[HTML][HTML] Certain trends in uncertainty and sensitivity analysis: An overview of software tools and techniques
Uncertainty and sensitivity analysis (UA/SA) aid in assessing whether model complexity is
warranted and under what conditions. To support these analyses a variety of software tools …
warranted and under what conditions. To support these analyses a variety of software tools …
Sparse Bayesian learning of explicit algebraic Reynolds-stress models for turbulent separated flows
Abstract A novel Sparse Bayesian Learning (SBL) framework is introduced for generating
stochastic Explicit Algebraic Reynolds Stress (EARSM) closures for the Reynolds-Averaged …
stochastic Explicit Algebraic Reynolds Stress (EARSM) closures for the Reynolds-Averaged …
[PDF][PDF] Space-dependent aggregation of data-driven turbulence models
S Cherroud, X Merle, P Cinnella… - arXiv preprint arXiv …, 2023 - academia.edu
A machine-learning approach for data-driven Reynolds-Averaged Navier–Stokes (RANS)
predictions of turbulent flows including estimates of turbulence modelling uncertainties is …
predictions of turbulent flows including estimates of turbulence modelling uncertainties is …
Effectively subsampled quadratures for least squares polynomial approximations
This paper proposes a new deterministic sampling strategy for constructing polynomial
chaos approximations for expensive physics simulation models. The proposed approach …
chaos approximations for expensive physics simulation models. The proposed approach …
Sensitivity analysis of a coupled hydrodynamic-vegetation model using the effectively subsampled quadratures method (ESQM v5. 2)
TS Kalra, A Aretxabaleta, P Seshadri… - Geoscientific Model …, 2017 - gmd.copernicus.org
Coastal hydrodynamics can be greatly affected by the presence of submerged aquatic
vegetation. The effect of vegetation has been incorporated into the Coupled Ocean …
vegetation. The effect of vegetation has been incorporated into the Coupled Ocean …
Blade envelopes Part I: Concept and methodology
Blades manufactured through flank and point milling will likely exhibit geometric variability.
Gauging the aerodynamic repercussions of such variability, prior to manufacturing a …
Gauging the aerodynamic repercussions of such variability, prior to manufacturing a …
Programming with equadratures: an open-source package for uncertainty quantification, dimension reduction, and optimisation
View Video Presentation: https://doi. org/10.2514/6.2022-2108. vid This paper presents an
overview of the open-source code equadratures. While originally developed to replicate …
overview of the open-source code equadratures. While originally developed to replicate …
Design space exploration of stagnation temperature probes via dimension reduction
AD Scillitoe, B Ubald… - … Expo: Power for …, 2020 - asmedigitalcollection.asme.org
The measurement of stagnation temperature is important for turbomachinery applications as
it is used in the calculation of component efficiency and engine specific fuel consumption …
it is used in the calculation of component efficiency and engine specific fuel consumption …
[PDF][PDF] Space-dependent Aggregation of Stochastic Data-driven Turbulence Models
XM Cherroud, P Cinnella… - arXiv preprint arXiv …, 2023 - researchgate.net
A stochastic Machine-Learning approach is developed for data-driven Reynolds-Averaged
Navier-Stokes (RANS) predictions of turbulent flows, with quantified model uncertainty. This …
Navier-Stokes (RANS) predictions of turbulent flows, with quantified model uncertainty. This …
Least squares approximation-based polynomial chaos expansion for uncertainty quantification and robust optimization in aeronautics
For many engineering problems, reliability and robustness are far more important than the
nominal performance when it comes to the choice of a design over another. Availability of …
nominal performance when it comes to the choice of a design over another. Availability of …