本文選題：多學(xué)科設(shè)計(jì)優(yōu)化 + 序列優(yōu)化與可靠性評(píng)估��； 參考：《電子科技大學(xué)》2014年博士論文

【摘要】：現(xiàn)代科學(xué)技術(shù)的日新月異,使得工程系統(tǒng)愈發(fā)復(fù)雜化,其具體設(shè)計(jì)過(guò)程往往涉及諸多學(xué)科,且學(xué)科之間的聯(lián)系耦合緊密。為了解決傳統(tǒng)設(shè)計(jì)優(yōu)化方法的局限性,多學(xué)科設(shè)計(jì)優(yōu)化(Multidisciplinary Design Optimization,MDO)應(yīng)運(yùn)而生。MDO方法在充分考慮耦合學(xué)科之間協(xié)同效應(yīng)的同時(shí),從工程系統(tǒng)全局的角度進(jìn)行設(shè)計(jì)優(yōu)化,實(shí)現(xiàn)提高系統(tǒng)綜合性能,縮短研發(fā)周期并降低生產(chǎn)成本的目的。不確定性因素廣泛地存在于實(shí)際工程系統(tǒng)中。特別是在復(fù)雜耦合的工程系統(tǒng)中,不確定性因素會(huì)隨著耦合信息的傳播而累積,最終對(duì)工程系統(tǒng)的綜合性能產(chǎn)生影響,給工程系統(tǒng)的可靠性、穩(wěn)定性以及安全性帶來(lái)隱患。為了在設(shè)計(jì)優(yōu)化過(guò)程中有效考慮這些不確定性因素的影響,基于可靠性的多學(xué)科設(shè)計(jì)優(yōu)化(Reliability based Multidisciplinary Design Optimization,RBMDO)已成為現(xiàn)代工程系統(tǒng)設(shè)計(jì)的研究熱點(diǎn)之一。迄今為止,對(duì)于考慮隨機(jī)不確定性的RBMDO方法,在結(jié)合經(jīng)典概率論等可靠性分析方法后日趨成熟。同時(shí),由于序列優(yōu)化與可靠性評(píng)估(Sequential Optimization and Reliability Assessment,SORA)策略的采用,使得可靠性分析過(guò)程與設(shè)計(jì)優(yōu)化過(guò)程相互解耦,整個(gè)RBMDO過(guò)程分解為一系列相互交替進(jìn)行的確定性MDO與可靠性分析過(guò)程,運(yùn)算效率得以進(jìn)一步提升�；赟ORA策略,本文分別從“RBMDO問(wèn)題中的確定性MDO方法創(chuàng)新”和“不同可靠性分析方法在RBMDO問(wèn)題中的引入與應(yīng)用”兩個(gè)方面展開(kāi)研究。具體地,利用大系統(tǒng)遞階控制理論與方法在處理復(fù)雜系統(tǒng)協(xié)調(diào)問(wèn)題中的策略,針對(duì)SORA下RBMDO中的確定性MDO方法進(jìn)行創(chuàng)新研究;利用鞍點(diǎn)近似方法(Saddlepoint Approximation,SPA)對(duì)一階可靠性方法評(píng)估精度的改進(jìn),以及利用子集模擬可靠性分析方法(Subset Simulation Reliability Analysis,SSRA)對(duì)小概率失效事件的可靠性分析評(píng)估效率的改進(jìn),分別將上述兩種新的可靠性分析方法引入并應(yīng)用到SORA下RBMDO中的可靠性分析環(huán)節(jié)。兩個(gè)方面的理論研究工作圍繞SORA策略下RBMDO整體的計(jì)算效率提高與優(yōu)化精度改進(jìn)展開(kāi),擬拓展和完善現(xiàn)有RBMDO的理論體系。最后,在利用已有和上述理論研究成果的基礎(chǔ)上,以某型號(hào)變體飛行器的翻轉(zhuǎn)驅(qū)動(dòng)機(jī)構(gòu)為例,展開(kāi)RBMDO方法在機(jī)構(gòu)設(shè)計(jì)優(yōu)化中的工程應(yīng)用研究。系統(tǒng)地分析該機(jī)構(gòu)的多學(xué)科耦合特性以及不確定性因素影響。完成該機(jī)構(gòu)的RBMDO同時(shí),與原始設(shè)計(jì)方案進(jìn)行對(duì)比分析,對(duì)優(yōu)化后的設(shè)計(jì)方案進(jìn)一步地進(jìn)行研究。本文的研究成果主要體現(xiàn)在如下四個(gè)方面:(1)關(guān)聯(lián)預(yù)測(cè)優(yōu)化(interactionpredictionoptimization,ipo)與關(guān)聯(lián)平衡優(yōu)化(interactionbalanceoptimization,ibo)。利用大系統(tǒng)遞階控制理論中的關(guān)聯(lián)預(yù)測(cè)控制與關(guān)聯(lián)平衡控制兩種方法,分別結(jié)合協(xié)同優(yōu)化(collaborativeoptimization,co)方法的子學(xué)科分布式并行優(yōu)化和協(xié)調(diào)策略,提出兩種新的mdo方法用于sora策略下rbmdo中的確定性優(yōu)化,避免了co方法中的相容性約束給原rbmdo問(wèn)題增加非線性程度的缺陷。所提出方法與co方法相比,學(xué)科間的協(xié)調(diào)策略更加簡(jiǎn)單,對(duì)于優(yōu)化問(wèn)題的求解具有更高的運(yùn)算效率和精度。通過(guò)算例驗(yàn)證了所提出方法的有效性。(2)基于一階鞍點(diǎn)近似方法的多學(xué)科設(shè)計(jì)優(yōu)化(firstordersaddlepointapproximationbasedmdo,fospa-mdo)。當(dāng)優(yōu)化問(wèn)題中存在隨機(jī)不確定性時(shí),采用一階鞍點(diǎn)近似(firstordersaddlepointapproximation,fospa)方法對(duì)sora策略下rbmdo中的確定性mdo優(yōu)化結(jié)果進(jìn)行可靠性分析與評(píng)估,不需要將隨機(jī)變量轉(zhuǎn)化成標(biāo)準(zhǔn)正態(tài)空間中的標(biāo)準(zhǔn)正態(tài)分布隨機(jī)變量,避免了由于采用傳統(tǒng)一階或二階可靠性方法所帶來(lái)的增加原優(yōu)化問(wèn)題非線性程度的缺陷。在搜索獲得似然設(shè)計(jì)驗(yàn)算點(diǎn)(mostlikelihoodpoint,mlp)后,利用隨機(jī)變量與參數(shù)的移動(dòng)向量建立新一輪運(yùn)算中的確定性優(yōu)化模型。所提出方法與基于一階可靠性方法(firstorderreliabilitymethod,form)的rbmdo相比,在保證計(jì)算效率的同時(shí),擁有更加準(zhǔn)確的可靠性評(píng)估精度。通過(guò)算例驗(yàn)證了所提出方法的有效性。