Slope Reliability Analysis Based On Critical Slip Field

Slope stability analysis has always been one of the research hotspots in geotechnical engineering and geological engineering.The uncertainty of the slope itself makes the traditional slope stability analysis method can not reflect the stability of the slope.As an uncertain analysis method,reliability analysis can be applied to slope stability analysis to make the analysis results more in line with the objective facts.In slope reliability analysis,the reliability of single failure mode is calculated on the critical deterministic sliding surface with the minimum safety factor or the maximum failure probability,and the system reliability of multiple failure modes is calculated on multiple potential sliding surfaces.However,the shapes of these sliding surfaces are generally assumed in advance such as circular arc,so it is very important to study the slope reliability of arbitrary sliding surfaces.Considering the above problems,a slope reliability analysis method based on critical sliding field is established in this paper.The main research results are as follows:(1)The reliability analysis method based on critical sliding field is established.The slope reliability analysis is combined with critical sliding field and Monte Carlo simulation,divided into critical uncertainty based on the critical sliding field on the surface of the reliability and multiple potential sliding surface system reliability analysis,and the problem of slope reliability based on arbitrary shape sliding surface is solved.(2)The reliability theory based on critical sliding field is implemented.For the reliability of critical deterministic sliding surface,the critical sliding surface obtained when the mean value of random variables is taken as the critical deterministic sliding surface.In the cumulative random sampling,the number of times the maximum residual thrust E of the critical deterministic sliding surface is greater than 0 when the safety factor FS=1.0,and the failure probability P_fof the slope is obtained.For the system reliability of multiple potential sliding surfaces,calculate the maximum residual thrust E of all dangerous sliding surfaces under each group of random variables when the safety factor FS=1.0,and accumulate the times that E is greater than 0 in random sampling to obtain the failure probability P_fof the slope.(3)The reliability simulation program based on critical sliding field is illustrated,and the slope stability analysis module of critical sliding field method and the probability analysis module of Monte Carlo simulation method are established by MATLAB.For the reliability of the critical deterministic sliding surface,the Monte Carlo module generates random variable samples and inputs them into the critical sliding field module to calculate the maximum residual thrust E of the critical deterministic sliding surface.For the reliability of multiple potential sliding surfaces,the Monte Carlo module generates random variable samples and inputs them into the critical sliding field module to calculate the maximum residual thrust E in all dangerous sliding surfaces.(4)Through the analysis and comparison of numerical examples,the results show that this method is suitable for both the single failure mode reliability of slope with critical deterministic sliding surface and the multi failure mode system reliability of slope with multiple potential sliding surfaces.At the same time,the simulation times,the variability,correlation and distribution type of parameters have an impact on the reliability analysis results.If these factors are ignored,the actual failure probability of slope may be underestimated.(5)The reliability of critical deterministic sliding surface and multiple potential sliding surfaces are compared and analyzed.The system reliability of multiple potential sliding surfaces can not only more truly reflect the possibility of overall instability of the slope,but also obtain the sliding volume of the slope.The product of sliding volume and failure probability P_fcan be used to judge the sliding risk of slope and provide a theoretical basis for engineering risk analysis.