首页|基于失效概率的涡轮后机匣全局灵敏度分析

基于失效概率的涡轮后机匣全局灵敏度分析

扫码查看
涡轮后机匣作为航空发动机安全的关键部件,具有工况复杂、不确定性因素多的缺点.为了探究输入随机变量的不确定性对涡轮后机匣结构失效概率的影响,建立参数化有限元模型进行确定性分析.考虑材料性能、几何参数及外部载荷的不确定性,对涡轮后机匣两种典型失效模式建立极限状态函数;通过构造自适应Kriging代理模型并结合重要抽样方法评估涡轮后机匣结构失效概率,利用基于失效概率的全局灵敏度方法对涡轮后机匣结构可靠度的不确定性来源进行分析,对各输入随机变量重要性进行排序,构建一种涡轮后机匣全局灵敏度分析框架.结果表明:涡轮后机匣在两种失效模式以及系统失效模式下,发动机推力以及线性膨胀系数对结构失效概率影响最为显著,应对其重点考虑;内外机匣长度以及材料弹性模量对涡轮后机匣结构失效概率影响较小,可对其适当忽略.
Global sensitivity analysis of turbine rear casing based on failure probability
The aero-engine turbine rear casing is a key component for aero-engine safety,but it has complex wor-king conditions and multiple uncertain factors.In order to explore the influence of the uncertainty of input random variables on the failure probability of a turbine rear casing structure,a parametric finite element model is established for the deterministic analysis of the aero-engine intermediate casing.Considering the uncertainty of material proper-ties,geometric parameters and external loads of the aero-engine intermediate casing,the limit state functions are constructed for the two most typical failure modes:static strength and stiffness failures.By constructing an adaptive Kriging surrogate model and combining importance sampling method,the failure probability of the casing structure is predicted.The uncertainty source of the reliability of the turbine rear casing structure is analyzed by a global sensi-tivity analysis method based on failure probability.The importance order of all input random variables is identified,and a global sensitivity analysis framework for aero-engine turbine rear casing is proposed.The results show that,under the two failure modes and system failure modes,the engine thrust and linear expansion coefficient have the most significant influence on the structural failure probability,which should be considered emphatically.The length of inner and outer casing and the elastic modulus of the material have little influence on the structural failure proba-bility of the turbine rear casing,which could be ignored.

turbine rear casingglobal sensitivity analysisadaptive Krigingimportance samplingMarkov chain

邸昊源、李洪双

展开 >

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

涡轮后机匣 全局灵敏度分析 自适应Kriging 重要抽样 马尔科夫链

2024

航空工程进展
中国航空学会 西北工业大学

航空工程进展

CSTPCD
影响因子:0.207
ISSN:1674-8190
年,卷(期):2024.15(1)
  • 7