橋梁風(fēng)荷載的非高斯特性研究
發(fā)布時間：2018-08-07 21:16
【摘要】：隨著建造技術(shù)的逐漸進(jìn)步,現(xiàn)代橋梁向著“長大輕柔”的方向不斷發(fā)展。結(jié)構(gòu)剛度及阻尼隨之降低,使得橋梁對風(fēng)荷載的作用更加敏感。風(fēng)荷載作為典型的隨機(jī)過程,其作用極值一直是影響橋梁結(jié)構(gòu)設(shè)計的重要因素,傳統(tǒng)計算方法一般將其假設(shè)為高斯過程來估計極值。越來越多的試驗及現(xiàn)場觀測結(jié)果表明,橋梁所受風(fēng)荷載有時呈現(xiàn)出明顯的非高斯特性,若根據(jù)高斯假定計算極值,結(jié)果可能偏于危險。在此背景下,本文針對橋梁風(fēng)荷載的非高斯特性展開研究,主要工作包括以下幾方面：(1)介紹風(fēng)荷載非高斯特性研究現(xiàn)狀及荷載極值的主要算法,結(jié)合理論分析和實際應(yīng)用總結(jié)各種算法的優(yōu)勢及缺點。經(jīng)過計算驗證,發(fā)現(xiàn)改進(jìn)峰值因子法計算結(jié)果偏保守；Gumbel法受短時距下極值間相關(guān)性影響,其計算結(jié)果穩(wěn)定性不佳;Sadek-Simiu法僅適用于偏度值較大的一類非高斯過程極值計算。(2)總結(jié)了非高斯風(fēng)荷載極值計算的幾大難題：A.如何借助前四階統(tǒng)計矩盡量全面地描述無窮多樣的非高斯分布?B.如何由少量試驗樣本提取更多信息,從而更好地描述隨機(jī)過程?C.如何在解決好相關(guān)性影響的同時保證極值樣本數(shù)量,從而保障極值分布的擬合精度?D.如何實現(xiàn)一種計算方法適用范圍的最大化,即同時適用于軟、硬響應(yīng)過程,同時適用于最大、最小峰值的計算?(3)針對性提出一種基于仿真技術(shù)的風(fēng)荷載過程極值算法：利用仿真技術(shù)生成多條風(fēng)壓時程來模擬時程樣本空間,更好地描述了隨機(jī)過程,且滿足了極值分布擬合的樣本數(shù)量；利用Johnson變換生成具有任意前四階統(tǒng)計矩的非高斯序列,來模擬無窮多樣的非高斯分布；利用AR自回歸模型完成對風(fēng)壓過程相關(guān)性的仿真；本文算法對非高斯過程的概率特性和相關(guān)特性均具有自適應(yīng)性,針對不同原始測量結(jié)果,產(chǎn)生不同概率密度函數(shù)及AR模型完成仿真,最終利用經(jīng)典極值理論完成對風(fēng)壓極值的計算,因此本文算法適用于全部類型的平穩(wěn)風(fēng)壓過程極值計算。(4)基于橋梁主梁節(jié)段模型測壓試驗結(jié)果,總結(jié)主梁表面非高斯風(fēng)壓區(qū)域分布特點。采用幾種已有風(fēng)荷載極值計算方法及本文提出的算法分別計算典型測點處風(fēng)壓極值,并與真實測量結(jié)果進(jìn)行對比分析,證明了本文算法可適用于全部類型的風(fēng)荷載過程,且與其他算法相比具有更高的計算精度。
[Abstract]:With the gradual progress of construction technology, modern bridges are developing in the direction of "growing up and soft". The stiffness and damping of the bridge are reduced, which makes the bridge more sensitive to wind load. As a typical stochastic process, the action extremum of wind load is always an important factor that affects the design of bridge structure. The traditional calculation method usually assumes the extreme value as Gao Si process to estimate the extreme value. More and more experiments and field observations show that the wind loads of bridges sometimes show obvious non-Gao Si characteristics. If the extreme value is calculated according to the Gao Si assumption, the results may be partial to the danger. In this context, the non-Gao Si characteristics of wind load of bridges are studied in this paper. The main work includes the following aspects: (1) introduce the research status of non-Gao Si characteristics of wind load and the main algorithms of load extremum. Combined with theoretical analysis and practical application, the advantages and disadvantages of various algorithms are summarized. It is found that the modified peak factor method is more conservative than the Gumbel method, which is influenced by the correlation between the extreme values at short time intervals. The Sadek-Simiu method is only suitable for the extreme value calculation of a class of non-Gao Si processes with large deviation. (2) several difficult problems in calculating the extreme value of non-Gao Si wind load are summarized. With the help of the first four order statistical moments, how to describe the infinite variety of non-Gao Si distributions as comprehensively as possible. How to extract more information from a small number of experimental samples, so as to better describe the stochastic process. How to solve the influence of correlation and ensure the number of extreme samples so as to ensure the fitting accuracy of extreme value distribution? How to maximize the scope of application of a calculation method, that is, to apply to both soft and hard response processes, and at the same time to maximize, (3) A wind load process extremum algorithm based on simulation technology is proposed. The simulation technique is used to generate multiple wind pressure time history to simulate the time history sample space, which better describes the stochastic process. Johnson transform is used to generate the non-Gao Si sequence with arbitrary first four order moments to simulate the infinite variety of non-Gao Si distribution, and AR autoregressive model is used to simulate the correlation of wind pressure process. This algorithm is adaptive to the probability and correlation characteristics of non-Gao Si processes. Different probability density functions and AR models are generated for different original measurement results. Finally, the classical extreme value theory is used to calculate the extreme value of wind pressure, so this algorithm is suitable for all types of extreme value calculation of stationary wind pressure process. (4) based on the test results of bridge main girder segment model, The distribution characteristics of non-Gao Si wind pressure on the main beam surface are summarized. Several existing wind load extremum calculation methods and the algorithm proposed in this paper are used to calculate the wind pressure extremum at typical measuring points, and the results are compared with the real measurement results. It is proved that the proposed algorithm is suitable for all types of wind load processes. Compared with other algorithms, the algorithm has higher accuracy.
