A modified back analysis method for deep excavation with multi-objective optimization procedure

Real-time prediction of excavation-induced displacement of retaining pile during the deep excavation process is crucial for construction safety.This paper proposes a modified back analysis method with multi-objective optimization procedure,which enables a real-time prediction of horizontal displacement of retaining pile during construction.As opposed to the traditional stage-by-stage back analysis,time series monitoring data till the current excavation stage are utilized to form a multi-objective function.Then,the multi-objective particle swarm optimization (MOPSO) algorithm is applied for parameter identification.The optimized model parameters are immediately adopted to predict the excavation-induced pile deformation in the continuous construction stages.To achieve efficient parameter optimization and real-time prediction of system behavior,the back propagation neural network (BPNN) is established to substitute the finite element model,which is further implemented together with MOPSO for automatic operation.The proposed approach is applied in the Taihu tunnel excavation project,where the effectiveness of the method is demonstrated via the comparisons with the site monitoring data.The method is reliable with a prediction accuracy of more than 90%.Moreover,different optimization algorithms,including non-dominated sorting genetic algorithm (NSGA-II),Pareto Envelope-based Selection Algorithm II (PESA-II) and MOPSO,are compared,and their influences on the prediction accuracy at different excavation stages are studied.The results show that MOPSO has the best performance for high dimensional optimization task.

A post-peak dilatancy model for soft rock and its application in deep tunnel excavation

The dilation angle is the most commonly used parameter to study nonlinear post-peak dilatancy(PPD)behavior and simulate surrounding rock deformation;however,simplified or constant dilatancy models are often used in numerical calculations owing to their simple mathematical forms.This study developed a PPD model for rocks(rock masses)based on the Alejanoe-Alonso(A-A)dilatancy model.The developed model comprehensively reflects the influences of confining pressure(σ_(3))and plastic shear strain(γ^(p)),with the advantages of a simple mathematical form,while requiring fewer parameters and demonstrating a clear physical significance.The overall fitting accuracy of the PPD model for 11 different rocks was found to be higher than that of the A-A model,particularly for Witwatersrand quartzite and jointed granite.The applicability and reliability of the PPD model to jointed granites and different scaled Moura coals were also investigated,and the model was found to be more suitable for the soft and large-scale rocks,e.g.deep rock mass.The PPD model was also successfully applied in studying the mechanical response of a circular tunnel excavated in strain-softening rock mass,and the developed semi-analytical solution was compared and verified with existing analytical solutions.The sensitivities of the rock dilatancy to γ^(p) and σ_(3) showed significant spatial variabilities along the radial direction of the surrounding rock,and the dilation angle did not exhibit a monotonical increasing or decreasing law from the elasticeplastic boundary to the tunnel wall,thereby presenting the σ3-or γ^(p)-dominated differential effects of rock dilatancy.Tunnel deformation parabolically or exponentially increased with increasing in situ stress(buried depth).The developed PPD model is promising to conduct refined numerical and analytical analyses for deep tunneling,which produces extensive plastic deformation and exhibits significant nonlinear post-peak behavior.

Construction Technology and Safety Risk Control Measures of Deep Foundation Pit Excavation

Deep foundation pit excavation is a basic and key step involved in modern building construction.In order to ensure the construction quality and safety of deep foundation pits,this paper takes a project as an example to analyze deep foundation pit excavation technology,including the nature of this construction project,the main technical measures in the construction of deep foundation pit,and the analysis of the safety risk prevention and control measures.The purpose of this analysis is to provide scientific reference for the construction quality and safety of deep foundation pits.

Deterministic and probabilistic analysis of great-depth braced excavations:A 32 m excavation case study in Paris

The Fort d’Issy-Vanves-Clamart(FIVC)braced excavation in France is analyzed to provide insights into the geotechnical serviceability assessment of excavations at great depth within deterministic and probabilistic frameworks.The FIVC excavation is excavated at 32 m below the ground surface in Parisian sedimentary basin and a plane-strain finite element analysis is implemented to examine the wall deflections and ground surface settlements.A stochastic finite element method based on the polynomial chaos Kriging metamodel(MSFEM)is then proposed for the probabilistic analyses.Comparisons with field measurements and former studies are carried out.Several academic cases are then conducted to investigate the great-depth excavation stability regarding the maximum horizontal wall deflection and maximum ground surface settlement.The results indicate that the proposed MSFEM is effective for probabilistic analyses and can provide useful insights for the excavation design and construction.A sensitivity analysis for seven considered random parameters is then implemented.The soil friction angle at the excavation bottom layer is the most significant one for design.The soil-wall interaction effects on the excavation stability are also given.

