The hybrid simulation method is used to test one or some components of a prototype structure subjected to a plausible loading history, accounting for their interaction with the untested ones, which are simulated numerically. If tested components have similar numerical counterparts, a possible approach to reduce simulation errors is to update the parameters of numerical substructures based on tested physical substructures. For this reason, online parameter estimation has gained the attention of the hybrid simulation community in the last decade. The term online indicates that the parameters of the identification model of the physical substructure are updated during the experiment. Main state‐of‐the‐art middleware tools (e.g., OpenFresco and UI‐SIMCOR) have been extended to support online model updating for the pseudodynamic hybrid simulation method. In this case, both numerical substructures and dynamic identification models are implemented on existing finite‐element analysis software, which communicates with the middleware using a data exchange protocol with non‐deterministic time schedule (e.g., TCP/IP). On the other hand, fast‐ and real‐time hybrid simulation methods require a deterministic data exchange schedule between substructures, which imposes the adoption of hard real‐time implementations. In this context, partitioned time integration is proposed to coordinate the parallel execution of simulation and model updating processes with heterogeneous sampling rates. As a result, the allocation of computational resources can leverage parallelization capabilities of multi‐core CPUs.

中文翻译：

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具有在线模型更新的混合仿真框架，适用于硬实时计算

混合仿真方法用于测试原型结构的一个或某些组件经受合理的加载历史，并考虑它们与未经测试的组件之间的相互作用，并对其进行数值模拟。如果测试的零部件具有相似的数值对应物，则减少仿真错误的一种可行方法是根据测试的物理子结构更新数值子结构的参数。由于这个原因，在线参数估计在最近十年中已经引起了混合仿真社区的关注。在线一词表示在实验过程中物理子结构识别模型的参数已更新。主要的最新中间件工具（例如，OpenFresco和UI-SIMCOR）已得到扩展，以支持针对伪动态混合仿真方法的在线模型更新。在这种情况下，数字子结构和动态识别模型都在现有的有限元分析软件上实现，该软件使用具有不确定性时间表（例如TCP / IP）的数据交换协议与中间件进行通信。另一方面，快速和实时混合仿真方法需要确定子结构之间的确定性数据交换计划，这迫使采用硬实时实现。在这种情况下，提出了分段时间积分的方法，以协调具有异构采样率的仿真和模型更新过程的并行执行。因此，计算资源的分配可以利用多核CPU的并行化功能。