Using Big Analytics Tools in Performance of Gas Dynamics and Acoustics Tasks

The paper centers around big data processing and analytics, as well as big data compression when doing numerical simulations of hydrodynamic and acoustic processes in large industrial applications. One of the typical cases is the simulation of supersonic turbulent jets and high-intensity acoustic loads in rocket lift-off process. We give some estimates of the memory amount for correct simulations of gas dynamic and acoustic processes in this case. Moreover, we describe one of the most common technologies of big data compression and analytics --- Proper Orthogonal Decomposition. This technology was implemented using the Apache Spark framework for large-scale data processing. The necessary memory for the storing of the results of simulation of acoustic pressure propagation can be reduced by 30 times for 1D case and 160 times for 2D case

The work was supported by the Ministry of Education and Science of Russia (identifier RFMEFI60714X0090, agreement no. 14.607.21.0090)

References

[1] Bieder U., Fauchet G., Calvin C. High performance Large Eddy Simulation of turbulent flows around PWR mixing grids. The 16th IEEE Int. Conf. on High Performance Computing and Communications. Paris, 2014. 5 p.

[2] Quarteroni A., Rozza G. Reduced order methods for modeling and computational reduction. Springer, 2014. 334 p.

[3] Holmes P., Lumley J.L., Berkooz G., Rowley C.W. Turbulence, coherent structures, dynamical systems and symmetry. Cambridge University Press, 2012. 402 p.

[4] Kerschen G., Golinval J.-C., Vakakis A.F., Bergman L.A. The method of proper orthogonal decomposition for dynamical characterization and order reduction of mechanical systems: an overview. Nonlinear Dynamics, 2005, vol. 41, iss. 1-3, pp. 147–169. DOI: 10.1007/s11071-005-2803-2

[5] Schmid P.J. Dynamic mode decomposition of numerical and experimental data. J. Fluid Mech., 2010, vol. 656, pp. 5–28.

[6] Tosh A., Liever P., Owens F., Liu Y.A. High-fidelity CFD/BEM methodology for launch pad acoustic environment prediction. 18th AIAA/CEAS Aeroacoustics Conf. 2012. Colorado Springs, Paper AIAA 2012−2107.

[7] Kudimov N.F., Safronov A.V., Tretyakova O.N. Prikladnye zadachi gazodinamiki i teploobmena v energeticheskikh ustanovkakh raketnoy tekhniki [Applied problems of gas dynamics and heat exchange in energetic plants of rocket technique]. Moscow, MAI Publ., 2014. 168 p.

[8] Seiner J.M., Norum T.D. Experiments of shock associated noise on supersonic jets. AIAA 12th Fluid and Plasma Dynamics Conf. Williamsburg, Virginia, 1979, pp. 79−152. DOI: 10.2514/6.1979-1526 Available at: https://arc.aiaa.org/doi/10.2514/6.1979-1526

[9] Kraposhin M., Bovtrikova A., Strijhak S. Adaptation of Kurganov — Tadmor numerical scheme for applying in combination with the PISO method in numerical simulation of flows in a wide range of Mach numbers. Procedia Computer Science, 2015, vol. 66, pp. 43–52. DOI: 10.1016/j.procs.2015.11.007

[10] Menter F.R., Kuntz M., Langtry R. Ten years of industrial experience with the SST turbulence model. Turbulence, Heat and Mass Transfer, 2003, no. 4, pp. 625–632.

[11] Daubechies I. Ten lectures on wavelets. SIAM, 1992. 377 p.

[12] Kalugin M.D., Strijhak S.V. Implementation of POD and DMD methods in Apache Spark framework for simulation of unsteady turbulent flow in the model combustor. Proc. 7th European Congress on Computational Methods in Applied Sciences and Engineering. Crete, Greece, 2016, pp. 857–864.