A case study on behaviors of composite soil nailed wall with bored piles in a deep excavation

A complete case of a deep excavation was explored. According to the practical working conditions, a 3D non-linear finite element procedure is used to simulate a deep excavation supported by the composite soil nailed wall with bored piles in soft soil. The modified cam clay model is employed as the constitutive relationship of the soil in the numerical simulation. Results from the numerical analysis are fitted well with the field data, which indicate that the research approach used is reliable. Based on the field data and numerical results of the deep excavation supported by four different patterns of the composite soil nailed wall, the significant corner effect is founded in the 3D deep excavation. If bored piles or soil anchors are considered in the composite soil nailed wall, they are beneficial to decreasing deformations and internal forces of bored piles, cement mixing piles, soil anchors, soil nailings and soil around the deep excavation. Besides, the effects due to bored piles are more significant than those deduced from soil anchors. All mentioned above prove that the composite soil nailed wall with bored piles is feasible in the deep excavation.

Prediction of Rock Burst with Deep Mining Excavation in Linglong Gold Mine

To predict rock burst in deep mining excavation in Linglong gold mine, systematical laboratory tests of mechanical properties of rock, in situ stress measurement and 3-D FEM analysis on energy distribution in rock mass surrounding deep mining rooms were carried out. According to various prediction criteria of rock burst, it is concluded that rock burst is liable to occur during deep mining excavation in the mine.

Lessons learnt from a deep excavation for future application of the observational method

This paper draws lessons learnt from a comprehensive case study in overconsolidated clay. Apart from the introduction of the case study, including field measurements, the paper draws on the observations and a three-dimensional（3 D） numerical analysis to discuss the implications of observations in the application of the observational method（OM） in the context of the requirements of EUROCODE 7（EC7）.In particular, we focus on corner effects and time-dependent movements and provide initial guidance on how these could be considered. Additionally, we present the validation of a new set of parameters to check that it provides a satisfactory compliance with EC7 as a set of design parameters. All these findings and recommendations are particularly important for those who want to use the OM in similar future projects.

Deformation Control of Deep Excavation Pit and Numerical Simulation with Finite Element Method

The authors firstly introduce deformation control of deep excavation pit indetail, and then put forward new conceptions such as: effective coefficient of excavation pit,effective area, ineffective area and critical line, and also put forward the referential criteria ofdeformation control. The System of Optimization Design with Deformation Control of Deep ExcavationPit and Numerical Simulation with Finite Element Method (SDCDEFEM) is also briefly introduced.Factors influencing deformation of excavation pit are analyzed by the system. The measured andsimulated data of maximum deformations (settlement, displacement and upheaval) and their positionsare analyzed and discussed. The statistic formula estimating maximum deformations and theirpositions was gained, and economical-effective measures of deformation control were brought forward.

Deep Foundation Pit Excavations Adjacent to Disconnected Piled Rafts: A Review on Risk Control Practice

Foundation pit excavation engineering is an old subject full of decision making. Yet, it still deserves further research due to the associated high failure cost and the complexity of the geological conditions and/or the surrounding existing infrastructure around it. This article overviews the risk control practice of foundation pit excavation projects in close proximity to existing disconnected piled raft. More focus is given to geotechnical aspects. The review begins with achievements to ensure excavation performance requirements, and follows to discuss the complex soil structure interaction involved among the fundamental components: the retaining wall, mat, piles, cushion, and the soil. After bringing consensus points to practicing engineers and decision makers, it then suggests possible future research directions.

