• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.11
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• pp.973-982
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• 2007

In this paper, optimal design framework is developed by automatic mesh generation and PSO(Particle Swarm Optimization) algorithm based on parallel computing environment and applied to structural optimal design of satellite adapter module. By applying automatic mesh generation, it became possible to change the structural shape of adapter module. PSO algorithm was merged with parallel computing environment and for maximizing a computing performance, asynchronous PSO algorithm was developed and could reduce the computing time of optimization process. As constraint conditions, eigen-frequency and maximum stress was considered. Finally using optimal design framework, weight reduction of satellite adapter module is derived with satisfaction of structural safety.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.21 no.12
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• pp.1063-1070
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• 2008

The performance of an acoustic transducer is determined by the effects of many design variables, and mostly the influences of these design variables are not linearly independent of each other. To achieve the optimal performance of an acoustic transducer, we must consider the cross-coupled effects of the design variables. In this study, the variation of the performances of underwater acoustic transducer in relation to its structural variables was analyzed. In addition, the new optimal design scheme of an acoustic transducer that could reflect not only individual but also all the cross-coupled effects of multiple structural variables, and could determine the detailed geometry of the transducer with great efficiency and rapidity was developed. The validation of the new optimal design scheme was verified by applying the optimal structure design of a flextensional transducer which are the most common use for high power underwater acoustic transducer. With the finite element analysis(FEA), we analyzed the variation of the resonance frequency, sound pressure, and working depth of a flextensional transducer in relation to its design variables. Through statistical multiple regression analysis of the results, we derived functional forms of the resonance frequency, sound pressure, and working depth in terms of the design variables. By applying the constrained optimization technique, Sequential Quadratic Programming Method of Phenichny and Danilin(SQP-PD), to the derived function, we designed and verified the optimal structure of the Class IV flextensional transducer that could provide the highest sound pressure level and highest working depth at a given operation frequency of 1 kHz.

• Journal of Korean Society of Steel Construction
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• v.18 no.3
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• pp.361-371
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• 2006

In recent years, to overcome drawbacks related to the aplicati on of classical structural optimization algorithms, various drift design methods based on factores of member displacement participation factors have been developed to size members if they satisfy stiffness criteria. In particular, a resizing algorithm based on dynamic displacement participation factors from the response spectrum analysis has been applied in the drift design of steel structures subjec ted to seismic lateral forces. In this aproach, active members are selected for displacement control based on the displacement participation fa ve members may be taken out and added to the active members for the drift control. The resizing algorithm can be practically and effectively applied to drift design of high-rise buildings however, the inelastic behavior o f the resizing algorithm has not ben evaluated yet. To develop the resizing algorithm considering the performance of nonlinearity as well a s elastic stifness, the evaluation model of resizing algorithm s is developed and aplied to the examples of moment-resisting steel frame, which is one of the simplest structural systems. The inelastic behavior of moment-resisting steel frame designed by the resizing algorithm is also discussed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2352-2360
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• 2011

In this paper, we introduce a comprehensive design methodology of Radial Basis Function Neural Networks (RBFNN) that is based on mechanism of clustering and optimization algorithm. We can divide some clusters based on similarity of input dataset by using clustering algorithm. As a result, the number of clusters is equal to the number of nodes in the hidden layer. Moreover, the centers of each cluster are used into the centers of each receptive field in the hidden layer. In this study, we have applied Fuzzy-C Means(FCM) and K-Means(KM) clustering algorithm, respectively and compared between them. The weight connections of model are expanded into the type of polynomial functions such as linear and quadratic. In this reason, the output of model consists of relation between input and output. In order to get the optimal structure and better performance, Particle Swarm Optimization(PSO) is used. We can obtain optimized parameters such as both the number of clusters and the polynomial order of weights connection through structural optimization as well as the widths of receptive fields through parametric optimization. To evaluate the performance of proposed model, NXT equipment offered by National Instrument(NI) is exploited. The situation awareness system-related intelligent model was built up by the experimental dataset of distance information measured between object and diverse sensor such as sound sensor, light sensor, and ultrasonic sensor of NXT equipment.

