A greedy algorithm for automatic recursion parameter selection in the OWNS method for hyperbolic equations yields faster convergence than heuristics in boundary-layer flow simulations.
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EnVar assimilation of wall-pressure data from seven sensors is required to accurately predict separation onset and downstream pressures in Mach 6 cone-flare DNS, while upstream sensors alone are insufficient.
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Greedy recursion parameter selection for one-way spatial integration of hyperbolic equations
A greedy algorithm for automatic recursion parameter selection in the OWNS method for hyperbolic equations yields faster convergence than heuristics in boundary-layer flow simulations.
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Assimilation of wall-pressure measurements in direct numerical simulations of high-speed flow over a cone-flare geometry
EnVar assimilation of wall-pressure data from seven sensors is required to accurately predict separation onset and downstream pressures in Mach 6 cone-flare DNS, while upstream sensors alone are insufficient.