2017
DOI: 10.29008/etc2017-143
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Numerical Characterization of Entropy Noise With a Density Based Solver

Abstract: In this work, dbnsTurbFoam, a new coupled density based solver, written in the framework of foam-extend, is considered. The solver is first assessed on two canonical compressible flow scenarios, namely the Sod's shock tube and the ONERA S8 transonic channel. Results are compared with analytical formulations and experiments, respectively. 2-D Unsteady Reynolds Averaged Navier-Stokes simulations and 3-D Large Eddy Simulations of the flow within the passages of a geometrically simplified High Pressure Turbine Noz… Show more

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Cited by 3 publications
(2 citation statements)
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“…The time integration is performed using an explicit 4-stage low-storage Runge-Kutta algorithm. The solver has been previously validated on two canonical compressible flow simulations by Chandramouli et al [12]. The LES simulations are initialized with the solution of the 2D Reynolds Averaged Navier-Stokes (RANS) equations using Favré averaging.…”
Section: Numerical Setupmentioning
confidence: 99%
“…The time integration is performed using an explicit 4-stage low-storage Runge-Kutta algorithm. The solver has been previously validated on two canonical compressible flow simulations by Chandramouli et al [12]. The LES simulations are initialized with the solution of the 2D Reynolds Averaged Navier-Stokes (RANS) equations using Favré averaging.…”
Section: Numerical Setupmentioning
confidence: 99%
“…It has been chosen because it is considered particularly suitable for simulating supersonic turbulent flows and results the only compressible solver exploiting the Harten-Lax-van Leer-Contact (HLLC) approximate Riemann solver, crucial to correctly capture shock waves without smearing them [4]. In [5] the fidelity of dbnsTurbFoam is assessed: taking as references the Sod's shock tube (analytical solution, [6]) and the Onera S8 Transonic Channel (experimental data, [7]) scenarios, it is shown how dbnsTurbFoam is suitable to study high speed compressible flows. Turbulence is taken into account by means of the k-ω SST model developed by Menter [8].…”
Section: Model Structurementioning
confidence: 99%