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The purpose of this paper is to further develop the truss‐like discrete element method (DEM) in order to make it suitable to deal with damage and fracture problems.

Finite and boundary elements are the best developed methods in the field of numerical fracture and damage mechanics. However, these methods are based on a continuum approach, and thus, the modelling of crack nucleation and propagation could be sometimes a cumbersome task. Besides, discrete methods possess the natural ability to introduce discontinuities in a very direct and intuitive way by simply breaking the link between their discrete components. Within this context, the present work extends the capabilities of a truss‐like DEM via the introduction of three novel features: a tri‐linear elasto‐plastic constitutive law; a methodology for crack discretization and the computation of stress intensity factors; and a methodology for the computation of the stress field components from the unixial discrete‐element results.

Obtained results show the suitability and the performance of the proposed methodologies to solve static and dynamic crack problems (including crack propagation) in brittle and elasto‐plastic materials. Computed results are in good agreement with experimental and numerical results reported in the bibliography.

This paper demonstrates the versatility of the truss‐like DEM to deal with damage mechanics problems. The approach used in this work can be extended to the implementation of time‐dependent damage mechanisms. Besides, the capabilities of the discrete approach could be exploited by coupling the truss‐like DEM to finite and boundary element methods. Coupling strategies would allow using the DEM to model the regions of the problem where crack nucleation and propagation occurs, while finite or boundary elements are used to model the undamaged regions.

The scope of the truss‐like DEM has been extended. New procedures have been introduced to deal with elastoplastic‐crack problems and to improve the post processing of the stress results.

Methods to optimize lattice structure design, such as ground structure optimization, have been shown to be useful when generating efficient design concepts with complex truss-like cellular structures. Unfortunately, designs suggested by lattice structure optimization methods are often infeasible because the obtained cross-sectional parameter values cannot be fabricated by additive manufacturing (AM) processes, and it is often very difficult to transform a design proposal into one that can be additively designed. This paper aims to propose an improved, two-phase lattice structure optimization framework that considers manufacturing constraints for the AM process.

The proposed framework uses a conventional ground structure optimization method in the first phase. In the second phase, the results from the ground structure optimization are modified according to the pre-determined manufacturing constraints using a second optimization procedure. To decrease the computational cost of the optimization process, an efficient gradient-based optimization algorithm, namely, the method of feasible directions (MFDs), is integrated into this framework. The developed framework is applied to three different design examples. The efficacy of the framework is compared to that of existing lattice structure optimization methods.

The proposed optimization framework provided designs more efficiently and with better performance than the existing optimization methods.

The proposed framework can be used effectively for optimizing complex lattice-based structures.

An improved optimization framework that efficiently considers the AM constraints was reported for the design of lattice-based structures.

The purpose of this paper is to propose a novel non-probabilistic reliability-based topology optimization (NRBTO) method for continuum structural design under interval uncertainties of load and material parameters based on the technology of 3D printing or additive manufacturing.

First, the uncertainty quantification analysis is accomplished by interval Taylor extension to determine boundary rules of concerned displacement responses. Based on the interval interference theory, a novel reliability index, named as the optimization feature distance, is then introduced to construct non-probabilistic reliability constraints. To circumvent convergence difficulties in solving large-scale variable optimization problems, the gradient-based method of moving asymptotes is also used, in which the sensitivity expressions of the present reliability measurements with respect to design variables are deduced by combination of the adjoint vector scheme and interval mathematics.

The main findings of this paper should lie in that new non-probabilistic reliability index, i.e. the optimization feature distance which is defined and further incorporated in continuum topology optimization issues. Besides, a novel concurrent design strategy under consideration of macro-micro integration is presented by using the developed RBTO methodology.

Uncertainty propagation analysis based on the interval Taylor extension method is conducted. Novel reliability index of the optimization feature distance is defined. Expressions of the adjoint vectors between interval bounds of displacement responses and the relative density are deduced. New NRBTO method subjected to continuum structures is developed and further solved by MMA algorithms.

This paper proposes a bar‐system graph representation for structural topology optimization using a genetic algorithm (GA).

Based on graph theory, a graph is first used to represent a skeletal structure consisting of joining paths in the design domain, each of which is represented by a chain subgraph with finite number of vertices. Based on the edges of this graph, a bar‐system representation is proposed to define all the bars and the resulting topology is obtained by mapping each bar with its corresponding thickness to the design domain which is discretized into a regular mesh. The design variables are thus reduced to the spatial distribution of the vertices and the thickness of each bar. This method combines the advantages of both continuum and ground structure optimization methods.

The overall procedure is applied to classical structural topology optimization problems and its good performance is illustrated in the numerical examples.

It is suggested that the present representation method is both physically meaningful and computationally effective in the framework of topological optimum design using GAs.

The purpose of this paper is to describe an element addition strategy for topology optimization of thermally actuated compliant mechanisms under uniform temperature fields.

The proposed procedure is based on the evolutionary structural optimization (ESO) method. In previous works, this group of authors has successfully applied the ESO method for compliant mechanism optimization under directly applied input loads. The present paper progresses on this work line developing an extension of this procedure, based on an additive version of the method, to approach the more complicated case of thermal actuators.

