Firefly Optimization Algorithm for the Prediction of Uplift due to High‐Pressure Jet Grouting

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 Δ a , 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.

Study on the Construction Method and Effects of Ipsilateral, Multi-Nozzle, High-Pressure Jet Grouting Cut-Off Wall

“…(9) Slurry transportation, gas transportation, static injection and lift injection Adjust the drill pipe so that the nozzle faces the direction of the previous drilling, pause the rotation of the drill pipe, jet high-pressure cement slurry from the nozzle on the side of the drill bit, and then lift the jet rod to mix the cement slurry fully with the formation materials after breaking the formation. (10) Lift the nozzle to the design elevation, stop jetting, and move it to the next hole. (11) Consolidate into a wall Repeat the above steps, in a hole-by-hole cycle, to form a continuous and complete high-pressure jet grouting cut-off wall.…”

“…Since the drilling holes are small, the drill pipe is relatively thin and the rigidity is small, in order to balance the grouting pressure released by the nozzle, the nozzles at the bottom of the nozzle are usually arranged in opposite directions [9]. Therefore, the conventional high-pressure jet grouting method has the problem of low drilling efficiency [10]. Specifically, once the conventional high-pressure jet grouting meets the thicker particles, the nozzle is blocked, which makes it difficult to drill holes and ensure the continuity and integrity of the wall surface, and it is easy to cause the quality defects of local leakage jet grouting [11,12].…”

A review of swarm intelligence algorithms deployment for scheduling and optimization in cloud computing environments

“…To solve several non-linear ''convex'' optimal power flow (OPF), a hybrid algorithm consists of FA and PSO named ''HFPSO'' algorithm was introduced by Khan et al (2020). Additionally, Dai, Liang & Zhang (2020) proposed a new FA-based algorithm to search for the optimal solution for uplift effect in the high-pressure jet grouting (HPJG) project. Another study (Peng et al, 2018) proposed a hybrid fish swarm algorithm based on the behavior of Lévy flight and firefly named LFFSA to overcome the problem of local optimum convergence.…”

Modeling diameter of jet grouting columns using Bayesian framework

“…However, these models were mainly derived from cases using single a jet grouting system. Some researchers 28,29 found imperfections when dealing with double and triple jet grouting systems with high pressure. In recent years, some scholars [30][31][32] introduced artificial intelligence (AI) methods into this field and established different AI models.…”