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Rotor Loads Prediction Using Helios: A Multisolver Framework for Rotorcraft Aeromechanics Analysis

Published Online:https://doi.org/10.2514/1.C031897

This paper documents the prediction of UH-60A Black Hawk aerodynamic loading using the multisolver Computational Fluid Dynamics/Computational Structural Dynamics analysis framework for rotorcraft Helios for a range of critical steady forward flight conditions. Comparisons with available flight test data are provided for all of the predictions. The Helios framework combines multiple solvers and multiple grid paradigms (unstructured and adaptive Cartesian) such that the advantages of each paradigm is preserved. Further, the software is highly automated for execution and designed in a modular fashion to minimize the burden on both the users and developers. The technical approach presented herein provides details of all of the participant modules and the interfaces used for their integration into the software framework. The results composed of sectional aerodynamic loading and wake visualizations are presented. Solution-based adapative mesh refinement, a salient feature of the Helios framework, is explored for all flight conditions and comparisons are provided for both aerodynamic loading and vortex wake structure with and without adaptive mesh refinement.

References

  • [1] Wissink A., Sitaraman J., Mavriplis D., Pulliam T. and Sankaran V., “A Python-Based Infrastructure for Overset CFD with Adaptive Cartesian Grids,” AIAA Paper  2008-0927, 2008. LinkGoogle Scholar

  • [2] Sitaraman J., Katz A., Jayaraman B., Wissink A. and Sankaran V., “Evaluation of a Multisolver Paradigm for CFD Using Overset Unstructured and Structured Adaptive Cartesian Grids,” AIAA Paper  2008-0660, 2008. Google Scholar

  • [3] Sitaraman J., Floros M., Wissink A. and Potsdam M., “Parallel Domain Connectivity Algorithm For Unsteady Flow Computations Using Overlapping And Adaptive Grids,” Journal of Computational Physics, Vol. 229, No. 12, June 2010, pp. 4703–4723. doi:https://doi.org/10.1016/j.jcp.2010.03.008 JCTPAH 0021-9991 CrossrefGoogle Scholar

  • [4] Choi S. and Datta A., “CFD Prediction of Main Rotor Vibratory Loads Using Time-Spectral Method,” AIAA Paper  2008-7325, 2008. Google Scholar

  • [5] Sitaraman J. and Baeder J. D., “Evaluation of the Wake Prediction Methodologies Used in CFD Based Rotor Airload Computations,” AIAA Paper  2006-3472, 2006. LinkGoogle Scholar

  • [6] Potsdam M., Yeo H. and Johnson W., “Rotor Airloads Prediction Using Loose Aerodynamic/Structural Dynamic Coupling,” 60th Forum of the American Helicopter Society, AHS International, Alexandria, Virginia, May 2004. Google Scholar

  • [7] Biedron R. and Lee-Rausch E., “Rotor Airloads Prediction Using Unstructured Meshes and Loose CFD/CSD Coupling,” AIAA Paper  2008-7341, 2008. LinkGoogle Scholar

  • [8] Yang Z. and Mavriplis D., “Higher-Order Time Integration Schemes for Aeroelastic Applications on Unstructured Meshes,” AIAA Paper  2006-0441, 2006. LinkGoogle Scholar

  • [9] Hornung R. D., Wissink A. M. and Kohn S. R., “Managing Complex Data and Geometry in Parallel Structured Amr Applications,” Engineers and Computers, Vol. 22, No. 3, 2006, pp. 181–195. doi:https://doi.org/10.1007/s00366-006-0038-6 CrossrefGoogle Scholar

  • [10] Saberi H., Khoshlahjeh M., Ormiston R. and Rutkowski M. J., “Overview of RCAS and Application to Advanced Rotorcraft Problems,” 4th AHS Decennial Specialist’s Conference on Aeromechanics, AHS International, Alexandria, Virginia, 21–23 Jan. 2004. Google Scholar

  • [11] Alonso J. J., LeGresley P. and Van Der Weide E., “pyMDO: A Framework for High-Fidelity Multi-Disciplinary Optimization,” AIAA Paper  2004-4480, 2004. Google Scholar

