A Global Sensitivity Analysis Framework for Hybrid Simulation with Stochastic Substructures
Hybrid simulation is an experimental method used to investigate the dynamic response of a reference prototype structure by decomposing it to physically-tested and numerically-simulated substructures. The latter substructures interact with each other in a real-time feedback loop and their coupling fo...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-12-01
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| Series: | Frontiers in Built Environment |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fbuil.2021.778716/full |
| _version_ | 1819044055571496960 |
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| author | Nikolaos Tsokanas Xujia Zhu Giuseppe Abbiati Stefano Marelli Bruno Sudret Božidar Stojadinović |
| author_facet | Nikolaos Tsokanas Xujia Zhu Giuseppe Abbiati Stefano Marelli Bruno Sudret Božidar Stojadinović |
| author_sort | Nikolaos Tsokanas |
| collection | DOAJ |
| description | Hybrid simulation is an experimental method used to investigate the dynamic response of a reference prototype structure by decomposing it to physically-tested and numerically-simulated substructures. The latter substructures interact with each other in a real-time feedback loop and their coupling forms the hybrid model. In this study, we extend our previous work on metamodel-based sensitivity analysis of deterministic hybrid models to the practically more relevant case of stochastic hybrid models. The aim is to cover a more realistic situation where the physical substructure response is not deterministic, as nominally identical specimens are, in practice, never actually identical. A generalized lambda surrogate model recently developed by some of the authors is proposed to surrogate the hybrid model response, and Sobol’ sensitivity indices are computed for substructure quantity of interest response quantiles. Normally, several repetitions of every single sample of the inputs parameters would be required to replicate the response of a stochastic hybrid model. In this regard, a great advantage of the proposed framework is that the generalized lambda surrogate model does not require repeated evaluations of the same sample. The effectiveness of the proposed hybrid simulation global sensitivity analysis framework is demonstrated using an experiment. |
| first_indexed | 2024-12-21T10:06:36Z |
| format | Article |
| id | doaj.art-f7614b0dc5344daba7c972b109da0067 |
| institution | Directory Open Access Journal |
| issn | 2297-3362 |
| language | English |
| last_indexed | 2024-12-21T10:06:36Z |
| publishDate | 2021-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Built Environment |
| spelling | doaj.art-f7614b0dc5344daba7c972b109da00672022-12-21T19:07:49ZengFrontiers Media S.A.Frontiers in Built Environment2297-33622021-12-01710.3389/fbuil.2021.778716778716A Global Sensitivity Analysis Framework for Hybrid Simulation with Stochastic SubstructuresNikolaos Tsokanas0Xujia Zhu1Giuseppe Abbiati2Stefano Marelli3Bruno Sudret4Božidar Stojadinović5Department of Civil, Environmental and Geomatic Engineering, Institute of Structural Engineering, ETH Zurich, Zurich, SwitzerlandDepartment of Civil, Environmental and Geomatic Engineering, Institute of Structural Engineering, ETH Zurich, Zurich, SwitzerlandDepartment of Civil and Architectural Engineering, University of Aarhus, Aarhus, DenmarkDepartment of Civil, Environmental and Geomatic Engineering, Institute of Structural Engineering, ETH Zurich, Zurich, SwitzerlandDepartment of Civil, Environmental and Geomatic Engineering, Institute of Structural Engineering, ETH Zurich, Zurich, SwitzerlandDepartment of Civil, Environmental and Geomatic Engineering, Institute of Structural Engineering, ETH Zurich, Zurich, SwitzerlandHybrid simulation is an experimental method used to investigate the dynamic response of a reference prototype structure by decomposing it to physically-tested and numerically-simulated substructures. The latter substructures interact with each other in a real-time feedback loop and their coupling forms the hybrid model. In this study, we extend our previous work on metamodel-based sensitivity analysis of deterministic hybrid models to the practically more relevant case of stochastic hybrid models. The aim is to cover a more realistic situation where the physical substructure response is not deterministic, as nominally identical specimens are, in practice, never actually identical. A generalized lambda surrogate model recently developed by some of the authors is proposed to surrogate the hybrid model response, and Sobol’ sensitivity indices are computed for substructure quantity of interest response quantiles. Normally, several repetitions of every single sample of the inputs parameters would be required to replicate the response of a stochastic hybrid model. In this regard, a great advantage of the proposed framework is that the generalized lambda surrogate model does not require repeated evaluations of the same sample. The effectiveness of the proposed hybrid simulation global sensitivity analysis framework is demonstrated using an experiment.https://www.frontiersin.org/articles/10.3389/fbuil.2021.778716/fullhybrid simulationstochastic hybrid modelglobal sensitivity analysis (GSA)Sobol’ indicesstochastic surrogate modelinggeneralized lambda model |
| spellingShingle | Nikolaos Tsokanas Xujia Zhu Giuseppe Abbiati Stefano Marelli Bruno Sudret Božidar Stojadinović A Global Sensitivity Analysis Framework for Hybrid Simulation with Stochastic Substructures Frontiers in Built Environment hybrid simulation stochastic hybrid model global sensitivity analysis (GSA) Sobol’ indices stochastic surrogate modeling generalized lambda model |
| title | A Global Sensitivity Analysis Framework for Hybrid Simulation with Stochastic Substructures |
| title_full | A Global Sensitivity Analysis Framework for Hybrid Simulation with Stochastic Substructures |
| title_fullStr | A Global Sensitivity Analysis Framework for Hybrid Simulation with Stochastic Substructures |
| title_full_unstemmed | A Global Sensitivity Analysis Framework for Hybrid Simulation with Stochastic Substructures |
| title_short | A Global Sensitivity Analysis Framework for Hybrid Simulation with Stochastic Substructures |
| title_sort | global sensitivity analysis framework for hybrid simulation with stochastic substructures |
| topic | hybrid simulation stochastic hybrid model global sensitivity analysis (GSA) Sobol’ indices stochastic surrogate modeling generalized lambda model |
| url | https://www.frontiersin.org/articles/10.3389/fbuil.2021.778716/full |
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