[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Freedom of design, mass customisation, waste minimisation and the ability to manufacture complex structures, as well as fast prototyping, are the main benefits of additive manufacturing (AM) or 3D printing. A comprehensive review of the main 3D printing methods, materials and their development in trending applications was carried out. In particular, the revolutionary applications of AM in biomedical, aerospace, buildings and protective structures were discussed. The current state of materials development, including metal alloys, polymer composites, ceramics and concrete, was presented. In addition, this paper discussed the main processing challenges with void formation, anisotropic behaviour, the limitation of computer design and layer-by-layer appearance. Overall, this paper gives an overview of 3D printing, including a survey on its benefits and drawbacks as a benchmark for future research and development.

Additive manufacturing (3D printing): A review of materials, methods, applications and challenges

Topology optimization has undergone a tremendous development since its introduction in the seminal paper by Bendsoe and Kikuchi in 1988. By now, the concept is developing in many different directions, including “density”, “level set”, “topological derivative”, “phase field”, “evolutionary” and several others. The paper gives an overview, comparison and critical review of the different approaches, their strengths, weaknesses, similarities and dissimilarities and suggests guidelines for future research.

Topology optimization approaches: A comparative review

The mechanical properties of ordinary materials degrade substantially with reduced density because their structural elements bend under applied load. We report a class of microarchitected materials that maintain a nearly constant stiffness per unit mass density, even at ultralow density. This performance derives from a network of nearly isotropic microscale unit cells with high structural connectivity and nanoscale features, whose structural members are designed to carry loads in tension or compression. Production of these microlattices, with polymers, metals, or ceramics as constituent materials, is made possible by projection microstereolithography (an additive micromanufacturing technique) combined with nanoscale coating and postprocessing. We found that these materials exhibit ultrastiff properties across more than three orders of magnitude in density, regardless of the constituent material.

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Ultralight, ultrastiff mechanical metamaterials

Topological design and additive manufacturing of porous metals for bone scaffolds and orthopaedic implants: A review.

Foam-filled thin-wall structures have exhibited significant advantages in light weight and high energy absorption and been widely applied in automotive, aerospace, transportation and defence industries. Unlike existing uniform foam materials, this paper introduces functionally graded foam (FGF) fillers to fill thin-walled structures, aiming to improve crashworthiness. In this novel structure, the foam density varies throughout the depth in a certain gradient. Numerical simulations showed that gradient exponential parameter m that controls the variation of foam density has significant effect on system crashworthiness. In this study, the single and multiobjective particle swarm optimization methods are used to seek for optimal gradient, where response surface models are established to formulate specific energy absorption and peak crushing force. The results yielded from the optimizations indicate that the FGF material is superior to its uniform counterparts in overall crashworthiness. The data has considerable implication in design of FGF materials for optimizing structural crashworthiness.

Crashworthiness design for functionally graded foam-filled thin-walled structures

This paper describes a phase field method for the optimization of multimaterial structural topology with a generalized Cahn–Hilliard model. Similar to the well-known simple isotropic material with penalization method, the mass concentration of each material phase is considered as design variable. However, a variational approach is taken with the Cahn–Hilliard theory to define a thermodynamic model, taking into account of the bulk energy and interface energy of the phases and the elastic strain energy of the structure. As a result, the structural optimization problem is transformed into a phase transition problem defined by a set of nonlinear parabolic partial differential equations. The generalized Cahn–Hilliard model regularizes the original ill-posed topology optimization problem and provides flexibility of topology changes with interface coalescence and break-up due to phase separation and coarsening. We employ a powerful multigrid algorithm and extend it to include four material phases for numerical solution of the Cahn–Hilliard equations. We demonstrate our approach through several 2-D and 3-D examples to minimize mean compliance of the multimaterial structures.

Multimaterial structural topology optimization with a generalized Cahn–Hilliard model of multiphase transition

Design of lattice structures with controlled anisotropy

Although deterministic optimization has to a considerable extent been successfully applied in various crashworthiness designs to improve passenger safety and reduce vehicle cost, the design could become less meaningful or even unacceptable when considering the perturbations of design variables and noises of system parameters. To overcome this drawback, we present a multiobjective robust optimization methodology to address the effects of parametric uncertainties on multiple crashworthiness criteria, where several different sigma criteria are adopted to measure the variations. As an example, a full front impact of vehicle is considered with increase in energy absorption and reduction of structural weight as the design objectives, and peak deceleration as the constraint. A multiobjective particle swarm optimization is applied to generate robust Pareto solution, which no longer requires formulating a single cost function by using weighting factors or other means. From the example, a clear compromise between the Pareto deterministic and robust designs can be observed. The results demonstrate the advantages of using multiobjective robust optimization, with not only the increase in the energy absorption and decrease in structural weight from a baseline design, but also a significant improvement in the robustness of optimum.

Shiwei Zhou

Papers

Topological design and additive manufacturing of porous metals for bone scaffolds and orthopaedic implants: A review.

Crashworthiness design for functionally graded foam-filled thin-walled structures

Multimaterial structural topology optimization with a generalized Cahn–Hilliard model of multiphase transition

Design of lattice structures with controlled anisotropy

Crashworthiness design of vehicle by using multiobjective robust optimization