Prediction of ground-borne vibration induced by impact pile driving:numerical approach and experimental validation
作者机构:CONSTRUCT-FEUPUniversity of PortoRua Dr.Roberto Frias4200-465 PortoPortugal University of La CoruñaDepartment of Civil EngineeringCampus de Elviña 15071La CoruñaSpain
出 版 物:《Earthquake Engineering and Engineering Vibration》 (地震工程与工程振动(英文刊))
年 卷 期:2023年第22卷第4期
页 面:921-935页
核心收录:
学科分类:081401[工学-岩土工程] 08[工学] 0814[工学-土木工程]
基 金:Programmatic funding-UIDP/04708/2020 of the CONSTRUCT-Instituto de I&D em Estruturas e Construções-funded by national funds through the FCT/MCTES(PIDDAC) Project PTDC/ECI-CON/29634/2017-POCI-01-0145-FEDER-029634-funded by FEDER funds through COMPETE2020-Programa Operacional Competitividade e Internacionalização(POCI) by national funds(PIDDAC)through FCT/MCTES.Grant No.2022.00898 CEECIND(Scientific Employment Stimulus-5th Edition)provided by “FCT-Fundação para a Ciência e Tecnologia”
主 题:pile driving ground-borne vibrations numerical modeling experimental validation
摘 要:Deep foundations are currently used in engineering practice to solve problems caused by weak geotechnical characteristics of the *** pile driving is an interesting and viable solution from economic and technical points of ***,it is necessary to ensure that the environmental drawbacks,namely ground-borne vibration,are adequately *** this purpose,the authors propose an axisymmetric finite element method-perfectly matched layer(FEM-PML)approach,where the nonlinear behavior of the soil is addressed through an equivalent linear *** the complexity of the problem,an experimental test site was developed and fully *** experimental work comprised in-situ and laboratory soil characterization,as well as the measurement of vibrations induced during pile *** comparison between experimental and numerical results demonstrated a very good agreement,from which it can be concluded that the proposed numerical approach is suitable for the prediction of vibrations induced by impact pile *** experimental database is available as supplemental data and may be used by other researchers in the validation of their prediction models.