Abstract

This paper employs a back analysis method to determine soil strength parameters of the Mohr-Coulomb model from in situ geotechnical measurements. The lateral displacement of a soil nailed wall retaining an excavation in Tehran city used as a criterion for the back analysis. For this purpose, a genetic algorithm is applied as an optimization algorithm to minimize the error function, which can perform the back analysis process. When the accuracy of modeling is verified, the back analysis is performed automatically by creating a link between genetic algorithm in MATLAB and Abaqus software using Python programming language. This paper demonstrated that the genetic algorithm is a particularly suitable tool to determine 9 soil strength parameters simultaneously for 3 soil layers of the project site to decrease the difference of lateral displacement between the results of project monitoring and numerical analysis. The soil strength parameters have increased, with the most changes in Young's modulus of the first to third layers as the most effective parameter, 49.45%, 61.67% and 64.35% respectively. The results can be used in advanced engineering analyses and professional works.

Highlights

  • Geotechnical in situ tests do not permit the identification of the soil parameters directly, which is considered as a limitation in engineering works

  • The lateral displacement of the soil nailed wall is affected by excessive uplift and has unreasonable lateral displacement, this problem is due to the soil elasticity modulus in the reloading situation is equal to the loading condition in Abaqus, which may lead to overestimation of uplift in the excavation bottom

  • The lateral displacement of the west wall ux is used as a criterion for determining the soil strength parameters

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Summary

Introduction

Geotechnical in situ tests do not permit the identification of the soil parameters directly, which is considered as a limitation in engineering works. Hui et al (2015) conducted a study to optimize the dynamic design of tunnels in shallow rock masses They used Python programming language to set up a dynamic model of tunnel span that could be analyzed and implemented via Abaqus software. Zhang et al (2014) presented the applications of the differential evolution (DE) algorithm in back analysis of soil parameters for deep excavation problems They used Python programming language based on DE to develop and incorporate into the commercial finite element software ABAQUS, a synthetic case and a well-instrumented real case (Taipei National Enterprise Center) is used to demonstrate the capability of the proposed back-analysis procedure. The multi-objective model is constructed by minimizing a set of multiobjective error functions between the time series of observations and corresponding calculated values They used the obtain inversion parameters in a forward analysis to predict displacements. The genetic algorithm is used as an effective method for the back analysis of a soil nailed wall by establishing a link between MATLAB and Abaqus software using Python programming language

Objective of Back Analysis in Geotechnical Problems
Stages in the Genetic Algorithm Optimization Method
Error Function
Convergence Criteria
Verification
Introduction of Case Study
Excavation Protection System and Loading
Numerical modeling via Python programming language by Abaqus software
Parameters of Genetic Algorithm
10. Investigation into Effective Parameters of Genetic Algorithm
11. Back Analysis Results
12. Conclusion
14. References

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