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Improved particle swarm method for geotechnical material constitutive model parameter recognition based on GPU acceleration

A technique for improving particle swarm and constitutive models, applied in computing models, biological models, electrical digital data processing, etc., can solve problems such as time-consuming calculations, reduce stress integration steps, save computing time, and have low computing efficiency Effect

Active Publication Date: 2021-08-10
POWERCHINA HUADONG ENG COPORATION LTD
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Problems solved by technology

According to the mechanism of particle swarm, in each iteration process, for each particle, a complete stress-strain curve needs to be calculated, which is very time-consuming

Method used

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  • Improved particle swarm method for geotechnical material constitutive model parameter recognition based on GPU acceleration
  • Improved particle swarm method for geotechnical material constitutive model parameter recognition based on GPU acceleration
  • Improved particle swarm method for geotechnical material constitutive model parameter recognition based on GPU acceleration

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Embodiment Construction

[0030]In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific real-time methods. In particular, in order to better illustrate the efficiency improvement brought about by the present invention, the von Wollfersdorf hypoplastic model is taken as an example to illustrate the acceleration situation. In addition, the terminology description about GPU computing in the present invention refers to OpenCL, but in fact this algorithm can also be implemented on the CUDA platform. It should be understood that the specific embodiments described here are only used to explain the present invention, and are not intended to limit the present invention.

[0031] The memory layout of this algorithm is as follows:

[0032] The main variables applied in the global memory (Global Memory) on the GPU side are as follows: the running statu...

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Abstract

The invention discloses an improved particle swarm method for geotechnical material constitutive model parameter recognition based on GPU acceleration, and the method employs a particle swarm algorithm to search for optimal model parameters, and enables the cumulative error of the deviation square of a model calculation value and an experiment value of stress to be minimum. Based on the characteristic that the calculation amount is large in the calculation process, the problem of calculation efficiency is solved from the two aspects of algorithm optimization and high-performance hardware application. On one hand, an early termination mechanism is introduced according to the characteristics of error function accumulation, so that the calculation amount is saved; and on the other hand, the computing equipment applying the GPU makes optimization of a program structure according to the characteristics of an instruction set of the computing equipment. The method has the beneficial effect that the cross-order-of-magnitude calculation efficiency is improved.

Description

technical field [0001] The invention relates to a method for identifying rock and soil constitutive model parameters, which belongs to the field of geotechnical engineering indoor tests and material mechanics, and provides an auxiliary method for calibrating mechanical constitutive model parameters using indoor triaxial mechanical test data, and specifically relates to the conventional particle swarm method The error function accumulation introduces an early termination mechanism to improve computational efficiency, and uses GPUs for parallel acceleration calculations. Background technique [0002] For numerical simulation in geotechnical engineering, it is necessary to select an appropriate constitutive model and parameter values ​​to reflect the nonlinear relationship of the material unit scale, so that it is possible to obtain relatively accurate calculation results in macro-scale calculations. As the pre-work of numerical simulation, it is extremely important to conduct ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06F9/38G06T1/20G06N3/00G06F111/10G06F119/14
CPCG06F30/27G06F9/3887G06T1/20G06N3/006G06F2111/10G06F2119/14Y02T90/00
Inventor 康恒一闫自海王紫娟刘世明甘鹏路严佳佳
Owner POWERCHINA HUADONG ENG COPORATION LTD
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