Fast Multipole Method for Nonlinear, Unsteady Aerodynamic Simulations

The authors study the use of the Fast Multipole Method (FMM) for accelerating an aeroelastic simulator, comprised of the Unsteady Vortex Lattice Method (UVLM) for fluid dynamics simulations, and the Finite Element (FE) method for structural dynamics simulations. The FMM is integrated with UVLM based simulator. This accelerated UVLM model will in turn be used to accelerate the aeroelastic simulator. Considering the joined-wing SensorCraft, progress made thus far is reported in this work. The FMM algorithm is applied to a UVLM aerodynamic model for a large aspect ratio, planar, rectangular lifting surface and the results obtained on the computational cost reduction are presented. The current approach has broad applicability for the study of aerodynamic and aeroelastic responses of aircraft systems.

[1]  R. K. Nangia,et al.  Unconventional High Aspect Ratio Joined-Wing Aircraft with Aft- and Forward-Swept Wing-Tips , 2003 .

[2]  Ramani Duraiswami,et al.  GPU accelerated fast multipole methods for vortex particle simulation , 2013 .

[3]  Leslie Greengard,et al.  A fast algorithm for particle simulations , 1987 .

[4]  Ramani Duraiswami,et al.  Fast multipole methods on graphics processors , 2008, J. Comput. Phys..

[5]  Karen Willcox,et al.  Multifidelity DDDAS Methods with Application to a Self-aware Aerospace Vehicle , 2014, ICCS.

[6]  Jack J. Dongarra,et al.  Guest Editors Introduction to the top 10 algorithms , 2000, Comput. Sci. Eng..

[7]  Charbel Farhat,et al.  Recent Advances in Reduced-Order Modeling and Application to Nonlinear Computational Aeroelasticity , 2008 .

[8]  William Wolf,et al.  Fast multipole method applied to Lagrangian simulations of vortical flows , 2017, Commun. Nonlinear Sci. Numer. Simul..

[9]  Sergio Preidikman,et al.  Numerical Simulations of Interactions Among Aerodynamics, Structural Dynamics, and Control Systems , 1998 .

[10]  J. CARRIERt,et al.  A FAST ADAPTIVE MULTIPOLE ALGORITHM FOR PARTICLE SIMULATIONS * , 2022 .

[11]  R. Duraiswami,et al.  Fast Multipole Methods for the Helmholtz Equation in Three Dimensions , 2005 .

[12]  Ramani Duraiswami,et al.  Efficient FMM accelerated vortex methods in three dimensions via the Lamb-Helmholtz decomposition , 2012, J. Comput. Phys..

[13]  Bruno A. Roccia,et al.  Computational Dynamics of Flapping Wings in Hover Flight: A Co-Simulation Strategy , 2017 .

[14]  David Broman,et al.  Co-simulation: State of the art , 2017, ArXiv.

[15]  Balakumar Balachandran,et al.  Implementation and Benchmarking of Two-Dimensional Vortex Interactions on a Graphics Processing Unit , 2014, J. Aerosp. Inf. Syst..

[16]  Balakumar Balachandran,et al.  GPGPU implementation and benchmarking of the unsteady vortex lattice method , 2013 .

[17]  Tamás Kalmár-Nagy,et al.  Can complex systems really be simulated? , 2014, Appl. Math. Comput..

[18]  L. Greengard,et al.  Regular Article: A Fast Adaptive Multipole Algorithm in Three Dimensions , 1999 .

[19]  L. Greengard,et al.  A new version of the Fast Multipole Method for the Laplace equation in three dimensions , 1997, Acta Numerica.

[20]  Balakumar Balachandran,et al.  GPU Based Simulation of Physical Systems Characterized by Mobile Discrete Interactions , 2013 .

[21]  Frederica Darema,et al.  Dynamic Data Driven Applications Systems: A New Paradigm for Application Simulations and Measurements , 2004, International Conference on Computational Science.

[22]  J. Katz,et al.  Low-Speed Aerodynamics , 1991 .

[23]  Balakumar Balachandran,et al.  Motion visualization and estimation for flapping wing systems , 2017 .

[24]  Carl P. Tilmann Emerging Aerodynamic Technologies for High- Altitude Long-Endurance SensorCraft UAVs , 2002 .

[25]  Shinnosuke Obi,et al.  Fast multipole methods on a cluster of GPUs for the meshless simulation of turbulence , 2009, Comput. Phys. Commun..