Research on Robotized Advance Support and Supporting Time for Deep Fully Mechanized Excavation Roadway

To keep coal workers away from the hazardous area with frequent accidents such as the roof fall and rib spalling in an underground coalmine,we put forward the solution with robotized self-moving anchor-supporting unit.The existing research shows that the surrounding rock of the roadway has self-stability,and the early or late support is not conducive to the safe and reliable support of the roadway,so there is a problem of support opportunity.In order to study the supporting effect and the optimal supporting time of the above solution,we established the mechanical coupling model of surrounding rock and advance support,and investigated the surrounding rock deformation and advance support pressure distribution under different reserved roof subsidence by using the numerical simulation software FLAC3D.The results show that the deformation of surrounding rock increases and finally tends to a stable level with the increase of pre settlement of roadway roof,and when the pre settlement of roof is between 8-15 mm,the vertical pressure of the top beam of advance support reaches the minimum value,about 0.58 MPa.Based on the above research,we put forward the optimum supporting time in roadway excavation,and summarized the evaluation method based on the mechanical coupling model of surrounding rock-advance support.

Predicting the strut forces of the steel supporting structure of deep excavation considering various factors by machine learning methods

The application of steel strut force servo systems in deep excavation engineering is not widespread,and there is a notable scarcity of in-situ measured datasets.This presents a significant research gap in the field.Addressing this,our study introduces a valuable dataset and application scenarios,serving as a reference point for future research.The main objective of this study is to use machine learning(ML)methods for accurately predicting strut forces in steel supporting structures,a crucial aspect for the safety and stability of deep excavation projects.We employed five different ML methods:radial basis function neural network(RBFNN),back propagation neural network(BPNN),K-Nearest Neighbor(KNN),support vector machine(SVM),and random forest(RF),utilizing a dataset of 2208 measured points.These points included one output parameter(strut forces)and seven input parameters(vertical position of strut,plane position of strut,time,temperature,unit weight,cohesion,and internal frictional angle).The effectiveness of these methods was assessed using root mean square error(RMSE),correlation coefficient(R),and mean absolute error(MAE).Our findings indicate that the BPNN method outperforms others,with RMSE,R,and MAE values of 72.1 kN,0.9931,and 57.4 kN,respectively,on the testing dataset.This study underscores the potential of ML methods in precisely predicting strut forces in deep excavation engineering,contributing to enhanced safety measures and project planning.

Performance and environmental impacts of deep foundation excavation in soft soils:A field and modeling-based case study in Nanjing,China

This paper focuses on the performance of a braced deep excavation in soft soil based on field monitoring and numerical modeling.Laboratory tests were conducted to determine the soil parameters used in the modified Cam–Clay(MCC)model.Intelligent field monitoring means were adopted and a three-dimensional model was established.Spatial and temporal effects induced by the excavation are investigated for the deep-large foundation pit in soft soil.Deformation characteristics of the enclosure structure and the surrounding environment throughout the excavation process are presented.The behaviors of diaphragm walls,columns,the maximum wall deflection rate,ground surface settlement,and utility pipelines were focused on and investigated during the whole excavation process.Besides,the axial forces of the internal supports are analyzed.Based on the measured and simulated data,the following main conclusions were obtained:the numerical simulation results are in good agreement with the measured values,which proves the accuracy of the model parameters;the wall and the ground surface showed the maximum displacement increment at stage 9,which was a coupled product of the"creep effect"of the soft soil in Nanjing,China and the"depth effect"of the excavation;as the excavation progressed,the ground settlement changed from a"rising"to a"spoon-shaped"trend,dvm was measured betweenδ_(vm)=0.0686%H andδ_(vm)=0.1488%H;the rebound deformation curve of the pit bottom was corrugated,and the depth of disturbance of the pit bottom after the completion of soil unloading was 2–3 times the excavation depth;the closer the pipeline is to the corner of the pit,the less the excavation process will affect the settlement of the pipeline and the less the obvious pit corner effect will occur;the support strength of the buttress and the longest corner brace should be strengthened during the actual construction process to ensure the stability of the foundation deformation.

