Alemseged G. Weldeyesus, PhD student Mathias Stolpe, Senior Researcher

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Presentation transcript:

Alemseged G. Weldeyesus, PhD student Mathias Stolpe, Senior Researcher Multidisciplinary Free Material Optimization for Laminated Plates and Shells Alemseged G. Weldeyesus, PhD student Mathias Stolpe, Senior Researcher

Free Material Optimization (FMO) FMO is a one of the different approaches to structural optimization. In FMO, the design variable is the full material tensor, can vary freely at each point of the design domain, necessary condition for physical attainability is the only requirement. M. P. Bendsøe, J. M. Guedes, R. B. Haber, P. Pedersen, and J. E. Taylor. An analytical model to predict optimal material properties in the context of optimal structural design. J. Appl. Mech. Trans. ASME, 61:930–937, 1994. M. Kočvara and M. Stingl. Free material optimization for stress constraints. Structural and Multidisciplinary Optimization, 33:323-335, 2007. M. Kočvara, M. Stingl, and J. Zowe. Free material optimization: Recent progress. Optimization, 57(1):79–100, 2008. WCCM 21 November 201821 November 201821 November 2018

Optimal solution Solution to FMO yields optimal distribution of the material as well as optimal local material properties. The obtained design can be considered as an ultimately best structure. Conceptual, since it is difficult (or actually impossible) to manufacture a structure such that its property varies at each point of the design. FMO can be used to generate benchmarks and to propose novel ideas for new design situations. 21 November 201821 November 201821 November 2018

The FMO problem formulation (solids) Mechanical assumptions static loads, linear elasticity, anisotropic material. The basic minimum compliance problem(Discrete) 2D, 3D structures Constraints on local stresses Highly nonlinear involving matrix variables. Adding such constraints destroys suitable problem properties, e.g. convexity. 21 November 201821 November 201821 November 2018

Goals Propose FMO model for laminated plates and shells. (Such models are not available today) Develop special purpose optimization method that can efficiently solve FMO problems. (FMO problems lead to large-scale nonlinear SDP problems) 21 November 201821 November 201821 November 2018

FMO for laminated plates and shells Based on FSDT (C,D ), fixed within a layer in the thickness direction. Slightly violates the idea of FMO. 21 November 201821 November 201821 November 2018

FMO for laminated plates and shells contd… Minimum compliance problem 21 November 201821 November 201821 November 2018

Stress constraints Linear stress variation across the thickness within a layer. Two stress evaluations in each layer (at the top and lower surfaces) over each finite element to capture stress extremities. 21 November 201821 November 201821 November 2018

Optimization method Primal-dual interior point method (second-order method). Combines standard known interior point methods for nonlinear programmings & linear SDPs. 21 November 201821 November 201821 November 2018

Optimization method contd… FMO problems can be represented by Introducing slack variables and barrier paramter , the associated barrier problem is We solve problem (BP) for a sequence of barrier parameter k0. 21 November 201821 November 201821 November 2018

Numerical results Optimal density distribution 4 layers Design domain, bc and forces # FEs 20,000. # 160,000 matrix inequalities. # 720,000 design variables. No distinction between layers. Similar to 2D results. No deformation out of the midsurface. No material for D. # 52 iterations. 21 November 201821 November 201821 November 2018

Numerical results … Optimal density distribution 8 layers Design domain, bc and forces 4 load-case. # FEs 10,000. # 160,000 matrix inequalities. # 720,000 design variables. Symmetric laminate. High material distribution on top and bottom layers, implies sandwich structures. ( similar results in DMO) # 25 iterations. 21 November 201821 November 201821 November 2018

Numerical results contd… Curved surfaces single layer Optimal density distribution Design domain, bc and forces # FEs 80,000. # 160,000 matrix inequalities. # 720,000 design variables. # 54 iterations. # FEs 40,000. # 80,000 matrix inequalities. # 360,000 design variables. # 51 iterations. 21 November 201821 November 201821 November 2018

Numerical results contd… Stress-constrained FMO problems Optimal density distribution Optimal stress norms Design domain, bc and forces Without stress constraints # FEs 7,500. # 7,500 matrix inequalities. # 45,000 design variables. # 7,500 stress constraints. With stress constraints 21 November 201821 November 201821 November 2018

Numerical results contd… Without stress constraints With stress constraints Optimal principal stresses Without stress constraints With stress constraints , 60% # iterations 30 85 compliance 1.8951 1.9281 21 November 201821 November 201821 November 2018

Numerical results contd… 8 layers Optimal density distribution of the top 4 layers Design domain, bc and forces Without stress constraints With stress constraints # FEs 2,500. # 40,000 matrix inequalities. # 180,000 design variables. # 40,000 stress constraints. Optimal density distribution – no such a significant difference 21 November 201821 November 201821 November 2018

Numerical results contd… Optimal stress norms at the upper and lower surfaces of the first top four layers Without stress constraints With stress constraints Upper Lower Without stress constraints With stress constraints, 30% # iterations 47 115 compliance 5.4771 5.5624 21 November 201821 November 201821 November 2018

Conclusions The developed optimization method solves FMO problems in a reasonable number of iterations. Number of iterations is almost independent to problem size. More number of iterations is required for solving the stress constrained problems (but expected). FMO has been extended to optimal design of laminated structures. The change of material properties plays main role in reducing high stresses in FMO. Reduction of high stresses is achieved at a small increase in compliance. 21 November 201821 November 201821 November 2018

Thank you for your attention ! 21 November 201821 November 201821 November 2018