基于危险区保持约束的中机身气密压窝板参数优化
Parameter optimization of a mid-fuselage pressurized dimpled panel based on critical region retention constraints
针对某型号民机中机身气密压窝板疲劳裂纹萌生的风险,本文建立面向裂纹危险区(R区)主导构型的多目标优化流程首先,将压窝圆角半径r、板厚t和压窝高度h作为设计变量,以R区最大主应力和压窝板结构体积最小化作为目标;其次,在其余应力集中区域设立危险区保持约束;最后,基于试验设计与代理模型进行优化结果表明,代理模型对R区最大主应力和结构体积的预测平均绝对误差分别为0.39%和2.59%,尺寸参数对R区应力的影响程度为t > h > r,危险区保持约束可有效避免主导高应力区域转移;推荐构型的R区最大主应力预测误差分别为-0.16%和-0.49%本文所提方法能够在兼顾轻量化和降低R区应力水平的同时,保持R区为主导危险区域,可为气密压窝板的尺寸设计与构型筛选提供参考。
To address the risk of fatigue crack initiation in the pressurized dimpled panel of the mid-fuselage of a certain civil aircraft type, this paper establishes a multi-objective optimization procedure oriented to the dominant configuration of the crack critical region (R region). Firstly, the dimple fillet radius r, the panel thickness t and the dimple height h are taken as design variables. The objectives to be minimized are the maximum principal stress in the R region and the structural volume of the dimpled panel. Secondly, critical region retention constraints are imposed on the remaining stress concentration regions. Finally, the optimization is carried out based on the design of experiments and surrogate models. The results show that the mean absolute errors of the surrogate models in predicting the maximum principal stress in the R region and the structural volume are 0.39% and 2.59%, respectively. The degree of influence of the dimensional parameters on the stress in the R region follows the order t > h > r. The critical region retention constraints can effectively prevent the migration of the dominant high-stress region. The prediction errors of the maximum principal stress in the R region for the recommended configurations are -0.16% and -0.49%, respectively. The proposed method can reduce the stress level in the R region while taking lightweight design into account, and can maintain the R region as the dominant critical region. It thus provides a reference for the dimensional design and configuration screening of pressurized dimpled panels.
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国家自然科学基金面上项目(11972364)
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