Cuda-based technology for improving the efficiency of the aircraft motion

Authors

  • S. S. Tovkach National Aviation University

DOI:

https://doi.org/10.18372/1990-5548.50.11388

Keywords:

Graphics processing unit, multi-threaded, flight dynamics, adaptive motion control, wavelet analysis, turbulence flow, parallel computing

Abstract

Considered the method of parallel computing based on CUDA-architecture with detecting largeand small scale details of turbulence flow to adapt flight dynamics for motion control of the aircraft. Definedthe acceleration value of the parallel implementation relatively to series and the integraleffectiveness of parallel computing that allows to use the NVIDIA Tegra graphics processors toincrease the processing power of massively parallel calculations

Author Biography

S. S. Tovkach, National Aviation University

Candidate of Science (Engineering). Associate Professor. Automation and Energy Management Department

References

David A. Caughey, “Introduction to Aircraft Stability and Control.” Sibley School of Mechanical & Aerospace Engineering Cornell University. New York. 2011, 147 p.

Nairita Pal, Prasad Perlekar, Anupam Gupta, and Rahul Pandit “Binary-Fluid Turbulence: Signatures of Multifractal Droplet Dynamics and Dissipation Reduction” Indian Institute of Science. Bangalore, India. 2016, pp. 1–11.

T. Brandvik, and G. Pullan, “Acceleration of a 3D Euler solver using commodity graphics hardware,” 46th AIAA Aerospace Sciences Meeting and Exhibit, 2008.

E. Elsen, P. LeGresley, and E. Darve, “Large calculation of the flow over a hypersonic vehicle using a GPU,” Journal of Computational Physics, vol. 227, no. 24, 2008, pp. 10148–10161.

M. Farge, N.K.R. Kevlahan, V. Perrier, “Turbulence analysis, modelling and computing using wavelets” Laboratoire de Meteorologie Dynamique, Paris Cedex 5, 2009, pp. 1–66.

Parallel computing CUDA. [Online]. Available: http://www.nvidia.com.ua/object/cuda-parallel-computing-ru.html (in Russian).

Andrew Kerr, Gregory Diamos, Sudhakar Yalamanchili, “A Characterization and Analysis of PTX Kernels.” Georgia Institute of Technology, Atlanta, Georgia, 2013, pp. 1–10.

Downloads

Issue

Vol. 4 No. 50 (2016)

Section

AUTOMATIC CONTROL SYSTEMS

License

Authors who publish with this journal agree to the following terms:

Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.

Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).