BESO topological optimization method based on dynamic evolution rate and adaptive grid and application of BESO topological optimization method

Abstract

The invention discloses a BESO topological optimization method based on a dynamic evolution rate and an adaptive grid and application thereof, and the method comprises the steps: building a finite element model for a to-be-topologically optimized basic structure, and defining a design domain, a load, a boundary condition and a grid size; determining a constraint value and BESO necessary parameters; performing finite element analysis on the structure after mesh division, and calculating unit sensitivity under a target function and a constraint condition; filtering the unit sensitivity and updating the constrained Lagrange multiplier, and constructing the sensitivity of a Lagrange function; determining an evolution rate of the current iterative step based on a dynamic evolution rate functionof a Logistic function according to the volume rate of the current iterative step; and updating a design variable according to a set constraint function, judging whether constraint conditions and convergence conditions are met or not, if not, performing grid adaptive updating, then performing unit updating, and stopping iteration until the constraint conditions and the convergence conditions aremet. According to the invention, the calculation amount of single finite element analysis and the number of iterations required by topological optimization are effectively reduced while high calculation precision is ensured, so that the total calculation time consumption of topological optimization is greatly reduced.

Description

technical field [0001] The invention relates to the technical field of structural topology optimization, in particular to a BESO topology optimization method based on dynamic evolution rate and self-adaptive grid and its application. Background technique [0002] Structural topology optimization is often applied in the field of construction and optimization processing such as 3D printing. The goal of topology optimization is to find the optimal topology that satisfies the design conditions in the design domain of the structure, so as to give full play to the material properties and make the structure have the best efficiency of resisting external forces. Among the most commonly used structural optimization design methods at present, most continuum topology optimization methods including Bidirectional Progressive Optimization (BESO) are based on finite element technology, that is, it is necessary to discretize the continuum grid , and then perform the iterative operation of ...

AI Technical Summary

Problems solved by technology

BESO topology optimization is an evolutionary topology optimization technology based on iterative operations. In each iterative step, finite element analysis of the structural form of the current iterative step is required. Therefore, topology optimization requires multiple structural finite element calculations. How many optimization iteration steps are needed, how many finite element structure calculations need to be performed, there is a certain amount of calculation time and calculation

[0003] For a topology optimization design domain, the calculation amount of a single finite element is closely related to the grid density. For a two-dimensional structure, doubling the grid density per unit length means that the number of grids in the entire calculation domain increases to the original 4 For a three-dimensional structure, doubling the grid density per unit length means that the number of grids in the entire computational domain increases to 8 times, but the optimal design itself theoretically needs to subdivide the grid as much as possible to approximate Continuum, although an overly coarse grid can save calculation time, it cannot guarantee calculation accuracy

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