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Gaussian Process for Aerodynamic Pressures Prediction in Fast Fluid Structure Interaction Simulations

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Advances in Structural and Multidisciplinary Optimization (WCSMO 2017)

Abstract

The interaction between inertial, elastic and aerodynamic forces for structures subjected to a fluid flow may cause unstable coupled vibrations that can endanger the structure itself. Predicting these interactions is a time consuming but crucial task in an aircraft design process. In order to reduce the computational time surrogate reduced order models can be used in both structural and aerodynamic models. More over it is possible to avoid launching CFD computations at every time step. A database of aerodynamic pressure distribution on the structural component can be created conveniently sampling the space of the structural model DoF. Starting from the knowledge of the pre-computed data-set a Gaussian Process can be applied to predict the pressure distribution on an unexplored point of the space of DoF. The knowledge of the standard deviation can be used to give indications on where to launch further CFD computations to enrich the database. This technique will be first applied to a database of pressures obtained using the software Xfoil®, later it will be applied to CFD simulations of type RANS launched with elsA® on one Flap track Fairing of an Airbus aircraft.

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References

  1. Sandboge, R.: Fluid-structure interaction with OpenFSITM and MD NastranTM structural solver. Ann. Arbor 1001, 9 (2010)

    Google Scholar 

  2. Montgomery, D.C., Peck, E.A., Vining, G.G.: Introduction to Linear Regression Analysis. Wiley, Hoboken (2015)

    MATH  Google Scholar 

  3. Drela, M.: XFOIL: An Analysis and Design System for Low Reynolds Number Airfoils. Low Reynolds Number Aerodynamics. Springer, Heidelberg (1989)

    Google Scholar 

  4. Cambier, L., Veuillot, J.: Status of the elsA CFD software for flow simulation and multidisciplinary applications. AIAA Paper 664, 2008 (2008)

    Google Scholar 

  5. Sadek, R.A.: SVD based image processing applications: state of the art, contributions and research challenges. arXiv preprint arXiv:1211.7102 (2012)

  6. Friswell, M., Mottershead, J.E.: Finite Element Model Updating in Structural Dynamics, vol. 38. Springer Netherlands (1995)

    Google Scholar 

  7. Schmid, P.J.: Dynamic mode decomposition of numerical and experimental data. J. Fluid Mech. 656, 5–28 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  8. Rasmussen, C.E., Williams, C.K.I.: Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning). The MIT Press, Cambridge (2005)

    Google Scholar 

  9. Rasmussen, C.E., Ghahramani, Z.: Infinite mixtures of Gaussian process experts. Adv. Neural Inf. Process. Syst. 2, 881–888 (2002)

    Google Scholar 

  10. Chen, T., Ren, J.: Bagging for Gaussian process regression. Neurocomputing 72(7), 1605–1610 (2009)

    Article  Google Scholar 

  11. Deisenroth, M.P., Ng, J.W.: Distributed Gaussian processes. arXiv preprint arXiv:1502.02843 (2015)

  12. Cao, Y., Fleet, D.J.: Generalized product of experts for automatic and principled fusion of gaussian process predictions. CoRR, Vol. abs/1410.7827 (2014)

    Google Scholar 

  13. MathWorks, I.: MATLAB: the language of technical computing. In: Desktop Tools and Development Environment, version 7, vol. 9. MathWorks (2005)

    Google Scholar 

  14. Vassberg, J.C., DeHaan, M.A., Rivers, S.M., Wahls, R.A.: Development of a common research model for applied CFD validation studies (2008)

    Google Scholar 

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Correspondence to Ankit Chiplunkar .

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Chiplunkar, A., Bosco, E., Morlier, J. (2018). Gaussian Process for Aerodynamic Pressures Prediction in Fast Fluid Structure Interaction Simulations. In: Schumacher, A., Vietor, T., Fiebig, S., Bletzinger, KU., Maute, K. (eds) Advances in Structural and Multidisciplinary Optimization. WCSMO 2017. Springer, Cham. https://doi.org/10.1007/978-3-319-67988-4_15

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  • DOI: https://doi.org/10.1007/978-3-319-67988-4_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67987-7

  • Online ISBN: 978-3-319-67988-4

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