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KaiChengDM/Probabilistic-parametric-reduced-order-model
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Matlab (R2023b) code of manuscript "ADAPTIVE DATA-DRIVEN PROBABILISTIC REDUCED-ORDER MODELS FOR PARAMETERIZED DYNAMICAL SYSTEMS", submitted to SIAM journal on Scientific Computing. The following functions are used to Construct reduced order model (ROM) for the numerical examples: Burger_ROM.m: Burger equation Redi_ROM.m: 2d-reaction-diffusion equation Redi_10d_ROM.m: 10-d reaction-diffusion equation NS_ROM.m: N-S equation The following functions are used to develop adaptive parametric reduced order model (pROM) for the numerical examples : Burger_Adaptive_ROM.m: Burger equation Redi_Adaptive_ROM.m: 2-d reaction-diffusion equation Redi_10d_Adaptive_ROM.m: 10-d reaction-diffusion equation NS_Adaptive_ROM_GPR.m: N-S equation The N-S equation is solved by the following code https://github.com/JamieMJohns/Navier-stokes-2D-numerical-solve-incompressible-flow-with-custom-scenarios-MATLAB-
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