Tuned mass dampers for response control of torsional buildings

This paper presents an approach for optimum design of tuned mass dampers for response control of torsional building systems subjected to bi‐directional seismic inputs. Four dampers with fourteen distinct design parameters, installed in pairs along two orthogonal directions, are optimally designed. A genetic algorithm is used to search for the optimum parameter values for the four dampers. This approach is quite versatile as it can be used with different design criteria and definitions of seismic inputs. It usually provides a globally optimum solution. Several optimal design criteria, expressed in terms of performance functions that depend on the structural response, are used. Several sets of numerical results for a torsional system excited by random and response spectrum models of seismic inputs are presented to show the effectiveness of the optimum designs in reducing the system response. Copyright © 2002 John Wiley & Sons, Ltd.     

Optimal displacement feedback control law for active tuned mass damper

Optimal displacement feedback control law is derived for a vibration control of a single‐degree‐of‐freedom structure with an active tuned mass damper (ATMD). Analytical expressions of the linear quadratic regulator (LQR) feedback gains for the ATMD are derived by solving the Ricatti equation straightforwardly. Based on these solutions, it is found that if the stiffness of the tuned mass damper (TMD) is calibrated to satisfy a certain condition, the control law is simplified to be composed of the feedback gains only for the displacement of the structure and the velocity of the auxiliary mass stroke, which is referred to as ‘optimal displacement feedback control’. The mean‐square responses of the structure as well as the auxiliary mass against Gaussian white noise excitations are evaluated by solving the Lyapunov equation analytically based on the stochastic optimal control theory. Using these analytical solutions, the optimal damping parameter for the auxiliary mass is also derived. Finally, the optimal displacement feedback control law is presented. Copyright © 2001 John Wiley & Sons, Ltd.     

基于瞬时最优算法的磁流变阻尼隔震结构半主动控制

采用瞬时最优控制算法，对附加了磁流变阻尼器的多自由度隔震结构进行了半主动控制的数值模拟。首先，将被动隔震装置——叠层钢板橡胶垫与磁流变阻尼器相结合，形成磁流变智能隔震系统。其次，根据瞬时最优控制算法的基本原理，针对磁流变阻尼器的特点，建立与之相适应的半主动控制算法。最后，以六层隔震结构为例，进行数值分析。比较了被动与半主动控制的结构反应，并得到较好的控制效果。     

青海湖水量平衡分析与水资源优化配置研究

在充分收集有关资料的基础上研究青海湖1959-2000年间降水径流蒸发湖泊水位地下水补给量的动态变化建立水量平衡分析方程.青海湖水位在波动中持续下降42年来年平均水位累计下降了 3.32 m平均每年下降了0.079 m近年来下降的幅度减小. 同时青海湖储水量不断减少而湖区降水呈增加的趋势河川径流量地下水的入湖补给量 蒸发量呈现下降的趋势. 根据青海湖水平衡分析计算结果预测2010年青海湖流域耗水量将达1.27108m3为维护生态平衡和社会经济持续发展需要跨流域调水量引大济湖4.1108m3.     

基于二次型性能指标的控制器优化布置方法

本文建立了基于二次型性能指标的结构控制系统控制器最优布置方法。以控制器撤除时的系统最优控制性能指标增量作为控制器对系统最优控制的贡献，并用做确定经济的控制器数量和最优控制器位置的定量分析准则。本文中的控制器位置和控制器设计采用同一个优化性能指标，使得控制系统设计为最优。根据逼近满设置控制器结构控制系统的最优状态求得控制器降阶后等价的反馈控制增益。应用本文的方法对剪切模型框架结构上安装的锚索控制器进行了控制器的总体优化设计。数值分析表明，本文提出的控制器数量、位置和参数优化方法不仅易于实现，而且甚为有效。     

Modified genetic algorithm with simulated annealing applied to optimal load dispatch of the Three Gorges Hydropower Plant in China

A method is presented for optimal load dispatch in large-scale hydropower plants using a genetic algorithm integrated with simulated annealing. The genetic algorithm overcomes dependence on an initial value and provides parallel processing and fast convergence, whereas simulated annealing prevents prematurity and retrieving of the local instead of the global optimum. Thus, the integrated genetic-simulated annealing algorithm improves efficiency and robustness to obtain solutions close to the global optimum. We evaluated the proposed algorithm to determine the optimal load dispatch of 32 units of the Three Gorges Hydropower Plant in China. Test results show that the minimum water consumption obtained using the proposed algorithm is similar to the optimum obtained from a previously proposed “improved” genetic algorithm when the total load of the plant is relatively high. However, for reduced load, the proposed algorithm clearly outperforms the “improved” genetic algorithm.     

