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Grid unit particle number optimization method in rarefied airflow numerical simulation

A grid unit and numerical simulation technology, applied in design optimization/simulation, etc., can solve problems such as long simulation time, inaccurate simulation results, and inability to solve collisions, so as to improve simulation efficiency and simulation accuracy

Active Publication Date: 2020-04-14
上海索辰信息科技股份有限公司
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Problems solved by technology

As mentioned, this will make the simulation long and inefficient
Conversely, depending on the physics problem, if this number is too small, simulation results may be inaccurate due to the inability to solve for collisions in each simulated cell

Method used

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  • Grid unit particle number optimization method in rarefied airflow numerical simulation
  • Grid unit particle number optimization method in rarefied airflow numerical simulation
  • Grid unit particle number optimization method in rarefied airflow numerical simulation

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Embodiment Construction

[0041] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0042] This embodiment provides a method for optimizing the number of particles in grid cells in numerical simulation of rarefied airflow, which includes the following steps:

[0043]In the numerical simulation of rarefied airflow using DSMC, the relationship between the number of simulated particles in any grid unit and a set range (for exam...

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Abstract

The invention relates to a grid unit particle number optimization method in rarefied airflow numerical simulation. The method comprises the following steps of: judging whether the number of simulationparticles in any grid cell is within a set range or not in the numerical simulation of the thin air flow by adopting a DSMC, and if the number of the simulation particles is within the set range, notoptimizing the number of the particles in the grid cell; if the number of the simulation particles exceeds the upper limit value of the set range, repeatedly executing particle fusion operation according to a particle fusion criterion so as to enable the number of the simulation particles in each grid unit to be within the set range; and if the number of the simulation particles is lower than thelower limit value of the set range, repeatedly executing particle separation operation according to the particle separation criterion, so that the number of the simulation particles in each grid unitis within the set range; and controlling the particle number of each grid unit in the simulation domain, so that the simulation particle number in each grid unit does not change greatly along with the unit density and the unit size, and the distribution of the simulation particles on different grid units is balanced.

Description

technical field [0001] The invention relates to the technical field of rarefied airflow numerical simulation, in particular to a method for optimizing the particle number of a grid unit in the rarefied airflow numerical simulation. Background technique [0002] Due to the failure of the continuum assumption of the N-S equation in the region of rarefied gas flow, the direct Monte Carlo simulation method (DSMC) method for numerical simulation of rarefied gas flow has attracted more and more attention in recent years. [0003] DSMC is a probabilistic discrete particle simulation method. The DSMC method uses a small number of simulated particles in the computer to represent a large number of real gas molecules, and the space coordinates, speed, and internal energy of the simulated particles are stored in the computer, and change with time due to particle movement, collision, and interaction with the boundary. Particle sampling restores the molecular velocity distribution functi...

Claims

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Application Information

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IPC IPC(8): G06F30/20
Inventor 赵杰陈灏蒋光南
Owner 上海索辰信息科技股份有限公司
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