摘要 :
Topology optimization has become very popular in industrial applications, and most FEM codes have implemented certain capabilities of topology optimization. However, most codes do not allow simultaneous treatment of sizing and sha...
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Topology optimization has become very popular in industrial applications, and most FEM codes have implemented certain capabilities of topology optimization. However, most codes do not allow simultaneous treatment of sizing and shape optimization during the topology optimization phase. This poses a limitation on the design space and therefore prevents finding possible better designs since the interaction of sizing and shape variables with topology modification is excluded. In this paper, an integrated approach is developed to provide the user with the freedom of combining sizing, shape, and topology optimization in a single process.
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A novel optimization method, stiffness spreading method (SSM), is proposed for layout optimization of truss structures. In this method, stiffness matrices of the bar elements in a truss structure are represented by a set of equiva...
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A novel optimization method, stiffness spreading method (SSM), is proposed for layout optimization of truss structures. In this method, stiffness matrices of the bar elements in a truss structure are represented by a set of equivalent stiffness matrices which are embedded in a weak background mesh. When the proposed method is used, it is unnecessary for the bar elements in a truss structure to be connected to each other during the optimization process, and each of the bar elements can move independently in the design domain to form an optimized design. Another feature of the method is that the sensitivity analysis can be done analytically, making gradient based optimization algorithms applicable in the solution. This method realizes the size, shape and topology design optimization of truss structures simultaneously and allows for more flexibility in topology change. Numerical examples illustrate the feasibility and effectiveness of the proposed method.
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While the weight of a steel structure is a major component of the total cost, the minimization of the cost should be the final objective for optimum use of available resources. The total cost of a steel structure includes (a) the ...
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While the weight of a steel structure is a major component of the total cost, the minimization of the cost should be the final objective for optimum use of available resources. The total cost of a steel structure includes (a) the material cost of structural members such as beams, columns, and bracings, (b) the fabrication cost including the material costs of connection elements, bolts, and electrodes and the labor cost, (c) the cost of transporting the fabricated pieces to the construction field, and (d) the erection cost including the material costs of connection elements, bolts, and electrodes and the labor cost. In this article, a chronological review of the journal articles on cost optimization of steel structures is presented. Articles on deterministic, reliability-based, and fuzzy logic-based optimization of steel structures are reviewed. Research on cost optimization can encourage the use of the optimization approach in structural steel design practice by providing a more realistic way of modeling structural steel design and resulting in additional savings compared with the weight optimization problem.
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A very simple method for finding the minimum weight of a structure designed from a list of available parameters is presented. The structure can be subjected to multiple loading conditions with constraints imposed on displacements,...
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A very simple method for finding the minimum weight of a structure designed from a list of available parameters is presented. The structure can be subjected to multiple loading conditions with constraints imposed on displacements, stresses and eigenfrequency. The method consists of a recursive removal of redundant material, starting from the heaviest structure. The number of analyses required is a factor of 10{sup}2 less than for most stochastic methods. The knowledge needed for application of the method is limited to the finite-element method.
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In this paper, plasma generation optimization (PGO) as a newly developed physics-based metaheuristic algorithm is applied to perform the size, layout, and topology optimization problems of skeletal structures. PGO is a population-...
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In this paper, plasma generation optimization (PGO) as a newly developed physics-based metaheuristic algorithm is applied to perform the size, layout, and topology optimization problems of skeletal structures. PGO is a population-based optimizer inspired by the process of plasma generation. In this optimization method, each agent is modeled as an electron. The movement of electrons and changing their energy level are performed based on simulating the process of excitation, de-excitation, and ionization. These processes occur iteratively through the plasma generation. Evaluating the robustness and performance of the PGO is illustrated through six design examples for different types of structural optimization. The results reveal that the PGO algorithm outperforms other state-of-the-art optimization techniques considered from the literature.
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Commonly available optimization methods typically produce a single optimal design as a constrained minimum of a particular objective function. However, in engineering design practice it is quite often important to explore as much ...