(3)基于子集模擬可靠性分析方法的多學(xué)科設(shè)計(jì)優(yōu)化(subsetsimulationreliabilityanalysisbasedmdo,ssra-mdo)。當(dāng)優(yōu)化設(shè)計(jì)對(duì)象系統(tǒng)擁有極高的可靠性,需要對(duì)其發(fā)生小概率失效事件進(jìn)行可靠性評(píng)估時(shí),為了能準(zhǔn)確且高效地完成rbmdo,采用基于子集模擬可靠性分析方法(subsetsimulationreliabilityanalysis,ssra)對(duì)sora策略下rbmdo中的確定性mdo優(yōu)化結(jié)果進(jìn)行可靠性分析與評(píng)估。該方法將原失效概率計(jì)算問(wèn)題轉(zhuǎn)變?yōu)橐幌盗邪l(fā)生概率較高的條件失效概率計(jì)算問(wèn)題,通過(guò)馬爾可夫鏈蒙特卡羅仿真(markovchainmontecarlosimulation)方法分別計(jì)算各個(gè)中間條件失效概率。在搜索獲得模擬設(shè)計(jì)驗(yàn)算點(diǎn)(simulationmostprobablepoint,smpp)后,利用隨機(jī)變量與參數(shù)的移動(dòng)向量建立新一輪運(yùn)算中的確定性優(yōu)化模型。所提出方法與基于傳統(tǒng)蒙特卡洛仿真(montecarlosimulation,mcs)的rbmdo相比,在保證計(jì)算精度的同時(shí),使用更少數(shù)量的仿真樣本點(diǎn),擁有更加高效的計(jì)算效率。通過(guò)算例驗(yàn)證了所提出方法的有效性。(4)某翻轉(zhuǎn)驅(qū)動(dòng)機(jī)構(gòu)的考慮隨機(jī)不確定性的多學(xué)科設(shè)計(jì)優(yōu)化。根據(jù)某翻轉(zhuǎn)驅(qū)動(dòng)機(jī)構(gòu)的組成與運(yùn)動(dòng)原理,將該機(jī)構(gòu)劃分為動(dòng)力輸入學(xué)科與動(dòng)力傳遞學(xué)科。在分別對(duì)各個(gè)構(gòu)件以及機(jī)構(gòu)整體進(jìn)行有限元分析與動(dòng)力學(xué)分析的基礎(chǔ)上,構(gòu)造相應(yīng)的性能函數(shù)響應(yīng)面。分析實(shí)際工程中的不確定性來(lái)源,建立該翻轉(zhuǎn)驅(qū)動(dòng)機(jī)構(gòu)的RBMDO模型并利用本文所提出的SSRA-MDO方法在SORA策略下進(jìn)行優(yōu)化求解。將優(yōu)化后的設(shè)計(jì)方案與原始設(shè)計(jì)方案進(jìn)行比較分析,進(jìn)一步闡述了所得結(jié)果的合理性。
[Abstract]:With the rapid development of modern science and technology, the engineering system is becoming more and more complex, and its specific design process often involves many disciplines, and the connection between the disciplines is closely coupled. In order to solve the limitations of the traditional design optimization method, Multidisciplinary Design Optimization (MDO) has emerged as the times require the.MDO method. Considering the synergistic effect among the coupling subjects, the design optimization is carried out from the point of view of the overall engineering system to improve the comprehensive performance of the system, shorten the R & D cycle and reduce the cost of production. The uncertain factors exist widely in the actual engineering system. Especially in the complex coupled Engineering system, the uncertainty factors will follow The accumulation of coupling information will eventually influence the comprehensive performance of the engineering system and bring hidden dangers to the reliability, stability and security of the engineering system. In order to consider the influence of these uncertainties effectively in the process of design optimization, Reliability based Multidisciplinary based on Reliability Design Optimization, RBMDO (RBMDO) has become one of the hot topics in modern engineering system design. To date, the RBMDO method considering random uncertainty is becoming more and more mature after the combination of the classical probability theory and other reliability analysis methods. At the same time, because of the sequence optimization and reliability evaluation (Sequential Optimization and Reliability Assessment, SORA) the adoption of the strategy makes the reliability analysis process and the design optimization process decouple each other. The whole RBMDO process is decomposed into a series of alternative deterministic MDO and reliability analysis processes, and