黏滞阻尼器控制偏心结构扭转耦联振动效果分析

为了有效控制地震作用下偏心结构扭转耦联振动所引起的灾变问题,在理论分析和数值计算的基础上,建立了地震作用下偏心结构的扭转耦联运动方程,通过研究黏滞阻尼器对偏心结构扭转耦联振动的控制效果,对比分析4种黏滞阻尼器常用布置方案下偏心结构的地震响应,量化了黏滞阻尼器和钢支撑共同保护作用下对偏心结构减震效果的影响。研究结果表明:设置有黏滞阻尼器的偏心结构,在双向地震作用下偏心结构最大层位移和层间位移角均得到有效的控制;在多遇地震作用下黏滞阻尼器人字型布置方式对控制偏心结构扭转效果明显,罕遇地震作用下不同布置方式的控制效果相差不大,其结果可为地震作用下类似的偏心结构扭转效应的振动控制提供借鉴参考。     

基于黏滞阻尼器的框架结构随机地震响应分析

考虑到地震动具有随机性,利用平稳过滤白噪声地震动模型,首先建立黏滞阻尼结构的动力方程,运用虚拟激励法将平稳随机地震激励转化为简谐振动分析,求解黏滞阻尼结构在随机地震作用下的响应,然后通过选用相同数量的阻尼器在最大层间位移处集中布置、循环布置、权数布置三种布置方案,对比分析布置前后结构的地震反应,得出最优的黏滞阻尼器空间位置布置方案。由此可知,黏滞阻尼器具有明显的减震效果,得到的黏滞阻尼器布置建议对抗震设计和加固具有参考意义,同时使用虚拟激励法能高效快捷的求出结构的随机响应。     

建筑结构空间减震性能优化技术研究

针对高层建筑结构抗震问题,研究基于黏滞阻尼器建筑结构空间抗震性能优化技术。论文考虑黏滞阻尼器阻尼参数、位置布置等因素,并从两方面对建筑结构抗震反应影响进行分析。通过设置不同方案的仿真实验,探究建筑结构的抗震性能。最终实验结果表明,黏滞阻尼器阻尼指数较大时,其消能减震结构的耗能减震性能更优;对黏滞阻尼合理布置可以改善建筑结构的抗震性能。     

层高对框架-核心筒结构层间速度的影响分析

在设备层或避难层中设置黏滞阻尼器可显著减小超高层结构的侧向变形,为了有效发挥黏滞阻尼器耗能效果,研究其沿楼层竖向布置的规律非常有必要。本文采用ETABS软件对一栋272.5m高的超高层框架-核心筒结构模型进行地震作用下的非线性动力时程反应分析,综合考虑楼层层高和楼层竖向布置位置等因素的变化,研究其对楼层层间速度和层间位移角等动力反应的控制规律。结果表明:典型框架-核心筒结构中部及上部楼层层间位移角相对较大,下部层间位移角相对较小,而层间速度随着结构高度的上升呈逐渐增大的趋势,且层间速度值大小沿结构高度分布相对均匀;考虑本层层高及竖向布置位置组合变化时,层高变化的楼层层间速度随其对应层高的增大基本呈线性增长趋势,但对应楼层层间位移角的增大比例则不明显。     

考虑平-扭耦联效应黏弹性阻尼器最优位置研究

为了研究控制平-扭耦联效应黏弹性阻尼器最优位置问题,推导不同偏心形式单层偏心结构,采用不同方式布置黏弹性阻尼器减震结构考虑平-扭耦联效应的振动方程,建立基于结构平动与扭转位移响应相关性的目标函数。利用随机振动理论中的李雅普诺夫方程和最优控制理论,建立并求解偏心结构平面几何中心位移响应协方差矩阵,通过求得目标函数最小值找到阻尼器的最优偏心位置。在此基础上编制相应程序对典型算例进行数值计算,分析不同偏心形式下,地震荷载输入条件、等效阻尼比、静力偏心率、扭平频率比、结构周期、结构尺寸效应对考虑平-扭耦联效应时黏弹性阻尼器最优位置的影响规律。     

