Soil-pipe interaction modeling for pipe behavior prediction with super learning based methods

Fang Shi; Xiang Peng; Huan Liu; Yafei Hu; Zheng Liu; Eric Li

doi:10.1117/12.2300812

27 March 2018 Soil-pipe interaction modeling for pipe behavior prediction with super learning based methods

Fang Shi, Xiang Peng, Huan Liu, Yafei Hu, Zheng Liu, Eric Li

Proceedings Volume 10602, Smart Structures and NDE for Industry 4.0; 1060207 (2018) https://doi.org/10.1117/12.2300812
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2018, Denver, Colorado, United States

Abstract

Underground pipelines are subject to severe distress from the surrounding expansive soil. To investigate the structural response of water mains to varying soil movements, field data, including pipe wall strains in situ soil water content, soil pressure and temperature, was collected. The research on monitoring data analysis has been reported, but the relationship between soil properties and pipe deformation has not been well-interpreted. To characterize the relationship between soil property and pipe deformation, this paper presents a super learning based approach combining feature selection algorithms to predict the water mains structural behavior in different soil environments. Furthermore, automatic variable selection method, e.i. recursive feature elimination algorithm, were used to identify the critical predictors contributing to the pipe deformations. To investigate the adaptability of super learning to different predictive models, this research employed super learning based methods to three different datasets. The predictive performance was evaluated by R-squared, root-mean-square error and mean absolute error. Based on the prediction performance evaluation, the superiority of super learning was validated and demonstrated by predicting three types of pipe deformations accurately. In addition, a comprehensive understand of the water mains working environments becomes possible.

Conference Presentation

Citation Download Citation

Fang Shi, Xiang Peng, Huan Liu, Yafei Hu, Zheng Liu, and Eric Li "Soil-pipe interaction modeling for pipe behavior prediction with super learning based methods", Proc. SPIE 10602, Smart Structures and NDE for Industry 4.0, 1060207 (27 March 2018); https://doi.org/10.1117/12.2300812

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available