首页|基于自适应Kriging的中介机匣结构可靠性分析

基于自适应Kriging的中介机匣结构可靠性分析

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为了探究中介机匣在多失效模式下的结构可靠性分析方法,建立了参数化有限元模型进行确定性分析。考虑航空发动机中介机匣的材料性能、几何参数及外部载荷的不确定性,对中介机匣两种最典型失效模式:静强度失效以及刚度失效建立极限状态函数。通过构造两失效模式下的自适应Kriging(adapt-ive Kriging,AK)模型并结合广义子集模拟(generalized subset simulation,GSS)方法评估中介机匣结构失效概率,并基于Copula函数理论对中介机匣失效模式的相关性进行建模,明确两失效模式之间的相互影响,并与AK-GSS方法计算结果进行对比。结果表明:中介机匣结构系统失效概率在10-6量级;相较于传统方法,AK-GSS方法求解中介机匣结构失效概率时计算时长缩减了 87。7%且几乎未损失计算精度。除此之外,考虑中介机匣两失效模式相关时AK-GSS方法依旧具有高精度。
Reliability analysis of intermediate casing based on adaptive Kriging
In order to explore the structural reliability analysis method of the intermediate casing under multiple failure modes,a parametric finite element model was established for the deterministic analysis of an aero-engine intermediate casing.Considering the uncertainty of material properties,geometric parameters and external loads of the aero-engine intermediate casing,the limit state functions were constructed for the two most typical failure modes of the intermediate casing:static strength failure and stiffness failure.By constructing an adaptive Kriging(AK)surrogate model for two failure modes and combining with the generalized subset simulation(GSS)method,the failure probability of the intermediate casing structure was predicted.And the correlation of the two failure modes was modeled based on the Copula function theory to determine the mutual influence between them,and the calculation results were compared with AK-GSS method.The results showed that the failure probability of the intermediate casing structure system was in the order of 10-6.Compared with the conventional method,the computational time of the AK-GSS method for solving the failure probability was reduced by 87.7%almost without loss of computational accuracy.In addition,the AK-GSS method still had high accuracy when considering the correlation between the two failure modes of the intermediary magazine.

intermediate casingparametric modelingCopula modelingadaptive Kriginggeneralized subset simulation

邸昊源、李洪双

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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

中介机匣 参数化建模 Copula模型 自适应Kriging 广义子集模拟

江苏高校优势学科建设工程资助

2024

航空动力学报
中国航空学会

航空动力学报

CSTPCD北大核心
影响因子:0.59
ISSN:1000-8055
年,卷(期):2024.39(9)
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