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Advanced Modeling and Simulation in Engineering Sciences
Fig. 18 | Advanced Modeling and Simulation in Engineering Sciences

Fig. 18

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

Fig. 18

The \(L^2\) relative errors for the approximation of the drag and lift coefficients in the time span [100, 150] as function of the number of modes. A base-10 logarithmic scale on the y-axis is used in both plots, the error values are already in percentages. (a) The \(L^2\) relative error in approximating the drag coefficient \(C_d\) over the time span [100,150] as function of the number of modes. (b) The \(L^2\) relative error in approximating the lift coefficient \(C_l\) over the time span [100,150] as function of the number of modes

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