  • [12] Miller P., “pyMPI—An Introduction to Parallel Python Using MPI,” UCRL WEB-150152, http://pympi.sourceforge.net [retrieved Sept. 2002]. Google Scholar

  • [13] Kaiser H. T., “Using a Generalized MPI Interface for Python,” SciPY 2005 Conference: Python for Scientific Computing, Enthought Inc., Austin, Texas, Sept. 2005. Google Scholar

  • [14] Berger M. J. and Colella P., “Local Adaptive Mesh Refinement for Shock Hydrodynamics,” Journal of Computational Physics, Vol. 82, No. 1, 1989, pp. 65–84.doi:https://doi.org/10.1016/0021-9991(89)90035-1 JCTPAH 0021-9991 CrossrefGoogle Scholar

  • [15] Mavriplis D. and Levy W. D., “Transonic Drag Prediction Using an Unstructured Multigrid Solver,” Journal of Aircraft, Vol. 42, No. 4, 2005, pp. 887–893. doi:https://doi.org/10.2514/1.8233 JAIRAM 0021-8669 LinkGoogle Scholar

  • [16] Vassberg J., Edward N. T., Mani M., Broderson O. P., Eisfeld B., Wahls R. A., Morrison J. H., Zickuhr T., Laflin K. R. and Mavriplis D. J., “Summary of Third AIAA CFD Drag Prediction Workshop,” AIAA Paper  2007-0260, June 2006. Google Scholar

  • [17] Pulliam T. H., “Euler and Thin-Layer Navier–Stokes Codes: ARC2D, and ARC3D,” Computational Fluid Dynamics Users Workshop, Univ. of Tennessee Space Inst., Tullahoma, TN, 12–16 March 1984. Google Scholar

  • [18] Lee Y. and Baeder J. D., “Implicit Hole Cutting—A New Approach to Overset Grid Connectivity,” AIAA Paper  2003-4128, 2003. LinkGoogle Scholar

  • [19] Meakin R. L., Wissink A. M., Chan W. C., Pandya S. A. and Sitaraman J., “On Strand Grids for Complex Flows,” AIAA Paper  2007-3834, 2007. LinkGoogle Scholar

  • [20] Tung C., Caradonna F. X. and Johnson W. R., “The Prediction of Transonic Flows on an Advancing Rotor,” 40th Forum of the American Helicopter Society, AHS International, Alexandria, Virginia, May 1984. Google Scholar

  • [21] Kufeld R. M., Balough D. L., Cross J. L., Studebaker K. F., Jennison C. D. and Bousman W. G., “Flight Testing of the UH-60A Airloads Aircraft,” 50th Forum of the American Helicopter Society, AHS International, Alexandria, Virginia, May 1994. Google Scholar

  • [22] Bousman W. G. and Kufeld R. M., “UH-60A Airloads Catalog,” NASA/AFDD TM-2005-212827/TR-05-003, 2005. Google Scholar

  • [23] Kamkar S., Wissink A. M., Jameson A. and Sankaran V., “Feature-Driven Cartesian Adaptive Mesh Refinement in the Helios Code,” AIAA Paper  2010-0171, 2010. Google Scholar

  • [24] Sankaran V., Potsdam M., Wissink A., Datta A., Jayaraman B. and Sitaraman J., “Rotor Loads Prediction in Level and Manevering Flight Using Unstructured Adaptive Cartesian CFD,” American Helicopter Society, 67th Annual Forum, AHS International, Alexandria, Virginia, May 2011. Google Scholar

  • [25] Bierdon R. and Lee-Rauch E. M., “An Examination of Unsteady Airloads on a UH-60A Rotor: Computation Versus Measurement,” American Helicopter Society, 68th Annual Forum, AHS International, Alexandria, Virginia, May 2012. Google Scholar

  • [26] Buning P. G. and Pulliam T. H., “Cartesian Off-Body Adaptation For Viscous Time-Accurate Flow Simulations,” AIAA Paper  2011-3693, 2011. LinkGoogle Scholar