This study examines the stability of three-dimensional rectangular tunnel headings in drained c-ϕ soils,incor-porating surcharge effects using 3D Finite Element Limit Analysis(FELA).It focuses on the upper and lower b...This study examines the stability of three-dimensional rectangular tunnel headings in drained c-ϕ soils,incor-porating surcharge effects using 3D Finite Element Limit Analysis(FELA).It focuses on the upper and lower bound solutions for three stability factors:cohesion,surcharge,and soil unit weight(Nc,Ns,and Nγ).Based on Terzaghi’s principle of superposition,the analysis evaluates tunnel stability under varying parameters,such as cover-depth ratio(H/D),width-depth ratio(B/D),and friction angle(ϕ).The results align closely with previous studies,and practical design charts are provided for calculating minimum support pressures.Additionally,machine learning models(ANN and XGBoost)are used to develop accurate correlations between input param-eters and stability results.A relative importance index analysis is conducted to assess the impact of these pa-rameters.This research enhances understanding of tunnel stability and offers practical insights for tunnel design.展开更多
Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered so...Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered soils remains a complex challenge.This study presents a novel application of five ensemble machine(ML)algorithms-random forest(RF),gradient boosting machine(GBM),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),and categorical boosting(CatBoost)-to predict the undrained bearing capacity factor(Nc)of circular open caissons embedded in two-layered clay on the basis of results from finite element limit analysis(FELA).The input dataset consists of 1188 numerical simulations using the Tresca failure criterion,varying in geometrical and soil parameters.The FELA was performed via OptumG2 software with adaptive meshing techniques and verified against existing benchmark studies.The ML models were trained on 70% of the dataset and tested on the remaining 30%.Their performance was evaluated using six statistical metrics:coefficient of determination(R²),mean absolute error(MAE),root mean squared error(RMSE),index of scatter(IOS),RMSE-to-standard deviation ratio(RSR),and variance explained factor(VAF).The results indicate that all the models achieved high accuracy,with R²values exceeding 97.6%and RMSE values below 0.02.Among them,AdaBoost and CatBoost consistently outperformed the other methods across both the training and testing datasets,demonstrating superior generalizability and robustness.The proposed ML framework offers an efficient,accurate,and data-driven alternative to traditional methods for estimating caisson capacity in stratified soils.This approach can aid in reducing computational costs while improving reliability in the early stages of foundation design.展开更多
The increasing occurrence of sinkholes caused by water main bursts has attracted significant research attention in recent years.This study addresses the gap in evaluating soil blowout stability resulting from water ma...The increasing occurrence of sinkholes caused by water main bursts has attracted significant research attention in recent years.This study addresses the gap in evaluating soil blowout stability resulting from water main failures by investigating the three-dimensional stability of blowouts with circular,hemispherical,and spherical openings.Advanced finite element limit analysis(FELA)combined with adaptive meshing is employed to analyze critical factors,including soil cover depth,surcharge pressure,and internal water pressure,that contribute to blowout failure.In addition,dimensionless ratios are used throughout the paper to assess the influence of these factors.Numerical findings are rigorously validated,ensuring reliability and accuracy.Practical design charts are provided to accommodate a wide range of design scenarios,offering valuable guidance for engineers.This study introduces a pioneering sinkhole simulation methodology,leading to the understanding of three-dimensional blowout stability mechanisms.展开更多
In recent years, finite element analyses have increasingly been utilized for slope stability problems. In comparison to limit equilibrium methods, numerical analyses do not require any definition of the failure mechan...In recent years, finite element analyses have increasingly been utilized for slope stability problems. In comparison to limit equilibrium methods, numerical analyses do not require any definition of the failure mechanism a priori and enable the determination of the safety level more accurately. The paper compares the performances of strength reduction finite element analysis(SRFEA) with finite element limit analysis(FELA), whereby the focus is related to non-associated plasticity. Displacement-based finite element analyses using a strength reduction technique suffer from numerical instabilities when using non-associated plasticity, especially when dealing with high friction angles but moderate dilatancy angles. The FELA on the other hand provides rigorous upper and lower bounds of the factor of safety(FoS) but is restricted to associated flow rules. Suggestions to overcome this problem, proposed by Davis(1968), lead to conservative FoSs; therefore, an enhanced procedure has been investigated. When using the modified approach, both the SRFEA and the FELA provide very similar results. Further studies highlight the advantages of using an adaptive mesh refinement to determine FoSs. Additionally, it is shown that the initial stress field does not affect the FoS when using a Mohr-Coulomb failure criterion.展开更多
