Hi all,
I’m a PhD student comparing PyFR to standard CFD tools in a hope to transferring high-order technology to industrial applications.
As a start, I’ve recently tried to run 3D Taylor-Green vortex case (Re=1600, M=0.1 Ref:[1]) using compressible PyFR solver (PyFR 1.7.5). I’m running the case using coarser grids (uniform hexahedra, 16^3 and 32^3 using polynomial order 4) with respect to what would be required by a DNS. I observe a matching kinetic-energy (E) vs. time curve to the reference DNS. However, the time derivative of E (-dissipation rate) is wiggly, the magnitude of wiggles being significant for 16^3 P4 case. Figures are attached for clarity. Has anyone seen similar things before?
Things I’ve tried to ensure the wiggles are not originating from how often I save the data but the simulation itself:
1. Saving of two very close instances in time (5 time steps apart) and taking time derivative based on these.
2. Reducing the time step by 1/8th of the one shown in the config file attached.
The above treatment did not change the result.
I also tried over integration in element volume and interfaces using 2x integration points, but in vain. On the other hand the exponential filter helped a bit, although a lot of tweaking in strength and cut-off number was required. Any comments on their usage?
Thank you for your time.Attachments: config file (also showing over integration approach), mesh file, E vs. time and -dE/dt vs. time curves obtained. The attachments correspond to 16^3 P4 simulation.
[1] B. C. Vermeire, F. D. Witherden, and P. E. Vincent, “On the utility of GPU accelerated high-order methods for unsteady flow simulations: A comparison with industry-standard tools,” J. Comput. Phys., vol. 334, 2017.--
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