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  本文關(guān)鍵詞：結(jié)構(gòu)可靠度分析與設(shè)計(jì)的可視化程序?qū)崿F(xiàn)　出處：《北京交通大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： MATLAB GUI 可視化程序 結(jié)構(gòu)可靠度 一次二階矩法 二次二階矩法 蒙特卡洛法 Nataf變換 當(dāng)量正態(tài)化

【摘要】：結(jié)構(gòu)可靠度分析需要進(jìn)行復(fù)雜的運(yùn)算,一般要通過(guò)計(jì)算機(jī)來(lái)完成。目前國(guó)內(nèi)用于工程結(jié)構(gòu)可靠度分析的程序存在著通用性差、功能不完善、人機(jī)交互性差等缺點(diǎn),因此有必要開發(fā)通用性強(qiáng)、功能全面、界面友好的結(jié)構(gòu)可靠度可視化分析程序供科研工作者和工程技術(shù)人員使用。 本文在掌握了常用可靠度分析方法的基礎(chǔ)上,提出了一種估計(jì)非正態(tài)隨機(jī)變量聯(lián)合概率密度的方法,并基于MATLABGUI開發(fā)了“結(jié)構(gòu)可靠度分析與設(shè)計(jì)系統(tǒng)”(Structural Reliability Analysis and Design System,簡(jiǎn)稱SRADS),具體工作如下： (1)針對(duì)非正態(tài)隨機(jī)變量聯(lián)合概率密度函數(shù)難以表達(dá)的問(wèn)題,提出了一種利用當(dāng)量正態(tài)化思路來(lái)估計(jì)聯(lián)合概率密度的方法,并將該方法應(yīng)用于含有相關(guān)隨機(jī)變量的蒙特卡洛重要抽樣法； (2)基于MATLAB GUI開發(fā)了由"JC Method"(簡(jiǎn)稱JCM)、"Mapping Transformation Method"(簡(jiǎn)稱MTM)、" Second Order Reliability Method in Laplace Mode"(簡(jiǎn)稱SORMLM)、"Monte Carlo Direct Sampling Method"(簡(jiǎn)稱MCDSM)、"Monte Carlo Importance Sampling Method"(簡(jiǎn)稱MCISM)、"Design Based On Reliability Index"(簡(jiǎn)稱DBORI)以及"Nataf Transformation Method"(簡(jiǎn)稱NTM)等七個(gè)子模塊構(gòu)成的“結(jié)構(gòu)可靠度分析與設(shè)計(jì)系統(tǒng)”,實(shí)現(xiàn)了一次二階矩法、二次二階矩法和蒙特卡洛模擬法范疇內(nèi)的五種可靠度分析方法以及基于目標(biāo)可靠指標(biāo)的結(jié)構(gòu)設(shè)計(jì)方法和Nataf變換的可視化,各子模塊的操作很簡(jiǎn)單,并且分析結(jié)果都可以顯示在界面上； (3)利用MATLAB的I/O功能將分析結(jié)果和計(jì)算過(guò)程按照一定的格式寫入TXT文件,實(shí)現(xiàn)了用戶保存結(jié)構(gòu)可靠度分析或者基于目標(biāo)可靠指標(biāo)設(shè)計(jì)的“計(jì)算書”的功能； (4)通過(guò)對(duì)有關(guān)文獻(xiàn)中的大量例題進(jìn)行分析與計(jì)算,驗(yàn)證了“結(jié)構(gòu)可靠度分析與設(shè)計(jì)系統(tǒng)”和本文所提方法的有效性。
[Abstract]:Structural reliability analysis needs complex calculation, which is generally completed by computer. At present, the program used for structural reliability analysis in China has poor universality and imperfect function. Therefore, it is necessary to develop a visual analysis program for structural reliability with strong versatility, comprehensive function and friendly interface for use by researchers and engineers. On the basis of mastering the commonly used reliability analysis methods, a new method for estimating the joint probability density of non-normal random variables is proposed in this paper. The structural reliability analysis and design system is developed based on MATLABGUI (. Structural Reliability Analysis and Design System. Abbreviated as SRADS, the specific work is as follows: 1) aiming at the problem that the joint probability density function of non-normal random variables is difficult to express, a method of estimating joint probability density using equivalent normalization is proposed. The method is applied to the Monte Carlo important sampling method with correlated random variables. Based on MATLAB GUI, JC Method has been developed. "Mapping Transformation Method". "Second Order Reliability Method in Laplace Mode" (SORMLM). "Monte Carlo Direct Sampling Method". "Monte Carlo Importance Sampling Method". "Design Based on Reliability Index" And "structure reliability analysis and design system" composed of "Nataf Transformation Method" and other seven sub-modules. Five reliability analysis methods in the category of first-order second-moment method, second-order moment method and Monte Carlo simulation method, as well as the visualization of structure design based on target reliability index and Nataf transformation are realized. The operation of each sub-module is very simple, and the analysis results can be displayed on the interface; 3) using the I / O function of MATLAB to write the analysis results and the calculation process to the TXT file according to a certain format. The function of the user saving structure reliability analysis or the calculation book based on the target reliability index is realized. 4) through the analysis and calculation of a large number of examples in the relevant literature, the validity of the "structural reliability analysis and design system" and the method proposed in this paper are verified.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TU311.2

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