An interface-preserving level set update strategy for topology optimisation of mechanical assemblies

Multi-material thermomechanical topology optimization with applications to additive manufacturing: Design of main composite part and its support structure

Stress-based topology optimization and nonlinear structural topology optimization is gaining increasing attention in order to make topology optimization more realistic. Thus, this paper extends current concepts of topology optimization to the design of structures made of nonlinear materials. An extended bi-directional evolutionary structural optimization (BESO) method for stress minimization topology optimization of material nonlinear structures is proposed in this work. BESO method based on discrete variables can effectively avoid the well-known singularity problem in density-based methods with low-density elements. The maximum von Mises stress is approximated by the p-norm global stress. The sensitivity information for designing variable updates is derived in detail by adjoint method. As for the highly nonlinear stress behavior, the updated scheme takes advantages from two filters respectively of the sensitivity and topological variables to improve convergence. Moreover, the filtered sensitivity numbers are combined with their historical sensitivity information to further stabilize the optimization process. The effectiveness of the proposed method is demonstrated by several 2D benchmark design problems.

This paper introduces a general fully stabilized mesh based shape optimization strategy, which allows for shape optimization of mechanical problems on FE-based parametrization. The well-known mesh dependent results are avoided by application of filter methods and mesh regularization strategies. Filter methods are successfully applied to SIMP (Solid Isotropic Material with Penalization) based topology optimization for many years. The filter method presented here uses a specific formulation that is based on convolution integrals. It is shown that the filter methods ensure mesh independency of the optimal designs. Furthermore they provide an easy and robust tool to explore the whole design space with respect to optimal designs with similar mechanical properties. A successful application of optimization strategies with FE-based parametrization requires the combination of filter methods with mesh regularization strategies. The latter ones ensure reliable results of the finite element solutions that are crucial for the sensitivity analysis. This presentation introduces a new mesh regularization strategy that is based on the Updated Reference Strategy (URS). It is shown that the methods formulated on this mechanical basis result in fast and robust mesh regularization methods. The resulting grids show a minimum mesh distortion even for large movements of the mesh boundary. The performance of the proposed regularization methods is demonstrated by several illustrative examples.

In our previous works [1–3], we introduced a variational approach derived from thermodynamical principles, i.e. Hamilton's principle for dissipative processes. The Hamilton principle directly yields evolution equations providing an iterative update scheme for the design variables of the problem, requiring no additional (mathematical) minimization algorithms.We enhance our approach to reduce the calculation effort and improve the overall results: we introduce a regularization by penalizing the gradient of the density field, which gives us a well‐posed optimization problem. The strong form of the stationary condition results in a parabolic partial differential equation (PDE) which is solved by a finite difference method requiring minimal calculation effort. The regularization yields mesh‐independent results without checkerboarding. No additional filtering techniques are introduced and the complexity of the structure can be controlled a priori by a numerical parameter introduced along with the gradient penalization.

This study presents a topology optimization method for design of complaint mechanisms with maximum output displacement as the objective function. Unlike traditional approaches, one special characteristic of this method is that the volume fraction, which is defined as the calculated volume divided by the full volume, remains the same value throughout the optimization process based on the proposed pseudodensity and sensitivity number update scheme. The pseudodensity of each element is initially with the same value as the prespecified volume fraction constraint and can be decreased to a very small value or increased to one with a small increment. Two benchmark problems, the optimal design of a force–displacement inverter mechanism and a crunching mechanism, are provided as the illustrative examples to demonstrate the effectiveness of the proposed method. The results agree well with the previous studies. The proposed method is a general approach which can be used to synthesize the optimal designs of compliant mechanisms with better computational efficiency.

This paper introduces a heuristic topology optimization framework for thin-walled, 2D extruded lattice structures subject to complex high-speed loading. The proposed framework optimizes the wall thickness distribution in the lattice cross section through different thickness update schemes, inspired by the idea of equalization of absorbed energy density across all lattice walls. The proposed framework is ubiquitous and can be used in explicit dynamic simulations, which is the primary numerical method used in crashworthiness studies. No information on the material tangent stiffness matrix is required, and complex material behaviors and complex loading conditions can be handled. Three numerical examples are presented to demonstrate framework capabilities: (1) Optimization of a long, slender column under axial compression to maximize specific energy absorption, (2) Optimization of a lattice-filled sandwich panel under off-center blast loading to minimize material damage, (3) Generation of a periodic lattice core design under blast loading. The results show that the framework can effectively increase specific energy absorption or minimize material damage with as few as 25 finite element simulations and optimization iterations.