Pages that link to "Item:Q822137"
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The following pages link to A hybrid approach combining DNS and RANS simulations to quantify uncertainties in turbulence modelling (Q822137):
Displaying 9 items.
- An efficient approach for quantifying parameter uncertainty in the SST turbulence model (Q667443) (← links)
- Gradient-based methods for uncertainty quantification in hypersonic flows (Q2015969) (← links)
- Quantifying turbulence model uncertainty in Reynolds-averaged Navier-Stokes simulations of a pin-fin array. I: Flow field (Q2019928) (← links)
- Determining \textit{a priori} a RANS model's applicable range via global epistemic uncertainty quantification (Q2245534) (← links)
- A random matrix approach for quantifying model-form uncertainties in turbulence modeling (Q2308784) (← links)
- Uncertainty Quantification for Turbulent Mixing Flows: Rayleigh-Taylor Instability (Q3144137) (← links)
- Uncertainty quantification analysis for simulation of wakes in wind-farms using a stochastic RANS solver, compared with a deep learning approach (Q6100092) (← links)
- Efficient prediction of turbulent flow quantities using a Bayesian hierarchical multifidelity model (Q6101048) (← links)
- Bayesian interface technique-based inverse estimation of closure coefficients of standard \(k-\epsilon\) turbulence model by limiting the number of DNS data points for flow over a periodic hill (Q6569724) (← links)
