Abstract
Optimizations based on adjoint sensitivity data are presented in this Chapter. RBF are adopted to set up an advanced filtering tool suitable for removing the noise usually observed when shape sensitivities data are computed using CFD so as to enable the adjoint sculpting method where surfaces are updated according to the information provided by the flow solution to get the desired performances (as drag reduction or pressure loss control). Advanced mesh morphing is used to propagate, once properly filtered if needed, the shape data known at surfaces into the full volume mesh required for the calculation. The concept is demonstrated for FEM as well showing how a bracket and a T beam can be updated to control a target displacement. The adjoint preview approach, which consists of the computation of derivatives with respect of shape variations known in advance is then detailed. A collection of fluid shape optimizations, taking into account both internal and external flows, is provided at the end of the Chapter.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Ahmed SR, Ramm G (1984) Some salient features of the time-averaged ground vehicle wake. SAE Technical Paper 840300
Arora JS (2016) Introduction to optimum design. Academic Press. ISBN: 978-0-12-800806-5. https://www.elsevier.com/books/introduction-to-optimum-design/arora/978-0-12-800806-5
Ashlock D (2005) Evolutionary computation for modeling and optimization. Springer-Verlag New York. ISBN: 978-0-387-31909-4. http://www.springer.com/gp/book/9780387221960
Biancolini ME (2014) How to boost fluent adjoint using RBF morph. International Conference on Automotive and Electronics Technologies 2014. Proceedings of a meeting held 9-10 October 2014, Tokyo, Japan. Automotive Simulation World Congress 2014 and ANSYS Electronics Simulation EXPO 2014. ISBN: 9781510841031
Biancolini ME, Costa E, Cella U, Groth C, Veble G, Andrejašič M (2016) Glider fuselage-wing junction optimization using CFD and RBF mesh morphing. Aircr Eng Aerosp Technol 88(6):740–752. https://doi.org/10.1108/AEAT-12-2014-0211
Costa E, Biancolini ME, Groth C, Cella U, Veble G, Andrejasic M (2014a) RBF-based aerodynamic optimization of an industrial glider. In: 30th international CAE conference, Pacengo del Garda, Italy
Costa E, Porziani S, Biancolini ME, Groth C, Cella U, Veble G, Andrejasic M (2014b) Ottimizzazione aerodinamica di un aliante industriale mediante l’utilizzo di RBF, A&C. Analisi E Calcolo 64:31–48
Groth C (2017) Adjoint-based shape optimization workflows using RBF. Ph.D. thesis in industrial engineering, Cycle XXIX, University of Rome “Tor Vergata”
Groth C, Chiappa A, Biancolini ME (2018) Shape optimization using structural adjoint and RBF mesh morphing. Procedia Structural Integrity 8:379–389
Haftka RT, Gürdal Z (1992) Elements of structural optimization, ser. Solid mechanics and its applications. Dordrecht: Springer Netherlands, vol. 11, no. March
Heft AI, Indinger T, Adams NA (2012) Introduction of a new realistic generic car model for aerodynamic investigations. SAE International, warrendale
Kapsoulis DH, Asouti VG, Papoutsis-Kiachagias E, Giannakoglou K, Porziani S, Costa E, Groth C, Cella U, Biancolini ME, Andrejasic M, Erzen D, Bernaschi M, Sabellico A, Urso G (2016) Aircraft & car shape optimization on the RBF4AERO platform. In: 11th HSTAM international congress on mechanics, Athens
Mohammadi B, Pironneau O (2009) Applied shape optimization for fluids, vol 53, no 9. Oxford University Press, Oxford, p 9
Montgomery DC (2012) Design and analysis of experiments, vol 2, John Wiley & Sons, Inc. ISBN: 978-1-118-14692-7
Othmer C, Papoutsis-Kiachagias EM, Haliskos K (2011) CFD optimization via sensitivity-based shape morphing. In: Proceedings of 4th ANSA & µETA international conference
Papoutsis-Kiachagias EM, Porziani S, Groth C, Biancolini ME, Costa E, Giannakoglou KC (2015) Aerodynamic optimization of car shapes using the continuous adjoint method and an RBF morpher. EUROGEN 2015, 11th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems, Glasgow, UK, September 14-16, 2015.
Papoutsis-Kiachagias EM, Giannakoglou KC, Porziani S, Groth C, Biancolini ME, Costa E, Andrejasic (2018) Combining an OpenFOAM-based adjoint solver with RBF morphing for shape optimization problems on the RBF4AERO platform. In: OpenFOAM® selected papers of the 11th workshop, Springer International Publishing, ISBN: 978-3-319-60846-4 (in press)
Petrone G, Hill C, Biancolini ME (2014) Track by track robust optimization of a F1 front wing using adjoint solutions and radial basis functions. In: 32nd AIAA Applied Aerodynamics Conference, AIAA AVIATION Forum (AIAA 2014-3174). https://doi.org/10.2514/6.2014-3174
Vanderplaats GN (2005) Numerical optimization techniques for engineering design. Vanderplaats Research & Development, Incorporated. ISBN: 9780944956021
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG, part of Springer Nature
About this chapter
Cite this chapter
Biancolini, M.E. (2017). Adjoint Sensitivities and RBF Mesh Morphing. In: Fast Radial Basis Functions for Engineering Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-75011-8_8
Download citation
DOI: https://doi.org/10.1007/978-3-319-75011-8_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-75009-5
Online ISBN: 978-3-319-75011-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)