Pages that link to "Item:Q5308069"
From MaRDI portal
The following pages link to Sensitivity analysis of large-eddy simulations to subgrid-scale-model parametric uncertainty using polynomial chaos (Q5308069):
Displaying 28 items.
- Prediction of geometric uncertainty effects on fluid dynamics by polynomial chaos and fictitious domain method (Q435497) (← links)
- A hybrid anchored-ANOVA - POD/Kriging method for uncertainty quantification in unsteady high-fidelity CFD simulations (Q525934) (← links)
- Treatment of uncertain material interfaces in compressible flows (Q643959) (← links)
- A gPC-based approach to uncertain transonic aerodynamics (Q649219) (← links)
- Identification of high-dimension polynomial chaos expansions with random coefficients for non-Gaussian tensor-valued random fields using partial and limited experimental data (Q658826) (← links)
- On the influence of uncertainty in computational simulations of a high-speed jet flow from an aircraft exhaust (Q667392) (← links)
- Uncertainty quantification for systems of conservation laws (Q1008858) (← links)
- Epistemic uncertainties in RANS model free coefficients (Q1641578) (← links)
- Stochastic sensitivity analysis of large-eddy simulation predictions of the flow around a 5:1 rectangular cylinder (Q1672144) (← links)
- Systematic study of accuracy of wall-modeled large eddy simulation using uncertainty quantification techniques (Q1739820) (← links)
- Optimized parametric inference for the inner loop of the multigrid ensemble Kalman filter (Q2088341) (← links)
- Multigroup-like MC resolution of generalised polynomial chaos reduced models of the uncertain linear Boltzmann equation (+discussion on hybrid intrusive/non-intrusive uncertainty propagation) (Q2112538) (← links)
- Efficient uncertain \(k_{\mathrm{eff}}\) computations with the Monte Carlo resolution of generalised polynomial chaos based reduced models (Q2133777) (← links)
- On the use of derivatives in the polynomial chaos based global sensitivity and uncertainty analysis applied to the distributed parameter models (Q2214566) (← links)
- Intrusive generalized polynomial chaos with asynchronous time integration for the solution of the unsteady Navier-Stokes equations (Q2245366) (← links)
- On numerical uncertainties in scale-resolving simulations of canonical wall turbulence (Q2245432) (← links)
- On sensitivity of RANS simulations to uncertain turbulent inflow conditions (Q2361819) (← links)
- A Sparse Grid Method for Bayesian Uncertainty Quantification with Application to Large Eddy Simulation Turbulence Models (Q2808028) (← links)
- A stochastic view of isotropic turbulence decay (Q3097686) (← links)
- Numerical investigation of skewed spatially evolving mixing layers (Q3303687) (← links)
- Large eddy simulation for aerodynamics: status and perspectives (Q3559883) (← links)
- Stochastic finite element methods for partial differential equations with random input data (Q4683917) (← links)
- Lattice Boltzmann Method for Stochastic Convection-Diffusion Equations (Q4995115) (← links)
- Numerical Analysis of the Monte-Carlo Noise for the Resolution of the Deterministic and Uncertain Linear Boltzmann Equation (Comparison of Non-Intrusive gPC and MC-gPC) (Q5104572) (← links)
- Iterative Polynomial Approximation Adapting to Arbitrary Probability Distribution (Q5261599) (← links)
- Sensitivity of two-dimensional spatially developing mixing layers with respect to uncertain inflow conditions (Q5304072) (← links)
- Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees) (Q6187668) (← links)
- A non-Gaussian Bayesian filter for sequential data assimilation with non-intrusive polynomial chaos expansion (Q6554054) (← links)
