Pages that link to "Item:Q2222548"
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The following pages link to Kriging-enhanced ensemble variational data assimilation for scalar-source identification in turbulent environments (Q2222548):
Displaying 15 items.
- Cross-covariances and localization for EnKF in multiphase flow data assimilation (Q601225) (← links)
- Optimized parametric inference for the inner loop of the multigrid ensemble Kalman filter (Q2088341) (← links)
- Neural operator prediction of linear instability waves in high-speed boundary layers (Q2112489) (← links)
- DeepM\&Mnet: inferring the electroconvection multiphysics fields based on operator approximation by neural networks (Q2131084) (← links)
- A multigrid/ensemble Kalman filter strategy for assimilation of unsteady flows (Q2132567) (← links)
- DeepM\&Mnet for hypersonics: predicting the coupled flow and finite-rate chemistry behind a normal shock using neural-network approximation of operators (Q2133505) (← links)
- Optimal heat flux for delaying transition to turbulence in a high-speed boundary layer (Q3389271) (← links)
- Linear and nonlinear sensor placement strategies for mean-flow reconstruction via data assimilation (Q4957372) (← links)
- State estimation in turbulent channel flow from limited observations (Q4988005) (← links)
- Observation-infused simulations of high-speed boundary-layer transition (Q4988010) (← links)
- What is observable from wall data in turbulent channel flow? (Q5075031) (← links)
- Spatial reconstruction of steady scalar sources from remote measurements in turbulent flow (Q5379070) (← links)
- Synchronization of turbulence in channel flow (Q5864333) (← links)
- A novel estimation method for microstructural evolution based on data assimilation and phase field crystal model (Q6059009) (← links)
- A robust computational framework for variational data assimilation of mean flows with sparse measurements corrupted by strong outliers (Q6553824) (← links)
