Reliability-based topology optimization by ground structure method employing a discrete filtering technique

Structural and Multidisciplinary Optimization - When conventional filtering schemes are used in reliability-based topology optimization (RBTO), identified solutions may violate probabilistic...     

Efficient structure topology optimization by using the multiscale finite element method

Efficient SIMP and level set based topology optimization schemes are proposed based on the computation framework of the multiscale finite element method (MsFEM). In the proposed optimization schemes, the equilibrium equations are solved on a coarse-scale mesh and the design variables are updated on a fine-scale mesh. To describe more complex deformation, a multi-node coarse element is also presented in the MsFEM computation. In the MsFEM, a multiscale shape function is constructed numerically and employed to obtain the equivalent stiffness matrix and load vector of the multi-node coarse element. In the optimization schemes with the MsFEM, the coarse elements are divided into two categories: homogeneous and heterogeneous. For the homogeneous coarse elements, their multiscale shape functions are constructed only once before the iterations. Since the material distribution is varying locally in most of the iterations, one only needs to reconstruct them of a small part of the coarse elements where the material distribution is changed by comparison with that in the previous iteration step. This will save lots of computational cost. In addition, due to the independence of each coarse element, the constructions of the multiscale shape functions could be easily proceeded in parallel. In this work, the computational accuracy and efficiency of this method is investigated in detail, as well as the speedup ratio and parallel efficiency when using multiple processors to construct the multiscale shape functions simultaneously. Furthermore, several 2D and 3D examples show the effectiveness and efficiency of the proposed optimization schemes based on the MsFEM analysis framework.     

Structural topology optimization using a genetic algorithm with a morphological geometric representation scheme

This paper describes a versatile methodology for solving topology design optimization problems using a genetic algorithm (GA). The key to its effectiveness is a geometric representation scheme that works by specifying a skeleton which defines the underlying topology/connectivity of a structural continuum together with segments of material surrounding the skeleton. The required design variables are encoded in a chromosome which is in the form of a directed graph that embodies this underlying topology so that appropriate crossover and mutation operators can be devised to recombine and help preserve any desirable geometry characteristics of the design through succeeding generations in the evolutionary process. The overall methodology is first tested by solving ‘target matching’ problems—simulated topology optimization problems in each of which a ‘target’ geometry is first created and predefined as the optimum solution, and the objective of the optimization problem is to evolve design solutions to converge towards this target shape. The methodology is then applied to design two path-generating compliant mechanisms—large-displacement flexural structures that undergo some desired displacement paths at some point when given a straight line input displacement at some other point—by an actual process of topology/shape optimization.     

Topology optimization using a dual method with discrete variables

This paper deals with topology optimization of continuous structures in static linear elasticity. The problem consists in distributing a given amount of material in a specified domain modelled by a fixed finite element mesh in order to minimize the compliance. As the design variables can only take two values indicating the presence or absence of material (1 and 0), this problem is intrinsicallydiscrete. Here, it is solved by a mathematical programming method working in the dual space and specially designed to handle discrete variables. This method is very wellsuited to topology optimization, because it is particularly efficient for problems with a large number of variables and a small number of constraints. To ensure the existence of a solution, the perimeter of the solid parts is bounded. A computer program including analysis and optimization has been developed. As it is specialized for regular meshes, the computational time is drastically reduced. Some classical 2-D and new 3-D problems are solved, with up to 30,000 design variables. Extensions to multiple load cases and to gravity loads are also examined.     

Reliability-based topology optimization using a new method for sensitivity approximation - application to ground structures

This paper proposes an efficient gradient-based optimization approach for reliability-based topology optimization of structures under uncertainties. Our objective is to find the optimized topology of structures with minimum weight which also satisfy certain reliability requirements. In the literature, those problems are primarily performed with approaches that use a first-order reliability method (FORM) to estimate the gradient of the probability of failure. However, these approaches may lead to deficient or even invalid results because the gradient of probabilistic constraints, calculated by first order approximation, might not be sufficiently accurate. To overcome this issue, a newly developed segmental multi-point linearization (SML) method is employed in the optimization approach for a more accurate estimation of the gradient of failure probability. Meanwhile, this implementation also improves the approximation of the probability evaluation at no extra cost. In general, adoption of the SML method leads to a more accurate and robust approach. Numerical examples show that the new approach, based on the SML method, is numerically stable and usually provides optimized structures that have more of the desired features than conventional FORM-based approaches. The present approach typically does not lead to a fully stressed design, and thus this feature will be verified by numerical examples.     

Design of an energy-absorbing structure using topology optimization with a multimaterial model

To accommodate the dual objectives of many engineering applications, one objective to minimize the mean compliance for the stiffest structure under normal service conditions and the other objective to maximize the strain energy for energy absorption during excessive loadings, topology optimization with a multimaterial model is applied to the design of an energy-absorbing structure in this paper. The effective properties of the three-phase material are derived using a spherical microinclusion model. The dual objectives are combined in a ratio formation. Numerical examples from the proposed method are presented and discussed.     

