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1.
介绍了基于人工神经网络(ANN)、遗传算法(GAM)的可靠度分析以及基于模糊数学的可靠度分析,对施工过程以及老化期的钢筋混凝土结构的可靠度进行了研究,从而为结构可靠度分析的智能化奠定了基础,为可靠度分析提供了新的思路和工具。  相似文献   

2.
基于遗传算法和人工神经网络的简支梁结构可靠度分析   总被引:2,自引:0,他引:2  
简要阐述遗传算法(GA)和人工神经网络(ANN),将这一类智能方法引入简支梁结构可靠度分析中,其结果与Monte Carlo法进行比较,并将遗传算法思想应用到结构体系可靠度分析中,为结构体系可靠度计算提供新的思路。  相似文献   

3.
杨俊雷 《四川建材》2011,37(6):44-45,49
遗传算法(GA)作为一种优化算法,用于结构可靠度分析,对目标函数和约束条件没有过于苛刻要求,利用MATLAB软件,引入遗传算法编制相应程序,验证已知功能函数的结构构件的可靠度。工程实例计算表明,结合遗传算法分析结构体系可靠度,不受搜索空间的限制性假设的约束,不要求目标函数具有连续性、可导等假设,其结果与其他算法结果具有一致性。  相似文献   

4.
以润扬大桥斜拉桥为分析对象,提出了扁平钢箱梁结构的多尺度可靠度分析方法。采用子结构方法将扁平钢箱梁整体结构尺度模型和局部构件尺度模型相互衔接,在此基础上采用改进响应面法分析了扁平钢箱梁结构的静力可靠度。分析结果表明:①采用改进响应面法能有效地解决传统响应面法存在的收敛失败和计算误差大的缺点;②采用钢箱梁多尺度模型可以较准确地计算斜拉桥在活荷载作用下的静力可靠指标;③钢箱梁活荷载的分布方式和斜拉桥的几何非线性对斜拉桥静力可靠度具有较大的影响;④采用钢箱梁多尺度模型,可以较真实地研究钢箱梁局部构件损伤对斜拉桥静力可靠度的影响。钢箱梁局部构件损伤对斜拉桥静力可靠指标的影响程度要明显大于对斜拉桥静力特性的影响。因此,在斜拉桥钢箱梁的可靠度设计与状态评估中需要计入结构多尺度效应的影响。  相似文献   

5.
张爱林  康浩 《山西建筑》2006,32(12):3-4
主梁的可靠度对于斜拉桥整体结构的可靠度具有重要影响,通过采用Monte-Carlo法对斜拉桥主梁的可靠度进行分析,用Matlab的数值计算功能解决了Monte-Carlo法直接抽样的困难,得到比较精确的结果,以推广Monte-Carlo法。  相似文献   

6.
在优化问题中,对于高度非线性的目标函数,遗传算法能够有效求出极值点。根据遗传算法原理和可靠度指标的几何涵义,提出了计算可靠度指标全局优化算法。采用无量纲随机变量的极限状态方程,结合混凝土管桩试桩资料进行了统计学分析和可靠度分析。采用了JC法和遗传算法两种方法进行可靠度指标的计算。在求解过程中,对于功能函数的复杂性,遗传算法仅需要目标函数的函数值而避免了JC法中繁复的求导数工作,计算表明了提出的方法进行可靠度分析的有效性。  相似文献   

7.
本文介绍了概率随机可靠度计算理论中改进的一次二阶矩法及可靠度反问题计算理论。为便于理解 ,以一算例简单介绍了多个设计参数可靠度反问题的计算思路。最后以一斜拉桥为例 ,应用改进的验算点法对斜拉桥主梁作了静力可靠性及相应的反问题计算 ,并对结果进行分析。  相似文献   

8.
自适应协方差矩阵进化策略(CMA-ES)算法是一种引导式随机优化算法,兼顾了深度搜索最优解和广度搜索解空间的能力。针对采用遗传算法(GA)、粒子群优化算法(PSO)等仿生优化算法求解复杂结构可靠度时往往遇到计算代价过高的问题,基于结构可靠度指标的几何涵义并结合验算点法,提出了结构可靠度计算的自适应协方差矩阵进化策略方法。研究结果表明,该方法是可行的,具有全局性好、收敛速度快的优点,与遗传算法、粒子群优化算法相比较,可大幅度地提高计算效率,为结构可靠度计算提供了一条新的途径。  相似文献   