This study presents a hybrid framework to predict stability solutions of buried structures under active trapdoor conditions in natural clays with anisotropy and heterogeneity by combining physics-based and data-driven...This study presents a hybrid framework to predict stability solutions of buried structures under active trapdoor conditions in natural clays with anisotropy and heterogeneity by combining physics-based and data-driven modeling.Finite-element limit analysis(FELA)with a newly developed anisotropic undrained shear(AUS)failure criterion is used to identify the underlying active failure mechanisms as well as to develop a numerical(physics-based)database of stability numbers for both planar and circular trapdoors.Practical considerations are given for natural clays to three linearly increasing shear strengths in compression,extension,and direct simple shear in the AUS material model.The obtained numerical solutions are compared and validated with published solutions in the literature.A multivariate adaptive regression splines(MARS)algorithm is further utilized to learn the numerical solutions to act as fast FELA data-driven surrogates for stability evaluation.The current MARS-based modeling provides both relative importance index and accurate design equations that can be used with confidence by practitioners.展开更多
The stability of strip footings subjected to eccentrically inclined loads is critical for reliable foundation design.This study investigates the effect of a circular unlined tunnel in a rock mass on the ultimate beari...The stability of strip footings subjected to eccentrically inclined loads is critical for reliable foundation design.This study investigates the effect of a circular unlined tunnel in a rock mass on the ultimate bearing capacity(UBC)of a foundation with width B under inclined and eccentric loads.Adaptive finite element limit analysis was employed to evaluate the reduction in UBC of the footing resting above a tunnel.The examined critical parameters include normalized load eccentricity(e/B),load inclination(β),and horizontal and vertical distances of the tunnel from the foundation(P/B and Q/B,respectively),along with rock mass properties.The results reveal that for e/B≥0.25 and β≤60°,the reduction coefficient,R_(c)≥0.90,suggesting that the presence of a tunnel has a minimal impact on the load-bearing capacity of the footing,with failure primarily governed by load eccentricity and inclination.Additionally,potential failure mechanisms are explored,showing that at lower e/B,higher β,and lower Q/B,the tunnel significantly affects footing's failure envelope.Conversely,at higher e/B and lower β,failure is due to rotational effects of footing,regardless of the tunnel's position.To predict the Rc more accurately,due to the time-consuming nature of direct calculations,both MLR and ANN models were developed.The MLR model provided a baseline for comparison,while the ANN model,with a coefficient of determination(R2)of 0.98,demonstrated superior accuracy compared to the R2=0.96 of MLR.Using both approaches ensured robust and efficient predictions of Rc.Since Rc does not directly provide the reduced UBC of footing due to presence of tunnel,the study introduced bearing capacity factor(Nc)to enable direct calculation of the reduced UBC of footing.These findings offer theoretical guidelines for preliminary design and provide practitioners with an effective tool for evaluating UBC reduction in complex loading scenarios involving tunnels.展开更多
The composite pile consisting of core-pile and surrounding cement-enhanced soil is a promising pile foundation in recent years.However,how and to what extent the cement-enhanced soil influences the ultimate lateral re...The composite pile consisting of core-pile and surrounding cement-enhanced soil is a promising pile foundation in recent years.However,how and to what extent the cement-enhanced soil influences the ultimate lateral resistance has not been fully investigated.In this paper,the ultimate lateral resistance of the composite pile was studied by finite element limit analysis(FELA)and theoretical upper-bound analysis.The results of FELA and theoretical analysis revealed three failure modes of laterally loaded composite piles.The effects of the enhanced soil thickness,strength,and pile-enhanced soil interface characteristics on the ultimate lateral resistance were studied.The results show that increasing the enhanced soil thickness leads to a significant improvement on ultimate lateral resistance factor(N P),and there is a critical thickness beyond which the thickness no longer affects the N P.Increasing the enhanced soil strength induced 6.2%-232.6%increase of N P.However,no noticeable impact was detected when the enhanced soil strength was eight times higher than that of the natural soil.The maximum increment of N P is only 30.5%caused by the increase of interface adhesion factor(a).An empirical model was developed to calculate the N P of the composite pile,and the results show excellent agreement with the analytical results.展开更多
