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Research on the Combination of Firefly Intelligent Algorithm and Asphalt Material Modulus Back Calculation
The modulus of asphalt pavement material is a necessary parameter for the design, strength measuring and stability evaluation of asphalt pavement. To get more precise test data for asphalt pavement material modulus, a new modulus back calculation method is proposed in this article, named as the Fire...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9101902/ https://www.ncbi.nlm.nih.gov/pubmed/35591695 http://dx.doi.org/10.3390/ma15093361 |
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author | Zhao, Runmin Gong, Jinzhi Zheng, Yangzezhi Huang, Xiaoming |
author_facet | Zhao, Runmin Gong, Jinzhi Zheng, Yangzezhi Huang, Xiaoming |
author_sort | Zhao, Runmin |
collection | PubMed |
description | The modulus of asphalt pavement material is a necessary parameter for the design, strength measuring and stability evaluation of asphalt pavement. To get more precise test data for asphalt pavement material modulus, a new modulus back calculation method is proposed in this article, named as the Firefly Asphalt Back Calculation Method (FABCM). This novel method uses the firefly optimization algorithm, which is a kind of particle swarm intelligence algorithm imitating the information transfer process among fireflies. To demonstrate the reliability and stability of FABCM, and to study the feasibility of multi-parameter modulus back calculation methods, this article used theoretical deflection curves calculated by BISAR3.0 and the actual measurement data of deflection curves and vertical pressures on the subgrade top surfaces on the full-scale test circular track in the Research Institute of Highway, Ministry of Transport (RIOHTrack) to conduct a modulus back calculation. The results show that FABCM only takes 0.5–1 s for each calculation, and the back calculation errors in the verification of FABCM are mostly smaller than 1%, which means that the firefly optimization algorithm was modified effectively in this article. Moreover, this article also indicates some key factors influencing the accuracy of modulus back calculation, and several reasonable suggestions to the application of modulus back calculation. |
format | Online Article Text |
id | pubmed-9101902 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91019022022-05-14 Research on the Combination of Firefly Intelligent Algorithm and Asphalt Material Modulus Back Calculation Zhao, Runmin Gong, Jinzhi Zheng, Yangzezhi Huang, Xiaoming Materials (Basel) Article The modulus of asphalt pavement material is a necessary parameter for the design, strength measuring and stability evaluation of asphalt pavement. To get more precise test data for asphalt pavement material modulus, a new modulus back calculation method is proposed in this article, named as the Firefly Asphalt Back Calculation Method (FABCM). This novel method uses the firefly optimization algorithm, which is a kind of particle swarm intelligence algorithm imitating the information transfer process among fireflies. To demonstrate the reliability and stability of FABCM, and to study the feasibility of multi-parameter modulus back calculation methods, this article used theoretical deflection curves calculated by BISAR3.0 and the actual measurement data of deflection curves and vertical pressures on the subgrade top surfaces on the full-scale test circular track in the Research Institute of Highway, Ministry of Transport (RIOHTrack) to conduct a modulus back calculation. The results show that FABCM only takes 0.5–1 s for each calculation, and the back calculation errors in the verification of FABCM are mostly smaller than 1%, which means that the firefly optimization algorithm was modified effectively in this article. Moreover, this article also indicates some key factors influencing the accuracy of modulus back calculation, and several reasonable suggestions to the application of modulus back calculation. MDPI 2022-05-07 /pmc/articles/PMC9101902/ /pubmed/35591695 http://dx.doi.org/10.3390/ma15093361 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhao, Runmin Gong, Jinzhi Zheng, Yangzezhi Huang, Xiaoming Research on the Combination of Firefly Intelligent Algorithm and Asphalt Material Modulus Back Calculation |
title | Research on the Combination of Firefly Intelligent Algorithm and Asphalt Material Modulus Back Calculation |
title_full | Research on the Combination of Firefly Intelligent Algorithm and Asphalt Material Modulus Back Calculation |
title_fullStr | Research on the Combination of Firefly Intelligent Algorithm and Asphalt Material Modulus Back Calculation |
title_full_unstemmed | Research on the Combination of Firefly Intelligent Algorithm and Asphalt Material Modulus Back Calculation |
title_short | Research on the Combination of Firefly Intelligent Algorithm and Asphalt Material Modulus Back Calculation |
title_sort | research on the combination of firefly intelligent algorithm and asphalt material modulus back calculation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9101902/ https://www.ncbi.nlm.nih.gov/pubmed/35591695 http://dx.doi.org/10.3390/ma15093361 |
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