the operational efficiency is further improved. Based on the SORA strategy, this paper separately from "the deterministic MDO method in the RBMDO problem" and "no". The introduction and application of reliability analysis method in the RBMDO problem is studied in two aspects. Specifically, the strategy of the large system hierarchical control theory and method in the coordination of complex systems is used to study the deterministic MDO method in RBMDO under SORA; and the saddle point approximation (Saddlepoint Approximation, SP) is used. A) improvement on the evaluation accuracy of first order reliability method and the improvement of reliability analysis and evaluation efficiency of small probability failure events by using the Subset Simulation Reliability Analysis (SSRA) method (Analysis, SSRA). The two new reliability analysis methods are introduced and applied to the reliability of RBMDO in SORA. The two aspects of the theoretical research work around the overall calculation efficiency of RBMDO and the improvement of the optimization precision under the SORA strategy. The theoretical system of the existing RBMDO is expanded and perfected. Finally, on the basis of the existing and above theoretical research results, the RBMDO square is carried out with the overturning drive mechanism of a certain type of variant aircraft. The study of engineering application in the optimization of mechanism design. A systematic analysis of the multidisciplinary coupling characteristics and uncertainty factors of the mechanism is made. The RBMDO of the organization is completed and the original design scheme is compared and analyzed. The optimized design scheme is further studied. The results of this paper are mainly reflected in the following four Aspects: (1) association prediction optimization (interactionpredictionoptimization, IPO) and association equilibrium optimization (interactionbalanceoptimization, IBO). Using the two methods of associated predictive control and association balance control in the hierarchical control theory of large systems, the sub Discipline Distribution of the cooperative optimization (collaborativeoptimization, CO) method is combined respectively. In parallel optimization and coordination strategy, two new MDO methods are proposed for the deterministic optimization of RBMDO under the Sora strategy, which avoids the defect that the compatibility constraint in the co method increases the nonlinearity of the original RBMDO problem. Compared with the co method, the coordination strategy between the subjects is more simple, and the solution of the optimization problem is higher. Efficiency and accuracy. The effectiveness of the proposed method is verified by an example. (2) the multidisciplinary design optimization (firstordersaddlepointapproximationbasedmdo, fospa-mdo) based on the first order saddle point approximation (fospa-mdo). When the stochastic uncertainty exists in the optimization problem, the first order saddle point approximation (firstordersaddlepointapproximation, fospa) square is used. The reliability analysis and evaluation of the deterministic