively. The indicators of the fatigue life prediction model are superior to the conventional phenomenological fatigue equation model. The GA-BPNN provides an effective method for predicting the rubber asphalt mixture strength and fatigue life, which significantly improves the accuracy of the resistance design of the rubber asphalt pavement structure. |
topic |
rubber asphalt mixture strength fatigue life genetic algorithm back propagation neural network |
url |
https://www.mdpi.com/1996-1944/13/15/3325 |
work_keys_str_mv |
AT jiangyuan investigationofstrengthandfatiguelifeofrubberasphaltmixture AT songtaolv investigationofstrengthandfatiguelifeofrubberasphaltmixture AT xinghaipeng investigationofstrengthandfatiguelifeofrubberasphaltmixture AT lingyunyou investigationofstrengthandfatiguelifeofrubberasphaltmixture AT milkosborgescabrera investigationofstrengthandfatiguelifeofrubberasphaltmixture |
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