Unloading responses of pre-flawed rock specimens under different unloading rates

Based on the stress redistribution analysis of rock mass during the deep underground excavation, the unloading process of pre-flawed rock material was simulated by distinct element method (DEM). The effects of unloading rate and flaw inclination angle on unloading strengths and cracking properties of pre-flawed rock specimens are numerically revealed. The results indicate that the unloading failure strength of pre-flawed specimen exhibits a power-function increase trend with the increase of unloading period. Moreover, combined with the stress state analysis on the flaws, it is found that the unloading failure strength increases with the increase of flaw inclination angle. The cracking distribution of pre-flawed specimens under the unloading condition closely depends on the flaw inclination angle, and three typical types of flaw coalescence are observed. Furthermore, at a faster unloading rate, the pre-flawed specimen experiences a sharper and quicker unloading failure process, resulting in more splitting cracks in the specimens.

Application of Modified Genetic Algorithm to Optimal Design of Supporting Structure

The modified genetic algorithm was used for the optimal design of supporting structure in deep pits.Based on the common genetic algorithm, using niche technique and reserving the optimum individual the modified genetic algorithm was presented. By means of the practical engineering, the modified genetic algorithm not only has more expedient convergence, but also can enhance security and operation efficiency.

Performance of a deep excavation and the influence on adjacent piles:A case history in karst region covered by clay and sand

This paper presents a case study of deep excavation adjacent to an existing bridge in karst region of Guangzhou city,China.The movements of retaining structures,settlements of surrounding ground and pipelines,and the responses of bridge piles were measured and evaluated.A sudden surge of groundwater was recorded at the north pit when excavated halfway.Soil-cement columns using the Metro Jet System(MJS)method was employed along the outer perimeters of the diaphragm wall where water inflow occurred,for the sake of blocking the flow channels.The measured maximum wall deflection dhm in this case ranged from 0.13%H to 0.3%H,with a mean value of 0.2%H(H is the excavation depth),which agreed well with the empirical prediction in mixed ground.During the MJS treatment,the wall and surrounding soils experienced notable lateral deflection and settlement.The bridge piles experienced significant settlement since the excavation commenced,which might be attributed to the inherent deficiency in geological condition and pile length.The soil disturbance induced by the adjacent deep excavation accelerated bridge settlement.The finite element analysis revealed that the excessive settlement of the bridge piles and ground surface resulted from confined-water withdrawal in sand layers.

Reliability assessment of deep excavations in spatially random cohesion weakening friction strengthening massive rocks:Application to nuclear repositories

An augmented methodology is developed to estimate the reliability of deep excavations along spatially variable massive rock masses using the cohesion weakening friction strengthening(CWFS)model.Sensitive parameters of the CWFS model were initially identified using Sobol’s global sensitivity analysis based on their influence on the displacements and excavation damage zone around excavations.The probability of failure was estimated by performing Mont–Carlo Simulations on random finite difference models of excavations generated via MATLAB-FLAC2D coupling,considering the spatial variation of these sensitive parameters.Spatial variation was modeled by generating anisotropic random fields of sensitive CWFS parameters via the recently developed Fourier series method and updated correlations suggested by Walton(2019).The proposed methodology was demonstrated for a proposed deep nuclear waste repository to be located in Canada.Results from the developed methodology were systematically compared with those of traditional reliability(ignoring spatial variation)and deterministic methods(ignoring uncertainty).Although the developed methodology was computationally complex,it was judged to be the most realistic due to the realistic consideration of heterogeneous distributions of rock properties.Traditional methodologies underestimate/overestimate the excavation performance due to negligence of uncertainty and spatial variability.Finally,a parametric analysis was performed using developed methodology by varying the initial friction angle,scale of fluctuations(SOFs)and dilation angle.The effect of initial friction angle was observed to be more pronounced on the probability of failures as compared to SOFs and dilation angle.Similar observations were made related to the excavation damage zone(EDZ)development quantified using yield area ratio.