The adopted method has been tested in several numerical applications and benchmark examples to illustrate and validate the approach, and designs obtained with this method are compared favorably with the analytical solutions and results derived by other authors using different optimization methods, showing the viability of this technique for uniformly heated actuators optimization.

As a simple initial approach, this research considers only uniform heating of the system, while many thermal actuators are heated nonuniformly. Future works will be based on electrothermal actuation, and nonuniform Joule heating will be considered as well, which might lead to more elegant and efficient solutions.

Compliant micromechanisms that are responsible for movement play a crucial role in microelectromechanical systems (MEMS) design, which cannot be manufactured using typical assembly processes and may not make use of traditional hinges or bearings. The topology optimization method described in this paper enables the systematic design of these devices, which can result in reduced conception time and manufacturing cost.

The ESO method has been successfully applied to several optimum material distribution problems, but not for thermal compliant mechanisms. Even if most applications of this method have been oriented for maximum stiffness structure design, this paper shows that this computation method may be also useful in the design of thermal compliant mechanisms and provides engineers with a very simple and practical alternative design tool.

Solid freeform fabrication is particularly suitable for fabricating customized parts, but it has not been used for fabricating deployable structures that can be stored in a compact configuration and deployed quickly and easily in the field. The purpose of this paper is to present a methodology for deploying flexible, freeform structure with lattice skins as the deploying mechanism.

A ground structure‐based topology optimization procedure is utilized, with a penalization scheme that encourages convergence to sets of thick lattice elements that are manufacturable and extremely thin lattice elements that are removed from the final structure.

A deployable wing is designed for a miniature unmanned aerial vehicle. A physical prototype of the optimal configuration is fabricated with selective laser sintering and compared with the virtual prototype. The proposed methodology results in a 78 percent improvement in deviations from the intended surface profile of the deployed part.

The results presented in the paper provide proof‐of‐concept for the use of lattice skins as a deployment mechanism. A topology optimization framework is also provided for designing these lattice skins. Potential applications include portable, camouflaged shelters and deployable aerial vehicles.

This paper aims to provide a comprehensive review of the state-of–the-art design methods for additive manufacturing (AM) technologies to improve functional performance.

In this survey, design methods for AM to improve functional performance are divided into two main groups. They are design methods for a specific objective and general design methods. Design methods in the first group primarily focus on the improvement of functional performance, while the second group also takes other important factors such as manufacturability and cost into consideration with a more general framework. Design methods in each groups are carefully reviewed with discussion and comparison.

The advantages and disadvantages of different design methods for AM are discussed in this paper. Some general issues of existing methods are summarized below: most existing design methods only focus on a single design scale with a single function; few product-level design methods are available for both products’ functionality and assembly; and some existing design methods are hard to implement for the lack of suitable computer-aided design software.

This study is a useful source for designers to select an appropriate design method to take full advantage of AM.

In this survey, a novel classification method is used to categorize existing design methods for AM. Based on this classification method, a comprehensive review is provided in this paper as an informative source for designers and researchers working in this field.

An automated fully stressed design approach based on the Xie and Steven algorithm is presented. With this algorithm a fully stressed design is obtained by a gradual removal of low stressed material. By applying this evolutionary procedure a layout or topology of a structure can be found from an initial block of material. A fully integrated, interactive program is presented which incorporates automatic mesh generation, finite element analysis and the fully stressed design algorithm. The feasibility of the approach is demonstrated using several examples.

The goal of structural optimization is to find the best possible configuration that minimizes the objective function and satisfies a set of constraints. Here we present a method based on the evolutionary structural optimization method, where the quality of the solution is improved by avoiding the chain‐like sets of elements which are sources of potential kinematic instabilities, and by including local error estimators. Both of these enhancements are employed to activate refining the mesh so as to obtain accurate and stable solutions as the volume removal proceeds. Several related contributions of Professor E. Hinton are cited.

Modern CAD systems facilitate the creation of any surface geometry imaginable, and complex surfaces for free-form grid shells are often represented by a set of Non-Uniform Rational B-Splines surface patches. But it remains an intractable issue how to generate high-quality grids on complex surfaces efficiently. To solve this issue, an automatic triangular mesh generation method is presented, based on bubble dynamics simulation and a modified Delaunay method.

A moderate amount of points are first distributed on a given surface. Next, by regarding the points as elastic bubbles with the same size and introducing the forces acting on bubbles, the motion control equations of bubbles are established. The equilibrium state of the bubble system is found by Verlet algorithm. Then, the Voronoi diagram on the surface is obtained by calculating the intersection between the surface and the three-dimensional (3D) Voronoi diagram of the centers of bubbles. Finally, a triangular mesh, Delaunay triangulation on the surface, is determined based on the dual change of the Voronoi diagram.

This method generates meshes on the surface directly, unlike mapping-based methods, avoiding the mapping distortion. Examples are given to demonstrate the successful execution of this method. The result also illustrates that this method is applicable to various surfaces in high automation level and resultant meshes are highly uniform and well-shaped.

Thus, this method provides the convenience for the geometry design of complex free-form grid structure.