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Commonly available optimization methods typically produce a single optimal design as a constrained minimum of a particular objective function. However, in engineering design practice it is quite often important to explore as much of the design space as possible, with respect to many attributes, to discover what behaviors are possible and not possible within the initially adopted design concept. This paper shows that the very simple method of the sum of weighted objectives is useful for such exploration. By geometrical argument it is demonstrated that if every weighting coefficient is allowed to change its magnitude and its sign then the method returns a set of designs that are all feasible, diverse in their attributes, and include the Pareto and non-Pareto solutions, at least for convex cases. Numerical examples in the paper include the case of an aircraft wing structural box with thousands of degrees of freedom and constraints, and over 100 design variables, whose attributes are structural mass, volume, displacement, and frequency. The weighted coefficients method is inherently suitable for parallel, coarse-grained implementation that enables exploration of the design space in the elapsed time of a single structural optimization.
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The current study proposes a new metaheuristic algorithm based on the clan behavior of elephants, called elephant clan optimization (ECO), to solve structural optimization problems. This method is a new version of the previously d...
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The current study proposes a new metaheuristic algorithm based on the clan behavior of elephants, called elephant clan optimization (ECO), to solve structural optimization problems. This method is a new version of the previously developed algorithm; namely, the elephant herding optimization (EHO). While the EHO algorithm has been inspired by the behavior of elephants, the theory behind this method is based on the herding behavior of the elephants, and also the selection of random members to replace the worst members, which is far from the real-life behavior of this animal. Since elephants are animals with powerful memories and a high capability for learning, it seems that by accurately modeling the real-life behavior of this animal, a more powerful algorithm can be developed. The proposed ECO algorithm attempts to simulate the most essential individual and collective behaviors of elephants. The performance of the ECO method is evaluated by solving several structural optimization problems, including the size optimization of truss structures. The findings of the study confirm the reliable performance of the proposed ECO algorithm to expedite the convergence rate and achieve superior solutions in comparison with the EHO. Moreover, the ECO method produces better or very competitive results by consuming less computational effort compared to well-known metaheuristic methods.
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This review presents developed models, theory, and numerical methods for structural optimization of trusses with discrete design variables in the period 1968 - 2014. The comprehensive reference list collects, for the first time, t...
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This review presents developed models, theory, and numerical methods for structural optimization of trusses with discrete design variables in the period 1968 - 2014. The comprehensive reference list collects, for the first time, the articles in the field presenting deterministic optimization methods and meta heuristics. The field has experienced a shift in focus from deterministic methods to meta heuristics, i.e. stochastic search methods. Based on the reported numerical results it is however not possible to conclude that this shift has improved the competences to solve application relevant problems. This, and other, observations lead to a set of recommended research tasks and objectives to bring the field forward. The development of a publicly available benchmark library is urgently needed to support development and assessment of existing and new heuristics and methods. Combined with this effort, it is recommended that the field begins to use modern methods such as performance profiles for fair and accurate comparison of optimization methods. Finally, theoretical results are rare in this field. This means that most recent methods and heuristics are not supported by mathematical theory. The field should therefore re-focus on theoretical issues such as problem analysis and convergence properties of new methods.
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The focus of this study is two-dimensional optimization problem of fillets and holes in plates considering curvature constraints, defined with the goal of minimizing stress concentration factor. The optimality criteria of uniform ...
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The focus of this study is two-dimensional optimization problem of fillets and holes in plates considering curvature constraints, defined with the goal of minimizing stress concentration factor. The optimality criteria of uniform energy density are extended to shape optimization with curvature constraint assuming that a good shape design can be obtained when constant energy density along the segment of the designed boundary is achieved, except for the section that has to satisfy the geometry constraint. Feasible solutions are sought out under the assumption that the minimum curvature radius is constant on the last part of the designed boundary, and some interesting features of optimal shape of fillets and holes with prescribed minimum curvature radii are revealed. A finite-element-based method in conjunction with a gradientless algorithm is developed to obtain the optimal shape with curvature constraint. Numerical examples of optimal fillets and holes in flat plates are presented to validate the proposed assumption.
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Evolutionary Structural Optimization (ESO) method is one of the most powerful and promising technique for pursuing the optimal structural form among the other methods as the homogenization design technique and the bubble method. A...
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Evolutionary Structural Optimization (ESO) method is one of the most powerful and promising technique for pursuing the optimal structural form among the other methods as the homogenization design technique and the bubble method. Although it is easy to carry out the calculation of ESO, there have been remained some weak points in its evolutionary process, by which inefficiency of calculation is caused or unreasonable solutions are concluded. A new method through theusage of the contour lines is proposed in order to remove such defects of the usual ESO as well as to enable the structures to not only be scraped off but also grow up toward the final optimal structures. Some numerical examples clearly show the effectiveness of the proposed scheme.
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