• Smart Structures and Systems
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• v.33 no.3
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• pp.177-188
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• 2024

The fatigue-induced sequential failure of a structure having structural redundancy requires system-level analysis to account for stress redistribution. System reliability-based design optimization (SRBDO) for preventing fatigue-initiated structural failure is numerically costly owing to the inclusion of probabilistic constraints. This study incorporates the Branch-and-Bound method employing system reliability Bounds (termed the B³ method), a failure-path structural system reliability analysis approach, with a metaheuristic optimization algorithm, namely grey wolf optimization (GWO), to obtain the optimal design of structures under fatigue-induced system failure. To further improve the efficiency of this new optimization framework, an additional bounding rule is proposed in the context of SRBDO against fatigue using the B³ method. To demonstrate the proposed method, it is applied to complex problems, a multilayer Daniels system and a three-dimensional tripod jacket structure. The system failure probability of the optimal design is confirmed to be below the target threshold and verified using Monte Carlo simulation. At earlier stages of the optimization, a smaller number of limit-state function evaluation is required, which increases the efficiency. In addition, the proposed method can allocate limited materials throughout the structure optimally so that the optimally-designed structure has a relatively large number of failure paths with similar failure probability.

• Structural Engineering and Mechanics
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• v.3 no.4
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• pp.359-372
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• 1995

This study presents an efficient method for optimum design of plate and shell structures, when the design variables are continuous or discrete. Both sizing and shape design variables are considered. First the structural responses such as element forces are approximated in terms of some intermediate variables. By substituting these approximate relations into the original design problem, an explicit nonlinear approximate design task with high quality approximation is achieved. This problem with continuous variables, can be solved by means of numerical optimization techniques very efficiently, the results of which are then used for discrete variable optimization. Now, the approximate problem is converted into a sequence of second level approximation problems of separable form and each of which is solved by a dual strategy with discrete design variables. The approach is efficient in terms of the number of required structural analyses, as well as the overall computational cost of optimization. Examples are offered and compared with other methods to demonstrate the features of the proposed method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.2
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• pp.223-233
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• 2011

A design optimization problem was formulated to minimize the volume of an RC building structure while satisfying design constraints on structural displacements under vertical, wind and seismic loads. We employed metamodel-based design optimization using design of experiments, metamodeling and optimization algorithm to circumvent the difficulty of the automation of structural analysis procedure. Especially, we proposed a design approach of repetitive design optimizations by stages with changing the side constraint values on design variables and limit values on design constraints until a satisfactory design result was obtained. Using the proposed design approach, the volume of the RC building structure has been reduced by 53.3 % compared to the initial one while satisfying all the design constraints. This design result clearly shows the validity of the proposed design approach.

• Structural Engineering and Mechanics
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• v.7 no.5
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• pp.485-502
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• 1999

Using the continuous Hopfield network model as the basis to solve the general crisp and fuzzy constrained optimization problem is presented and examined. The model lies in its transformation to a parallel algorithm which distributes the work of numerical optimization to several simultaneously computing processors. The method is applied to different structural engineering design problems that demonstrate this usefulness, satisfaction or potential. The computing algorithm has been given and discussed for a designer who can program it without difficulty.

• Journal of Korean Association for Spatial Structures
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• v.19 no.3
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• pp.51-59
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• 2019

A hybrid mid-story seismic isolation system with a smart damper has been proposed to mitigate seismic responses of tall buildings. Based on previous research, a hybrid mid-story seismic isolation system can provide effective control performance for reduction of seismic responses of tall buildings. Structural design of the hybrid mid-story seismic isolation system is generally performed after completion of structural design of a building structure. This design concept is called as an iterative design which is a general design process for structures and control devices. In the iterative design process, optimal design solution for the structure and control system is changed at each design stage. To solve this problem, the integrated optimal design method for the hybrid mid-story seismic isolation system and building structure was proposed in this study. An existing building with mid-story isolation system, i.e. Shiodome Sumitomo Building, was selected as an example structure for more realistic study. The hybrid mid-story isolation system in this study was composed of MR (magnetorheological) dampers. The stiffnessess and damping coefficients of the example building, maximum capacity of MR damper, and stiffness of isolation bearing were simultaneously optimized. Multi-objective genetic optimization method was employed for the simultaneous optimization of the example structure and the mid-story seismic isolation system. The optimization results show that the simultaneous optimization method can provide better control performance than the passive mid-story isolation system with reduction of structural materials.