辽河流域太子河大型底栖动物群落与水环境因子关联性的量化分析

大型底栖动物群落结构与水环境因子具有较强的响应关系,为了量化分析大型底栖动物群落水环境因子适宜状态以及响应关系,在太子河进行3次流域水生态调查,共获得136个站位的生态数据,通过筛选得到水环境驱动因子,并利用加权平均回归分析和临界点指示类群分析的方法,探究大型底栖动物群落物种、不同多样性水平以及功能摄食类群水环境驱动因子的最适值和阈值.结果显示,显著影响大型底栖动物群落结构的水环境因子是溶解氧、电导率、总氮.大型底栖动物敏感种的溶解氧最适值较高,耐污种较低;敏感种的电导率和总氮最适值较低,耐污种较高;大型底栖动物群落多样性水平Shannon-Wiener指数(0-1]区间的溶解氧最适值最低,(3-4]区间的溶解氧最适值最高,各Shannon-Wiener指数区间电导率和总氮最适值排序为:(0-1]区间(1-2]区间(2-3]区间(3-4]区间;在5个功能摄食类群中溶解氧最适值最高和最低分别为撕食者和直接收集者,电导率最适值最高和最低分别为直接收集者和过滤收集者,总氮最适值最高和最低分别为直接收集者和刮食者.大型底栖动物敏感种的溶解氧阈值高于耐污种类群与其他物种,而敏感种的电导率和总氮阈值低于耐污种和其他物种;大型底栖动物群落多样性水平Shannon-Wiener指数(0-1]区间与溶解氧阈值呈负响应关系,而与电导率和总氮阈值呈正响应关系,(1-2]区间、(2-3]区间、(3-4]区间与溶解氧阈值呈正响应关系,而与电导率和总氮阈值呈负响应关系;溶解氧指示的大型底栖动物功能摄食类群为撕食者,且呈正响应关系,而电导率和总氮指示的功能摄食类群都包括过滤收集者、刮食者、撕食者,且呈负响应关系,其中刮食者的电导率和总氮阈值均最高.研究表明,通过分析大型底栖动物群落水环境因子的最适值和阈值,能以数据的形式量化反映大型底栖动物群落与河流水环境因子的响应关系,对河流生态环境的保护和修复具有重要的指导意义.     

On the Application of a Genetic Algorithm to the Predictability Problems Involving "On-Off" Switches

The lower bound of maximum predictable time can be formulated into a constrained nonlinear opti- mization problem, and the traditional solutions to this problem are the filtering method and the conditional nonlinear optimal perturbation (CNOP) method. Usually, the CNOP method is implemented with the help of a gradient descent algorithm based on the adjoint method, which is named the ADJ-CNOP. However, with the increasing improvement of actual prediction models, more and more physical processes are taken into consideration in models in the form of parameterization, thus giving rise to the on-off switch problem, which tremendously affects the effectiveness of the conventional gradient descent algorithm based on the ad- joint method. In this study, we attempted to apply a genetic algorithm (GA) to the CNOP method, named GA-CNOP, to solve the predictability problems involving on-off switches. As the precision of the filtering method depends uniquely on the division of the constraint region, its results were taken as benchmarks, and a series of comparisons between the ADJ-CNOP and the GA-CNOP were performed for the modified Lorenz equation. Results show that the GA-CNOP can always determine the accurate lower bound of maximum predictable time, even in non-smooth cases, while the ADJ-CNOP, owing to the effect of on-off switches, often yields the incorrect lower bound of maximum predictable time. Therefore, in non-smooth cases, using GAs to solve predictability problems is more effective than using the conventional optimization algorithm based on gradients, as long as genetic operators in GAs are properly configured.     

Application of the Conditional Nonlinear Optimal Perturbation Method to the Predictability Study of the Kuroshio Large Meander

A reduced-gravity barotropic shallow-water model was used to simulate the Kuroshio path variations.The results show that the model was able to capture the essential features of these path variations.We used one simulation of the model as the reference state and investigated the effects of errors in model parameters on the prediction of the transition to the Kuroshio large meander (KLM) state using the conditional nonlinear optimal parameter perturbation (CNOP-P) method.Because of their relatively large uncertainties,three model parameters were considered:the interfacial friction coefficient,the wind-stress amplitude,and the lateral friction coefficient.We determined the CNOP-Ps optimized for each of these three parameters independently,and we optimized all three parameters simultaneously using the Spectral Projected Gradient 2 (SPG2) algorithm.Similarly,the impacts caused by errors in initial conditions were examined using the conditional nonlinear optimal initial perturbation (CNOP-I) method.Both the CNOP-I and CNOP-Ps can result in significant prediction errors of the KLM over a lead time of 240 days.But the prediction error caused by CNOP-I is greater than that caused by CNOP-P.The results of this study indicate not only that initial condition errors have greater effects on the prediction of the KLM than errors in model parameters but also that the latter cannot be ignored.Hence,to enhance the forecast skill of the KLM in this model,the initial conditions should first be improved,the model parameters should use the best possible estimates.     

Multiobjective optimization for performance‐based seismic design of steel moment frame structures

The performance‐based seismic design of steel special moment‐resisting frame (SMRF) structures is formulated as a multiobjective optimization problem, in which conflicting design criteria that respectively reflect the present capital investment and the future seismic risk are treated simultaneously as separate objectives other than stringent constraints. Specifically, the initial construction expenses are accounted for by the steel material weight as well as by the number of different standard steel section types, the latter roughly quantifying the degree of design complexity related additional construction cost; the seismic risk is considered in terms of maximum interstory drift demands at two hazard levels with exceedance probabilities being 50% and 2% in 50 years, respectively. The present formulation allows structural engineers to find an optimized design solution by explicitly striving for a desirable compromise between the initial investment and seismic performance. Member sizing for code‐compliant design of a planar five‐story four‐bay SMRF is presented as an application example using the proposed procedure that is automated by a multiobjective genetic algorithm. Copyright © 2004 John Wiley & Sons, Ltd.