本文選題：最優(yōu)提議分布 + 馬爾可夫鏈蒙特卡羅抽樣��； 參考：《中國地震局工程力學研究所》2015年碩士論文

【摘要】：結構地震損傷識別是土木工程領域的重要研究方向。受各種不確定性因素影響,結構損傷識別是高度不確定性問題,發(fā)展可靠、高效的結構地震損傷識別概率方法與技術成為當前亟待解決的關鍵科學問題。本文針對目前貝葉斯方法在實際結構損傷概率識別中存在的突出問題,采用理論分析、數(shù)值模擬和試驗相結合的手段,從結構響應出發(fā),改進隨機抽樣技術,提出了基于貝葉斯模型更新的結構物理參數(shù)識別和損傷診斷改進方法,并將Park-Ang雙參數(shù)損傷模型與該方法相結合,實現(xiàn)了結構地震損傷水平概率識別與評估。本文主要研究工作如下:1、馬爾可夫鏈蒙特卡羅(MCMC)抽樣方法改進MCMC抽樣是實現(xiàn)貝葉斯模型更新的最重要技術手段之一,目前該抽樣技術在實際工程應用中還存在計算效率低、收斂速度慢甚至不收斂、求解維度低等問題,針對這些問題,本文提出了基于最優(yōu)提議分布的逐分量自適應Metropolis-Hastings(MH)抽樣技術與改進算法,提高了算法的計算效率、收斂速度和穩(wěn)定性,并通過一個數(shù)值算例,驗證了所提抽樣算法的有效性與可靠性。2、基于結構時域響應的物理參數(shù)識別貝葉斯方法針對結構損傷識別非確定性問題及目前傳統(tǒng)貝葉斯模型更新兩階段識別方法依賴于模態(tài)參數(shù)識別問題,本文將結構時域響應作為觀測量,根據(jù)貝葉斯模型更新方法確定結構物理參數(shù)的后驗聯(lián)合分布,并采用所提基于最優(yōu)提議分布的逐分量自適應MH抽樣算法進行分析,得到各物理參數(shù)的后驗邊緣概率分布和最優(yōu)估計值,從而給出了基于結構時域響應的物理參數(shù)識別貝葉斯方法。對某五層剪切型數(shù)值模擬結構進行參數(shù)識別,結果表明:所提方法可以準確的識別出結構物理參數(shù)及其變化,并可有效降低物理參數(shù)的不確定性。3、鋼筋混凝土(RC)框架結構振動臺試驗損傷識別利用所提的基于結構時域響應的物理參數(shù)識別貝葉斯方法對一個3層RC框架結構試驗模型在多次地震動作用下的物理參數(shù)及累積損傷進行了識別,驗證了方法的有效性、可靠性與實用性。進一步與傳統(tǒng)基于模態(tài)參數(shù)的結構物理參數(shù)識別方法分析結果進行對比,結果表明:基于結構時域響應的物理參數(shù)識別貝葉斯方法得到的結果更為可靠。4、結構地震損傷水平概率評估將Park-Ang雙參數(shù)損傷模型與貝葉斯模型更新方法相結合,綜合結構非線性地震反應分析與改進的抽樣算法,確定結構定量化損傷指標的概率分布,從而給出了一種結構地震損傷水平概率識別與評估新方法。對上述3層框架結構試驗模型進行損傷識別與評估,并與試驗現(xiàn)象進行對比,驗證了方法的有效性與合理性。
[Abstract]:Structural seismic damage identification is an important research direction in the field of civil engineering. Under the influence of various uncertain factors, structural damage identification is a highly uncertain problem. The development of reliable and efficient probabilistic methods and techniques for structural seismic damage identification has become a key scientific problem to be solved. In this paper, aiming at the outstanding problems of Bayesian method in actual structural damage probability identification, the random sampling technique is improved by combining theoretical analysis, numerical simulation and experiment. An improved method of structural physical parameter identification and damage diagnosis based on Bayesian model updating is proposed, and the probability identification and evaluation of seismic damage level of structure is realized by combining Park-Ang two-parameter damage model with this method. The main research work of this paper is as follows: 1) the Markov chain Monte Carlo (MCM) sampling method is one of the most important technical means to realize Bayesian model updating. At present, the sampling technique has low computational efficiency in practical engineering application. The convergence rate is slow or not, and the dimension is low. In order to solve these problems, an adaptive Metropolis-HastingsMH sampling technique and an improved algorithm based on the optimal proposed distribution are proposed in this paper, which improves the computational efficiency of the algorithm. Convergence rate and stability, and through a numerical example, The validity and reliability of the proposed sampling algorithm are verified. The Bayesian method of physical parameter identification based on the time-domain response of structure is used to solve the non-deterministic problem of structural damage identification and the traditional Bayesian model updating two-stage identification method. The method depends on the identification of modal parameters. In this paper, the time-domain response of the structure is taken as the observation, and the posteriori joint distribution of the physical parameters of the structure is determined according to the Bayesian model updating method, and the proposed component-by-component adaptive MH sampling algorithm based on the optimal proposed distribution is used to analyze it. The posterior edge probability distribution and optimal estimation of each physical parameter are obtained, and a Bayesian method for identifying physical parameters based on structural time domain response is presented. The parameters of a five-layer shear numerical simulation structure are identified. The results show that the proposed method can accurately identify the physical parameters of the structure and its changes. And can effectively reduce the uncertainty of physical parameters .3. reinforced concrete frame structure vibration table test damage identification using the proposed time domain response based on the physical parameters identification Bayesian method for a three-story RC frame structure The physical parameters and cumulative damage of the experimental model under repeated ground motions are identified. The validity, reliability and practicability of the method are verified. Compared with the traditional structural physical parameter identification method based on modal parameters, The results show that the Bayesian method based on the time-domain response of structure is more reliable. The probability evaluation of structural damage level combines Park-Ang two-parameter damage model with Bayesian model updating method. The probability distribution of the quantitative damage index is determined by combining the nonlinear seismic response analysis and the improved sampling algorithm, and a new method to identify and evaluate the seismic damage level is presented. The damage identification and evaluation of the above three story frame structure test model are carried out, and compared with the experimental phenomena, the validity and rationality of the method are verified.
【學位授予單位】：中國地震局工程力學研究所
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TU317

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相關期刊論文 前1條

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本文編號：1911459