Neural networks for fatigue cracking prediction using outputs from pavement mechanistic-empirical design-Reference-Cited by-同舟云学术

Neural networks for fatigue cracking prediction using outputs from pavement mechanistic-empirical design

Published:2019-02-17 Issue:2 Volume:22 Page:162-172
ISSN:1029-8436
Container-title:International Journal of Pavement Engineering
language:en
Short-container-title:International Journal of Pavement Engineering

Author:

Gong Hongren¹,Sun Yiren²,Hu Wei¹^ORCID,Huang Baoshan¹³

Affiliation:

1. Department of Civil and Environmental Engineering, The University of Tennessee, Knoxville, TN, USA

2. School of Transportation and Logistics, Dalian University of Technology, Dalian, China

3. Department of Transportation, Tongji University, Shanghai, China

Publisher

Informa UK Limited

Subject

Mechanics of Materials,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10298436.2019.1580367

Reference53 articles.

1. Abadi, M. et al., 2016. Tensorflow: a system for large-scale machine learning. In: OSDI. vol. 16, 265–283.

2. ARA, 2004b. Guide for mechanistic-empirical design guide of new and rehabilitated pavement structures: Calibration of fatigue cracking models for flexible pavements. Transporation Research Board of the National Academies, Washington D.C., Final Report Appendix EE-1: NCHRP 1-37A.

3. ARA, 2004a. Guide for mechanistic-empirical design guide of new and rehabilitated pavement structures. Transporation Research Board of the National Academies, Washington D.C., Final Report NCHRP 1-37A.

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