Fast calculation method for slope earthquake reliability based on FLAC3D-Python secondary development

Abstract

The invention provides a fast calculation method for the slope earthquake reliability based on FLAC3D-Python secondary development. The method comprises the following steps: building a strength reduction quasi-static analysis model and a dynamic time-history analysis nonlinear coupling model, solving a reliability index under an earthquake load through the strength reduction quasi-static analysis model by employing an engineering reliability iterative algorithm, and enabling the dynamic time history analysis nonlinear coupling model to adopt an improved engineering reliability iterative algorithm to quickly solve a reliability index under an earthquake load. The method overcomes the defects that in the prior art, due to the fact that soil parameters are uncertain and seismic oscillation randomness is difficult to simulate, the safety coefficient and the permanent displacement serve as slope instability criteria through the two methods of quasi-static analysis and dynamic time history analysis, and the reliability index is calculated through a first-order reliability iterative algorithm, an engineering reliability iterative algorithm and an improved engineering reliability iterative algorithm. The seismic stability of the slope can be quickly and reliably judged, and an effective judgment means is provided for related engineers.

Description

technical field [0001] The invention relates to the field of slope engineering risk assessment, in particular to a rapid calculation method for slope seismic reliability based on secondary development of FLAC3D-Python. Background technique [0002] my country is a country with frequent earthquake disasters. Natural disasters such as landslides caused by earthquake loads will cause great damage to human life and property. In the face of a large number of hidden dangers of slope disasters, from the perspective of disaster prevention and mitigation, it is necessary to evaluate the stability of slopes under earthquakes and the impact of instability. [0003] The existing technology is often very complicated and time-consuming for slope seismic performance evaluation and probability analysis, and it is necessary to establish a fast and accurate slope displacement and failure probability calculation model; the seismic performance evaluation of slopes is mostly based on the seismi...

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Problems solved by technology

[0003] The existing technology is often very complicated and time-consuming for slope seismic performance evaluation and probability analysis, and it is necessary to establish a fast and accurate slope displacement and failure probability calculation model; the seismic performance evaluation of slopes is mostly based on the seismic design of slopes The standard, that is, consider the influence of seismic intensity in the design of slope reinforcement; the accurate soil parameters of the slope need to be surveyed to obtain, and at the same time, the seismic time history and seismic macroscopic values ​​such as seismic peak acceleration are uncertain, and there is a lack of accurate For natural slope seismic failure probability assessment under the conditions of random ground motion and soil parameter uncertainty, traditional probability analysis methods are mostly based on Monte Carlo simulation (MCS) to analyze the probability characteristics of permanent displacement of the slope, which is complex to calculate And time-consuming, some inventions have been carried out to improve computing efficiency

"A Multi-threaded Parallel Calculation Method for Slope Strength Reduction Coefficient" (application number 201711353469.3) proposes a multi-threaded parallel computing method, which improves the calculation efficiency of the slope strength reduction method, but this method only converts the calculation strength The number of iteration steps in the process of reducing the coefficient has been reduced, which cannot be applied to the analysis of the randomness of ground motion and the uncertainty of soil parameters

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