Reliability-based topology optimization of double layer grids using a two-stage optimization method

This paper presents a two-stage optimization method for reliability-based topology optimization (RBTO) of double layer grids that considers uncertainties in applied loads. The optimization is performed using a two-stage optimization by employing the method of moving asymptotes (MMA) and ant colony optimization (ACO), which is called MMA-ACO method. For implementation of MMA-ACO, the structural stiffness is maximized using MMA, first. Then, the results of MMA are used to enhance ACO through the following four modifications: (I) finding the structural importance rate of elements or joints and using this to achieve a better topology, (II) determining the number of compressive and tensile element types, (III) changing the lower limit of available cross-sectional areas for the elements of each group and (IV) modifying the generation of random stable structures. In reliability analysis, multiple criteria i.e. stiffness and eigenvalue are considered where the probability of failure in each mode is calculated by Monte Carlo simulation (MCS). To reduce the computational time, the eigenvalues are evaluated using the third order approximation (TOA). Through numerical examples, reliability-based topology designs of typical double layer grids are obtained by ACO and MMA-ACO methods. The numerical results reveal the computational advantages and effectiveness of the proposed MMA-ACO method for the RBTO of double layer grids. Also, the importance of considering uncertainties is then demonstrated by comparing the results obtained by those of other failure probabilities.     

A topology optimization approach using VOF method

Topology optimization methods with continuous design variables obtained by the homogenization formula or the solid isotropic microstructure with penalty (SIMP) model are widely used in the layout of structures. In the implementation of these approaches, one must take into account several issues, e.g., irregularity of the problem, occurrence of the checkerboard pattern, and intermediate density. To suppress these phenomena, the employment of additional strategies such as the perimeter control or the filtering method will be required. In this paper, a topology optimization method which can eliminate these difficulties is developed based on the volume of fluid (VOF) method. In the method, shape design is described in terms of the VOF function. Since this function is defined by a volume fraction of material occupying each element, it can be recognized as a continuous material density in the SIMP model. Within the framework of the VOF analysis, the topology optimization procedure is reduced to a convection motion of the material density governed by a Hamilton–Jacobi equation as in the level set method. Through numerical examples, the validity of the proposed method is investigated.     

Component and system reliability-based topology optimization using a single-loop method

We perform reliability-based topology optimization by combining reliability analysis and material distribution topology design methods to design linear elastic structures subject to random inputs, such as random loadings. Both component reliability and system reliability are considered. In component reliability, we satisfy numerous probabilistic constraints which quantify the failure of different events. In system reliability, we satisfy a single probabilistic constraint which encompasses the component events. We adopt the first-order reliability method to approximate the component reliabilities and the inclusion-exclusion rule to approximate the system reliability. To solve the probabilistic optimization problem, we use a variant of the single loop method, which eliminates the need for an inner reliability analysis loop. The proposed method is amenable to implementation with existing deterministic topology optimization software, and hence suitable for practical applications. Designs obtained from component and system reliability-based topology optimization are compared to those obtained from traditional deterministic topology optimization and validated via Monte Carlo simulation.     

Shape preserving design of geometrically nonlinear structures using topology optimization

Structural and Multidisciplinary Optimization - Subparts of load carrying structures like airplane windows or doors must be isolated from distortions and hence structural optimization needs to take...     

Eigenvalue topology optimization of structures using a parameterized level set method

Preventing a structure from resonance is important in many real-world applications. Because an external excitation frequency can be lower than the fundamental eigenfrequency or between the eigenfrequencies of a structure, there is a strong need for eigenfrequency optimization technology to optimize the fundamental eigenfrequency and, in addition, the k-th eigenfrequency and to maximize the gap between eigenfrequencies. However, previous optimization studies on vibrating elastic structures that used the level set method have been devoted to the optimization of the fundamental eigenfrequency, whereas the higher-order eigenfrequencies optimization problem has seldom been considered. This paper presents an eigenfrequency optimization technology that is based on the compactly supported radial basis functions (CS-RBFs) parameterized level-set method, using the fundamental eigenfrequency, the eigenfrequency of a given higher-order, and the gap between two consecutive eigenfrequencies as the optimization objectives. Furthermore, to address the oscillation problem of the objective function, we adopt an exponential weighted optimization model of a number of the lower eigenfrequencies for multiple eigenvalue optimizations, and we utilize mode-tracking technology for the single eigenvalue optimization.In addition, we further extend the CS-RBFs parameterized level-set method to an optimization that is performed with geometric constraints, which means that the size and position of the regular holes in the structure can be optimized with the shape and topology. This approach is useful in real-world applications. The effectiveness of this method is demonstrated by several widely investigated examples that have various objectives.     