高层减震结构地震响应及方案优化研究

针对某高层建筑结构,利用ETABS有限元分析软件建立计算模型,探讨原结构和设置黏滞阻尼器的减震结构在多遇地震作用下的抗震性能,通过进行五种黏滞阻尼器布设方案下结构响应的比较,以不同的控制函数为目标,进而优化黏滞阻尼器的布设位置。结果表明,黏滞阻尼器在保证不增加结构刚度的基础上,通过提供附加阻尼,能有效协助结构耗散地震输入的能量,降低了结构的动力响应,起到了很好的减震效果。同时,在考虑黏滞阻尼器的布设位置时,应根据结构的实际动力响应和变形特性综合确定,并且考虑结构的功能需求以获得最佳的减震效果。     

基于能量和控制效果指标的黏滞阻尼器优化设计

提出以能量和控制效果指标为目标函数的黏滞阻尼器优化设计方法。基于黏滞阻尼器参数对其滞回曲线的影响,在分别以加速度控制效果指标和能量为目标函数的情况下,采用遗传算法对黏滞阻尼器进行了布置及参数的同步优化,在综合考虑了位移控制效果指标、加速度控制效果指标及能量的情况下,再次对黏滞阻尼器进行了优化设计,将三种黏滞阻尼器优化设计结果与传统设计结果进行了比较,并分析了四种阻尼器设计结果对地震的敏感性。研究表明:考虑能量的黏滞阻尼器优化设计是有效的,在目标函数中引入能量可以减小设计结果对地震波的敏感性。     

空间结构振动控制的阻尼器位置寻优分析

推导了基于阻尼器速度反馈的结构振动方程和状态控制方程,提出以控制系统闭环传递函数的H∞范数为位置寻优指标,提出基于结构动能和弹性能度量结构振动控制效果的指标.针对空间网格结构,利用遗传算法,在对阻尼器的布置位置实施二进制编码基础上,通过代际交叉和变异操作,寻找阻尼器优化位置.研究显示,本方法可有效寻找阻尼器的优化布置位置,有助于减小空间网格结构的振动反应.     

黏弹性阻尼器对框架结构抗震性能的影响分析

黏弹性阻尼器作为一种减震装置，能够较好地抵抗和减少建筑物受到的地震作用影响。基于Midas/GEN软件，选取三条普通地震波，对一栋5层混凝土框架结构模型进行非线性地震反应分析，提出了布置有黏弹性阻尼器的框架减震结构，分析其减震效果，通过分析不同位置的黏弹性阻尼器的耗能能力优化布置。结果表明：通过合理布置黏弹性阻尼器可以更好地实现框架结构耗能，降低结构地震响应，使结构的层间位移、层剪力以及层加速度都得到有效控制，并且在结构下部布置阻尼器，其耗能能力更优于布置在结构上部。     

基于遗传算法的偏心结构粘滞阻尼器优化布置研究

本文基于改进的遗传算法(MGA)和有限元分析软件SAP2000 API接口,开发了一种面向偏心结构中阻尼器快速优化布置的平台,提出了两种为抑制偏心结构扭转效应而设计的评价函数,分别采用了二进制的对称分组和自由分组两种编码方法,基于拟合标准反应谱生成的人工地震动记录,首先与穷举法结果比较,验证了该优化平台对于偏心结构中、给定数目粘滞阻尼器位置优化结果的可靠性和高效性;然后引入两个性能评价指标,通过数值分析,研究了对偏心结构中阻尼器位置优化产生影响的不同因素。结果表明:评价函数的设计和编码方法的选择对阻尼器优化影响较大,场地地震动输入会影响阻尼器的位置优化,且与编码方法的选择相关,同一编码影响不大;力学参数的改变不影响阻尼器的位置分布,但粘滞阻尼器阻尼系数和阻尼指数取值适中,可以兼顾层间位移角最大楼层和结构总体反应两个方面的减震效果。     

