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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...

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Detalles Bibliográficos
Autores principales: Zhao, Runmin, Gong, Jinzhi, Zheng, Yangzezhi, Huang, Xiaoming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
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.
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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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