9.
针对地下结构可靠度分析中功能函数不能显示表达的特点,提出基于三维有限元的可靠度分析方法。以下穿高速双孔并行隧道为例,根据三维有限元计算结果,分别以DP2与DP3准则作为塑性屈服的判定准则,采用遗传算法选取样本点构建二次响应面模型,通过对Monte Carlo法,基于BP神经网络的Monte Carlo法,中心点法,JC法和遗传算法得出的可靠度指标的比较分析,得出遗传算法的运用可显著提高响应面模型的逼近精度,中心点法计算出的可靠度指标误差较大,Monte Carlo法、BP-Monte Carlo法、JC法及遗传算法求得的可靠度指标精度相近,JC法因操作简便、计算精度高可广泛用于地下结构的可靠度分析。基于遗传算法选取的样本点构建响应面模型,以JC法计算地下结构的可靠度分布,得出在公路线荷载作用下,衬砌上下两侧向内变形,上下两侧围岩应力释放多,可靠度相应增大;衬砌左右两侧向外变形,左右两侧围岩应力增大,可靠度相应减小;并行隧道的相互影响导致邻近另一隧道侧的衬砌可靠度较小。  相似文献   

10.
标准遗传算法在解决像斜拉桥这类复杂结构的损伤识别问题时会出现提前收敛,即所谓"早熟"的现象。为了避免此现象的发生,提高损伤识别的效率与精度,提出一种基于改进分层遗传算法的斜拉桥主梁损伤识别方法。采用索力变化作为优化目标函数,将3种具有不同遗传算子的标准遗传算法与变量微调和灾变策略相结合,形成了一种具有灾变特性的分层遗传算法,以实验室独塔斜拉桥模型作为研究对象进行了数值仿真,结果表明:改进的分层遗传算法成功的避免了标准遗传算法"早熟"现象的发生,能快速有效的完成斜拉桥主梁各种损伤的识别;同时对此方法进行抗噪性分析发现,该方法具有良好的抗噪能力。  相似文献   

11.
Two artificial neural network (ANN)-based response surface methods for reliability analysis of pre-stressed concrete bridges are presented. The first method is the traditional ANN-based response surface method, originally introduced by Papadrakakis et al. in 1996 (Papadrakakis, M., Papadopoulos, V. and Lagaro, N., 1996. Structural reliability analysis of elastic-plastic structures using neural network and Monte carlo simulation. Computer Methods in Applied Mechanics and Engineering, 136, 145–163), which is applied here to the reliability analysis of pre-stressed concrete bridges. The second method is an improved ANN-based response surface method developed recently by the authors for the reliability analysis of truss structures, in which the key idea is that the uniform design method (UDM) is adopted to select training data for establishing an ANN model, thereby greatly improving the quality of training datasets for establishing an ANN model and dramatically reducing the required number of training datasets. There are two main objectives of the present work. Firstly, an attempt is made to extensively examine the performance of the traditional ANN-based response surface method since no detailed study has been carried out to investigate the effectiveness of this ANN-based response surface method on the basis of the reliability analysis of complicated structures such as pre-stressed concrete bridges. Secondly, the recently developed ANN-based response surface method is extended to the reliability analysis of pre-stressed concrete bridges. A detailed numerical investigation is carried out to compare the performance of the two methods.  相似文献   

12.
对带可靠锚固FRP受剪加固混凝土梁的非剥离剪切破坏模式做了细化分类,即包括FRP断裂控制的破坏、受压区混凝土(达到极限应力状态)压碎控制的破坏、FRP断裂与混凝土压碎同步发生的界限破坏等3种模式;利用BP神经网络建立了带锚纤维受剪加固梁破坏模式的智能预测模型,与31根非剥离破坏加固梁试验的对比结果显示:模型总体精度达到90%,说明建立的破坏模式网络预测模型适用于带锚纤维受剪加固梁非剥离剪切破坏模式的判别。  相似文献   

13.
A wide variety of models have been proposed for estimating the reliability of highway bridges. For reinforced concrete bridges subjected to environmental attack, time-variant reliability methods have to be used. In this study, the condition of reinforced concrete girder bridges is assessed using a time-variant system reliability approach in which both load and resistance are time-variant quantities. Several system models are considered, including failure of any girder (series system) and failure of a specified number of adjacent girders (series-parallel system). Adaptive importance sampling is used to determine the cumulative-time system failure probability. An existing reinforced concrete T-beam bridge located near Pueblo, Colorado, is investigated. The influence of resistance degradation and post-failure load redistribution is included. A comparison of reliability estimates for several system models is given, including the influence of correlation among initial girder strengths. The results can be used as a guide for the selection of system models for bridge reliability analysis, identification of critical girders in a bridge system, and for the development of optimal reliability-based maintenance strategies for reinforced concrete highway bridges.  相似文献   