【學(xué)位授予單位】：大連理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：U441.2
本文編號：2171367
[Abstract]:With the gradual progress of construction technology, modern bridges are developing in the direction of "growing up and soft". The stiffness and damping of the bridge are reduced, which makes the bridge more sensitive to wind load. As a typical stochastic process, the action extremum of wind load is always an important factor that affects the design of bridge structure. The traditional calculation method usually assumes the extreme value as Gao Si process to estimate the extreme value. More and more experiments and field observations show that the wind loads of bridges sometimes show obvious non-Gao Si characteristics. If the extreme value is calculated according to the Gao Si assumption, the results may be partial to the danger. In this context, the non-Gao Si characteristics of wind load of bridges are studied in this paper. The main work includes the following aspects: (1) introduce the research status of non-Gao Si characteristics of wind load and the main algorithms of load extremum. Combined with theoretical analysis and practical application, the advantages and disadvantages of various algorithms are summarized. It is found that the modified peak factor method is more conservative than the Gumbel method, which is influenced by the correlation between the extreme values at short time intervals. The Sadek-Simiu method is only suitable for the extreme value calculation of a class of non-Gao Si processes with large deviation. (2) several difficult problems in calculating the extreme value of non-Gao Si wind load are summarized. With the help of the first four order statistical moments, how to describe the infinite variety of non-Gao Si distributions as comprehensively as possible. How to extract more information from a small number of experimental samples, so as to better describe the stochastic process. How to solve the influence of correlation and ensure the number of extreme samples so as to ensure the fitting accuracy of extreme value distribution? How to maximize the scope of application of a calculation method, that is, to apply to both soft and hard response processes, and at the same time to maximize, (3) A wind load process extremum algorithm based on simulation technology is proposed. The simulation technique is used to generate multiple wind pressure time history to simulate the time history sample space, which better describes the stochastic process. Johnson transform is used to generate the non-Gao Si sequence with arbitrary first four order moments to simulate the infinite variety of non-Gao Si distribution, and AR autoregressive model is used to simulate the correlation of wind pressure process. This algorithm is adaptive to the probability and correlation characteristics of non-Gao Si processes. Different probability density functions and AR models are generated for different original measurement results. Finally, the classical extreme value theory is used to calculate the extreme value of wind pressure, so this algorithm is suitable for all types of extreme value calculation of stationary wind pressure process. (4) based on the test results of bridge main girder segment model, The distribution characteristics of non-Gao Si wind pressure on the main beam surface are summarized. Several existing wind load extremum calculation methods and the algorithm proposed in this paper are used to calculate the wind pressure extremum at typical measuring points, and the results are compared with the real measurement results. It is proved that the proposed algorithm is suitable for all types of wind load processes. Compared with other algorithms, the algorithm has higher accuracy.
【學(xué)位授予單位】：大連理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：U441.2
【參考文獻(xiàn)】
相關(guān)期刊論文 前1條
1 周群艷,田澎,田志友;基于Johnson轉(zhuǎn)換體系的非正態(tài)過程能力指數(shù)估計[J];系統(tǒng)工程;2004年05期
，本文編號：2171367
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