Multi‐objective optimal design of FLC driven hybrid mass damper for seismically excited structures

Structural vibration control using active or passive control strategy is a viable technology for enhancing structural functionality and safety against natural hazards such as strong earthquakes and high wind gusts. Both the active and passive control systems have their limitations. The passive control system has limited capability to control the structural response whereas the active control system depends on external power. The power requirement for active control of civil engineering structures is usually quite high. Thus, a hybrid control system is a viable solution to alleviate some of the limitations. In this paper a multi‐objective optimal design of a hybrid control system for seismically excited building structures has been proposed. A tuned mass damper (TMD) and an active mass driver (AMD) have been used as the passive and active control components of the hybrid control system, respectively. A fuzzy logic controller (FLC) has been used to drive the AMD as the FLC has inherent robustness and ability to handle the non‐linearities and uncertainties. The genetic algorithm has been used for the optimization of the control system. Peak acceleration and displacement responses non‐dimensionalized with respect to the uncontrolled peak acceleration and displacement responses, respectively, have been used as the two objectives of the multi‐objective optimization problem. The proposed design approach for an optimum hybrid mass damper (HMD) system, driven by FLC has been demonstrated with the help of a numerical example. It is shown that the optimum values of the design parameters of the hybrid control system can be determined without specifying the modes to be controlled. The proposed FLC driven HMD has been found to be very effective for vibration control of seismically excited buildings in comparison with the available results for the same example structure but with a different optimal absorber. Copyright © 2002 John Wiley & Sons, Ltd.     

重磁遗传算法三维反演中高速计算及有效存储方法技术

将地下场源区域规则划分成很多小长方体单元，并且通过反演确定这些单元的物性变 化，勾画出场源的分布图像，这种方式逐步成为重磁反演，特别是三维反演的重要方向；遗 传算法等非线性技术进行该类反演将逐步成为发展趋势. 本文指出，在应用遗传算法进行该 类反演过程中，隐含着数据量较大时超常规的计算量，它已成为制约该类反演充分发挥作用 的瓶颈问题；同时，本文提出了针对性的分离并存储几何格架的计算策略、以及独特的几何 格架等效压缩存储技术，可以从根本上提高非线性反演计算速度，为该类反演的有效应用奠 定了坚实的基础.     

Streeter-Phelps模型参数估计的遗传算法

提出Streeter-Phelps模型参数估计的新方法--遗传算法(Genetic Algorithm),它不同于常规参数估计方法,其优点在于,从多个初始点开始寻优,并采用交迭和变异运算避免过早地收敛到局部最优解,可获得全局最优解,且不受初始值影响.该方法不必求导计算,编程简单快捷.给出了实例计算及与其他方法相比较的结果.     

Simulation of normal distributed smooth fields by Karhunen-Loéve expansion in combination with kriging

Simulation of multigaussian stochastic fields can be made after a Karhunen-Loéve expansion of a given covariance function. This method is also called simulation by Empirical Orthogonal Functions. The simulations are made by drawing stochastic coefficients from a random generator. These numbers are multiplied with eigenfunctions and eigenvalues derived from the predefined covariance model. The number of eigenfunctions necessary to reproduce the stochastic process within a predefined variance error, turns out to be a cardinal question. Some ordinary analytical covariance functions are used to evaluate how quickly the series of eigenfunctions can be truncated. This analysis demonstrates extremely quick convergence to 99.5% of total variance for the 2nd order exponential (‘gaussian’) covariance function, while the opposite is true for the 1st order exponential covariance function. Due to these convergence characteristics, the Karhunen-Loéve method is most suitable for simulating smooth fields with ‘gaussian’ shaped covariance functions. Practical applications of Karhunen-Loéve simulations can be improved by spatial interpolation of the eigenfunctions. In this paper, we suggest interpolation by kriging and limits for reproduction of the predefined covariance functions are evaluated.     

Testing an earthquake prediction algorithm

A test to evaluate earthquake prediction algorithms is being applied to a Russian algorithm known asM8 TheM8 algorithm makes intermediate term predictions for earthquakes to occur in a large circle, based on integral counts of transient seismicity in the circle. In a retroactive prediction for the period January 1, 1985 to July 1, 1991 the algorithm as configured for the forward test would have predicted eight of ten strong earthquakes in the test area. A null hypothesis, based on random assignment of predictions, predicts eight earthquakes in 2.87% of the trials. The forward test began July 1, 1991 and will run through December 31, 1997. As of July 1, 1995, the algorithm had forward predicted five out of nine earthquakes in the test area, which success ratio would have been achieved in 53% of random trials with the null hypothesis.     

