Automatic calibration method for discrete element hertz contact parameters during geotechnical material simulation

A geotechnical material, automatic calibration technology, used in the analysis of materials, the use of applied stable tension/pressure to test the strength of materials, electrical digital data processing, etc., can solve the problem that the convergence efficiency and convergence accuracy cannot be guaranteed, and the model cannot achieve the best convergence. Efficiency, lack of mathematical foundation and other problems, to achieve the effect of clear implementation process, promotion of analysis and research, and good convergence of calibration

Inactive Publication Date: 2020-09-01
TAIYUAN UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, there are also the following shortcomings: (1) All mesoscopic parameters are trained at the same time, and each parameter interferes with each other in the process, which affects the calibration efficiency; (2) The update strategy comes from empirical assumptions, lacks strict mathematical foundation, and cannot guarantee sufficient convergence efficiency (3) The input mesoscopic initial value comes from the deformation relationship of particles with a single particle size and regular arrangement, which is quite different from the reality that the particle structure and particle size are randomly distributed in the actual geotechnical materials
The initial estimate of the macroscopic response that deviates too much from the actual bulk not only makes the training time too long, but also increases

Method used

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  • Automatic calibration method for discrete element hertz contact parameters during geotechnical material simulation
  • Automatic calibration method for discrete element hertz contact parameters during geotechnical material simulation
  • Automatic calibration method for discrete element hertz contact parameters during geotechnical material simulation

Examples

Experimental program
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Effect test

Embodiment approach 1

[0170] Apply the method of the present invention to a two-dimensional single-size random particle sample (such as figure 2 ), the test parameters are as follows:

[0171]

[0172] Table 1 Parameters of the two-dimensional single particle random arrangement particle model

[0173] The calibration steps are as follows:

[0174] Step (1): Determine the macroscopic parameters of rock and soil materials through laboratory tests. In this example, the small strain Young's modulus 10Gpa, Poisson's ratio 0.2 is the calibration target.

[0175] Step (2): Enter the target macroscopic parameters into the following formula, in the case of 2D simulation, the initial estimates of particle contact shear modulus and Poisson's ratio and

[0176] 2D discrete element model:

[0177]

[0178]

[0179] Among them, φ is the porosity in the sample; is the average coordination number of the particle sample; when the sample has a single particle size distribution, r is the parti...

Embodiment approach 2

[0207] Apply the method of the present invention to three-dimensional single-size random particle samples (such as image 3 ), the test parameters are as follows:

[0208]

[0209] Table 3 Parameters of the three-dimensional single particle random arrangement particle model

[0210] The calibration steps are as follows:

[0211] Step (1): Determine the macroscopic parameters of rock and soil materials through laboratory tests. In this example, the small strain Young's modulus 10Gpa, Poisson's ratio 0.2 is the calibration target.

[0212] Step (2): Enter the target macroscopic parameters into the following formula, in the case of 2D simulation, the initial estimates of particle contact shear modulus and Poisson's ratio and

[0213] 3D discrete element model:

[0214]

[0215]

[0216] Among them, φ is the porosity in the sample; is the average coordination number of the particle sample; when the sample has a single particle size distribution, r is the par...

Embodiment approach 3

[0226] Apply the method of the present invention to three-dimensional multi-size random particle samples (such as Figure 4 ), the test parameters are as follows:

[0227]

[0228] Table 5 Parameters of three-dimensional multi-size random arrangement particle model

[0229] The calibration steps are as follows:

[0230] Step (1): Determine the macroscopic parameters of rock and soil materials through laboratory tests. In this example, the small strain Young's modulus 10Gpa, Poisson's ratio 0.2 is the calibration target.

[0231] Step (2): Enter the target macroscopic parameters into the following formula, in the case of 2D simulation, the initial estimates of particle contact shear modulus and Poisson's ratio and

[0232] 3D discrete element model:

[0233]

[0234]

[0235] Among them, φ is the porosity in the sample; is the average coordination number of the particle sample; when the sample has a single particle size distribution, r is the particle rad...

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Abstract

The invention discloses an automatic calibration method for discrete element hertz contact parameters during geotechnical material simulation, and the method comprises the following steps: substituting a target macroscopic parameter calibrated by a discrete element into an analytical formula to calculate a particle shear modulus and a Poisson's ratio, taking the particle shear modulus and the Poisson's ratio as initial estimation values of particle parameters, and establishing a numerical triaxial or biaxial test to obtain a macroscopic Young modulus and a Poisson's ratio; calculating the sizeof an error function, and judging whether particle parameters are updated or not; adopting different strategies according to different iteration times; during primary iteration, manually giving smalldisturbance in direct proportion to an initial estimated value; and adopting an adaptive moment estimation strategy to update parameters in multiple iterations. An embodiment shows that after finiteiteration of a single-particle-size or multi-particle-size discrete element sample, errors of calibration parameters are effectively controlled within a certain range. The calibration method has the advantages of automatic calibration capability, strong convergence capability and high calibration efficiency, and can effectively solve the calibration problem of the Hertz deformation parameter whenthe discrete element simulates the rock-soil body material.

Description

technical field [0001] The invention belongs to the field of geotechnical engineering. Specifically, the invention relates to an automatic calibration method of discrete element hertz contact parameters when simulating rock and soil materials. Background technique [0002] DEM is widely used in the analysis and research of geotechnical engineering problems such as foundation reinforcement and tunnel excavation. However, since the mesoscale parameters adopted by the discrete element algorithm are not easy to measure directly through physical tests, most of the current discrete element simulations for geotechnical engineering must first simulate certain types of conventional geotechnical tests (such as triaxial tests). By continuously adjusting the discrete element mesoscopic parameters, until the simulated object is basically consistent with the physical test in the target macroscopic index, the used simulation parameters are regarded as a set of reliable input parameters. T...

Claims

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Application Information

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IPC IPC(8): G01N3/08G06F30/20G06F111/10G06F119/14
CPCG01N3/08G06F30/20G01N2203/0075G01N2203/0256G01N2203/0254G06F2111/10G06F2119/14
Inventor 赵婷婷瞿同明冯云田王志勇王志华
Owner TAIYUAN UNIV OF TECH
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