Dynamical systems and topology optimization

Structural and Multidisciplinary Optimization - Tập 42 - Trang 179-192 - 2010
Anders Klarbring1, Bo Torstenfelt2
1Division of Mechanics, Institute of Technology, Linköping University, Linköping, Sweden
2Division of Solid Mechanics, Institute of Technology, Linköping University, Linköping, Sweden

Tóm tắt

This paper uses a dynamical systems approach for studying the material distribution (density or SIMP) formulation of topology optimization of structures. Such an approach means that an ordinary differential equation, such that the objective function is decreasing along a solution trajectory of this equation, is constructed. For stiffness optimization two differential equations with this property are considered. By simple explicit Euler approximations of these equations, together with projection techniques to satisfy box constraints, we obtain different iteration formulas. One of these formulas turns out to be the classical optimality criteria algorithm, which, thus, is receiving a new interpretation and framework. Based on this finding we suggest extensions of the optimality criteria algorithm. A second important feature of the dynamical systems approach, besides the purely algorithmic one, is that it points at a connection between optimization problems and natural evolution problems such as bone remodeling and damage evolution. This connection has been hinted at previously but, in the opinion of the authors, not been clearly stated since the dynamical systems concept was missing. To give an explicit example of an evolution problem that is in this way connected to an optimization problem, we study a model of bone remodeling. Numerical examples, related to both the algorithmic issue and the issue of natural evolution represented as bone remodeling, are presented.

Tài liệu tham khảo

Achtziger W, Bendsøe MP, Taylor JE (1998) Bounds on the effect of progressive structural degradation. J Mech Phys Solids 46(6):1055–1087 Bejan A (2000) Shape and structure, from engineering to nature. Cambridge University Press, Cambridge Bendsøe MP, Sigmund O (2003) Topology optimization: theory, methods and applications. Springer, Heidelberg Borrvall T (2001) Topology optimization of elastic continua using restriction. Arch Comput Methods Eng 8:351–385 Brown AA, Bartholomew-Biggs MC (1989) Some effective methods for unconstrained optimization based on the solution of systems of ordinary differential equations. J Optim Theory Appl 62(2):211–224 Chen G, Pettet G, Pearcy M, McElwain DLS (2007) Comparison of two numerical approaches for bone remodelling. Med Eng Phys 29(1):134–139 Christensen PW, Klarbring A (2009) An introduction to structural optimization. Springer, Heidelberg Dontchev A, Lempio F (1992) Difference methods for differential inclusions: a survey. SIAM Rev 34(2):263–294 Francfort GA, Bourdin B, Marigo J-J (2008) The variational approach to fracture. J Elast 91(1–3):5–148 Harrigan TP, Hamilton JJ (1992) Optimality conditions for finite element simulation of adaptive bone remodeling. Int J Solids Struct 29(23):2897–2906 Harrigan TP, Hamilton JJ (1994a) Necessary and sufficient conditions for global stability and uniqueness in finite element simulations of adaptive bone remodeling. Int J Solids Struct 31(1):97–107 Harrigan TP, Hamilton JJ (1994b) Bone remodeling and structural optimization. J Biomech 27(3):323–328 Klarbring A (2009) Topology optimization, dynamical systems, thermodynamics and growth. In: Damkilde L, Andersen L, Kristensen AS, Lund E (eds) Proceedings of the twenty second nordic seminar on computational mechanics, Aalborg, pp 337–344 Klarbring A, Petersson J, Torstenfelt B, Karlsson M (2003) Topology optimization of flow networks. Comput Methods Appl Mech Eng 192:3909–3932 Liao L-Z, Qi H, Qi L (2004) Neurodynamical optimization. J Glob Optim 28:175–195 Mullender MG, Huiskes R, Weinans H (1994) A physiological approach to the simulation of bone remodeling as a self-organizational control process. J Biomech 27(11):1389–1394 Nagurney A, Zhang D (1996) Projected dynamical systems and variational inequalities with applications. Kluwer, Dordrecht Pang J-S, Stewart DE (2008) Differential variational inequalities. Math Program 113(2):345–424 Pappalardo M, Passacantando M (2002) Stability for equilibrium problems: from variational inequalities to dynamical systems. J Optim Theory Appl 113(3):567–582 Payten WM, Ben-Nissan B, Mercer DJ (1998) Optimal topology design using a global self-organisational approach. Int J Solids Struct 35(3–4):219–237 Pettermann HE, Reiter TJ, Rammerstorfer FG (1997) Computational simulation of internal bone remodeling. Arch Comput Methods Eng 4(4):295–323 Sigmund O (2007) Morphology-based black and white filters for topology optimization. Struct Multidisc Optim 33:401–424 Stolpe M, Svanberg K (2001) An alternative interpolation scheme for minimum compliance topology optimization. Struct Multidisc Optim 22(2):116–124 Svanberg K (1994) On the convexity and concavity of compliances. Struct Optim 7(1–2):42–46 Torstenfelt B (2009) The TRINITAS project. http://www.solid.iei.liu.se/Offered_services/Trinitas/index.html Wang S, Yang XQ, Teo KL (2003) A unified gradient flow approach to constrained nonlinear optimization problems. Comput Optim Appl 25:251–268 Xia YS (2004) Further results on global convergence and stability of globally projected dynamical systems. J Optim Theory Appl 122(3):637–649 Xinghua Z, He G, Dong Z, Bingzhao G (2002) A study of the effect of non-linearity in the equations of bond remodeling. J Biomech 35:951–960