Simulation of normal distributed smooth fields by Karhunen-Loéve expansion in combination with kriging

Simulation of multigaussian stochastic fields can be made after a Karhunen-Loéve expansion of a given covariance function. This method is also called simulation by Empirical Orthogonal Functions. The simulations are made by drawing stochastic coefficients from a random generator. These numbers are multiplied with eigenfunctions and eigenvalues derived from the predefined covariance model. The number of eigenfunctions necessary to reproduce the stochastic process within a predefined variance error, turns out to be a cardinal question. Some ordinary analytical covariance functions are used to evaluate how quickly the series of eigenfunctions can be truncated. This analysis demonstrates extremely quick convergence to 99.5% of total variance for the 2nd order exponential (‘gaussian’) covariance function, while the opposite is true for the 1st order exponential covariance function. Due to these convergence characteristics, the Karhunen-Loéve method is most suitable for simulating smooth fields with ‘gaussian’ shaped covariance functions. Practical applications of Karhunen-Loéve simulations can be improved by spatial interpolation of the eigenfunctions. In this paper, we suggest interpolation by kriging and limits for reproduction of the predefined covariance functions are evaluated.     

Evolutionary aseismic design and retrofit of structures with passive energy dissipation

A new computational framework is developed for the design and retrofit of building structures by considering aseismic design as a complex adaptive process. For the initial phase of the development within this framework, genetic algorithms are employed for the discrete optimization of passively damped structural systems. The passive elements may include metallic plate dampers, viscous fluid dampers and viscoelastic solid dampers. The primary objective is to determine robust designs, including both the non‐linearity of the structural system and the uncertainty of the seismic environment. Within the present paper, this computational design approach is applied to a series of model problems, involving sizing and placement of passive dampers for energy dissipation. In order to facilitate our investigations and provide a baseline for further study, we introduce several simplifications for these initial examples. In particular, we employ deterministic lumped parameter structural models, memoryless fitness function definitions and hypothetical seismic environments. Despite these restrictions, some interesting results are obtained from the simulations and we are able to gain an understanding of the potential for the proposed evolutionary aseismic design methodology. Copyright © 2005 John Wiley & Sons, Ltd.     

基于行道树的道路快速提取和面积计算研究

在城市遥感中,道路自动(半自动)提取一直是研究的霞点.本文在现有道路自动(半自动)提取技术的基础上,结合高分辨率遥感影像中行道树的分布特点,从地学知识出发,利用归一化筹值植被指数、阀值分割、数学形态学算子及地理信息系统的分析功能等实现基于行道树的道路自动(半自动)提取和道路面积快速、自动计算.结论表明基于行道树的道路提取和面积计算方法具有一定的实用性.     

基于投影寻踪模型和加速遗传算法的石羊河流域水资源承载力综合评价

针对区域水资源承载力状况,采用高维降维技术——投影寻踪分类模型（PPC）,利用基于实数编码的加速遗传算法（RAGA）优化其投影方向,将多维数据指标（样本评价指标）转换到低维子空间,根据投影函数值的大小评价出样本的优劣,从而做出评价,最大限度避免了灰色关联法评判中权重矩阵取值的人为干扰,为区域水资源承载力状况评价及其它评判问题提供一条新的方法与思路。     

基于敏感性分析的裂隙岩体渗流与应力静态全耦合参数反演

基于求解稳定渗流场与弹性位移场耦合问题的全耦合分析方法,应用提出的混合遗传算法作为优化算法,同时利用水头、位移等多类型量测资料,提出了裂隙岩体渗流与应力静态全耦合的参数反演方法。在目标函数建立中考虑了实测水头对渗流参数的敏感性,在待反演力学未知参数的选取中,依据提出的相对灵敏度概念,考虑了实测位移对力学参数的敏感性。针对某裂隙岸坡算例,研究了水库蓄水过程中位移场对力学参数敏感性,据此实现位移测点的优化布置,并以渗流场与位移场全耦合正分析计算结果作为假想实测值,进行该岩坡的全耦合参数反演分析,从而验证了所提出理论与研制程序的正确性和可行性。