本文選題：重要性測(cè)度 + 區(qū)域重要性��； 參考：《西北工業(yè)大學(xué)》2015年博士論文

【摘要】：航空及機(jī)械等復(fù)雜工程結(jié)構(gòu)系統(tǒng)中廣泛存在各種各樣的不確定性。針對(duì)復(fù)雜結(jié)構(gòu)的特點(diǎn),研究這些不確定性對(duì)輸出性能的影響,預(yù)測(cè)復(fù)雜結(jié)構(gòu)系統(tǒng)在不確定性環(huán)境下的風(fēng)險(xiǎn)評(píng)估和可靠性模型的不確定性傳遞具有重要的意義。為了提高復(fù)雜結(jié)構(gòu)在不確定性環(huán)境下的性能,在已有研究的基礎(chǔ)上,本文展開以下研究:1)在結(jié)構(gòu)可靠性分析和設(shè)計(jì)中,往往存在部分不確定性分布特征不明確而僅知其不確定參數(shù)的邊界,因此基于凸集非概率模型的不確定性描述得到廣泛關(guān)注。為了有效分析凸集非概率輸入變量對(duì)可靠性工程中所關(guān)心的結(jié)構(gòu)系統(tǒng)失效的影響,在矩獨(dú)立重要性測(cè)度的基礎(chǔ)上,擴(kuò)展了其在非概率可靠性分析中的工程應(yīng)用,建立了基于凸模型非概率可靠性的矩獨(dú)立重要性測(cè)度。針對(duì)凸集非概率輸入變量對(duì)非概率可靠性貢獻(xiàn)表達(dá)式的特點(diǎn),將態(tài)相關(guān)參數(shù)(State Dependent Parameter,SDP)方法和主動(dòng)學(xué)習(xí)Kriging(Active learning Kriging,ALK)方法建立代理模型的優(yōu)點(diǎn)推廣到該重要性測(cè)度的計(jì)算當(dāng)中,并以實(shí)際算例驗(yàn)證了所提重要性測(cè)度的合理性,所推導(dǎo)的非概率可靠性重要性測(cè)度的普遍適用性以及所建求解方法的可行性。2)為研究輸入變量分布參數(shù)對(duì)基于失效概率的重要性測(cè)度的影響程度,建立一個(gè)基于失效概率的重要性測(cè)度對(duì)輸入變量分布參數(shù)的靈敏度分析體系。該參數(shù)靈敏度首先分析各個(gè)不確定性分布參數(shù)對(duì)基于失效概率的重要性測(cè)度不確定性傳遞,得到重要性測(cè)度后在分布參數(shù)處求導(dǎo)。針對(duì)復(fù)雜結(jié)構(gòu)模型,將重要性分析中高效的ALK方法引入到基于失效概率的重要性測(cè)度參數(shù)的靈敏度分析中,解決了傳統(tǒng)的MC求解中計(jì)算量過于龐大的困難,大大提高了計(jì)算效率。3)為了降低復(fù)合隨機(jī)振動(dòng)系統(tǒng)動(dòng)力學(xué)輸出的失效概率,引入了基于失效概率主重要性測(cè)度指標(biāo)和總重要性測(cè)度指標(biāo),通過控制重要性程度高的輸入變量的不確定性來降低失效概率。結(jié)合復(fù)合隨機(jī)振動(dòng)系統(tǒng)動(dòng)力學(xué)輸出的特點(diǎn),采用ALK方法能在不減少精確度的條件下大幅減少計(jì)算量。其次從隨機(jī)結(jié)構(gòu)無條件動(dòng)力可靠度的表達(dá)式出發(fā),利用條件概率密度函數(shù)的解析變換,給出了一種衡量基本隨機(jī)變量對(duì)動(dòng)力可靠性影響的矩獨(dú)立重要性測(cè)度指標(biāo)�；趹B(tài)相關(guān)參數(shù)模型,提出了求解矩獨(dú)立重要性測(cè)度指標(biāo)的態(tài)相關(guān)參數(shù)(SDP)法。與直接Monte-Carlo法對(duì)比,所提方法可以在保證計(jì)算精度的同時(shí)大幅度提高計(jì)算效率,適用于分析復(fù)合隨機(jī)振動(dòng)系統(tǒng)的非線性可靠性響應(yīng)。4)將基于均值和方差的區(qū)域重要性指標(biāo)進(jìn)一步推廣到復(fù)合隨機(jī)結(jié)構(gòu)結(jié)構(gòu)系統(tǒng),分別定義了輸入變量的任意取值區(qū)域?qū)敵鰟?dòng)力學(xué)可靠度及動(dòng)力學(xué)可靠性測(cè)度主貢獻(xiàn)的區(qū)域重要性指標(biāo),為復(fù)雜結(jié)構(gòu)動(dòng)力學(xué)可靠性設(shè)計(jì)工程提供更多的有用信息。另外,本文還針對(duì)當(dāng)前基于輸出動(dòng)力學(xué)可靠性測(cè)度主貢獻(xiàn)的區(qū)域重要性指標(biāo)定義中的問題,根據(jù)了其表達(dá)式的特點(diǎn)建立了所提各種指標(biāo)高效的求解方法。5)針對(duì)同時(shí)含有主、客觀混合不確定性的結(jié)構(gòu)系統(tǒng),考慮到主客觀變量含有非概率變量的情況,提出了新的主客觀重要性測(cè)度。所提指標(biāo)體系能夠很好的度量含非概率變量情況下主客觀輸入變量對(duì)結(jié)構(gòu)可靠度的影響,為主、客觀混合不確定性情況下減縮模型維度和減少輸出響應(yīng)的不確定性提供指導(dǎo)。同時(shí)建立了主、客觀混合不確定性從主觀輸入變量向輸出性能可靠度的傳遞過程,給出了兩種重要性測(cè)度的基本求解方法和實(shí)現(xiàn)步驟。針對(duì)所提出的主、客觀變量重要性測(cè)度指標(biāo)求解中存在的問題,建立了兩種主、客觀輸入變量重要性分析算法,并采用數(shù)值和工程算例驗(yàn)證了其效率和精度,滿足實(shí)際復(fù)雜工程結(jié)構(gòu)的需要。
[Abstract]:There are various uncertainties in the complex engineering structure systems such as aviation and machinery. In view of the characteristics of complex structures, it is important to predict the impact of these uncertainties on the output performance and to predict the risk assessment and the uncertainty transmission of the reliability model in the uncertain environment. The performance of complex structures in the uncertain environment has been studied on the basis of the existing research. 1) in structural reliability analysis and design, there are often some uncertainties in the uncertain distribution characteristics and only the boundary of the uncertain parameters. Therefore, the uncertainty description based on the non probabilistic model of convex sets has been widely concerned. In order to effectively analyze the effect of the non probabilistic input variable on the failure of the structural system in the reliability engineering, the engineering application in the non probabilistic reliability analysis is extended on the basis of the moment independent importance measure, and a moment independent importance measure based on the non probabilistic reliability of the convex model is established. The characteristics of the contribution expression to the non probabilistic reliability contribution are presented. The advantages of the State Dependent Parameter (SDP) method and the active learning Kriging (Active learning Kriging, ALK) method are extended to the calculation of the importance measure, and the reasonableness of the importance measure is verified by a practical example. The generalized applicability of the importance measure of non probabilistic reliability and the feasibility of