CN-122020781-A - Slope soil body parameter random field simulation method, system, equipment and medium

CN122020781ACN 122020781 ACN122020781 ACN 122020781ACN-122020781-A

Abstract

The invention relates to the technical field of geotechnical engineering, in particular to a slope soil body parameter random field simulation method, system, equipment and medium, wherein the method comprises the steps of constructing an information diffusion distribution model based on soil body parameter data to obtain a probability distribution type with high fitting degree, establishing a slope finite element model through finite element software according to space dimension and geometric dimension, extracting finite element grid information and node coordinates, calculating a standard Gaussian random field according to the node coordinates and an autocorrelation function, mapping the standard Gaussian random field into a non-Gaussian random field discrete value conforming to the probability distribution type through equal probability transformation, writing the non-Gaussian random field discrete value into an input file generated by the finite element software, extracting the input file by a matrix laboratory, submitting the input file to the finite element software, and executing finite element analysis to obtain a slope soil body parameter random field simulation result. And the batch automatic operation is realized, and the numerical calculation efficiency is improved.

Inventors

YU SHUNING
LI ZEYING
CAO ZIHAN
GONG YANMING
HAN ZHIDONG
WANG KAI
HAN WENQI
LIU ZHIQIANG
ZHAO YINGZHI
XING FENG
LI BIAO
LI DONGCAI

Assignees

中国三峡新能源(集团)股份有限公司
青岛润莱风力发电有限公司
中国长江三峡集团有限公司

Dates

Publication Date: 20260512
Application Date: 20260107

Claims (10)

1. The slope soil body parameter random field simulation method is characterized by comprising the following steps of: The method comprises the steps of determining space dimension and geometric dimension of a field to be simulated according to soil parameter data, constructing an information diffusion distribution model based on the soil parameter data, carrying out fitting comparison with a plurality of probability distributions to obtain probability distribution types with high fitting degree, establishing a slope finite element model through finite element software according to the space dimension and geometric dimension, extracting finite element grid information and node coordinates, calculating a standard Gaussian random field according to an autocorrelation function corresponding to the node coordinates and the soil parameter data, mapping the standard Gaussian random field into a non-Gaussian random field discrete value conforming to the probability distribution types through equal probability transformation, writing the non-Gaussian random field discrete value into an input file generated by the finite element software, extracting the input file by a matrix laboratory, and carrying out finite element analysis to obtain a slope soil parameter random field simulation result.
2. The slope soil parameter random field simulation method of claim 1, wherein the constructing an information diffusion distribution model based on the soil parameter data comprises: calculating the width of an information diffusion window based on the soil body parameter data; calculating a probability density function and an accumulated distribution function through the width of the information diffusion window; And constructing an information diffusion distribution model of the spatial variability of the soil parameters to be simulated by the probability density function and the accumulated distribution function.
3. The slope soil parameter random field simulation method according to claim 2, wherein the information diffusion window width is calculated according to a maximum value and a minimum value in the soil parameter data.
4. The method of claim 1, wherein the plurality of probability distributions comprises an information diffusion distribution, a truncated normal distribution, a lognormal distribution, a truncated Geng Beier distribution, and a Weibull distribution.
5. The method according to claim 1, wherein the calculating a standard gaussian random field according to an autocorrelation function of the node coordinates corresponding to the soil parameter data, and mapping the standard gaussian random field to a non-gaussian random field discrete value conforming to the probability distribution type by an equal probability transformation, comprises: Calculating an autocorrelation matrix according to the node coordinates and the autocorrelation function; performing a Georll Stroke decomposition on the autocorrelation matrix to obtain a lower triangular matrix; Calculating a standard Gaussian random field according to the lower triangular matrix; Mapping the standard Gaussian random field through the equal probability transformation to obtain a non-Gaussian random field discrete value conforming to the probability distribution type.
6. The slope soil parameter random field simulation method of claim 1, wherein writing the non-gaussian random field discrete values to an input file generated by finite element software comprises: Extracting an input file which is generated by the finite element software when the slope finite element model is established and contains node coordinates and unit information; Matching corresponding unit sets, section attributes and material parameters in the input file with the non-Gaussian random field discrete values; and replacing the corresponding material attribute parameters in the input file with the matched non-Gaussian random field discrete values to obtain an updated input file.
7. The slope soil parameter random field simulation method of claim 1, further comprising: Extracting the slope soil body parameter random field simulation result through an interface of the matrix laboratory; and carrying out statistical processing on the slope soil body parameter random field simulation result and outputting a statistical result.
8. A slope soil parameter random field simulation system, comprising: The system comprises a soil parameter data acquisition module, a construction module, an extraction module, a calculation module, an output module and a matrix laboratory, wherein the soil parameter data acquisition module is used for acquiring space dimension and geometric dimension of a field to be simulated, the construction module is used for constructing an information diffusion distribution model based on the soil parameter data and carrying out fitting comparison with a plurality of probability distributions to obtain a probability distribution type with high fitting degree, the extraction module is used for establishing a slope finite element model through finite element software according to the space dimension and the geometric dimension and extracting finite element grid information and node coordinates, the calculation module is used for calculating a standard Gaussian random field according to an autocorrelation function corresponding to the node coordinates and the soil parameter data and mapping the standard Gaussian random field into a non-Gaussian airport discrete value conforming to the probability distribution type through equal probability transformation, and the output module is used for writing the non-Gaussian random field discrete value into an input file generated by the finite element software, extracting the input file from a matrix laboratory and submitting the input file to the finite element software to execute finite element analysis to obtain a slope soil parameter airport simulation result.
9. A computer device comprising a memory and a processor, the memory having stored therein computer readable instructions which when executed by the processor implement the steps of the slope soil parameter random field simulation method of any one of claims 1 to 7.
10. A computer readable storage medium having stored thereon computer readable instructions which when executed by a processor perform the steps of the slope soil parameter random field simulation method according to any one of claims 1 to 7.

