Penalization Techniques for Fatigue‐Based Topology Optimizations of Structures with Embedded Functionally Graded Lattice Materials

2022 ◽  
Author(s):  
Eric Trudel ◽  
Mostafa S. A. ElSayed
Keyword(s):  
Functionally Graded ◽  
Lattice Materials ◽  
Penalization Techniques ◽  
Graded Lattice

Stress-Constrained Design of Functionally Graded Lattice Structures With Spline-Based Dimensionality Reduction

2019 ◽  
Author(s):  
Jenmy Zimi Zhang ◽  
Conner Sharpe ◽  
Carolyn Conner Seepersad
Keyword(s):  
Three Dimensional ◽  
Surrogate Models ◽  
Functionally Graded ◽  
Unit Cell ◽  
Cell Stiffness ◽  
Stress Constraint ◽  
Compact Representation ◽  
Lattice Structures ◽  
Worst Case ◽  
Graded Lattice

Abstract This paper presents a computationally tractable approach for designing lattice structures for stiffness and strength. Yielding in the mesostructure is determined by a worst-case stress analysis of the homogenization simulation data. This provides a physically meaningful, generalizable, and conservative way to estimate structural failure in three-dimensional functionally graded lattice structures composed of any unit cell architectures. Computational efficiency of the design framework is ensured by developing surrogate models for the unit cell stiffness and strength as a function of density. The surrogate models are then used in the coarse-scale analysis and synthesis. The proposed methodology further uses a compact representation of the material distribution via B-splines, which reduces the size of the design parameter space while ensuring a smooth density variation that is desirable for manufacturing. The proposed method is demonstrated in compliance minimization studies using two types of unit cells with distinct mechanical properties. The effects of B-spline mesh refinement and the presence of a stress constraint on the optimization results are also investigated.

scholarly journals Stress-Constrained Design of Functionally Graded Lattice Structures With Spline-Based Dimensionality Reduction

2020 ◽  
Vol 142 (9) ◽  
Author(s):  
Jenmy Zimi Zhang ◽  
Conner Sharpe ◽  
Carolyn Conner Seepersad
Keyword(s):  
Three Dimensional ◽  
Surrogate Models ◽  
Functionally Graded ◽  
Unit Cell ◽  
Cell Stiffness ◽  
Stress Constraint ◽  
Compact Representation ◽  
Lattice Structures ◽  
Worst Case ◽  
Graded Lattice

Abstract This paper presents a computationally tractable approach for designing lattice structures for stiffness and strength. Yielding in the mesostructure is determined by a worst-case stress analysis of the homogenization simulation data. This provides a physically meaningful, generalizable, and conservative way to estimate structural failure in three-dimensional functionally graded lattice structures composed of any unit cell architectures. Computational efficiency of the design framework is ensured by developing surrogate models for the unit cell stiffness and strength as a function of density. The surrogate models are then used in the coarse-scale analysis and synthesis. The proposed methodology further uses a compact representation of the material distribution via B-splines, which reduces the size of the design parameter space while ensuring a smooth density variation that is desirable for manufacturing. The proposed method is demonstrated in compliance with minimization studies using two types of unit cells with distinct mechanical properties. The effects of B-spline mesh refinement and the presence of a stress constraint on the optimization results are also investigated.

Steering column support topology optimization including lattice structure for metal additive manufacturing

2020 ◽  
pp. 095440622094712
Author(s):  
S Mantovani ◽  
GA Campo ◽  
M Giacalone
Keyword(s):  
Additive Manufacturing ◽  
Bulk Material ◽  
Optimization Methods ◽  
Functionally Graded ◽  
Lattice Structures ◽  
Advantages And Disadvantages ◽  
Thin Walled Structures ◽  
Wide Range ◽  
Thin Walled ◽  
Graded Lattice

Structural engineering in the automotive industry has moved towards weight reduction and passive safety whilst maintaining a good structural performance. The development of Additive Manufacturing (AM) technologies has boosted design freedom, leading to a wide range of geometries and integrating functionally-graded lattice structures. This paper presents three AM-oriented numerical optimization methods, aimed at optimizing components made of: i) bulk material, ii) a combination of bulk material and graded lattice structures; iii) an integration of solid, lattice and thin-walled structures. The optimization methods were validated by considering the steering column support of a mid-rear engine sports car, involving complex loading conditions and shape. The results of the three methods are compared, and the advantages and disadvantages of the solutions are discussed. The integration between solid, lattice thin-walled structures produced the best results, with a mass reduction of 49.7% with respect to the existing component.

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