the proposed solution method.2) to study the influence degree of the input variable distribution parameters on the importance measure based on the failure probability, a sensitivity analysis system based on the importance measure of the failure probability on the input variable distribution parameters is established. The sensitivity first analyzes the uncertainty transfer of the uncertainty distribution parameters to the importance measure based on the failure probability, and obtains the guidance after the importance measure. For the complex structure model, the efficient ALK method in the importance analysis is introduced to the sensitivity analysis of the importance measure parameters based on the failure probability, and the solution is solved. In order to reduce the failure probability of the dynamic output of the composite random vibration system, the failure probability of the dynamic output of the composite random vibration system is reduced. In order to reduce the failure probability of the dynamic output of the composite random vibration system, the index of the main importance measure based on the failure probability and the measure of the total importance are introduced, and the uncertainty of the input variable of high importance is reduced to reduce the uncertainty of the MC. In combination with the characteristics of the dynamic output of the composite random vibration system, the ALK method can be used to reduce the amount of calculation without reducing the accuracy. Secondly, based on the expression of the unconditional dynamic reliability of the random structure and the analytical change of the conditional probability density function, a measure of the basic random variable pair motion is given. Based on the state dependent parameter model, the state dependent parameter (SDP) method for solving the moment independent importance measure is proposed. Compared with the direct Monte-Carlo method, the proposed method can greatly improve the calculation efficiency while ensuring the calculation precision, and is suitable for the analysis of the composite random vibration system. In the nonlinear reliability response.4), the regional importance index based on mean and variance is further extended to the composite stochastic structural system. The regional gravity index for the main contribution of the arbitrary value area of the input variable to the output dynamic reliability and the dynamic reliability measure is defined respectively, which is set up for the dynamic reliability of the complex structure. The project provides more useful information. In addition, this paper also aims at the problem of the current regional importance index definition based on the main contribution of the output dynamic reliability measurement. According to the characteristics of the expression, the paper establishes a method of solving all kinds of indexes high efficiency.5) for the structure system with both main and objective mixed uncertainty. Considering that the subjective and objective variables contain non probabilistic variables, a new subjective and objective importance measure is proposed. The proposed index system can well measure the influence of the subjective and objective input variables on the structural reliability under the case of non probability variables, and the uncertainty of the model dimension and the output response are reduced under the objective mixed uncertainty. At the same time, the transfer process of the objective mixed uncertainty from the subjective input variable to the output reliability is established, and the basic solution methods and the implementation steps of the two importance measures are given. Two kinds of main and objective inputs are established to solve the existing problems in the solution of the importance measure index of the subjective and objective variables. Variable importance analysis algorithm is applied, and numerical and engineering examples are used to verify its efficiency and accuracy, so as to meet the needs of practical complex engineering structures.
【學(xué)位授予單位】：西北工業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2015
【分類號(hào)】：TB114.3
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本文編號(hào)：1902230