Description

Slope soil body parameter random field simulation method, system, equipment and medium Technical Field The disclosure relates to the technical field of geotechnical engineering, in particular to a slope soil body parameter random field simulation method, a system, equipment and a medium. Background The rock-soil body is taken as a natural product, is influenced by factors such as internal soil body composition, deposition conditions, weathering degree, artificial transformation and the like, and the physical and mechanical parameters of the soil body show differences of different degrees, which is called space variability. The probability model for representing the space variability of the parameters of the rock-soil body to be simulated by the prior art method is based on classical probability distribution, a curve obtained by adopting the classical probability distribution estimation method is unimodal, the actual soil body is influenced by factors such as environment, formation conditions and the like, and the fluctuation of the parameters of the soil body is very large, so that the random fluctuation characteristics of the soil layer are difficult to reflect by the method. If the selected theoretical distribution is not consistent with the actual distribution, the deviation of the analysis result cannot be reduced even if the data amount and the calculation accuracy are increased, and the deviation can cause distortion of the rock-soil reliability analysis. The commonly used slope stability deterministic analysis methods mainly comprise a limit balance method (LEM) and a Finite Element Method (FEM). Compared with the traditional FEM method which does not consider the influence of the slope deformation on the stability, the FEM method does not need to assume the damage form and position of a critical sliding surface, and a random finite element method for slope reliability analysis is provided based on the combination of random field theory, probability analysis theory and finite element method. However, the random finite element method needs to modify the finite element source code every time the random field is realized, and the combination time is long and the efficiency is low. Disclosure of Invention In order to solve the technical problems, the present disclosure provides a slope soil parameter random field simulation method, including: The method comprises the steps of determining space dimension and geometric dimension of a field to be simulated according to soil parameter data, constructing an information diffusion distribution model based on the soil parameter data, carrying out fitting comparison with a plurality of probability distributions to obtain probability distribution types with high fitting degree, establishing a slope finite element model through finite element software according to the space dimension and geometric dimension, extracting finite element grid information and node coordinates, calculating a standard Gaussian random field according to an autocorrelation function corresponding to the node coordinates and the soil parameter data, mapping the standard Gaussian random field into a non-Gaussian random field discrete value conforming to the probability distribution types through equal probability transformation, writing the non-Gaussian random field discrete value into an input file generated by the finite element software, extracting the input file by a matrix laboratory, and carrying out finite element analysis to obtain a slope soil parameter random field simulation result. Further, the constructing an information diffusion distribution model based on the soil parameter data includes: calculating the width of an information diffusion window based on the soil body parameter data; calculating a probability density function and an accumulated distribution function through the width of the information diffusion window; And constructing an information diffusion distribution model of the spatial variability of the soil parameters to be simulated by the probability density function and the accumulated distribution function. Further, the information diffusion window width is calculated according to the maximum value and the minimum value in the soil body parameter data. Further, the plurality of probability distributions includes an information diffusion distribution, a truncated normal distribution, a lognormal distribution, a truncated Geng Beier distribution, and a Weibull distribution. Further, the calculating a standard gaussian random field according to the node coordinates and the autocorrelation function, and mapping the standard gaussian random field into a non-gaussian random field discrete value conforming to the probability distribution type through an equal probability transformation, includes: Calculating an autocorrelation matrix according to the node coordinates and the autocorrelation function; performing a Georll Stroke decomposition on the autocorrelation matrix