【摘要】：對于半剛性連接的研究,主要集中于連接的本構(gòu)關(guān)系彎矩-轉(zhuǎn)角曲線的確定,然而這一曲線關(guān)系,無論是試驗研究還是理論研究,都是基于結(jié)構(gòu)設計變量完全確定的假定,單獨考慮設計變量變化對結(jié)構(gòu)整體響應的影響程度,忽略了各設計變量間的相關(guān)關(guān)系。經(jīng)研究發(fā)現(xiàn),由單因素變化擬合得到的曲線關(guān)系函數(shù)表達式往往在實際應用中會有悖常理。同樣,參數(shù)相關(guān)性問題普遍存在于工程分析和決策評估領域,不能充分考慮參數(shù)之間的相關(guān)關(guān)系將直接導致偏差較大甚至錯誤的分析結(jié)果,因此基于參數(shù)相關(guān)性研究的重要意義并不僅僅局限于對半剛性節(jié)點分析。在對基于參數(shù)相關(guān)特性的半剛性節(jié)點研究過程中發(fā)現(xiàn)了諸多問題,包括有限元計算軟件的局限性和算法上有待改進。在有限元計算過程中,軟件對參數(shù)變化范圍的限定成為了將確定尺寸節(jié)點的彎矩-轉(zhuǎn)角關(guān)系推廣到同類型節(jié)點形式的瓶頸。在有限元分析軟件中抽樣過程是基于蒙特卡羅法,因此在進行概率性設計時,有限元分析過程就會隨著抽樣次數(shù)的增加而增加,這就造成在分析確定參數(shù)的結(jié)構(gòu)時要進行大量的有限元仿真分析,需要耗費大量的機時,這種方法對于處理同一類型的半剛性節(jié)點彎矩-轉(zhuǎn)角曲線是難以實現(xiàn)的。基于此,有必要在數(shù)學方法上研究這類問題的改進計算。針對節(jié)點研究過程中衍生出的蒙特卡羅相關(guān)概率設計問題和隨機性分析問題,論文的主要研究內(nèi)容分為以下幾個部分:首先解決在蒙特卡羅抽樣中考慮參數(shù)相關(guān)性的分離變量研究方法,通過該方法可以方便的控制抽樣過程,核心是將原有的相關(guān)因素變?yōu)椴幌嚓P(guān)因素,這種參數(shù)轉(zhuǎn)換思路在其他考慮相關(guān)因素的綜合評價和規(guī)劃評估問題中也起到重要作用。然后利用混合神經(jīng)網(wǎng)絡良好的小樣本學習和泛化能力構(gòu)建結(jié)構(gòu)響應復雜的函數(shù)關(guān)系,采用改進的混沌粒子群算法優(yōu)化網(wǎng)絡尋址結(jié)構(gòu),建立與元模型匹配程度高的近似模型。同時對近似模型的構(gòu)建方法進入深入的研究,探索不同方法之間的利弊。結(jié)合蒙特卡羅法對結(jié)構(gòu)進行隨機性分析,并提出新的靈敏度度量參數(shù)計算方法以分析隨機變量的全局靈敏度系數(shù),并在靈敏度分析過程中考慮參變量之間的相關(guān)關(guān)系,以使得最終靈敏度分析結(jié)果更符合實際情況。最后將隨機分析方法與靈敏度計算方法應用于半剛性節(jié)點的彎矩-轉(zhuǎn)角模型研究中,期望通過簡便高效的計算方法擬合出便于工程應用的半剛性節(jié)點初始轉(zhuǎn)動剛度關(guān)系式。
[Abstract]:The research of semi-rigid connections is mainly focused on the determination of the moment-angle curve of the constitutive relation of the connection. However, this curve relationship, whether it is an experimental study or a theoretical study, is based on the assumption that the structural design variables are completely determined. The influence of the design variables on the overall response of the structure is considered separately, and the correlation among the design variables is neglected. It is found that the expression of curve relation function derived from single factor variation fitting is often contrary to common sense in practical application. Similarly, the problem of parameter correlation generally exists in the field of engineering analysis and decision evaluation, and it will lead to large deviation or even wrong analysis results if the correlation between parameters is not fully considered. Therefore, the significance of parameter-based correlation study is not limited to the analysis of semi-rigid nodes. Many problems have been found in the research of semi-rigid nodes based on parameter-dependent characteristics, including the limitation of finite element software and the need for improvement in the algorithm. In the process of finite element calculation, the limitation of the parameter variation range of the software becomes the bottleneck of extending the moment-rotation relation of the defined size node to the same type of node form. In the finite element analysis software, the sampling process is based on Monte Carlo method, so in the probability design, the finite element analysis process will increase with the increase of sampling times. As a result, a lot of finite element simulation analysis is needed when analyzing and determining the structure of parameters, and it needs a lot of machines. This method is difficult to realize for the same type of semi-rigid joint bending moment-rotation curve. Based on this, it is necessary to study the improved calculation of this kind of problem in mathematical method. In view of the Monte Carlo correlation probability design problem and the stochastic analysis problem derived from the nodal research process, The main research contents of this paper are as follows: firstly, the research method of separating variables considering the correlation of parameters in Monte Carlo sampling is solved, through which the sampling process can be controlled conveniently. The core is to change the original related factors into independent factors, and this idea of parameter conversion also plays an important role in the comprehensive evaluation and planning evaluation of other relevant factors. Then using the good small sample learning and generalization ability of the hybrid neural network to construct the complex function relation of the structure response, the improved chaotic particle swarm optimization algorithm is used to optimize the network addressing structure, and the approximate model with high matching degree with the metamodel is established. At the same time, the construction method of approximate model is studied deeply, and the advantages and disadvantages between different methods are explored. Based on the Monte Carlo method, the randomness of the structure is analyzed, and a new sensitivity measurement parameter calculation method is proposed to analyze the global sensitivity coefficient of random variables, and the correlation between parameters is considered in the process of sensitivity analysis. In order to make the final sensitivity analysis results more in line with the actual situation. Finally, the stochastic analysis method and the sensitivity calculation method are applied to the study of the moment and rotation angle model of semi-rigid joints. It is expected that the relationship between the initial rotational stiffness of semi-rigid joints and the engineering application can be fitted by a simple and efficient calculation method.
【學位授予單位】：華南理工大學
【學位級別】：博士
【學位授予年份】：2015
【分類號】：TU391

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