Implicit constraint handling for shape optimisation with POD-morphing

Authors

  • Balaji Raghavan Laboratoire Roberval, UMR 6253 UTC-CNRS, BP 20529, 60205 Compiegne, France
  • Manyu Xiao Laboratoire Roberval, UMR 6253 UTC-CNRS, BP 20529, 60205 Compiegne, France
  • Piotr Breitkopf Laboratoire Roberval, UMR 6253 UTC-CNRS, BP 20529, 60205 Compiegne, France
  • Pierre Villon Laboratoire Roberval, UMR 6253 UTC-CNRS, BP 20529, 60205 Compiegne, France

DOI:

https://doi.org/10.13052/17797179.2012.719316

Keywords:

model reduction, optimisation, diffuse approximation, POD

Abstract

In the former paper, we have introduced an original morphing approach based on Proper Orthogonal Decomposition (POD) of shapes, designed to replace parametrized CAD models in structural optimization. Here, we expand the method to interpolate exclusively between admissible instances of structural shapes, thus permitting a global understanding of the design domain and also reducing the size of the optimisation problem. The result is a bilevel reparametrization approach for structural geometries based on Diffuse Approximation in a properly chosen locally linearized space, and the geometric parameters are replaced with the smallest set of variables needed to represent a manifold of admissible shapes for a chosen precision. We demonstrate the approach in a typical shape optimisation problem.

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References

Allaire, G., DeGournay, F., Jouve, F., & Toader, A.M. (2005). Structural optimization using topological

and shape sensitivity via a level set method. Control & Cybernetics, 34, 59–80.

Berkooz, G., Holmes, P., & Lumley, J.L. (1993). The proper orthogonal decomposition in the analysis

of turbulent flows. Annual Review of Fluid Mechanics, 25(1), 539–575.

Bregler, C., & Omohundro, S.M. (1995). Nonlinear image interpolation using manifold learning. In G.

Tesauro, D.S. Touretzky, and T.K. Leen (Eds.), Advances in Neural Information Processing Systems

(pp. 973–980). Cambridge, MA: MIT Press.

Breitkopf, P. (1998). An algorithm for construction of iso-valued surfaces for finite elements. Engineering

with Computers, 14(2), 146–149.

Breitkopf, P., Naceur, H., Rassineux, A., & Villon, P. (2005). Moving least squares response surface

approximation: Formulation and metal forming applications. Computers and Structures, 83(17–18),

–1428.

Bui-Thanh, T., Willcox, K., Ghattas, O., & van Bloemen, W.B. (2007). Goal-oriented, model-constrained

optimization for reduction of large-scale systems. Journal of Computational Physics, 224(2),

–896.

Canny, J. (1986). A computational approach to edge detection. IEEE Transactions on Pattern Analysis

and Machine Intelligence, 8(6), 679–698.

Carlberg, K., & Farhat, C. (2010). A low-cost, goal-oriented compact proper orthogonal decomposition

basis for model reduction of static systems. International Journal for Numerical Methods in Engineering,

(3), 381–402.

Carlberg K., & Farhat C. (2008). A compact proper orthogonal decomposition basis for optimizationoriented

reduced-order models. 12th AIAA/ISSMO multidisciplinary analysis and optimization

conference, Victoria, Canada, 10–12, 2008.

Chappuis, C., Rassineux, A., Breitkopf, P., & Villon, P. (2004). Improving surface remeshing by feature

recognition. Engineering with Computers, 20(3), 202–209.

Chatterjee, A. (2005). An introduction to the proper orthogonal decomposition. Current Science, Special

Section: Computational Science, 78(7), 808–817.

Coelho, R.F., Breitkopf, P., & Knopf-Lenoir, C. (2009). Bi-level model reduction for coupled problems.

Structural and Multidisciplinary Optimization, 39(4), 401–418.

Cordier, L., El Majd, B.A., & Favier, J. (2010). Calibration of POD reduced order models using Tikhonov

regularization. International Journal for Numerical Methods in Fluids, 63(2), 269–296.

Couplet, M., Basdevant, C., & Sagaut, P. (2005). Calibrated reduced-order POD-Galerkin system for

fluid flow modeling. Journal of Computational Physics, 207(1), 192–220.

Dulong, J.-L., Druesne, F., & Villon, P. (2007). A model reduction approach for real-time part deformation

with nonlinear mechanical behavior. International Journal on Interactive Design and Manufacturing,

(4), 229–238.

Kaufman, A., Cohen, D., & Yagel, R. (1993). Volume graphics. IEEE, Computer, 26(7), 51–64.

Larsson, F., Diez, P., & Huerta, A. (2010). A flux-free a posteriori error estimator for the incompressible

Stokes problem using a mixed FE formulation. AIAA Journal, 199(37–40), 2383–2402.

Launder, B.E., & Spalding, D.B. (1974). The numerical computation of turbulent flows. Computer Methods

in Applied Mechanics and Engineering, 3(2), 269–289.

Nayroles, B., Touzot, G., & Villon, P. (1992). Generalizing the finite element method: Diffuse approximation

and diffuse elements. Computational Mechanics, 10(5), 307–318.

Raghavan, B., & Breitkopf, P. (2012). Asynchronous evolutionary shape optimization based on highquality

surrogates: application to an air-conditioning duct. Engineering with Computers.

Raghavan, B., Breitkopf, P., & Villon, P. (2011). POD-morphing: an a posteriori reparametrization

approach for shape optimization. European Journal of Computational Mechanics, 19(5–7), 673–699.

Ravindran, S.S. (2000). A reduced-order approach for optimal control of fluids using proper orthogonal

decomposition. International Journal for Numerical Methods in Fluids, 34(5), 425–448.

Sofia, A.Y.N., Meguid, S.A., & Tan, K.T. (2010). Shape morphing of aircraft wing: Status and challenges.

Materials & Design, 31(3), 1284–1292.

Willcox, K., & Peraire, J. (2002). Balanced model reduction via the proper orthogonal decomposition.

AIAA Journal, 40(11), 2323–2330.

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Published

2012-06-06

How to Cite

Raghavan, B. ., Xiao, M. ., Breitkopf, P. ., & Villon, P. . (2012). Implicit constraint handling for shape optimisation with POD-morphing. European Journal of Computational Mechanics, 21(3-6), 325–336. https://doi.org/10.13052/17797179.2012.719316

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