Predicting Rock Burst in Underground Engineering Leveraging a Novel Metaheuristic-Based LightGBM Model

Rock bursts represent a formidable challenge in underground engineering,posing substantial risks to both infrastructure and human safety.These sudden and violent failures of rock masses are characterized by the rapid release of accumulated stress within the rock,leading to severe seismic events and structural damage.Therefore,the development of reliable prediction models for rock bursts is paramount to mitigating these hazards.This study aims to propose a tree-based model—a Light Gradient Boosting Machine(LightGBM)—to predict the intensity of rock bursts in underground engineering.322 actual rock burst cases are collected to constitute an exhaustive rock burst dataset,which serves to train the LightGBMmodel.Two population-basedmetaheuristic algorithms are used to optimize the hyperparameters of the LightGBM model.Finally,the sensitivity analysis is used to identify the predominant factors that may incur the occurrence of rock bursts.The results show that the population-based metaheuristic algorithms have a good ability to search out the optimal hyperparameters of the LightGBM model.The developed LightGBM model yields promising performance in predicting the intensity of rock bursts,with which accuracy on training and testing sets are 0.972 and 0.944,respectively.The sensitivity analysis discloses that the risk of occurring rock burst is significantly sensitive to three factors:uniaxial compressive strength(σc),stress concentration factor(SCF),and elastic strain energy index(Wet).Moreover,this study clarifies the particular impact of these three factors on the intensity of rock bursts through the partial dependence plot.

Application of Glass Fiber Reinforced Polymer Composite (GFRPC) Escape Pipeline in Tunnel

During the tunnel construction process,unfavorable geological conditionsare often encountered.Geological disasters such as collapse,roof fall,water inrush,gas explosion,etc.occur frequently,causing different degrees of property damage and casualties to the construction of the tunnel,seriously affecting harmony during construction.The domestic emergency hedging is mainly the use of 8-10mm steel coils,but the steel is heavy and not suitable for the frequent movement of tunnels.This paper introduces the new Glass Fiber Reinforced Polymer Composite(GFRPC)escape pipeline used in Chongqing Jiuyongyi Jinyunshan Tunnel,and compares the traditional steel coil parameters to provide reference for subsequent tunnel hedging measures.

Facile fabrication of dolomite-doped biochar/bentonite for effective removal of phosphate from complex wastewaters

The removal of phosphate from wastewater using traditional biological or precipitation methods is a huge challenge.The use of high-performance adsorbents has been shown to address this problem.In this study,a novel composite adsorbent,composed of dolomite-doped biochar and bentonite(DO/BB),was first synthesized via co-pyrolysis.The combination of initial phosphate concentration of 100 mg/L and 1.6 g/L of DO/BB exhibited a high phosphate-adsorption capacity of 62 mg/g with a removal efficiency of 99.8%.It was also stable in complex water environments with various levels of solution pH,coexisting anions,high salinity,and humic acid.With this new composite,the phosphate concentration of the actual domestic sewage decreased from 9 mg/L to less than 1 mg/L,and the total nitrogen and chemical oxygen demand also decreased effectively.Further,the cross-flow treatment using a PVC membrane loaded with DO/BB(PVC-DO/BB),decreased the phosphate concentration from 1 to 0.08 mg/L,suggesting outstanding separation of phosphate pollutants via a combination of adsorption and separation.In addition,the removal of phosphate by the PVC-DO/BB membrane using NaOH solution as an eluent was almost 90%after 5 cycles.The kinetic,isotherm and XPS analysis before and after adsorption suggested that adsorption via a combination of electrostatic interaction,complexation and precipitation contributed to the excellent separation by the as-obtained membranes.

Mechanical properties and strengthening mechanism of silty sands stabilized with steel slag-based geopolymer binder

Geopolymer binder has the advantages of early strength,fast solidification,high volume stability,and low permeability.It is beneficial to improve the mechanical performance of silty sands,saving cement consumption and being environmentally friendly.However,the strength improvement of silty sand stabilized with steel slag-based geopolymer was significantly controlled by their material composition and technical parameters.This study conducted a series of unconfined compression tests to investigate the material composition of steel slag-based geopolymer binders and their reasonable mixing ratio for silty sand stabilization.The optimum mixing ratio of precursor(steel slag)to alkaline activator(the combination of Na2SiO3 and CaO)and the optimum dosage of steel slag-based geopolymer for silty sand stabilization were explored.The strengthening mechanism of geopolymer-stabilized silty sands was discussed based on microstructural images and elemental concentrations of primary components observed by SEM and EDS.The results show that when the mass ratio of steel slag:Na2SiO3:CaO was 80:35:21,and the steel slag-based geopolymer material was 15%,the silty sand could achieve the best mechanical performance improvement.The microstructural characteristics of geopolymer-stabilized silty sands at different curing ages illustrated that the compactness and integrity of silty sand structures were enhanced over the curing age.The improving cementitious contact among particles and enlarging particle size was responsible for the strength improvement of silty sand.This research can provide a reference for applying steel slag-based geopolymer in silty sand stabilization in engineering practices.

Intelligent feedback analysis on a deep excavation for the gravity anchorage foundation of a super suspension bridge

In order to ensure the construction safety of the 38.5 m deep excavation for the gravity anchorage foundation of Fuma Yangtze River Bridge, an intelligent feedback analysis was applied to this excavation project. First, a three-dimensional numerical model that simulating the construction process of the excavation was built,and the deformations of the supporting structures were calculated by the finite difference program FLAC3 D. Then,the non-linear mapping relationship between the geomechanical parameters and the excavation-induced displacements was established by the back-propagation neural network(BPNN). Last,the geomechanical parameters were optimized intelligently by the genetic algorithm(GA) based on the developed BPNN model and the measured displacements,and the deformations during the subsequent excavation stages were predicted based on the back-calculated parameters. The research results showed that:the back-calculated values of E1,μ1,c1,and φ1 of the completely weathered stratum,and E2 of the heavily weathered stratum were greater than the initial values,while the inversion value of E3 of the moderately weathered stratum was smaller than the initial value. The magnitudes and the variation tendencies of the predicted displacements were in good accordance with the measured displacements. At the end of the excavation,the retaining piles and the top beams had a maximum displacement of 15–20 mm,exhibiting a quite small magnitude as comparing with other case histories. Local concentration of shear stress mainly occurred at the soil-pile interface and at the toe of the excavation slope,and the plastic zones mainly appeared in the completely weathered stratum. After the completion of the excavation,there were no yielding elements in the model,and the convergence of the numerical computation was achieved,indicating the excavation was in a stable state. This study lays the basis for the subsequent construction and operation of the bridge,and offers a significant reference for the feedback analysis of similar anchorage excavation projects.