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Pre-shape calculus and its application to mesh quality optimization

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Deformations of the computational mesh, arising from optimization routines, usually lead to decrease of mesh quality or even destruction of the mesh. We propose a theoretical framework using pre-shapes to generalize the classical shape optimization and calculus. We define pre-shape derivatives and derive corresponding structure and calculus theorems. In particular, tangential directions are featured in pre-shape derivatives, in contrast to classical shape derivatives, featuring only normal directions. Techniques from classical shape optimization and calculus are shown to carry over to this framework. An optimization problem class for mesh quality is introduced, which is solvable with the use of pre-shape derivatives. This class allows for simultaneous optimization of the classical shape objectives and mesh quality without deteriorating the classical shape optimization solution. The new techniques are implemented and numerically tested for 2D and 3D.
Rocznik
Strony
263--301
Opis fizyczny
Bibliogr. 51 poz., rys.
Twórcy
autor
  • Trier University, Department of Mathematics, 54286 Trier, Germany
  • Trier University, Department of Mathematics, 54286 Trier, Germany
Bibliografia
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  • Bauer, M., Bruveris, M. and Michor, P.W. (2014) Overview of the Geometries of Shape Spaces and Diffeomorphism Groups. Journal of Mathematical Imaging and Vision, 50(1-2): 60–97.
  • Berggren, M. (2010) A Unified Discrete–Continuous Sensitivity Analysis Method for Shape Optimization. In: Applied and Numerical Partial Differential Equations, Computational Methods in Applied Sciences, 15, 25–39. Springer.
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  • Bochev, P., Liao, G. and dela Pena, G.(1996) Analysis and Computation of Adaptive Moving Grids by Deformation. Numerical Methods for Partial Differential Equations: An International Journal, 12(4): 489–506.
  • Cai, X., Jiang, B. and Liao, G. (2004) Adaptive Grid Generation Based on the Least-Squares Finite-Element Method. Computers & Mathematics with Applications, 48(7-8): 1077–1085.
  • Cao, W., Huang, W. and Russell, R.D. (1999) A Study of Monitor Functions for Two-Dimensional Adaptive Mesh Generation. SIAM Journal on Scientific Computing, 20(6): 1978–1994.
  • Cao, W., Huang, W. and Russell, R.D. (2002) A Moving Mesh Method Based on the Geometric Conservation Law. SIAM Journal on Scientific Computing, 24(1): 118–142.
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  • Delfour, M.C. and Zolésio, J.-P. (2001) Shapes and Geometries: Metrics, Analysis, Differential Calculus, and Optimization, Advances in Design and Control, 22. SIAM, 2nd edition.
  • Dziuk, G. (1990) An Algorithm for Evolutionary Surfaces. Numerische Mathematik, 58(1): 603–611.
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  • Etling, T., Herzog, R., Loayza, E. and Wachsmuth, G. (2018) First and second order shape optimization based on restricted mesh deformations. arXiv preprint arXiv:1810.10313.
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  • Frey, P.J. and Borouchaki, H. (1999) Surface Mesh Quality Evaluation. International Journal for Numerical Methods in Engineering, 45(1): 101–118.
  • Geuzaine, C. and Remacle, J.-F. (2007) Gmsh: A Three-Dimensional Finite Element Mesh Generator with Built-In Pre-and Post-Processing Facilities. In Proceedings of the Second Workshop on Grid Generation for Numerical Computations, Tetrahedron II.
  • Grajewski, M., Köster, M. and Turek, S. (2009) Mathematical and Numerical Analysis of a Robust and Efficient Grid Deformation Method in the Finite Element Context. SIAM Journal on Scientific Computing, 31(2): 1539–1557.
  • Grajewski, M., Köster, M. and Turek, S. (2010) Numerical Analysis and Implementational Aspects of a New Multilevel Grid Deformation Method. Applied Numerical Mathematics, 60(8): 767–781.
  • Haslinger, J. and Mäkinen, R.A.E. (2003) Introduction to Shape Optimization: Theory, Approximation, and Computation. Advances in Design and Control, 7. SIAM.
  • Henrot, A. and Pierre, M. (2018) Shape Variation and Optimization. Tracts in Mathematics, 7. European Mathematical Society.
  • Johnston, B.P., Sullivan Jr, J.M. and Kwasnik, A. (1991) Automatic Conversion of Triangular Finite Element Meshes to Quadrilateral Elements. International Journal for Numerical Methods in Engineering, 31(1): 67–84.