Adaptive mutation sparrow search algorithm-Elman-AdaBoost model for predicting the deformation of subway tunnels

A novel coupled model integrating Elman-AdaBoost with adaptive mutation sparrow search algorithm(AM-SSA),called AMSSAElman-AdaBoost,is proposed for predicting the existing metro tunnel deformation induced by adjacent deep excavations in soft ground.The novelty is that the modified SSA proposes adaptive adjustment strategy to create a balance between the capacity of exploitation and exploration.In AM-SSA,firstly,the population is initialized by cat mapping chaotic sequences to improve the ergodicity and randomness of the individual sparrow,enhancing the global search ability.Then the individuals are adjusted by Tent chaotic disturbance and Cauchy mutation to avoid the population being too concentrated or scattered,expanding the local search ability.Finally,the adaptive producer-scrounger number adjustment formula is introduced to balance the ability to seek the global and local optimal.In addition,it leads to the improved algorithm achieving a better accuracy level and convergence speed compared with the original SSA.To demonstrate the effectiveness and reliability of AM-SSA,23 classical benchmark functions and 25 IEEE Congress on Evolutionary Computation benchmark test functions(CEC2005),are employed as the numerical examples and investigated in comparison with some wellknown optimization algorithms.The statistical results indicate the promising performance of AM-SSA in a variety of optimization with constrained and unknown search spaces.By utilizing the AdaBoost algorithm,multiple sets of weak AMSSA-Elman predictor functions are restructured into one strong predictor by successive iterations for the tunnel deformation prediction output.Additionally,the on-site monitoring data acquired from a deep excavation project in Ningbo,China,were selected as the training and testing sample.Meanwhile,the predictive outcomes are compared with those of other different optimization and machine learning techniques.In the end,the obtained results in this real-world geotechnical engineering field reveal the feasibility of the proposed hybrid algorithm model,illustrating its power and superiority in terms of computational efficiency,accuracy,stability,and robustness.More critically,by observing data in real time on daily basis,the structural safety associated with metro tunnels could be supervised,which enables decision-makers to take concrete control and protection measures.

Base stability analysis of braced deep excavation in undrained anisotropic clay with upper bound theory

It is imperative to evaluate factor of safety against basal heave failure in the design of braced deep excavation in soft clay.Based on previously published field monitoring data and finite element analyses of ground settlements of deep excavation in soft clay,an assumed plastic deformation mechanism proposed here gives upper bound solutions for base stability of braced deep excavations.The proposed kinematic mechanism is optimized by the mobile depth(profile wavelength).The method takes into account the influence of strength anisotropy under plane strain conditions,the embedment of the retaining wall,and the locations of the struts.The current method is validated by comparison with published numerical study of braced excavations in Boston blue clay and two other cases of excavation failure in Taipei.The results show that the upper bound solutions obtained from this presented method is more accurate as compared with the conventional methods for basal heave failure analyses.

Effects of jet grouting slabs on responses for deep braced excavations

Jet grouting slabs are widely used in deep excavations owing to their effectiveness for reducing the deflection of the diaphragm wall and the prop forces acting on the struts and improving the basal-heave stability.In this paper,according to case histories in Singapore,a series of finite-element numerical simulations are performed to evaluate the effects of jet grouting slabs on responses to deep braced excavations.On the basis of a parametric sensitivity study,a reasonable thickness of jet grouting slabs is proposed.The effects of the wall depth,wall stiffness,soft-clay thickness,and stiffness on the performance of the jet grouting slabs are assessed by comparing and analyzing a series of simulation results.It is found that the soft-clay thickness significantly affects the wall deflection and basal heave in deep excavation.During the design of support structures,soil profiles should be considered first.The findings of this study provide a reference and guidance for the support system design of similar projects.

Tunneling and deep excavations in spatially variable soil and rock masses:A short review

In an urbanization process,infrastructure elements such as tunnels and deep excavations are widely used to service the development of cities.Owing to the lengthy geological processes of geomaterials and the limited availability of site-specific test data,soil and rock properties exhibiting spatial variability are frequently encountered in geological and geotechnical engineering.This paper presents a comprehensive review of the application of spatial variability in tunneling and deep excavation over the past 20 years.It is found that the spatial variability is generally modeled as a random field(RF)in finite element software,based on random field theory(RFT).This model has been widely used in the design,stability evaluation,and probabilistic analysis of tunnels and excavations.Previous works have proven that the performance of tunnels and deep excavations can be better captured by considering the spatial variability,as compared with conventional deterministic analysis methods.Nonetheless,current research still faces many factual scientific problems.Therefore,this paper also identifies some research gaps,as well as recommendations for further investigations.