On transmissible load formulations in topology optimization

Transmissible loads are external loads defined by their line of action, with actual points of load application chosen as part of the topology optimization process. Although for problems where the optimal structure is a funicular, transmissible loads can be viewed as surface loads, in other cases such loads are free to be applied to internal parts of the structure. There are two main transmissible load formulations described in the literature: a rigid bar (constrained displacement) formulation or, less commonly, a migrating load (equilibrium) formulation. Here, we employ a simple Mohr’s circle analysis to show that the rigid bar formulation will only produce correct structural forms in certain specific circumstances. Numerical examples are used to demonstrate (and explain) the incorrect topologies produced when the rigid bar formulation is applied in other situations. A new analytical solution is also presented for a uniformly loaded cantilever structure. Finally, we invoke duality principles to elucidate the source of the discrepancy between the two formulations, considering both discrete truss and continuum topology optimization formulations

Topology optimization for human proximal femur considering bi-modulus behavior of cortical bones

© Springer International Publishing Switzerland 2015. The material in the human proximal femur is considered as bi-modulus material and the density distribution is predicted by topology optimization method. To reduce the computational cost, the bi-modulus material is replaced with two isotropic materials in simulation. The selection of local material modulus is determined by the previous local stress state. Compared with density prediction results by traditional isotropic material in proximal femur, the bi-modulus material layouts are different obviously. The results also demonstrate that the bi-modulus material model is better than the isotropic material model in simulation of density prediction in femur bone

Poly[ethyl­enediammonium [tris­[μ3-hydrogenphosphato(2−)]dicadmium] monohydrate]

The title compound, {(C2H10N2)[Cd2(HPO4)3]·H2O}n, was synthesized under hydro­thermal conditions. The structure of this hybrid compound consists of CdO6, CdO5 and PO4 polyhedra arranged so as to build an anionic inorganic layer, namely [Cd2(HPO4)3]2−, parallel to the ab plane. The edge-sharing CdO6 octa­hedra form infinite chains running along the a axis and are linked by CdO5 and PO4 polyhedra. The ethyl­ene­diammonium cation and the water mol­ecule are located between two adjacent inorganic layers and ensure the cohesion of the structure via N—H⋯O and O—H⋯O hydrogen bonds

Structural topology and shape optimization for a frequency response problem

A topology and shape optimization technique using the homogenization method was developed for stiffness of a linearly elastic structure by Bendsøe and Kikuchi (1988), Suzuki and Kikuchi (1990, 1991), and others. This method has also been extended to deal with an optimal reinforcement problem for a free vibration structure by Diaz and Kikuchi (1992). In this paper, we consider a frequency response optimization problem for both the optimal layout and the reinforcement of an elastic structure. First, the structural optimization problem is transformed to an Optimal Material Distribution problem (OMD) introducing microscale voids, and then the homogenization method is employed to determine and equivalent “averaged” structural analysis model. A new optimization algorithm, which is derived from a Sequential Approximate Optimization approach (SAO) with the dual method, is presented to solve the present optimization problem. This optimization algorithm is different from the CONLIN (Fleury 1986) and MMA (Svanderg 1987), and it is based on a simpler idea that employs a shifted Lagrangian function to make a convex approximation. The new algorithm is called “Modified Optimality Criteria method (MOC)” because it can be reduced to the traditional OC method by using a zero value for the shift parameter. Two sensitivity analysis methods, the Direct Frequency Response method (DFR) and the Modal Frequency Response method (MFR), are employed to calculate the sensitivities of the object functions. Finally, three examples are given to show the feasibility of the present approach.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47814/1/466_2004_Article_BF00370133.pd