  • Kendall, D.G., Barden, D., Carne, T.K. and Le, H. (2009) Shape and Shape Theory. Wiley Series in Probability and Statistics, 500. John Wiley & Sons.
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  • Laurain, A. and Walker, S. (2020) Optimal Control of Volume-Preserving Mean Curvature Flow. Journal of Computational Physics, 483: 110373, 2021.
  • Lee, J.M. (2009) Manifolds and Differential Geometry. Graduate Studies in Mathematics, 107. American Mathematical Society.
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  • Liao, G. and Anderson, D. (1992) A New Approach to Grid Generation. Applicable Analysis, 44(3-4): 285–298.
  • Liu, F., Ji, S. and Liao, G. (1998) An Adaptive Grid Method and its Application to Steady Euler Flow Calculations. SIAM Journal on Scientific Computing, 20(3): 811–825.
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  • Luft, D. and Schulz, V. (2021) Simultaneous Shape and Mesh Quality Optimization using Pre-Shape Calculus. Control and Cybernetics, 50(4).
  • Michor, P.W. and Mumford, D. (2007) Overview of the Geometries of Shape Spaces and Diffeomorphism Groups. Applied and Computational Harmonic Analysis, 23(1): 74–113.
  • Moser, J. (1965) On the Volume Elements on a Manifold. Transactions of the American Mathematical Society, 120(2): 286–294.
  • Onyshkevych, S. and Siebenborn, M. (2020) Mesh Quality Preserving Shape Optimization using Nonlinear Extension Operators. arXiv preprint arXiv:2006.04420.
  • Pinkall, U. and Polthier, K. (1993) Computing Discrete Minimal Surfaces and their Conjugates. Experimental Mathematics, 2(1): 15–36.
  • Michor, P.W. and Mumford, D. (2005) Vanishing Geodesic Distance on Spaces of Submanifolds and Diffeomorphisms. Documenta Mathematica, 10: 217–245.
  • Rudin, W. (1991) Functional Analysis Internat. Ser. Pure Appl. Math. McGraw-Hill, Inc., 2nd edition.
  • Schmidt, S. (2014) A Two Stage CVT/Eikonal Convection Mesh Deformation Approach for Large Nodal Deformations. arXiv preprint arXiv:1411.7663.
  • Schulz, V. (2014) A Riemannian View on Shape Optimization. Foundations of Computational Mathematics, 14(3): 483–501.
  • Schulz, V., Siebenborn, M. and Welker, K. (2016) Efficient PDE Constrained Shape Optimization based on Steklov-Poincar´e Type Metrics. SIAM Journal on Optimization, 26(4): 2800–2819.
  • Shontz, S.M. and Vavasis, S.A. (2003) A Mesh Warping Algorithm Based on Weighted Laplacian Smoothing. In: J. Shepherd, ed., Proceedings of the 12th International Meshing Roundtable, IMR 2003, Santa Fe, Mew Mexico, USA, September 14-17, 2003, 147–158.
  • Smolentsev, N.K. (2007) Diffeomorphism groups of compact manifolds. Journal of Mathematical Sciences, 146(6): 6213–6312.
  • Sturm, K. (2016) A Structure Theorem for Shape Functions defined on Submanifolds. arXiv preprint arXiv:1604.04840.
  • Taylor, M. (2011) Partial Differential Equations I: Basic Theory. Applied Mathematical Sciences, 115. Springer Science & Business Media, 2nd edition.
  • Wan, D. and Turek, S. (2006) Numerical Simulation of Coupled Fluid-Solid Systems by Fictitious Boundary and Grid Deformation Methods. In: Numerical Mathematics and Advanced Applications, 906–914. Springer.
  • Welker, K. (2021) Suitable Spaces for Shape Optimization. Applied Mathematics & Optimization, 84, 869–902.
  • Zhang, Y., Bajaj, C. and Xu, G. (2009) Surface Smoothing and Quality Improvement of Quadrilateral/Hexahedral Meshes with Geometric Flow. Communications in Numerical Methods in Engineering, 25(1): 1–18.
  • Zhou, Z., Chen, X. and Liao, G. (2017) A Novel Deformation Method for Higher Order Mesh Generation. arXiv preprint arXiv:1710.00291.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-00517e75-1d12-4405-a45f-dfee2c248da4
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