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Robust design optimization of TMDs in vehicle-bridge coupled vibration problems

机译:车桥耦合振动问题中TMD的鲁棒设计优化

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Optimal design of Tuned-Mass-Dampers (TMD) and Multiple-Tuned-Mass-Dampers (MTMD) for vibration control has been a popular research theme. In most applications, one observes that uncertainty in dynamical excitations is considered (e.g., for earthquake or wind loading). However, a literature survey shows that parameter or system uncertainties are seldom taken into account. Moreover, we could not find applications of robust design optimization to coupled vehicle-bridge systems. Hence, this paper presents a novel application of robust design optimization of TMD and MTMD applied to vehicle-bridge coupled vibration problems. Robust optimization looks for designs which are less sensitive to uncertainties in system parameters and in parameters of excitation models. Parameters of the TMD, of pavement irregularity models and of the bridge-vehicle models are considered as random variables. The principle of maximum entropy is employed to obtain the probability distributions of these random variables. The robust optimization problem is solved by means of the Firefly Algorithm. Results show that the use MTMDs allows decreasing the expected value and the variance of the maximum vertical displacement of central bridge node when compared to solutions with single TMDs. The numerical solution developed herein is also compared to classical techniques of Den Hartog and Warburton. The paper shows that the classical analytical techniques can also be successfully employed in robust optimal design of single TMD devices. (C) 2016 Elsevier Ltd. All rights reserved.
机译:用于振动控制的调谐质量阻尼器(TMD)和多调谐质量阻尼器(MTMD)的优化设计一直是热门的研究主题。在大多数应用中,人们观察到考虑了动态激励的不确定性(例如,对于地震或风荷载)。但是,文献调查表明很少考虑参数或系统的不确定性。此外,我们找不到将稳健的设计优化应用于耦合车桥系统的应用。因此,本文提出了将TMD和MTMD进行鲁棒性设计优化的新应用,并将其应用于车桥耦合振动问题。稳健的优化寻找对系统参数和励磁模型参数的不确定性较不敏感的设计。 TMD,路面不规则模型和桥梁车辆模型的参数被视为随机变量。采用最大熵原理获得这些随机变量的概率分布。通过萤火虫算法解决了鲁棒的优化问题。结果表明,与具有单个TMD的解决方案相比,使用MTMD可以减小期望值和中心桥节点最大垂直位移的方差。本文开发的数值解也与Den Hartog和Warburton的经典技术进行了比较。本文表明,经典的分析技术也可以成功地用于单个TMD设备的稳健优化设计中。 (C)2016 Elsevier Ltd.保留所有权利。

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