遗传算法在给水管网优化设计中的应用

遗传算法是一种新型的进化算法，它是一种通过模拟自然进化过程搜索最优解的随机寻优的数学规划方法．阐述了应用遗传算法进行给水管网优化设计的原理、特点，并对青岛市城阳区某工业园给水管网工程进行优化求解．     

混合遗传算法在桁架优化中的应用

应用遗传算法,并对基本遗传算法进行相应的改进,对空间桁架结构截面进行优化。在应用遗传算法的同时,考虑满应力解通常处在最优解附近的原理,将满应力解作为种群中的一个个体参与计算,并通过MATLAB编制相应的程序实现。算例表明,该方法能得到理想效果,并减少程序运算时间。     

Semi-active control of a torsionally-responsive structure

The mitigation of torsional responses in structures using semi-active devices is pursued in the current study. Multiple magnetorheological (MR) dampers are employed for real-time control of the response of a benchmark structure to earthquake excitations. MR damper resistance levels are intelligently managed by a global fuzzy logic controller (FLC). The FLC is generated using a controlled-elitist genetic algorithm (GA). Development of an optimal FLC is expedited by a discretized search space of fuzzy logic membership functions. To enable robust control an excitation is created for training by a GA using the RSPMatch2005 algorithm that modifies historic ground records in the time-domain by wavelet operations. Both numerical and large-scale experimental efforts are undertaken to validate the proposed control system. Results show that the GA-optimized FLC control provides a favorable balance in reduction of inter-story drift and absolute acceleration levels.     

优化神经网络在多传感器火灾探测中的应用

针对BP神经网络在拟合过程中探测精度低、容易陷入局部最优的问题,提出一种基于遗传算法（GA）和模拟退火算法（SA）共同改进的BP神经网络模型,该网络模型可以有效提高火灾识别准确率,同时避免网络过拟合现象,使预测结果跳出局部最优从而达到全局最优。首先,通过GA改进隐藏层结构部分,然后通过SA改进连接权重部分,最后利用优化后的GA-SA-BP模型对火灾实验数据进行信息融合实现火灾探测。实验研究表明,对比单一BP神经网络,经GA和SA改进后的BP神经网络能够有效改善网络拟合能力,并提升火灾探测精度至98.91%。     

Fluid transients and pipeline optimization using GA and PSO: the diameter connection

This paper describes the optimal selection of pipe diameters in a network considering steady state and transient analysis in water distribution systems. Two evolutionary approaches, namely genetic algorithms (GA) and particle swarm optimization (PSO), are used as optimization methods to obtain pipe diameters. Both optimization programs, inspired by natural evolution and adaptation, show excellent performance for solving moderately complex real-world problems which are highly nonlinear and demanding. The case study shows that the integration of GA or PSO with a transient analysis technique can improve the search for effective and economical hydraulic protection strategies. This study also shows that not only is the selection of pipe diameters crucially sensitive for the surge protection strategies but also that more global systematic approaches should be involved in water distribution system design, preferably at an early stage in the design process.     

Genetic evolutionary structural optimization

Evolutionary structural optimization (ESO) is based on a simple idea that an optimal structure (with maximum stiffness but minimum weight) can be achieved by gradually removing ineffectively used materials from design domain. In general, the results from ESO are likely to be local optimums other than the global optimum desired. In this paper, the genetic algorithm (GA) is integrated with ESO to form a new algorithm called Genetic Evolutionary Structural Optimization (GESO), which takes the advantage of the excellent behavior of the GA in searching for global optimums. For the developed GESO method, each element in finite element analysis is an individual and has its own fitness value according to the magnitude of its sensitivity number. Then, all elements in an initial domain constitute a whole population in GA. After a number of generations, undeleted elements will converge to the optimal result that will be more likely to be a global optimum than that of ESO. To avoid missing the optimum layout of a structure in the evolution, an interim thickness is introduced into GESO and its validity is demonstrated by an example. A stiffness optimization with weight constraints and a weight optimization with displacement constraints are studied as numerical examples to investigate the effectiveness of GESO by comparison with the performance of ESO. It is shown through the examples that the developed GESO method has powerful capacity in searching for global optimal results and requires less computational effort than ESO and other existing methods.     

