Uncertainty quantification of SSG/LRR-ω turbulence model closure coefficients
Tài liệu tham khảo
Shi, 2016, Large-eddy simulation of a pulsed jet into a supersonic crossflow[J], Comput. Fluid, 140, 320, 10.1016/j.compfluid.2016.10.009
Liang, 2019, On developing data-driven turbulence model for DG solution of RANS[J], Chin. J. Aeronaut., 32, 1869, 10.1016/j.cja.2019.04.004
Leschziner, 2015
Edeling, 2014, Bayesian estimates of parameter variability in the k–ε turbulence model[J], J. Comput. Phys., 258, 73, 10.1016/j.jcp.2013.10.027
Eisfeld, 2016, Verification and validation of a second-moment-closure model[J], AIAA J., 54, 1524, 10.2514/1.J054718
Cécora, 2012, 465
Eisfeld, 2005, 4727
Probst, 2015
Slotnick, J., Khodadoust, A., Alonso, J., Darmofal, D., Gropp, W., Lurie, E., Mavriplis, D., “CFD Vision 2030 Study: A Path to Revolutionary Computational Aero Sciences,” NASA/CR-2014-218178, March 201.
Xiao, 2018
Godfrey, 2001, 1060
Schaefer, 2017, Uncertainty quantification and sensitivity analysis of SA turbulence model coefficients in two and three dimensions[C]//55th, AIAA Aerospace Sci. Meet., 1710
Schaefer, 2017, Uncertainty quantification of turbulence model closure coefficients for transonic wall-bounded flows[J], AIAA J., 55, 195, 10.2514/1.J054902
Zhao, 2019, Uncertainty and sensitivity analysis of SST turbulence model on hypersonic flow heat transfer[J], Int. J. Heat Mass Tran., 136, 808, 10.1016/j.ijheatmasstransfer.2019.03.012
Zhao, 2018, 526
Li, 2021, Bayesian model evaluation of three k–ω turbulence models for hypersonic shock wave–boundary layer interaction flows[J], Acta Astronaut., 189, 143, 10.1016/j.actaastro.2021.08.050
Jinping, 2022, Bayesian uncertainty analysis of SA turbulence model for supersonic jet interaction simulations[J], Chin. J. Aeronaut., 35, 185, 10.1016/j.cja.2021.07.039
Zhang, 2022, Uncertainty analysis and calibration of SST turbulence model for free shear layer in cavity-ramp flow[J], Acta Astronaut., 192, 168, 10.1016/j.actaastro.2021.12.027
Shen, 2020, Constraint-based parameterization using FFD and multi-objective design optimization of a hypersonic vehicle[J], Aero. Sci. Technol., 100, 10.1016/j.ast.2020.105788
Shen, 2019, Parametric modeling and aerodynamic optimization of EXPERT configuration at hypersonic speeds[J], Aero. Sci. Technol., 84, 641, 10.1016/j.ast.2018.11.007
Huang, 2014, Design exploration of three-dimensional transverse jet in a supersonic crossflow based on data mining and multi-objective design optimization approaches[J], Int. J. Hydrogen Energy, 39, 3914, 10.1016/j.ijhydene.2013.12.129
Huang, 2012, Effect of geometric parameters on the drag of the cavity flameholder based on the variance analysis method[J], Aero. Sci. Technol., 21, 24, 10.1016/j.ast.2011.04.009
Ou, 2019, Design exploration of combinational spike and opposing jet concept in hypersonic flows based on CFD calculation and surrogate model[J], Acta Astronaut., 155, 287, 10.1016/j.actaastro.2018.12.012
Ou, 2018, Detailed parametric investigations on drag and heat flux reduction induced by a combinational spike and opposing jet concept in hypersonic flows[J], Int. J. Heat Mass Tran., 126, 10, 10.1016/j.ijheatmasstransfer.2018.05.013
Bart, 1970, Transport equations in turbulence[J], Phys. Fluids, 13, 2634, 10.1063/1.1692845
Menter, 1994, Two-equation eddy-viscosity turbulence models for engineering applications[J], AIAA J., 32, 1598, 10.2514/3.12149
Wilcox, 1988, Reassessment of the scale-determining equation for advanced turbulence models[J], AIAA J., 26, 1299, 10.2514/3.10041
Speziale, 1991, Modelling the pressure–strain correlation of turbulence: an invariant dynamical systems approach[J], J. Fluid Mech., 227, 245, 10.1017/S0022112091000101
Launder, 1975, Progress in the development of a Reynolds-stress turbulence closure[J], J. Fluid Mech., 68, 537, 10.1017/S0022112075001814
Debusschere, 2017, 1807
Hosder, 2006, 891
Xiu, 2003, Modeling uncertainty in flow simulations via generalized polynomial chaos[J], J. Comput. Phys., 187, 137, 10.1016/S0021-9991(03)00092-5
Hosder, 2007, Efficient sampling for non-intrusive polynomial chaos applications with multiple uncertain input variables[C]//48th AIAA/ASME/ASCE/AHS/ASC Structures
Crestaux, 2009, Polynomial chaos expansion for sensitivity analysis[J], Reliab. Eng. Syst. Saf., 94, 1161, 10.1016/j.ress.2008.10.008
Haario, 2001, An adaptive Metropolis algorithm, Bernoulli, 7, 223, 10.2307/3318737
Devroye, 1983, 896
Krist, 1998