MDO optimization results in RBMDO under the Sora strategy do not need to convert random variables into standard normal distribution random variables in standard normal space, and avoid the defects caused by the use of traditional first or two order reliability methods to increase the nonlinear degree of the original optimization problem. After obtaining the likelihood design check point (mostlikelihoodpoint, MLP), the deterministic optimization model in a new round of operation is established by using the random variable and the moving vector of the parameter. The proposed method is more accurate than the RBMDO based on the first order reliability method (firstorderreliabilitymethod, form). The effectiveness of the proposed method is verified by an example. (3) the multidisciplinary design optimization (subsetsimulationreliabilityanalysisbasedmdo, ssra-mdo) based on the subset simulation reliability analysis method. The reliability evaluation of the small probability failure event is required when the optimal design object system has high reliability. In order to complete the RBMDO accurately and efficiently, the reliability analysis and evaluation of the deterministic MDO optimization results in RBMDO under the Sora strategy are analyzed and evaluated using the subset simulation reliability analysis method (subsetsimulationreliabilityanalysis, SsrA). This method transforms the original failure probability calculation problem into a series of conditions with higher probability of loss. The failure probability of each intermediate condition is calculated by the Markov Monte Carlo simulation (markovchainmontecarlosimulation) method. After searching for the simulated design checking point (simulationmostprobablepoint, SMPP), the determinacy of the new round operation is established by using the random variable and the moving vector of the parameter. The proposed method is compared with the RBMDO based on the traditional Monte Carlo simulation (montecarlosimulation, MCS). Compared with the RBMDO based on the traditional Monte Carlo simulation (MCS), a less number of simulation sample points are used while the computational efficiency is more efficient. The effectiveness of the proposed method is verified by an example. (4) the random uncertainty of a flipped drive mechanism is considered. According to the composition and movement principle of a overturned driving mechanism, the mechanism is divided into dynamic input subject and dynamic transmission subject. On the basis of finite element analysis and dynamic analysis of each component and mechanism, the corresponding response surface of performance function is constructed. The RBMDO model of the overturned driving mechanism is established by the deterministic source, and the SSRA-MDO method proposed in this paper is used to optimize the solution under the SORA strategy. The optimized design scheme is compared with the original design scheme, and the rationality of the results is further elaborated.

【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TH112
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本文編號(hào)：1799626