The accurate prediction of the bearing capacity of ring footings,which is crucial for civil engineering projects,has historically posed significant challenges.Previous research in this area has been constrained by con...The accurate prediction of the bearing capacity of ring footings,which is crucial for civil engineering projects,has historically posed significant challenges.Previous research in this area has been constrained by considering only a limited number of parameters or utilizing relatively small datasets.To overcome these limitations,a comprehensive finite element limit analysis(FELA)was conducted to predict the bearing capacity of ring footings.The study considered a range of effective parameters,including clay undrained shear strength,heterogeneity factor of clay,soil friction angle of the sand layer,radius ratio of the ring footing,sand layer thickness,and the interface between the ring footing and the soil.An extensive dataset comprising 80,000 samples was assembled,exceeding the limitations of previous research.The availability of this dataset enabled more robust and statistically significant analyses and predictions of ring footing bearing capacity.In light of the time-intensive nature of gathering a substantial dataset,a customized deep neural network(DNN)was developed specifically to predict the bearing capacity of the dataset rapidly.Both computational and comparative results indicate that the proposed DNN(i.e.DNN-4)can accurately predict the bearing capacity of a soil with an R2 value greater than 0.99 and a mean squared error(MSE)below 0.009 in a fraction of 1 s,reflecting the effectiveness and efficiency of the proposed method.展开更多
Tunnel heading stability in two dimensions(2D)has been extensively investigated by numerous scholars in the past decade.One significant limitation of 2D analysis is the absence of actual tunnel geometry modeling with ...Tunnel heading stability in two dimensions(2D)has been extensively investigated by numerous scholars in the past decade.One significant limitation of 2D analysis is the absence of actual tunnel geometry modeling with a considerable degree of idealization.Nevertheless,it is possible to study the stability of tunnels in three dimensions(3D)with a rectangular shape using finite element limit analysis(FELA)and a nonlinear programming technique.This paper employs 3D FELA to generate rigorous solutions for stability numbers,failure mechanisms,and safety factors for rectangular-shaped tunnels.To further explore the usefulness of the produced results,multivariate adaptive regression spline(MARS)is used for machine learning of big dataset and development of design equations for practical design applications.The study should be of great benefit to tunnel design practices using the developed equations provided in the paper.展开更多
This study evaluates the undrained uplift capacity of open-caisson anchors embedded in anisotropic clay using Finite Element Limit Analysis(FELA)and a hybrid machine learning framework.The FELA simulations inves-tigat...This study evaluates the undrained uplift capacity of open-caisson anchors embedded in anisotropic clay using Finite Element Limit Analysis(FELA)and a hybrid machine learning framework.The FELA simulations inves-tigate the influence of the radius ratio(R/B),anisotropic ratio(re),interface roughness factor(α),and inclination angle(β).Specifically,the results reveal that increasingβsignificantly enhances Nc,especially as soil behavior approaches isotropy.Higherαimproves resistance at steeper inclinations by mobilizing greater interface shear.Nc increases with re,reflecting enhanced strength under isotropic conditions.To enhance predictive accuracy and generalization,a hybrid machine learning model was developed by integrating Extreme Gradient Boosting(XGBoost)with Genetic Algorithm(GA)and Mutation-Based Genetic Algorithm(MGA)for hyperparameter tuning.Among the models,MGA-XGBoost outperformed GA-XGBoost,achieving higher predictive accuracy(R^(2)=0.996 training,0.993 testing).Furthermore,SHAP analysis consistently identified anisotropic ratio(re)as the most influential factor in predicting uplift capacity,followed by interface roughness factor(α),inclination angle(β),and radius ratio(R/B).The proposed framework serves as a scalable decision-support tool adaptable to various soil types and foundation geometries,offering a more efficient and data-driven approach to uplift-resistant design in anisotropic cohesive soils.展开更多
In this investigation,the bearing capacity solution of a strip footing in anisotropic clay under inclined and eccentric load is analyzed using the numerical simulation model.The lower and upper bound finite element li...In this investigation,the bearing capacity solution of a strip footing in anisotropic clay under inclined and eccentric load is analyzed using the numerical simulation model.The lower and upper bound finite element limit analysis(FELA)approaches are utilized to establish precise modeling and derive the numerical outcomes of a strip footing’s bearing capacity.All analyses use effective automated adaptive meshes with three iteration stages to enhance the accuracy of the outcomes.The parametric analysis is performed to examine the influence of four dimensionless parameters which are taken into account in this study,namely the anisotropic strength ratio,the dimensionless eccentricity,the load inclination angle,and the adhesion factor to the bearing capacity factor.Furthermore,a new model has been proposed to predict the bearing capacity factor for the calculation of the undrained bearing capacity for footings resting on an anisotropic clay using an advanced data-driven method(MOGA-EPR).The new model takes into account the anisotropy,eccentricity,and inclination of the applied load and could be used with confidence in routine designs of shallow foundations in undrained conditions with the consideration of the anisotropic strengths of clays.展开更多
基金Ho Chi Minh City University of Technology(HCMUT),VNU-HCM for supporting this study.
