Abstract

Robust Optimization Design of Bolt-Shotcrete Support Structure in Tunnel

Highlights

  • Because of the complex tunnel engineering technology and changeable geological environment, there are a lot of accidents frequently occurring during construction process

  • The results show that the method can improve the stability and adaptability of the supporting structure, and reduce the economic cost to the greatest extent, which provides a reference for the optimization design of other geotechnical engineering supporting structures

  • In order to solve the problem that the existing methods are too dependent on the design domain, an origin pedal method was put forward to identify the knee point on Pareto Front curve, which is the only optimal solution in design domain

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Summary

INTRODUCTION

Because of the complex tunnel engineering technology and changeable geological environment, there are a lot of accidents frequently occurring during construction process. Optimizing the supporting parameters to improve the safety and reliability of the supporting structure has become a continuous research topic in the field of tunnel engineering. Juang [10,11,12] first introduced robustness into geotechnical engineering, and put forward a robust design method of geotechnical engineering, which considered the influence of geotechnical parameters statistical characteristic uncertainty on the safety. Robustness can be used to evaluate the sensitivity of structural safety performance to the variability of design parameters, and solve the disturbance caused by parameters’ uncertainty to structural optimization design. The robust optimization design of the bolt-shotcrete support structure in tunnel is carried out, considering design objectives and design constraints. The Pareto front is formed by these non-dominant solutions, which can be called optimal design set

ROBUST OPTIMIZATION DESIGN OF BOLTSHOTCRETE SUPPORT STRUCTURE IN TUNNEL
Robustness Index
Design Parameters
Noise Factors
Multiobjective Optimization
Optimization Design
Relative Optimal Solution
Findings
CONCLUSION

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