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Advanced Modeling and Simulation in Engineering Sciences
Fig. 15 | Advanced Modeling and Simulation in Engineering Sciences

Fig. 15

From: POD-Galerkin reduced order models and physics-informed neural networks for solving inverse problems for the Navier–Stokes equations

Fig. 15

The results of the PINNs predictions for all reduced variables, the reduced order spaces are constructed with \(N_u=N_p=N_S=60\). The plots compare the reduced coefficients with the \(L^2\) projection coefficients. The red-dashed lines refers to the \(L^2\) projection coefficients, while the blue-dots correspond to the reduced coefficients obtained by the PINNs. (a) The first reduced coefficients for velocity, pressure, turbulent and convective terms compared to the ones obtained by the \(L^2\) projection. (b) The second reduced coefficients for velocity, pressure, turbulent and convective terms compared to the ones obtained by the \(L^2\) projection

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