A global sensitivity analysis framework for hybrid simulation

Abbiati, Giuseppe; Marelli, Stefano; Tsokanas, Nikolaos; Sudret, Bruno; Stojadinović, Božidar

doi:10.1016/j.ymssp.2020.106997

Cited by 37 publications

(30 citation statements)

References 27 publications

(27 reference statements)

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“…This paper extends the GSA framework for HS proposed in (Abbiati et al, 2021) to the case of PSs with non-deterministic behavior. Similarly to the original framework, the idea is to surrogate the hybrid model response as a function of the input parameters that can be controlled by the experimenter and originate from substructures and loading (physical and numerical).…”

Section: Scopementioning

confidence: 99%

“…An exhaustive exploration of all possible load cases is clearly not an option given the experimental cost associated with a single hybrid model evaluation. Accordingly, Abbiati and coworkers (Abbiati et al, 2021) proposed surrogate modeling to compute the variance-based global sensitivity analysis (GSA) of the response quantity of interest (QoI) of a given hybrid model with respect to a set of input parameters that characterize both substructures and loading excitations. In detail, polynomial chaos expansion (PCE) was used to construct a surrogate model (a.k.a.…”

Section: Background and Motivationmentioning

confidence: 99%

“…Variance-based sensitivity analysis has been extensively studied and successfully developed in the context of deterministic models (Abbiati et al, 2021;Saltelli, 2008). For a random vector X with independent components, any deterministic mapping Y = M s (X) with Var [Y ] < +∞ can be decomposed as (Sobol', 1993)…”

Section: Sobol' Sensitivity Indicesmentioning

confidence: 99%

See 2 more Smart Citations

A global sensitivity analysis framework for hybrid simulation with stochastic substructures

Tsokanas¹,

Zhu²,

Abbiati³

et al. 2021

Preprint

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Hybrid simulation is used to investigate the experimental dynamic response of a component or sub-assembly of a prototype structure using a hybrid model. The latter comprises both physically-tested and numerically-simulated substructures interacting with each other in a real-time feedback loop. 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. 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. The effectiveness of the proposed hybrid simulation global sensitivity analysis framework is demonstrated using an experiment.

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Section: Scopementioning

confidence: 99%

Section: Background and Motivationmentioning

confidence: 99%

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A global sensitivity analysis framework for hybrid simulation with stochastic substructures

Tsokanas¹,

Zhu²,

Abbiati³

et al. 2021

Preprint

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“…In other words, it may aid in finding the parameters that most affect the system response. In this way, it has been receiving increasing attention in many engineering systems, giving a comprehensive approach to how an input data variation can affect the underlying system response [1].…”

Section: Introductionmentioning

confidence: 99%

Global Sensitivity Analysis of (a)Symmetric Energy Harvesters

Norenberg

Cunha

Silva

et al. 2021

Preprint

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Parametric variability is inevitable in actual energy harvesters and can define crucial aspects of the system performance, especially in susceptible systems to small perturbations. In this way, this work aims to identify the most critical parameters in the dynamics of (a)symmetric bistable energy harvesters with nonlinear piezoelectric coupling, considering the variability of their physical and excitation parameters. For this purpose, a global sensitivity analysis based on the Sobol' indices is performed by an orthogonal decomposition in terms of conditional variances to access the dependence of the recovered power concerning the harvester parameters. This technique quantifies the variance concerning each parameter individually and jointly regarding the total variation of the model. The results indicate that the frequency and amplitude of excitation, asymmetric bias angle, and piezoelectric coupling at the electrical domain are the most influential parameters that affect the mean power harvested. It has also been shown that the order of importance of the parameters can change from stable conditions. In possession of this, a better understanding of the system under analysis is obtained, identifying vital parameters that rule the change of dynamic behavior and constituting a powerful tool in the robust design and prediction of nonlinear harvesters.

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“…Due to its closed-loop nature, a successful RTHS framework needs to control the delays and noises in the interfacing actuator and sensor systems, as they tend to bring destabilizing effect into RTHS, causing large experimental error or even failure (Christenson et al, 2014;Maghareh et al, 2014;Hayati and Song, 2017). Research studies have also been conducted to quantify uncertainties in RTHS due to experimental errors (Sauder et al, 2019) and modeling choices (Abbiati et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Conceptual Study of a Real-Time Hybrid Simulation Framework for Monopile Offshore Wind Turbines Under Wind and Wave Loads

Song

Sun

Zuo

et al. 2020

Front. Built Environ.

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As an attractive renewable energy source, offshore wind plants are becoming increasingly popular for energy production. However, the performance assessment of offshore wind turbine (OWT) structure is a challenging task due to the combined wind-wave loading and difficulties in reproducing such loading conditions in laboratory. Real-time hybrid simulation (RTHS), combining physical testing and numerical simulation in real-time, offers a new venue to study the structural behavior of OWTs. It overcomes the scaling incompatibilities in OWT scaled model testing by replacing the rotor components with an actuation system, driven by an aerodynamic simulation tool running in real-time. In this study, a RTHS framework for monopile OWTs is proposed. A set of sensitivity analyses is carried out to evaluate the feasibility of this RTHS framework and determine possible tolerances on its design. By simulating different scaling laws and possible error contributors (delays and noises) in the proposed framework, the sensitivity of the OWT responses to these parameters are quantified. An example using a National Renewable Energy Lab (NREL) 5-MW reference OWT system at 1:25 scale is simulated in this study to demonstrate the proposed RTHS framework and sensitivity analyses. Three different scaling laws are considered. The sensitivity results show that the delays in the RTHS framework significantly impact the performance on the response evaluation, higher than the impact of noises. The proposed framework and sensitivity analyses presented in this study provides important information for future implementation and further development of the RTHS technology for similar marine structures.

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A global sensitivity analysis framework for hybrid simulation

Cited by 37 publications

References 27 publications

A global sensitivity analysis framework for hybrid simulation with stochastic substructures

A global sensitivity analysis framework for hybrid simulation with stochastic substructures

Global Sensitivity Analysis of (a)Symmetric Energy Harvesters

Conceptual Study of a Real-Time Hybrid Simulation Framework for Monopile Offshore Wind Turbines Under Wind and Wave Loads

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