文摘This study examines the stability of three-dimensional rectangular tunnel headings in drained c-ϕ soils,incor-porating surcharge effects using 3D Finite Element Limit Analysis(FELA).It focuses on the upper and lower bound solutions for three stability factors:cohesion,surcharge,and soil unit weight(Nc,Ns,and Nγ).Based on Terzaghi’s principle of superposition,the analysis evaluates tunnel stability under varying parameters,such as cover-depth ratio(H/D),width-depth ratio(B/D),and friction angle(ϕ).The results align closely with previous studies,and practical design charts are provided for calculating minimum support pressures.Additionally,machine learning models(ANN and XGBoost)are used to develop accurate correlations between input param-eters and stability results.A relative importance index analysis is conducted to assess the impact of these pa-rameters.This research enhances understanding of tunnel stability and offers practical insights for tunnel design.
文摘Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered soils remains a complex challenge.This study presents a novel application of five ensemble machine(ML)algorithms-random forest(RF),gradient boosting machine(GBM),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),and categorical boosting(CatBoost)-to predict the undrained bearing capacity factor(Nc)of circular open caissons embedded in two-layered clay on the basis of results from finite element limit analysis(FELA).The input dataset consists of 1188 numerical simulations using the Tresca failure criterion,varying in geometrical and soil parameters.The FELA was performed via OptumG2 software with adaptive meshing techniques and verified against existing benchmark studies.The ML models were trained on 70% of the dataset and tested on the remaining 30%.Their performance was evaluated using six statistical metrics:coefficient of determination(R²),mean absolute error(MAE),root mean squared error(RMSE),index of scatter(IOS),RMSE-to-standard deviation ratio(RSR),and variance explained factor(VAF).The results indicate that all the models achieved high accuracy,with R²values exceeding 97.6%and RMSE values below 0.02.Among them,AdaBoost and CatBoost consistently outperformed the other methods across both the training and testing datasets,demonstrating superior generalizability and robustness.The proposed ML framework offers an efficient,accurate,and data-driven alternative to traditional methods for estimating caisson capacity in stratified soils.This approach can aid in reducing computational costs while improving reliability in the early stages of foundation design.
文摘The increasing occurrence of sinkholes caused by water main bursts has attracted significant research attention in recent years.This study addresses the gap in evaluating soil blowout stability resulting from water main failures by investigating the three-dimensional stability of blowouts with circular,hemispherical,and spherical openings.Advanced finite element limit analysis(FELA)combined with adaptive meshing is employed to analyze critical factors,including soil cover depth,surcharge pressure,and internal water pressure,that contribute to blowout failure.In addition,dimensionless ratios are used throughout the paper to assess the influence of these factors.Numerical findings are rigorously validated,ensuring reliability and accuracy.Practical design charts are provided to accommodate a wide range of design scenarios,offering valuable guidance for engineers.This study introduces a pioneering sinkhole simulation methodology,leading to the understanding of three-dimensional blowout stability mechanisms.
文摘In recent years, finite element analyses have increasingly been utilized for slope stability problems. In comparison to limit equilibrium methods, numerical analyses do not require any definition of the failure mechanism a priori and enable the determination of the safety level more accurately. The paper compares the performances of strength reduction finite element analysis(SRFEA) with finite element limit analysis(FELA), whereby the focus is related to non-associated plasticity. Displacement-based finite element analyses using a strength reduction technique suffer from numerical instabilities when using non-associated plasticity, especially when dealing with high friction angles but moderate dilatancy angles. The FELA on the other hand provides rigorous upper and lower bounds of the factor of safety(FoS) but is restricted to associated flow rules. Suggestions to overcome this problem, proposed by Davis(1968), lead to conservative FoSs; therefore, an enhanced procedure has been investigated. When using the modified approach, both the SRFEA and the FELA provide very similar results. Further studies highlight the advantages of using an adaptive mesh refinement to determine FoSs. Additionally, it is shown that the initial stress field does not affect the FoS when using a Mohr-Coulomb failure criterion.
