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The Machine Learning Based Finite Element Analysis on Road Engineering of Built-in Carbon Fiber Heating Wire

Yuhua Penga, Dingyue Chena, Lihao Chenb, Jiayu Yub, Mengjie Baoa

a Chang’an University, Xi’an, China
b Northwest University, Xi'an, China

* Corresponding Author: Dingyue Chen, email

Intelligent Automation & Soft Computing 2018, 24(3), 531-539. https://doi.org/10.31209/2018.100000020

Abstract

For the study of the effect of deicing with carbon fiber heating wire in the bridge pavement structure, through built-in carbon fiber heating wire in the bridge pavement structure, experimental studies were carried out indoor on the effects of thermal conductivity in different embedding positions, layout spacing and the installs power of carbon fiber heating wire. With indoor laboratory test data as the basic parameters, using ABAQUS finite element software simulation, an analysis was carried out of the degree that the surface temperature of the heating wire, the thermal physical parameters of asphalt concrete, and environmental conditions have influence on the melting effect. With a 50 m bridge between the left Shanggaoqiao tunnel exports with 2# Dabaozhai tunnel entrance in Ma Zhao Highway as the test section, this paper introduces the carbon fiber heating wire grooving laying process and construction methods.

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APA Style
Peng, Y., Chen, D., Chen, L., Yu, J., Bao, M. (2018). The machine learning based finite element analysis on road engineering of built-in carbon fiber heating wire . Intelligent Automation & Soft Computing, 24(3), 531-539. https://doi.org/10.31209/2018.100000020
Vancouver Style
Peng Y, Chen D, Chen L, Yu J, Bao M. The machine learning based finite element analysis on road engineering of built-in carbon fiber heating wire . Intell Automat Soft Comput . 2018;24(3):531-539 https://doi.org/10.31209/2018.100000020
IEEE Style
Y. Peng, D. Chen, L. Chen, J. Yu, and M. Bao "The Machine Learning Based Finite Element Analysis on Road Engineering of Built-in Carbon Fiber Heating Wire ," Intell. Automat. Soft Comput. , vol. 24, no. 3, pp. 531-539. 2018. https://doi.org/10.31209/2018.100000020



cc Copyright © 2018 The Author(s). Published by Tech Science Press.
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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