Establishment of a Shear Strength Prediction Model for Asphalt Mixtures with Raw Materials Properties and Design Parameters
Shear strength is one of the important mechanical properties of asphalt mixtures, which is affected by a combination of various parameters such as asphalt property, gradation, and asphalt content, so it often requires a large number of tests to obtain a satisfactory asphalt mix design result. Thus,...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2021/8818088 |
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| author | Bangwei Wu Xing Wu Liping Liu Peng Xiao |
| author_facet | Bangwei Wu Xing Wu Liping Liu Peng Xiao |
| author_sort | Bangwei Wu |
| collection | DOAJ |
| description | Shear strength is one of the important mechanical properties of asphalt mixtures, which is affected by a combination of various parameters such as asphalt property, gradation, and asphalt content, so it often requires a large number of tests to obtain a satisfactory asphalt mix design result. Thus, a shear strength prediction model considering the effects of various factors is proposed to guide the design of asphalt mixes. Firstly, on the foundation of analyzing the factors affecting the shear strength of asphalt mixtures, composed bulk specific gravity of mineral materials, aggregate surface energy, nonrecoverable creep compliance Jnr3.2, gradation index, aggregate specific surface area, asphalt content, and gyratory compaction number were selected as the input parameters for modeling. Secondly, the effects of modeling parameters on shear strength were analyzed, and an appropriate model was established using the software Origin with 101 sets of test results. In the end, the prediction model was verified using extra 18 sets of test data. The result showed that the correlation coefficient between the predicted and measured value reached 0.8 or more, indicating that the model has satisfactory prediction accuracy. This prediction model proposed in this article can be used to reduce the workload for designing asphalt mixtures and promote the establishment of the performance-based design method of asphalt mixtures. |
| format | Article |
| id | doaj-art-c61ceb5d86864bad8ff3e8a0c046b615 |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-c61ceb5d86864bad8ff3e8a0c046b6152025-02-03T01:29:18ZengWileyAdvances in Civil Engineering1687-80861687-80942021-01-01202110.1155/2021/88180888818088Establishment of a Shear Strength Prediction Model for Asphalt Mixtures with Raw Materials Properties and Design ParametersBangwei Wu0Xing Wu1Liping Liu2Peng Xiao3College of Civil Science and Engineering, Yangzhou University, Yangzhou 225127, ChinaCollege of Civil Science and Engineering, Yangzhou University, Yangzhou 225127, ChinaKey Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, ChinaCollege of Civil Science and Engineering, Yangzhou University, Yangzhou 225127, ChinaShear strength is one of the important mechanical properties of asphalt mixtures, which is affected by a combination of various parameters such as asphalt property, gradation, and asphalt content, so it often requires a large number of tests to obtain a satisfactory asphalt mix design result. Thus, a shear strength prediction model considering the effects of various factors is proposed to guide the design of asphalt mixes. Firstly, on the foundation of analyzing the factors affecting the shear strength of asphalt mixtures, composed bulk specific gravity of mineral materials, aggregate surface energy, nonrecoverable creep compliance Jnr3.2, gradation index, aggregate specific surface area, asphalt content, and gyratory compaction number were selected as the input parameters for modeling. Secondly, the effects of modeling parameters on shear strength were analyzed, and an appropriate model was established using the software Origin with 101 sets of test results. In the end, the prediction model was verified using extra 18 sets of test data. The result showed that the correlation coefficient between the predicted and measured value reached 0.8 or more, indicating that the model has satisfactory prediction accuracy. This prediction model proposed in this article can be used to reduce the workload for designing asphalt mixtures and promote the establishment of the performance-based design method of asphalt mixtures.http://dx.doi.org/10.1155/2021/8818088 |
| spellingShingle | Bangwei Wu Xing Wu Liping Liu Peng Xiao Establishment of a Shear Strength Prediction Model for Asphalt Mixtures with Raw Materials Properties and Design Parameters Advances in Civil Engineering |
| title | Establishment of a Shear Strength Prediction Model for Asphalt Mixtures with Raw Materials Properties and Design Parameters |
| title_full | Establishment of a Shear Strength Prediction Model for Asphalt Mixtures with Raw Materials Properties and Design Parameters |
| title_fullStr | Establishment of a Shear Strength Prediction Model for Asphalt Mixtures with Raw Materials Properties and Design Parameters |
| title_full_unstemmed | Establishment of a Shear Strength Prediction Model for Asphalt Mixtures with Raw Materials Properties and Design Parameters |
| title_short | Establishment of a Shear Strength Prediction Model for Asphalt Mixtures with Raw Materials Properties and Design Parameters |
| title_sort | establishment of a shear strength prediction model for asphalt mixtures with raw materials properties and design parameters |
| url | http://dx.doi.org/10.1155/2021/8818088 |
| work_keys_str_mv | AT bangweiwu establishmentofashearstrengthpredictionmodelforasphaltmixtureswithrawmaterialspropertiesanddesignparameters AT xingwu establishmentofashearstrengthpredictionmodelforasphaltmixtureswithrawmaterialspropertiesanddesignparameters AT lipingliu establishmentofashearstrengthpredictionmodelforasphaltmixtureswithrawmaterialspropertiesanddesignparameters AT pengxiao establishmentofashearstrengthpredictionmodelforasphaltmixtureswithrawmaterialspropertiesanddesignparameters |