Compliant mechanism design using multi-objective topology optimization scheme of continuum structures

Topology optimization problems for compliant mechanisms using a density interpolation scheme, the rational approximation of material properties (RAMP) method, and a globally convergent version of the method of moving asymptotes (GCMMA) are primarily discussed. First, a new multi-objective formulation is proposed for topology optimization of compliant mechanisms, in which the maximization of mutual energy (flexibility) and the minimization of mean compliance (stiffness) are considered simultaneously. The formulation of one-node connected hinges, as well as checkerboards and mesh-dependency, is typically encountered in the design of compliant mechanisms. A new hybrid-filtering scheme is proposed to solve numerical instabilities, which can not only eliminate checkerboards and mesh-dependency efficiently, but also prevent one-node connected hinges from occurring in the resulting mechanisms to some extent. Several numerical applications are performed to demonstrate the validity of the methods presented in this paper.     

Dual approach using a variant perimeter constraint and efficient sub-iteration scheme for topology optimization

To prevent numerical instabilities associated with the mesh-dependence, checkerboards and grey regions in topology optimization, a variant perimeter-constrained version of the SIMP algorithm is proposed using a smooth and quadratic function. In order to have an efficient implementation and to make sure the strict satisfaction of such an upper-bound perimeter constraint, a diagonal quadratic approximation of the perimeter constraint is used in the construction of each explicit optimization subproblem. The latter is then solved by a dual sub-iteration scheme. Numerical results show that the incorporation of such a sub-iteration scheme leads to a convergent solution without needs of move-limits or artificial control parameters. In addition to this, it is found that successive relaxations of the perimeter constraint by increasing the upper-bound tend to regularize the topology solution and result in a checkerboard free and satisfactory design solution without grey regions.     

Structural topology optimization of high-voltage transmission tower with discrete variables

In order to solve the structural optimization problem of long-span transmission tower, topology combination optimization (TCO) method and layer combination optimization (LCO) method based on discrete variables are presented, respectively. An adaptive genetic algorithm (AGA) is proposed as optimization algorithm. Four methods: cross-section size optimization (CSSO) method, shape combination optimization (SCO) method, the TCO method and the LCO method, are utilized to optimize the transmission steel tower, respectively. The topology optimization rules are presented for the TCO method, and the layering optimization rules are presented for the LCO method. A high-voltage steel tower is analyzed as a numerical example to illustrate the performance of the proposed methods. The simulation results demonstrate that the calculated results of both the proposed TCO method and the LCO method are obviously better than those of the CSSO method and the SCO method.     

Robust topology optimization using a posteriori error estimator for the finite element method

In our work, we consider the classical density-based approach to the topology optimization. We propose to modify the discretized cost functional using a posteriori error estimator for the finite element method. It can be regarded as a new technique to prevent checkerboards. It also provides higher regularity of solutions and robustness of results.     

Material interface effects on the topology optimizationof multi-phase structures using a level set method

A level set method is used as a framework to study the effects of including material interface properties in the optimization of multi-phase elastic and thermoelastic structures. In contrast to previous approaches, the material properties do not have a discontinuous change across the interface that is often represented by a sharp geometric boundary between material regions. Instead, finite material interfaces with monotonic and non-monotonic property variations over a physically motivated interface zone are investigated. Numerical results are provided for several 2D problems including compliance and displacement minimization of structures composed of two and three materials. The results highlight the design performance changes attributed to the presence of the continuously graded material interface properties.     

Chaos-based medical image encryption scheme using special nonlinear filtering function based LFSR

Multimedia Tools and Applications - In this paper, a new medical image encryption system is proposed using a special nonlinear filter function based linear feedback shift register (LFSR). This...     

A method for shape and topology optimization of truss-like structure

We present a method for the shape and topology optimization of truss-like structure. First, an initial design of a truss-like structure is constructed by a mesh generator of the finite element method because a truss-like structure can be described by a finite element mesh. Then, the shape and topology of the initial structure is optimized. In order to ensure a truss-like structure can be easily manufactured via intended techniques, we assume the beams have the same size of cross-section, and a method based on the concept of the SIMP method is used for the topology optimization. In addition, in order to prevent intersection of beams and zero-length beams, a geometric constraint based on the signed area of triangle is introduced to the shape optimization. The optimization method is verified by several 2D examples. Influence on compliance of the representative length of beams is investigated.     

Reliability-based topology optimization using a standard response surface method for three-dimensional structures

In this paper, a reliability-based topology optimization (RBTO) for 3-D structures was performed using bi-directional evolutionary structural optimization (BESO) and the standard response surface method (SRSM). In order to get a stable optimal topology, the most recently-developed filter scheme was implemented with BESO, and SRSM was used to generate an approximate limit state function. These results were compared with the recently announced results of RBTO for 2-D structures, and the differences between the results for the 3-D and 2-D structures were examined. A cantilever beam and an MBB beam were selected as the numerical examples. The comparison showed that the optimal topologies of deterministic topology optimization (DTO) and RBTO for the 2-D and 3-D MBB beams, respectively, are very different. Specifically, the two-support member on the left hand side comes into being along the width for the 3-D case, but not for the 2-D case. This shows that RBTO for 3-D structures should be performed as part of the design process.