A comparative study on optimization of constrained layer damping treatment for structural vibration control

This paper presents a comparison of optimization algorithms for constrained layer damping (CLD) patches’ layout with an objective to minimize the maximum vibration response of the odd modes, which constitutes the dominant acoustic radiation, of a simply supported beam excited by a harmonic transverse force. An analytical model developed for relating the displacement response of the beam with bonded CLD patches and their layout is adopted to formulate the optimization problem. Four different nonlinear optimization methods/algorithms, sub-problem approximation method, the first-order method, sequential quadratic programming (SQP) and genetic algorithm (GA), are then, respectively, used to optimize the CLD patches’ locations and lengths with the aim of minimum displacement amplitude at the middle beam. The efficiency of each considered optimization method is evaluated and also compared in terms of obtained optimal beam displacement and the added weight owing to damping treatment. The results show that GA is most efficient in obtaining the best optimum for this optimization problem in spite of highest computation efforts required to improve its stability.     

遗传渐进结构优化法

渐进结构优化法（ESO）是基于一个简单概念提出的一种方法,即可以通过在设计上逐渐消除无效材料而实现最优化结构（具有最大刚度和最轻重量）。一般而言,ESO的结果很可能是局部最优化,而不是整体最优化。将遗传算法（GA）与ESO相结合,形成一种新的算法,即遗传渐进结构优化法（GESO）,考虑了GA在整体优化计算方面的优势。     

An Advanced Stochastic Time‐Cost Tradeoff Analysis Based on a CPM‐Guided Genetic Algorithm

This article presents an advanced stochastic time‐cost tradeoff (ASTCT) method that performs time‐cost tradeoff analysis by identifying optimal set(s) of construction methods for activities, hence reducing the project completion time and cost simultaneously. ASTCT involves a stochastic time‐cost tradeoff analysis method based on a critical path method (CPM)‐guided genetic algorithm (GA). It makes use of CPM schedule data exported from a project management software, and alternative construction methods obtained from estimators (i.e., normal and accelerated durations and costs) for each activity. It simulates schedule networks, identifies an optimal set of GA parameters (i.e., population size, crossover rate, mutation rate, and stopping rule), implements several GA cycles, and computes near‐optimal solution(s) exhaustively. This study is of value to practitioners because ASTCT improves the computation time, reliability, and usability of existing GA‐based time‐cost tradeoff methods. The study is also of relevance to researchers because it facilitates experiments using different GA parameters expeditiously. Two test cases verify the usability and validity of the computational methods.     

基于并行改进遗传算法的三维电阻率反演方法

计算效率极低是阻碍遗传算法用于三维电阻率反演的瓶颈,使得很多对改善反演效果和搜索质量有利但又很耗时的改进方法无法应用到遗传算法中。针对上述问题,基于遗传算法天然的并行计算特性,提出了新的多重主从并行计算策略及其算法。提出了初始群体的严格均布产生方法,以提高初始群体接近最优解的概率;提出了基于交叉个体适应度差异的比例随机算术交叉算法,以保证优良个体的遗传竞争优势;建立了混合变异算法,将传统的随机变异算法与线性反演中确定性搜索优化算法相结合,即保持了变异的随机性又控制了优化方向。最后将并行改进遗传算法用于合成算例和实际应用案例中,发现并行改进遗传算法的计算效率显著提高,且在寻找最优解、压制假异常、提高反演效果方面具有明显优势,为实际工程中电阻率探测的三维成像提供了有效途径。