• Steel and Composite Structures
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• v.18 no.2
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• pp.289-303
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• 2015

This study presents a strategy so-called Subspace Search Mechanism (SSM) for reducing the computational time for convergence of population based metaheusristic algorithms. The selected metaheuristic for this study is the Cuckoo Search algorithm (CS) dealing with size optimization of trusses. The complexity of structural optimization problems can be partially due to the presence of high-dimensional design variables. SSM approach aims to reduce dimension of the problem. Design variables are categorized to predefined groups (subspaces). SSM focuses on the multiple use of the metaheuristic at hand for each subspace. Optimizer updates the design variables for each subspace independently. Updating rules require candidate designs evaluation. Each candidate design is the assemblage of responsible set of design variables that define the subspace of interest. SSM is incorporated to the Cuckoo Search algorithm for size optimizing of three small, moderate and large space trusses. Optimization results indicate that SSM enables the CS to work with less number of population (42%), as a result reducing the time of convergence, in exchange for some accuracy (1.5%). It is shown that the loss of accuracy can be lessened with increasing the order of complexity. This suggests its applicability to other algorithms and other complex finite element-based engineering design problems.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.1344-1349
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• 2007

Biped humanoids maintain their stability through precise controls during locomotion or operation. Dynamic forces are applied to the humanoid structure during locomotion or operation. If the humanoid has weakness from a structural viewpoint, these forces cause severe deformation or vibration of the structure, which can make the humanoid unstable. In this research, a design scenario is proposed to design a robust humanoid structure under the dynamic loads. The pelvis part is selected for design practice. Multibody dynamics is adopted to calculate the dynamic loads and a structural optimization technique is employed to design the pelvis structures. Since it is extremely difficult directly consider the dynamic loads in the optimization process, equivalent static loads are evaluated from the dynamic loads and the design result are discussed.

• Structural Engineering and Mechanics
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• v.6 no.1
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• pp.17-30
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• 1998

The method of pairwise comparison inherently contains information of ambiguity, fuzziness and conflict in design goals for a multiobjective structural design. This paper applies the principle of paired comparison so that the vaguely formulated problem can be modified and a set of numerically acceptable weight would reflect the relatively important degree of multiple objectives. This paper also presents a fuzzy global criterion method ($FGCM_{\lambda}$) included fuzzy constraints that coupled with the objective weighting rank obtained from the modified pairwise comparisons for fuzzy multiobjective optimization problems. Descriptions in sequence of this combined method and problem solving experiences are given in the current article. Multiobjective design examples of truss and mechanical spring structures illustrate this optimization process containing the revising judgement techniques.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.23-27
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• 1997

This paper introduces the structural design optimization of a high speed machining center using multi-step optimization combined with G.A.(Genetic Algorithm) and Weighted Method. In this case, the design problem is to find out the best design variables which minimize the static compliance, the dynamic compliance, and the weight of the machine structure simultaneously. Dimensional thicknesses of the thirteen structural members of the machine structure are adopted as design variables. The first step is the cross-section configuration optimization, in which the area moment of inertia of the cross-section for each structural member is maximized while its area is kept constant The second step is a static design optimization, In which the static compliance and the weight of the machine structure are minimized under some dimensional and safety constraints. The third step IS a dynamic design optimization, where the dynamic compliance and the structure weight are minimized under the same constraints. After optunization, static and dynamic compliances were reduced to 62.3% and 95.7% Eorn the initial design, while the weight of the moving bodies are also in the feaslble range.

• Journal of Ocean Engineering and Technology
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• v.35 no.2
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• pp.131-140
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• 2021

The paper deals with comparative study of various surrogate models based approximate optimization in the structural design of the passive type deck support frame under design load conditions. The passive type deck support frame was devised to facilitate both transportation and installation of 20,000 ton class topside. Structural analysis was performed using the finite element method to evaluate the strength performance of the passive type deck support frame in its initial design stage. In the structural analysis, the strength performances were evaluated for various design load conditions. The optimum design problem based on surrogate model was formulated such that thickness sizing variables of main structure members were determined by minimizing the weight of the passive type deck support frame subject to the strength performance constraints. The surrogate models used in the approximate optimization were response surface method, Kriging model, and Chebyshev orthogonal polynomials. In the context of numerical performances, the solution results from approximate optimization were compared to actual non-approximate optimization. The response surface method among the surrogate models used in the approximate optimization showed the most appropriate optimum design results for the structure design of the passive type deck support frame.