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A composite experimental dynamic substructuring method based on partitioned algorithms and localized Lagrange multipliers

机译:基于分区算法和局部拉格朗日乘子的复合实验动态子构造方法

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Successful online hybrid (numerical/physical) dynamic substructuring simulations have shown their potential in enabling realistic dynamic analysis of almost any type of nonlinear structural system (e.g., an as-built/isolated viaduct, a petrochemical piping system subjected to non-stationary seismic loading, etc.). Moreover, owing to faster and more accurate testing equipment, a number of different offline experimental substructuring methods, operating both in time (e.g. the impulse-based substructuring) and frequency domains (i.e. the Lagrange multiplier frequency-based substructuring), have been employed in mechanical engineering to examine dynamic substructure coupling. Numerous studies have dealt with the above-mentioned methods and with consequent uncertainty propagation issues, either associated with experimental errors or modelling assumptions. Nonetheless, a limited number of publications have systematically cross-examined the performance of the various Experimental Dynamic Substructuring (EDS) methods and the possibility of their exploitation in a complementary way to expedite a hybrid experimentumerical simulation. From this perspective, this paper performs a comparative uncertainty propagation analysis of three EDS algorithms for coupling physical and numerical subdomains with a dual assembly approach based on localized Lagrange multipliers. The main results and comparisons are based on a series of Monte Carlo simulations carried out on a five-DoF linearon-linear chain-like systems that include typical aleatoric uncertainties emerging from measurement errors and excitation loads. In addition, we propose a new Composite-EDS (C-EDS) method to fuse both online and offline algorithms into a unique simulator. Capitalizing from the results of a more complex case study composed of a coupled isolated tank-piping system, we provide a feasible way to employ the C-EDS method when nonlinearities and multi-point constraints are present in the emulated system.
机译:成功的在线混合(数字/物理)动态子结构仿真显示了其潜力,可以对几乎任何类型的非线性结构系统(例如,建成/隔离的高架桥,承受非平稳地震荷载的石化管道系统)进行逼真的动态分析。等)。此外,由于更快,更准确的测试设备,已经在时间(例如,基于脉冲的子结构)和频域(即基于频率的拉格朗日乘数子结构)中运行的许多不同的离线实验子结构方法已被采用。机械工程,以检查动态子结构耦合。许多研究已经涉及上述方法以及随之而来的不确定性传播问题,这些不确定性传播问题与实验误差或建模假设有关。尽管如此,有限的出版物已经系统地交叉检验了各种实验动态子结构(EDS)方法的性能以及以互补的方式利用它们以加快混合实验/数值模拟的可能性。从这个角度出发,本文对三种EDS算法进行了比较不确定性传播分析,这些算法将物理和数值子域与基于局部Lagrange乘子的双重组装方法耦合在一起。主要结果和比较结果是基于在五自由度线性/非线性链状系统上进行的一系列蒙特卡洛模拟得出的,该系统包括因测量误差和激励负载而产生的典型不确定性不确定性。此外,我们提出了一种新的Composite-EDS(C-EDS)方法,将在线和离线算法融合到一个独特的模拟器中。利用耦合的隔离储罐管道系统组成的更为复杂的案例研究的结果,当仿真系统中存在非线性和多点约束时,我们提供了一种可行的方法来采用C-EDS方法。

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