• Journal of Fisheries and Marine Sciences Education
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• v.29 no.2
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• pp.544-551
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• 2017

Metaheuristic algorithms are efficient techniques for a class of mathematical optimization problems without having to deeply adapt to the inherent nature of each problem. They are very useful for structural design optimization in which the cost of gradient computation can be very expensive. Among them, the characteristics of simulated annealing and genetic algorithms are briefly discussed. In Metropolis genetic algorithm, favorable features of Metropolis criterion in simulated annealing are incorporated in the reproduction operations of simple genetic algorithm. Numerical examples of structural design optimization are presented. The example structures are truss, breakwater and steel box girder bridge. From the theoretical evaluation and numerical experience, performance and applicability of metaheuristic algorithms for structural design optimization are discussed.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.4
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• pp.529-538
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• 2010

This paper presents a reliability-based topology optimization (RBTO) based on bidirectional evolutionary structural optimization (BESO). In design of a structure, uncertain conditions such as material property, operational load and dimensional variation should be considered. Deterministic topology optimization (DTO) is performed without considering the uncertainties related to the design variables. However, the RBTO can consider the uncertainty variables because it can deal with the probabilistic constraints. The reliability index approach (RIA) and the performance measure approach (PMA) are adopted to evaluate the probabilistic constraints in this study. In order to apply the BESO to the RBTO, sensitivity number for each element is defined as the change in the reliability index of the structure due to removal of each element. Smoothing scheme is also used to eliminate checkerboard patterns in topology optimization. The limit state indicates the margin of safety between the resistance (constraints) and the load of structures. The limit State function expresses to evaluate reliability index from finite element analysis. Numerical examples are presented to compare each optimal topology obtained from RBTO and DTO each other. It is verified that the RBTO based on BESO can be effectively performed from the results.

• Advances in Computational Design
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• v.6 no.1
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• pp.15-30
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• 2021

With improvement in innovative manufacturing technologies, it became possible to fabricate any complex shaped structural design for practical applications. This allows for the fabrication of curvilinearly stiffened pressure vessels and pipes. Compared to straight stiffeners, curvilinear stiffeners have shown to have better structural performance and weight savings under certain loading conditions. In this paper, an optimization framework for designing curvilinearly stiffened composite pressure vessels and pipes is presented. NURBS are utilized to define curvilinear stiffeners over the surface of the pipe. An integrated tool using Python, Rhinoceros 3D, MSC.PATRAN and MSC.NASTRAN is implemented for performing the optimization. Rhinoceros 3D is used for creating the geometry, which later is exported to MSC.PATRAN for finite element model generation. Finally, MSC.NASTRAN is used for structural analysis. A Bi-Level Programming (BLP) optimization technique, consisting of Particle Swarm Optimization (PSO) and Gradient-Based Optimization (GBO), is used to find optimal locations of stiffeners, geometric dimensions for stiffener cross-sections and layer thickness for the composite skin. A cylindrical pipe stiffened by orthogonal and curvilinear stiffeners under torsional and bending load cases is studied. It is seen that curvilinear stiffeners can lead to a potential 10.8% weight saving in the structure as compared to the case of using straight stiffeners.

• Structural Engineering and Mechanics
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• v.53 no.5
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• pp.847-865
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• 2015

This paper presents the application of a recently developed meta-heuristic algorithm, called Colliding Bodies Optimization (CBO), for size and topology optimization of steel trusses. This method is based on the one-dimensional collisions between two bodies, where each agent solution is considered as a body. The performance of the proposed algorithm is investigated through four benchmark trusses for minimum weight with static and dynamic constraints. A comparison of the numerical results of the CBO with those of other available algorithms indicates that the proposed technique is capable of locating promising solutions using lesser or identical computational effort, with no need for internal parameter tuning.

• Structural Engineering and Mechanics
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• v.62 no.3
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• pp.259-272
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• 2017

In this study, recently developed swarm intelligence algorithm called Social Spider Optimization (SSO) approach and its enhanced version of SSO algorithm with spider jump techniques is used to develop a structural optimization technique for steel space structures. The improved version of SSO uses adaptive randomness probability in generating new solutions. The objective function of the design optimization problem is taken as the weight of a steel space structure. Constraints' functions are implemented from American Institute of Steel Construction-Load Resistance factor design (AISC-LRFD) and Ad Hoc Committee report and practice which cover strength, serviceability and geometric requirements. Three steel space structures are optimized using both standard SSO and SSO with spider jump (SSO_SJ) algorithms and the results are compared with those available in the literature in order to investigate the performance of the proposed algorithms.

