Abstract

A project that needs to be uplifted by high‐pressure jet grouting (HPJG) is exposed to particular geological and engineering circumstances; meanwhile, HPJG has intense subjectivity, short of the theoretical base, to ascertain the influence angle β and enlarged radius Δa, which are the main parameters that affect the uplift effect. Therefore, we proposed a new method based on the firefly optimization algorithm to search for the optimal solution for the target function. Stochastic medium theory (SMT) was used in this article, in which the effect of single‐pile HPJG was simulated as the superposition effect of the foam slurry at the same distance, to construct a stochastic medium prediction model of the effect of uplift due to multi‐HPJG. In accordance with the range of the prediction results of single‐pile HPJG and combined with in situ monitoring data to define the target function, the optimal parameters are substituted into the prediction model to predict the subsequent uplift effect due to HPJG. As a result of the global optimization capacity and by comparison with the genetic algorithm, the FOA has a greater advantage in terms of effectiveness and precision. Finally, it is proven that the prediction result meets the requirement of the prediction in advance by statistical data.

Highlights

  • high-pressure jet grouting (HPJG) construction technology was developed in Japan in the 1970s and has been used as a primary technique in ground reinforcement projects because it has a wide range of applications in small working spaces; piles provide a higher bearing capacity [1,2,3,4,5].Grouting uplift technology reinforces the target ground by the grouting method and forces the ground surface or building to move upward to control and rectify the subsoil subsidence of the existing building

  • HPJG has favorable pile-forming performance, and the soil was compressed via the thick slurry injection in a borehole to realize surface uplift, which was different from pressure grouting. is method had a smaller dispersion area, and the effect of single piles on the surface uplift was less obvious than that of pressure grouting; the superposition effect of multi-HPJG grouting comprising multiple jet grouting piles can effectively realize the purpose of rectification [2,3,4,5]

  • Using stochastic medium theory to establish the deformation prediction model to predict the uplift due to HPJG, we proposed a new method to make an optimization algorithm through the target function established by the main influence angle β and enlarged radius Δα searched by the FOA and a genetic algorithm combined with in situ monitoring data. e results show that FOA has a greater advantage in the effectiveness and prediction precision

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Summary

Introduction

HPJG construction technology was developed in Japan in the 1970s and has been used as a primary technique in ground reinforcement projects because it has a wide range of applications in small working spaces; piles provide a higher bearing capacity [1,2,3,4,5]. With an existing project, based on the stochastic medium theory in rock movement introduced by the Polish scholar Litwiniszyn [16,17,18,19,20], this article established a theoretical computation model of simulating the uplift process induced by HPJG. Combined with the in situ monitoring data, this article used swarm intelligence optimization algorithm and genetic algorithm of evolution algorithm to define target function, respectively, in order to obtain the main flurry foam influence angle β and enlarged radius Δa, which are the main parameters that affect the uplift effect induced by HPJG, and substitute the optimal parameter into the prediction model, respectively, to predict the uplift displacement due to HPJG theoretically. We made a comparison with the two kinds of optimization algorithms in many ways and made a mutual check with the in situ monitoring data. e purpose was to control and rectify the foundation subsidence of existing buildings and structures based on this method

The Surface Uplift Induced by HPJG
The Scope of the Prediction of Uplift due to HPJG
The Comparison of the Optimization Algorithms for β and Δa
Analysis of the Uplift Effect Predictions
Conclusion and Discussion

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