• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.637-644
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• 2010

This paper presents a reliability-based shape optimization (RBSO) using the growth-strain method. An actual design involves uncertain conditions such as material property, operational load, Poisson's ratio and dimensional variation. The purpose of the RBSO is to consider the variations of probabilistic constraint and performances caused by uncertainties. In this study, the growth-strain method was applied to shape optimization of reliability analysis. Even though many papers for reliability-based shape optimization in mathematical programming method and ESO (Evolutionary Structural Optimization) were published, the paper for the reliability-based shape optimization using the growth-strain method has not been applied yet. Growth-strain method is applied to performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints in the change of average mises stress. Numerical examples are presented to compare the DO with the RBSO. The results of design example show that the RBSO model is more reliable than deterministic optimization. It was verified that the reliability-based shape optimization using growth-strain method are very effective for general structure. The purpose of this study is to improve structure's safety considering probabilistic variable.

• International Journal of Automotive Technology
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• v.8 no.1
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• pp.93-102
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• 2007

The frontal crash optimization of an engine room member using the response surface method was studied. The engine room member is composed of the front side member and the sub-frame. The thicknesses of the panels on the front side member and the sub-frame were selected as the design variables. The purpose of the optimization was to reduce the weight of the structure, under the constraint that the objective quantity of crash energy is absorbed. The response surface method was used to approximate the crash behavior in mathematical form for optimization procedure. To research the effect of the regression method, two different methodologies were used in constructing the response surface model, the least square method and the moving least square method. The optimum with the two methods was verified by the simulation result. The precision of the surrogate model affected the optimal design. The moving least square method showed better approximation than the least square method. In addition to the deterministic optimization, the reliability-based design optimization using the response surface method was executed to examine the effect of uncertainties in design variables. The requirement for reliability made the optimal structure be heavier than the result of the deterministic optimization. Compared with the deterministic optimum, the optimal design using the reliability-based design optimization showed higher crash energy absorption and little probability of failure in achieving the objective.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.157-162
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• 2007

A new level set based topology optimization employing inner-front creation algorithm is presented. In the conventional level set based topology optimization, the optimum topology strongly depends on the initial level set distribution due to the incapability of inner-front creation during optimization process. In the present work, in this regard, an inner-front creation algorithm is proposed. in which the sizes. shapes. positions, and number of new inner-fronts during the optimization process can be globally and consistently identified by considering both the value of a given criterion for inner-front creation and the occupied volume (area) of material domain. To facilitate the inner-front creation process, the inner-front creation map which corresponds to the discrete valued criterion of inner-front creation is applied to the level set function. In order to regularize the design domain during the optimization process, the edge smoothing is carried out by solving the edge smoothing partial differential equation (PDE). Updating the level set function during the optimization process, in the present work, the least-squares finite element method (LSFEM) is employed. As demonstrative examples for the flexibility and usefulness of the proposed method. the level set based topology optimization considering lightweight design of 3D shell structure is carried out.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.145-146
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• 2010

• Architectural research
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• v.17 no.1
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• pp.31-40
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• 2015

A simple force-finding process based on an optimization technique is proposed for tensegrity structures. For this purpose, the inverse problem of form-finding process is formulated. Therefore, the position vector of nodes and element connectivity information are provided as priori. Several benchmark tests are carried out to demonstrate the performance of the present force-finding process. In particular, the force density distributions of simplex tensegrity are thoroughly investigated with the important parameters such as the radius, height and twisting angle of simplex tensegrity. Finally, the force density distribution of arch tensegrity is produced by using the present force-finding process for a future reference solution.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.655-656
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• 2008

This research presents a topology optimization to minimize eddy current loss maintaining mechanical robustness of structure part in electrical machines A design sensitivity equation for the topology optimization is derived by employing the discrete system equations combined with the adjoint variable method. As a numerical example, frame design of a C-core actuator is performed by the proposed method.

• Bulletin of the Society of Naval Architects of Korea
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• v.17 no.4
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• pp.46-54
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• 1980

The ship structural design problem is formulated as a general nonlinear optimization problem with constraints. Characteristics of the general structural problems and various optimization techniques are discussed, with special emphasis on penalty function method for constrained problems. A simple example of the solution of a midship structure design of cargo vessel, which complies with the rules of the Korean Register of Shipping is shown using SUMT-exterior method with some search methods.

• Earthquakes and Structures
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• v.25 no.6
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• pp.399-415
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• 2023

In this study, we investigate the use of a negative stiffness tuned inerter damper system to improve the performance of a base-isolated structure. The negative stiffness tuned inerter damper system consists of a tuned inerter damper connected in parallel with a negative stiffness element. To find the optimal parameters for the base-isolated structure with negative stiffness tuned inerter damper system, we develop an optimization method based on performance criteria. The objective of the optimization is to minimize the superstructure acceleration response ratio, while ensuring that the base displacement response ratio remains below a specified target value. We evaluate the proposed method by conducting numerical analyses on an eight-story building. The structure is modeled using both a simplified 3-degree-of-freedom system and a more detailed story-by-story shear-beam model. Lastly, a comparative analysis using time history analysis is performed to compare the performance of the base-isolated structure with negative stiffness tuned inerter damper system with that of the base-isolated structure and base-isolated structure with tuned inerter damper systems. The results obtained from the comparative analysis show that the negative stiffness tuned inerter damper system outperforms the tuned inerter damper system in reducing the dynamic seismic response of the base-isolated structure. Overall, this study demonstrates that the negative stiffness tuned inerter damper system can effectively enhance the performance of base-isolated structures, providing improved seismic response reduction compared to other systems.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.405-406
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• 2007

• ETRI Journal
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• v.33 no.1
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• pp.39-49
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• 2011

A new structure learning approach for Bayesian networks based on asexual reproduction optimization (ARO) is proposed in this paper. ARO can be considered an evolutionary-based algorithm that mathematically models the budding mechanism of asexual reproduction. In ARO, a parent produces a bud through a reproduction operator; thereafter, the parent and its bud compete to survive according to a performance index obtained from the underlying objective function of the optimization problem: This leads to the fitter individual. The convergence measure of ARO is analyzed. The proposed method is applied to real-world and benchmark applications, while its effectiveness is demonstrated through computer simulations. Results of simulations show that ARO outperforms genetic algorithm (GA) because ARO results in a good structure and fast convergence rate in comparison with GA.