• Structural Engineering and Mechanics
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• v.58 no.6
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• pp.1109-1126
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• 2016

The present paper focuses on size optimization of double layer barrel vaults considering nonlinear behavior. In order to tackle the optimization problem an improved colliding bodies optimization (ICBO) algorithm is proposed. The important task that should be achieved before optimization of structural systems is to determine the best form having the least cost. In this study, an attempt is done to find the best form then it is optimized considering linear and non-linear behaviors. In the optimization process based on nonlinear behavior, the geometrical and material nonlinearity effects are included. A large-scale double layer barrel vault is presented as the numerical example of this study and the obtained results indicate that the proposed ICBO has better computational performance compared with other algorithms.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.6
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• pp.547-556
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• 2014

This paper discusses a one-way fluid structural interaction (FSI) analysis and shape optimization of the impeller blades for a 15,000 HP centrifugal compressor using the response surface method (RSM). Because both the aerodynamic performance and the structural safety of the impeller are affected by the shape of its blades, shape optimization is necessary using the FSI analysis, which includes a structural analysis for the induced fluid pressure and centrifugal force. The FSI analysis is performed in ANSYS Workbench: ANSYS CFX is used for the flow field and ANSYS Mechanical is used for the structural field. The response surfaces for the FSI results (efficiency, pressure ratio, maximum stress, etc.) generated based on the design of experiments (DOE) are used to find an optimal shape for the impeller blades, which provides the maximum aerodynamic performance subject to the structural safety constraints.

• Structural Engineering and Mechanics
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• v.42 no.3
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• pp.335-352
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• 2012

Particle Swarm Optimization (PSO) is a stochastic population based optimization algorithm which has attracted attentions of many researchers. This method has great potentials to be applied to many optimization problems. Despite its robustness the standard version of PSO has some drawbacks that may reduce its performance in optimization of complex structures such as laminated composites. In this paper by suggesting a new variation scheme for acceleration parameters and inertial weight factors of PSO a novel optimization algorithm is developed to enhance the basic version's performance in optimization of laminated composite structures. To verify the performance of the new proposed method, it is applied in two multi-objective design optimization problems of laminated cylindrical. The numerical results from the proposed method are compared with those from two other conventional versions of PSO-based algorithms. The convergancy of the new algorithms is also compared with the other two versions. The results reveal that the new modifications inthe basic forms of particle swarm optimization method can increase its convergence speed and evade it from local optima traps. It is shown that the parameter variation scheme as presented in this paper is successful and can evenfind more preferable optimum results in design of laminated composite structures.

• Structural Engineering and Mechanics
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• v.86 no.2
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• pp.249-260
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• 2023

The uncertainties involved in structural performances are of importance when the optimum number and property of seismic retrofit devices are determined. This paper proposes a seismic retrofit design framework for asymmetric soft-first-story buildings, considering uncertainties in the soil condition and seismic retrofit device. The effect of the uncertain parameters on the structural performance is used to find a robust and optimal seismic retrofit solution. The framework finds a robust and optimal seismic retrofit solution by finding the optimal locations and mechanical properties of the seismic retrofit device for different realizations of the uncertain parameters. The structural performance for each realization is computed to evaluate the effect of the uncertainty parameters on the seismic performance. The framework utilizes parallel processing to decrease the computationally intensive nonlinear dynamic analysis time. The framework returns a robust design solution that satisfies the given limit state for every realization of the uncertain parameters. The proposed framework is applied to the seismic retrofit design of a five-story asymmetric soft-first-story case study structure retrofitted with a viscoelastic damper. Robust optimal parameters for retrofitting a structure to satisfy the limit state for the different realizations of the uncertain parameter are found using the proposed framework. According to the performance evaluation results of the retrofitted structure, the developed framework is proved effective in the seismic retrofit of the asymmetric structure with inherent uncertainties.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.1
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• pp.31-43
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• 2021

In this study, approximate design optimization using various meta-models was performed for the structural design of active type deck support frame. The active type deck support frame was newly developed to facilitate both transportation and installation of 20,000 ton class offshore plant topside. Structural analysis was carried out using the finite element method to evaluate the strength performance of the active type deck support frame in its initial design stage. In the structural analysis, the strength performances were evaluated for various design load conditions that were regulated in ship classification organization. The approximate optimum design problem based on meta-model was formulated such that thickness sizing variables of main structure members were determined by achieving the minimum weight of the active type deck support frame subject to the strength performance constraints. The meta-models used in the approximate design optimization were response surface method, Kriging model, and Chebyshev orthogonal polynomials. The results from approximate design optimization were compared to actual non-approximate design optimization. The Chebyshev orthogonal polynomials among the meta-models used in the approximate design optimization represented the most pertinent optimum design results for the structure design of the active type deck support frame.