A framework for hybrid simulation with online model updating suitable for hard real‐time computing. Issue 1 (23rd October 2020)

• Record Type: Journal Article
• Authors: Abbiati, Giuseppe; Lanese, Igor; Eftekhar Azam, Saeed; Bursi, Oreste S.; Pavese, Alberto
• Is Part Of: Structural control and health monitoring. Volume 28:Issue 1(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-10-23
• Subjects: hard real‐time computing -- hybrid simulation -- online model updating -- partitioned time integration -- state‐space modeling; Structural engineering -- Periodicals; Structural control (Engineering) -- Periodicals; Automatic data collection systems -- Periodicals; Detectors -- Periodicals; 624.17
• DOI: 10.1002/stc.2652
• Languages: English
• ISSNs: 1545-2255

Abstract

Summary: 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.