14.
大跨度斜拉桥智能可靠度评估方法研究   总被引:3,自引:0,他引:3  
针对既有大跨度斜拉桥的评估管理系统中的可靠度评估问题,提出了基于RBF网络与Monte Carlo结合的可靠度评估方法。建立了招宝山大桥快速分析的RBF网络模型,网络训练样本按均匀设计方法,考虑几何非线性因素由ANSYS软件分析得到。对运营期的招宝山大桥进行了两类失效模式,三种极限状态下的可靠度评估,并分析了不同活载模式、不同功能函数及不同检测期对可靠度评估结果的影响。分析表明:基于RBF-MC的可靠度分析方法具有速度快、精度高的优点,并能同时计算多极限状态下的结构可靠指标,特别适合在基于可靠度的桥梁管理系统中采用;活载布置方式、选取的功能函数均影响可靠度评估的结果,招宝山大桥不同检测期可靠度水平变化不大,且均处于安全可靠状态。  相似文献   

15.
A fuzzy artificial neural network (ANN)–based approach is proposed for reliability assessment of oil and gas pipelines. The proposed ANN model is trained with field observation data collected using magnetic flux leakage (MFL) tools to characterize the actual condition of aging pipelines vulnerable to metal loss corrosion. The objective of this paper is to develop a simulation-based probabilistic neural network model to estimate the probability of failure of aging pipelines vulnerable to corrosion. The approach is to transform a simulation-based probabilistic analysis framework to estimate the pipeline reliability into an adaptable connectionist representation, using supervised training to initialize the weights so that the adaptable neural network predicts the probability of failure for oil and gas pipelines. This ANN model uses eight pipe parameters as input variables. The output variable is the probability of failure. The proposed method is generic, and it can be applied to several decision problems related with the maintenance of aging engineering systems.  相似文献   

16.
《钢结构》2012,(5):79
给出新的估算钢斜拉桥极限荷载的简便方法。采用新的用于迭代特征值计算的收敛准则来考虑斜拉桥系统中的梁-柱效应。采用新方法分别估算中等跨度和大跨度模型的极限荷载,并与非线性非弹性分析方法进行比较。结果显示,新方法能很方便的替代复杂的非线性非弹性分析而近似评估钢斜拉桥的极限荷载和失效模式。  相似文献   

17.
This paper proposes a new and simple method for estimating the collapse load of a steel cable-stayed bridge. A new convergence criterion for iterative eigenvalue computations is suggested to consider the beam–column effect of a cable-stayed bridge system. The collapse loads of two example bridges representing medium and long-span models are evaluated by the proposed method and compared to a nonlinear inelastic analysis. The results demonstrate that the proposed method is a good substitute for a complex nonlinear inelastic analysis to approximately evaluate the collapse loads as well as failure modes of steel cable-stayed bridges.  相似文献   

18.
An efficient analytical method for quantifying the correlation between performance functions of different slope failure modes in spatially variable soils is proposed, and its performance in slope system reliability analysis is investigated. First, a new correlation coefficient (NCC) is proposed to evaluate the correlation among slope failure modes considering spatial variability. For comparison and verification, the simulation-based correlation coefficient (SCC) is also presented. Second, appying these two types of correlation coefficients, the effects of soil spatial variability on the representative slip surfaces (RSSs) and the system probability of slope failure are investigated using different system reliability methods, including a probabilistic network evaluation technique, a risk aggregation approach, and a bimodal bounds method. A single-layered cohesive slope is investigated to illustrate the validity of the proposed NCC. The results indicate that the proposed NCC can efficiently and accurately quantify the correlation among slope failure modes considering soil spatial variability. The number of RSSs indicated by the NCC is in good agreement with the number obtained using the SCC. The system failure probabilities of slope stability obtained with the SCC and the NCC using a risk aggregation approach are generally comparable. Also, the system reliability bounds of slope stability obtained using the NCC are relatively close together and comparable to those obtained using the SCC. Thus, the NCC shows good performance when evaluating the correlation among slope failure modes, and was effectively applied to analyze a single-layered cohesive slope considering soil spatial variability.  相似文献   

19.
An efficient method for reliability assessment of long span steel arch bridges against wind-induced stability failure is presented in this paper. The prediction of wind-induced stability of such bridge structures is performed by an eigenvalue method and the reliability estimates are determined by a generalized first-order reliability algorithm. A software strategy for interfacing the present method with ANSYS is developed via a freely available MATLAB software tool (FERUM). A numerical example involving a detailed computational model of a long span steel arch bridge with a main span of 550 m is presented to demonstrate the applicability and merits of the present method and the software strategy. Finally, the most influential random variables on the reliability of long span steel bridges against wind-induced stability failure are identified by a sensitivity analysis.  相似文献   

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