基金the funding support provided by National Natural Science Foundation of China(Grant No.42177121)Thammasat University Research Unit in Structural and Foundation Engineering.
文摘This study presents a hybrid framework to predict stability solutions of buried structures under active trapdoor conditions in natural clays with anisotropy and heterogeneity by combining physics-based and data-driven modeling.Finite-element limit analysis(FELA)with a newly developed anisotropic undrained shear(AUS)failure criterion is used to identify the underlying active failure mechanisms as well as to develop a numerical(physics-based)database of stability numbers for both planar and circular trapdoors.Practical considerations are given for natural clays to three linearly increasing shear strengths in compression,extension,and direct simple shear in the AUS material model.The obtained numerical solutions are compared and validated with published solutions in the literature.A multivariate adaptive regression splines(MARS)algorithm is further utilized to learn the numerical solutions to act as fast FELA data-driven surrogates for stability evaluation.The current MARS-based modeling provides both relative importance index and accurate design equations that can be used with confidence by practitioners.
基金supported by the Civil Engineering Department, Madan Mohan Malaviya University of Technology, Gorakhpur, India
文摘The stability of strip footings subjected to eccentrically inclined loads is critical for reliable foundation design.This study investigates the effect of a circular unlined tunnel in a rock mass on the ultimate bearing capacity(UBC)of a foundation with width B under inclined and eccentric loads.Adaptive finite element limit analysis was employed to evaluate the reduction in UBC of the footing resting above a tunnel.The examined critical parameters include normalized load eccentricity(e/B),load inclination(β),and horizontal and vertical distances of the tunnel from the foundation(P/B and Q/B,respectively),along with rock mass properties.The results reveal that for e/B≥0.25 and β≤60°,the reduction coefficient,R_(c)≥0.90,suggesting that the presence of a tunnel has a minimal impact on the load-bearing capacity of the footing,with failure primarily governed by load eccentricity and inclination.Additionally,potential failure mechanisms are explored,showing that at lower e/B,higher β,and lower Q/B,the tunnel significantly affects footing's failure envelope.Conversely,at higher e/B and lower β,failure is due to rotational effects of footing,regardless of the tunnel's position.To predict the Rc more accurately,due to the time-consuming nature of direct calculations,both MLR and ANN models were developed.The MLR model provided a baseline for comparison,while the ANN model,with a coefficient of determination(R2)of 0.98,demonstrated superior accuracy compared to the R2=0.96 of MLR.Using both approaches ensured robust and efficient predictions of Rc.Since Rc does not directly provide the reduced UBC of footing due to presence of tunnel,the study introduced bearing capacity factor(Nc)to enable direct calculation of the reduced UBC of footing.These findings offer theoretical guidelines for preliminary design and provide practitioners with an effective tool for evaluating UBC reduction in complex loading scenarios involving tunnels.
基金The work was supported by the National Natural Science Foundation of China(Grant No.51978540).
文摘The composite pile consisting of core-pile and surrounding cement-enhanced soil is a promising pile foundation in recent years.However,how and to what extent the cement-enhanced soil influences the ultimate lateral resistance has not been fully investigated.In this paper,the ultimate lateral resistance of the composite pile was studied by finite element limit analysis(FELA)and theoretical upper-bound analysis.The results of FELA and theoretical analysis revealed three failure modes of laterally loaded composite piles.The effects of the enhanced soil thickness,strength,and pile-enhanced soil interface characteristics on the ultimate lateral resistance were studied.The results show that increasing the enhanced soil thickness leads to a significant improvement on ultimate lateral resistance factor(N P),and there is a critical thickness beyond which the thickness no longer affects the N P.Increasing the enhanced soil strength induced 6.2%-232.6%increase of N P.However,no noticeable impact was detected when the enhanced soil strength was eight times higher than that of the natural soil.The maximum increment of N P is only 30.5%caused by the increase of interface adhesion factor(a).An empirical model was developed to calculate the N P of the composite pile,and the results show excellent agreement with the analytical results.
