A deep-learning method for evaluating shaft resistance of the cast-in-site pile on reclaimed ground using field data

作     者：Sheng-liang LU Ning ZHANG Shui-long SHEN Annan ZHOU Hu-zhong LI Sheng-liang LU;Ning ZHANG;Shui-long SHEN;Annan ZHOU;Hu-zhong LI

作者机构：Department of Civil and Environmental EngineeringCollege of EngineeringShantou UniversityShantou 515063China Key Laboratory of Intelligence Manufacturing Technology of Ministry of EducationShantou UniversityShantou 515063China Department of Architecture and Civil EngineeringWenzhou Vocational and Technical CollegeWenzhou 325000China Discipline of Civil and InfrastructureSchool of EngineeringRoyal Melbourne Institute of Technology(RMIT)Victoria 3001Australia Wenzhou Huabang Engineering Project Management Co.Ltd.Wenzhou 325207China 

基　　金：the Research Funding of Shantou University for New Faculty Member(No.NTF19024-2019) the National Nature Science Foundation of China(No.41372283) 

出 版 物：《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 (浙江大学学报（英文版）A辑（应用物理与工程）)

年 卷 期：2020年第21卷第6期

页      码：496-508页

摘      要：This study proposes a deep learning-based approach for shaft resistance evaluation of cast-in-site piles on reclaimed ground,independent of theoretical hypotheses and engineering experience.A series of field tests was first performed to investigate the characteristics of the shaft resistance of cast-in-site piles on reclaimed ***,an intelligent approach based on the long short term memory deep-learning technique was proposed to calculate the shaft resistance of the cast-in-site *** proposed method allows accurate estimation of the shaft resistance of cast-in-site piles,not only under the ultimate load but also under the working *** with empirical methods confirmed the effectiveness of the proposed method for the shaft resistance estimation of cast-in-site piles on reclaimed ground in offshore areas.

主 题 词：Deep-learning method Cast-in-site pile Shaft resistance Field test Reclaimed ground 

学科分类：081401[081401] 08[工学] 0814[工学-地质类] 

核心收录：

D　O　I：10.1631/jzus.A1900544

馆 藏 号：203938285...