A Study on the Genetic Algorithm Optimization of an Asphalt Mixture’s Viscoelastic Parameters Based on a Wheel Tracking Test
The generalized Maxwell (GM) constitutive model has been widely applied to characterize the viscoelastic properties of asphalt mixtures. The parameters (Prony series) of the GM are usually obtained via interconversion between a dynamic modulus and relaxation modulus, and they are then input to a fin...
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MDPI AG
2023-11-01
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| Series: | Infrastructures |
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| Online Access: | https://www.mdpi.com/2412-3811/8/12/169 |
| _version_ | 1797380631078895616 |
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| author | Jinxi Zhang Weiqi Zhou Dandan Cao Jia Zhang |
| author_facet | Jinxi Zhang Weiqi Zhou Dandan Cao Jia Zhang |
| author_sort | Jinxi Zhang |
| collection | DOAJ |
| description | The generalized Maxwell (GM) constitutive model has been widely applied to characterize the viscoelastic properties of asphalt mixtures. The parameters (Prony series) of the GM are usually obtained via interconversion between a dynamic modulus and relaxation modulus, and they are then input to a finite element model (FEM) as viscoelastic parameters. However, the dynamic modulus obtained with the common loading mode only provides the compressive and tensile properties of materials. Whether the compression or tensile modulus can represent the shear properties of materials related to flow rutting is still open to discussion. Therefore, this study introduced a novel method that integrates the Kriging model into the genetic algorithm as a surrogate model to determine the viscoelastic parameters of an asphalt mixture in rutting research. Firstly, a wheel tracking test (WTT) for AC-13 was conducted to clarify the flow rutting development mechanism. Secondly, two sets of the AC-13 viscoelastic parameters obtained through the optimization method and the dynamic modulus were used as inputs into the FEM simulation of the WTT to compare the simulation results. Finally, a sensitivity analysis of viscoelastic parameters was performed to improve the efficiency of parameter optimization. The results indicating the viscoelastic parameters obtained by this method could precisely characterize the development law of flow rutting in asphalt mixtures. |
| first_indexed | 2024-03-08T20:40:01Z |
| format | Article |
| id | doaj.art-9ed3c34adf9c4b1ab99c5d761b92bb4c |
| institution | Directory Open Access Journal |
| issn | 2412-3811 |
| language | English |
| last_indexed | 2024-03-08T20:40:01Z |
| publishDate | 2023-11-01 |
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| record_format | Article |
| series | Infrastructures |
| spelling | doaj.art-9ed3c34adf9c4b1ab99c5d761b92bb4c2023-12-22T14:15:58ZengMDPI AGInfrastructures2412-38112023-11-0181216910.3390/infrastructures8120169A Study on the Genetic Algorithm Optimization of an Asphalt Mixture’s Viscoelastic Parameters Based on a Wheel Tracking TestJinxi Zhang0Weiqi Zhou1Dandan Cao2Jia Zhang3Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, ChinaBeijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, ChinaBeijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, ChinaSchool of Mechanics and Civil Engineering, China University of Mining Technology, Xuzhou 221116, ChinaThe generalized Maxwell (GM) constitutive model has been widely applied to characterize the viscoelastic properties of asphalt mixtures. The parameters (Prony series) of the GM are usually obtained via interconversion between a dynamic modulus and relaxation modulus, and they are then input to a finite element model (FEM) as viscoelastic parameters. However, the dynamic modulus obtained with the common loading mode only provides the compressive and tensile properties of materials. Whether the compression or tensile modulus can represent the shear properties of materials related to flow rutting is still open to discussion. Therefore, this study introduced a novel method that integrates the Kriging model into the genetic algorithm as a surrogate model to determine the viscoelastic parameters of an asphalt mixture in rutting research. Firstly, a wheel tracking test (WTT) for AC-13 was conducted to clarify the flow rutting development mechanism. Secondly, two sets of the AC-13 viscoelastic parameters obtained through the optimization method and the dynamic modulus were used as inputs into the FEM simulation of the WTT to compare the simulation results. Finally, a sensitivity analysis of viscoelastic parameters was performed to improve the efficiency of parameter optimization. The results indicating the viscoelastic parameters obtained by this method could precisely characterize the development law of flow rutting in asphalt mixtures.https://www.mdpi.com/2412-3811/8/12/169asphalt mixtureviscoelasticityflow ruttingkriging modelparameter optimization |
| spellingShingle | Jinxi Zhang Weiqi Zhou Dandan Cao Jia Zhang A Study on the Genetic Algorithm Optimization of an Asphalt Mixture’s Viscoelastic Parameters Based on a Wheel Tracking Test Infrastructures asphalt mixture viscoelasticity flow rutting kriging model parameter optimization |
| title | A Study on the Genetic Algorithm Optimization of an Asphalt Mixture’s Viscoelastic Parameters Based on a Wheel Tracking Test |
| title_full | A Study on the Genetic Algorithm Optimization of an Asphalt Mixture’s Viscoelastic Parameters Based on a Wheel Tracking Test |
| title_fullStr | A Study on the Genetic Algorithm Optimization of an Asphalt Mixture’s Viscoelastic Parameters Based on a Wheel Tracking Test |
| title_full_unstemmed | A Study on the Genetic Algorithm Optimization of an Asphalt Mixture’s Viscoelastic Parameters Based on a Wheel Tracking Test |
| title_short | A Study on the Genetic Algorithm Optimization of an Asphalt Mixture’s Viscoelastic Parameters Based on a Wheel Tracking Test |
| title_sort | study on the genetic algorithm optimization of an asphalt mixture s viscoelastic parameters based on a wheel tracking test |
| topic | asphalt mixture viscoelasticity flow rutting kriging model parameter optimization |
| url | https://www.mdpi.com/2412-3811/8/12/169 |
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