带襟翼导轨翼肋后缘尺寸-拓扑综合优化的摄动神经网络代理模型法OACSTPCD
The Perturbation Neural Network Surrogate Model Method for Size-Topology Synthetical Optimization of Wing Rib Trailing Edges With Flap Tracks
带襟翼导轨的翼肋后缘设计需要确定肋缘条、腹板的尺寸和肋腹板的拓扑形状,对此提出了一种针对尺寸-拓扑综合优化的摄动神经网络(perturbation neural network,PNN)代理模型法.其基本思想是基于拓扑优化对参数的敏感性,引入了对试验设计(design of experiments,DOE)样本点的摄动,通过过滤手段捕获拓扑突变点,并降低数值噪声,极大地提高了代理模型的预测精度,将拓扑优化过程作为黑盒,直接建立起尺寸变量与拓扑优化后结构响应的代理模型.最后在代理模型上进行优化,得到了结构尺寸与拓扑形状的最优组合.该文完成了一个翼肋后缘优化典型算例,证明了该方法的有效性和优越性.
The design of wing rib trailing edges with flap tracks requires the determination of sizes of the rib edge strips,the webs and the topological shapes of the rib webs.Therefore,a perturbation neural network sur-rogate model method was proposed for the size-topology synthetical optimization.The basic idea is that,based on the sensitivity of topology optimization to parameters,the perturbation is introduced in the DOE samples to capture the topological mutation points by means of the filtering measure,and reduce the numerical noise,which greatly improves the prediction accuracy of the surrogate model.With the topology optimization process viewed as a black box,the surrogate model for the size variables and topology optimized structural responses was directly built up.Finally,optimization was carried out on the surrogate model to obtain the optimal combi-nation of structural sizes and topological shapes.A typical calculation example of wing rib trailing edge optimi-zation demonstrates the validity and superiority of the proposed method.
谢川;徐超;周丹发;姚卫星
南京航空航天大学 航空航天结构力学及控制全国重点实验室,南京 210016上海机电工程研究所,上海 201109南京航空航天大学 航空航天结构力学及控制全国重点实验室,南京 210016||南京航空航天大学 飞行器先进设计技术国防重点学科实验室,南京 210016
力学
摄动神经网络尺寸优化拓扑优化代理模型翼肋
perturbation neural networksize optimizationtopology optimizationsurrogate modelwing rib
《应用数学和力学》 2024 (001)
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