Resampling Strategies to Improve Surrogate Model-based Uncertainty Quantification - Application to LES of LS89

التفاصيل البيبلوغرافية
العنوان: Resampling Strategies to Improve Surrogate Model-based Uncertainty Quantification - Application to LES of LS89
المؤلفون: Roy, Pamphile Tupui, Segui, Luis Miguel, Jouhaud, Jean-Christophe, Gicquel, Laurent
سنة النشر: 2018
المجموعة: Physics (Other)
مصطلحات موضوعية: Physics - Fluid Dynamics, Physics - Computational Physics
الوصف: Uncertainty Quantification (UQ) is receiving more and more attention for engineering applications in particular from robust optimization. Indeed, running a computer experiment only provides a limited knowledge in terms of uncertainty and variability of the input parameters. These experiments are often computationally expensive and surrogate models can be constructed to address this issue. The outcome of a UQ study is in this case directly correlated to the surrogate's quality. Thus, attention must be devoted to the Design of Experiments (DoE) to retrieve as much information as possible. This work presents two new strategies for parameter space resampling to improve a Gaussian Process (GP) surrogate model. These techniques indeed show an improvement of the predictive quality of the model with high dimensional analytical input functions. Finally, the methods are successfully applied to a turbine blade Large Eddy Simulation application: the aerothermal flow around the LS89 blade cascade.
Comment: Accepted in International Journal for Numerical Methods in Fluids
نوع الوثيقة: Working Paper
DOI: 10.1002/fld.4504
URL الوصول: http://arxiv.org/abs/1803.06134
رقم الأكسشن: edsarx.1803.06134
قاعدة البيانات: arXiv