文摘The accurate prediction of the bearing capacity of ring footings,which is crucial for civil engineering projects,has historically posed significant challenges.Previous research in this area has been constrained by considering only a limited number of parameters or utilizing relatively small datasets.To overcome these limitations,a comprehensive finite element limit analysis(FELA)was conducted to predict the bearing capacity of ring footings.The study considered a range of effective parameters,including clay undrained shear strength,heterogeneity factor of clay,soil friction angle of the sand layer,radius ratio of the ring footing,sand layer thickness,and the interface between the ring footing and the soil.An extensive dataset comprising 80,000 samples was assembled,exceeding the limitations of previous research.The availability of this dataset enabled more robust and statistically significant analyses and predictions of ring footing bearing capacity.In light of the time-intensive nature of gathering a substantial dataset,a customized deep neural network(DNN)was developed specifically to predict the bearing capacity of the dataset rapidly.Both computational and comparative results indicate that the proposed DNN(i.e.DNN-4)can accurately predict the bearing capacity of a soil with an R2 value greater than 0.99 and a mean squared error(MSE)below 0.009 in a fraction of 1 s,reflecting the effectiveness and efficiency of the proposed method.
基金supported by the Thailand Science Research and Innovation Fundamental Fund fiscal year 2023The fifth author (V.Kamchoom)acknowledges the financial support from the National Science,Research and Innovation Fund (NSRF)at King Mongkut's Institute of Technology Ladkrabang (KMITL),Thailand (Grant No.FRB66065/0258-RE-KRIS/FF66/53)+1 种基金the Climate Change and Climate Variability Research in Monsoon Asia (CMON3)from the National Research Council of Thailand (NRCT) (Grant No.N10A650844)the National Natural Science Foundation of China (NSFC).
文摘Tunnel heading stability in two dimensions(2D)has been extensively investigated by numerous scholars in the past decade.One significant limitation of 2D analysis is the absence of actual tunnel geometry modeling with a considerable degree of idealization.Nevertheless,it is possible to study the stability of tunnels in three dimensions(3D)with a rectangular shape using finite element limit analysis(FELA)and a nonlinear programming technique.This paper employs 3D FELA to generate rigorous solutions for stability numbers,failure mechanisms,and safety factors for rectangular-shaped tunnels.To further explore the usefulness of the produced results,multivariate adaptive regression spline(MARS)is used for machine learning of big dataset and development of design equations for practical design applications.The study should be of great benefit to tunnel design practices using the developed equations provided in the paper.
文摘This study evaluates the undrained uplift capacity of open-caisson anchors embedded in anisotropic clay using Finite Element Limit Analysis(FELA)and a hybrid machine learning framework.The FELA simulations inves-tigate the influence of the radius ratio(R/B),anisotropic ratio(re),interface roughness factor(α),and inclination angle(β).Specifically,the results reveal that increasingβsignificantly enhances Nc,especially as soil behavior approaches isotropy.Higherαimproves resistance at steeper inclinations by mobilizing greater interface shear.Nc increases with re,reflecting enhanced strength under isotropic conditions.To enhance predictive accuracy and generalization,a hybrid machine learning model was developed by integrating Extreme Gradient Boosting(XGBoost)with Genetic Algorithm(GA)and Mutation-Based Genetic Algorithm(MGA)for hyperparameter tuning.Among the models,MGA-XGBoost outperformed GA-XGBoost,achieving higher predictive accuracy(R^(2)=0.996 training,0.993 testing).Furthermore,SHAP analysis consistently identified anisotropic ratio(re)as the most influential factor in predicting uplift capacity,followed by interface roughness factor(α),inclination angle(β),and radius ratio(R/B).The proposed framework serves as a scalable decision-support tool adaptable to various soil types and foundation geometries,offering a more efficient and data-driven approach to uplift-resistant design in anisotropic cohesive soils.
基金financially supported by Office of the Permanent Secretary,Ministry of Higher Education,Science,Research and Innovation under Research Grant for New Scholar(RGNS 65-112).
文摘In this investigation,the bearing capacity solution of a strip footing in anisotropic clay under inclined and eccentric load is analyzed using the numerical simulation model.The lower and upper bound finite element limit analysis(FELA)approaches are utilized to establish precise modeling and derive the numerical outcomes of a strip footing’s bearing capacity.All analyses use effective automated adaptive meshes with three iteration stages to enhance the accuracy of the outcomes.The parametric analysis is performed to examine the influence of four dimensionless parameters which are taken into account in this study,namely the anisotropic strength ratio,the dimensionless eccentricity,the load inclination angle,and the adhesion factor to the bearing capacity factor.Furthermore,a new model has been proposed to predict the bearing capacity factor for the calculation of the undrained bearing capacity for footings resting on an anisotropic clay using an advanced data-driven method(MOGA-EPR).The new model takes into account the anisotropy,eccentricity,and inclination of the applied load and could be used with confidence in routine designs of shallow foundations in undrained conditions with the consideration of the anisotropic strengths of clays.
