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J u n e 0 6 - 0 7 , 2 0 1 9

P a r i s , F r a n c e

Page 29

Research & Reviews: Journal of Engineering and Technology

ISSN: 2319-9873

Civil engineering 2019

International Conference on

Structural and

Civil Engineering Research

T

he displacement prediction of retaining structure is a key problem in

foundation pit engineering which has many influencing factors and the

function is highly non-linear, so there are some shortcomings such as low

accuracy, slow convergence and heavy calculation when using traditional

response surface prediction. The displacement prediction model using

improved multiple response surfaces (MRS) is proposed to solve such

problems. Taking the shear strength parameters of soil as the key design

variables, taking the displacement of diaphragmwall retaining structure (DWRS)

at different working conditions and different depths as the target parameters,

the response surfaces between design variables and target parameters are

established combining uniform test design method and ACE non-parametric

regression technology. Based on Monte Carlo simulation technology and least

square approximation principle, the original design parameters are inverted by

using the monitoring data of existing working conditions and the established

MRS. Finally, the displacement prediction of DWRS for following working

conditions are obtained based on the modified design parameters. The case

study shows that the values of displacement prediction are consistent with

measured data based on MRS and the calculation convergence speed is

fast, which can be used to guide the design and subsequent construction of

foundation pit.

Biography

Jiang kaiyu is pursuing PhD degree in Southeast University

and also a Teacher in Chongqing three Gorges University from

China. His major research area is composite foundation and

foundation pit engineering. He has published more than eight

papers in reputed journals.

jiang_k_y@seu.edu.cn

Displacement prediction of foundation pit retaining structure

based on multiple response surfaces

Jiang Kaiyu, Gong Weiming and Dai Guoliang

Southeast University, China

Jiang Kaiyu et al., JET 2019, Volume:8