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dc.contributor.author
Tsokanas, Nikolaos
dc.contributor.author
Stojadinovic, Bozidar
dc.contributor.editor
Mao, Zhu
dc.date.accessioned
2020-10-30T14:03:24Z
dc.date.available
2020-10-28T14:29:46Z
dc.date.available
2020-10-30T14:03:24Z
dc.date.issued
2020
dc.identifier.isbn
978-3-030-47638-0
en_US
dc.identifier.isbn
978-3-030-48778-2
en_US
dc.identifier.other
10.1007/978-3-030-47638-0_8
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/448426
dc.description.abstract
Real-time hybrid simulation is a method to obtain the response of a system subjected to dynamic excitation by combining loading-rate-sensitive numerical and physical substructures. The interfaces between physical and numerical substructures are usually implemented using closed-loop-controlled actuation systems. In current practice, the parameters that characterize the hybrid model are deterministic. However, the effect of uncertainties may be significant. Stochastic hybrid simulation is an extension of the deterministic hybrid simulation where the parameters of the system are treated as random variables with known probability distributions. The results are probability distributions of the structural response quantities of interest. The arising question is to what extent does the actuation control system at the interface between physical and numerical substructures affect the outcomes of stochastic hybrid simulations. This question is most acute for real-time hybrid simulations. The response of a benchmark stochastic prototype to random excitation will be computed. Then, a part of the prototype will be replaced by a hybrid model whose substructure interfaces are actuated in closed-loop control. A controller that guarantees robustness and stability of the interfaces will be designed. The parameters of this hybrid model will be treated as random variables in repeated real-time hybrid response simulations to the same random excitation. The difference between the prototype and hybrid model responses will be used to determine if the controller design has an effect on the simulation outcomes, to predict such effects, and to propose guidelines for real-time controller design such that it has a predictable effect on the hybrid simulation. Additional criteria based on peak and root mean square tracking errors, as well as energy errors, are addressed in order to assess the overall system performance. Based on simulation data, surrogate models will be developed. Multiple additional runs of the surrogate models will give insight into the robustness and performance of the control system under uncertainties. Global sensitivity analysis of the overall system response will also be performed, identifying the most sensitive stochastic input variables. Cross-check validation of the results will take place using different meta-modeling techniques.
en_US
dc.language.iso
en
en_US
dc.publisher
Springer
en_US
dc.subject
Stochastic hybrid simulation
en_US
dc.subject
Uncertainty quantification
en_US
dc.subject
Surrogate modelling
en_US
dc.subject
Sensitivity analysis
en_US
dc.subject
Model-predictive control
en_US
dc.title
Design of an Actuation Controller for Physical Substructures in Stochastic Real-Time Hybrid Simulations
en_US
dc.type
Conference Paper
dc.date.published
2020-10-28
ethz.book.title
Model Validation and Uncertainty Quantification, Volume 3
en_US
ethz.journal.title
Conference Proceedings of the Society for Experimental Mechanics Series
ethz.pages.start
69
en_US
ethz.pages.end
82
en_US
ethz.event
38th IMAC Conference and Exposition on Structural Dynamics (IMAC 2020)
en_US
ethz.event.location
Houston TX, USA
en_US
ethz.event.date
February 10–13, 2020
en_US
ethz.grant
Dynamic virtualisation: modelling performance of engineering structures
en_US
ethz.publication.place
Cham
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02605 - Institut für Baustatik u. Konstruktion / Institute of Structural Engineering::03930 - Stojadinovic, Bozidar / Stojadinovic, Bozidar
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02605 - Institut für Baustatik u. Konstruktion / Institute of Structural Engineering::03930 - Stojadinovic, Bozidar / Stojadinovic, Bozidar
en_US
ethz.grant.agreementno
764547
ethz.grant.fundername
EC
ethz.grant.funderDoi
10.13039/501100000780
ethz.grant.program
H2020
ethz.date.deposited
2020-10-28T14:30:03Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2020-10-30T14:03:33Z
ethz.rosetta.lastUpdated
2021-02-15T19:30:36Z
ethz.rosetta.versionExported
true
ethz.COinS
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