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Thermal Properties Reconstruction and Temperature Fields in Asphalt Pavements: Inverse Problem and Optimisation Algorithms

Zhonghai Jiang1, Qian Wang1, Liangbing Zhou2,*, Chun Xiao3

1 School of Transportation and Civil Architecture, Foshan University, Foshan, 528000, China
2 Guangdong Yuanshun Architectural Design Co., Ltd., Foshan, 528000, China
3 Eternal Estate Engineering Design Co., Ltd., Chengdu, 610017, China

* Corresponding Author: Liangbing Zhou. Email: email

(This article belongs to this Special Issue: Computational Mechanics and Fluid Dynamics in Intelligent Manufacturing and Material Processing)

Fluid Dynamics & Materials Processing 2023, 19(6), 1693-1708. https://doi.org/10.32604/fdmp.2023.025270

Abstract

A two-layer implicit difference scheme is employed in the present study to determine the temperature distribution in an asphalt pavement. The calculation of each layer only needs four iterations to achieve convergence. Furthermore, in order to improve the calculation accuracy a swarm intelligence optimization algorithm is also exploited to inversely analyze the laws by which the thermal physical parameters of the asphalt pavement materials change with temperature. Using the basic cuckoo and the gray wolf algorithms, an adaptive hybrid optimization algorithm is obtained and used to determine the relationship between the thermal diffusivity of two types of asphalt pavement materials and the temperature. As shown by the results, the prediction accuracy achievable with this approach is higher than that of the linear model.

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Cite This Article

Jiang, Z., Wang, Q., Zhou, L., Xiao, C. (2023). Thermal Properties Reconstruction and Temperature Fields in Asphalt Pavements: Inverse Problem and Optimisation Algorithms. FDMP-Fluid Dynamics & Materials Processing, 19(6), 1693–1708.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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