• Transactions of the Society of Information Storage Systems
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• v.2 no.2
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• pp.130-137
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• 2006

The HDD(hard disk drive) using Load/unload(L/UL) technology includes the benefits which are increased areal density, reduced power consumption and improved shock resistance than those of contact-start-stop(CSS). It has been widely used in portable hard disk drive and will become the key technology for developing the small form factor hard disk drive. The main objects of L/UL are no slider-disk contact or no media damage. For realizing those, we must consider many design parameters in L/UL system. In this paper, we focus on lift-off force. The 'lift-off' force, defined as the minimum air bearing force, is another very important indicator of unloading performance. A large amplitude of lift-off force increases the ramp force, the unloading time, the slider oscillation and contact-possibility. To minimize 'lift-off' force we optimizes the slider and suspension using the integrated optimization frame, which automatically integrates the analysis with the optimization and effectively implements the repetitive works between them. In particular, this study is carried out the optimal design considering the process of modes tracking through the entire optimization processes. As a result, we yield the equation which can easily find a lift-off force and structural optimization for suspension.

• Composites Research
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• v.13 no.2
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• pp.61-71
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• 2000

Today, the use of composite materials become an essential part in the design and manufacturing process of the flight vehicles to reduce the structural weight. Since the structural properties can be varied largely due to the stacking sequence of ply angles, it is very important problem to determine the optimized ply angles under a design objective. Thus, in this study, the analysis of static aeroelastic optimization of a composite wing has been performed. An analytical system to calculate and optimize tile aero-structural equilibrium position has been developed and incorporated with the genetic algorithm. The effects of stacking sequence on the structural deformation and aerodynamic distribution have been studied and calculated with the condition of minimum structural deformation for a swept-back composite wing. For the set of practical stacking angles, the design results to maximize the performance of static aeroelasticity are also presented.

• Structural Engineering and Mechanics
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• v.19 no.1
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• pp.107-121
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• 2005

The suboptimal control rule is introduced in structural control implementation as an alternative over the optimal control because the optimal control may require large amount of processing time when applied to complex structural control problems. It is well known that any time delay in structural control implementation will cause un-synchronized application of the control forces, which not only reduce the effectiveness of an active control system, but also cause instability of the control system. The effect of time delay on the displacement and acceleration responses of building structures is studied when the suboptimal control rule is adopted. Two examples are given to show the effectiveness of the suboptimal control rule. It is shown through the examples that the present method is easy in implementation and high in efficiency and it can significantly reduce the time delay in structural control implementation without significant loss of performance.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.3
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• pp.159-165
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• 2021

This study introduces a topology optimization method for the simultaneous design of macro-scale structural configuration and unit structure variation to ensure effective heat conduction. Shape changes in the unit structure depending on its location within the macro-scale structure result in micro- as well as macro-scale design and enable better performance than using isotropic unit structures. They result in functionally graded composite structures combining both configurations. The representative volume element (RVE) method is applied to obtain various thermal conductivity properties of the multi-material based unit structure according to its shape change. Based on the RVE analysis results, the material properties of the unit structure having a certain shape can be derived using machine learning. Macro-scale topology optimization is performed using the traditional solid isotropic material with penalization method, while the unit structures composing the macro-structure can have various shapes to improve the heat conduction performance according to the simultaneous optimization process. Numerical examples of the thermal compliance minimization issue are provided to verify the effectiveness of the proposed method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.14 no.4
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• pp.495-503
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• 2001

In a functionally graded materials(FGM), two constituent material particles are mixed up according to a specific volume fraction distribution so that its thermoelastic behavior is definitely characterized by such a material composition distribution. Therefore, the designer should determine the most suitable volume fraction distribution in order to design a FGM that optimally meets the desired performance against the given constraints. In this paper, we address a numerical optimization procedure, with employing interior penalty function method(IPFM) and FDM, for optimizing 2D volume fractions of heat-resisting FGMs composed of metal and ceramic. We discretize a FGM domain into finite number of homogenized rectangular cells of single design variable in order for the optimization efficiency. However, after the optimization process, we interpolate the discontinuous volume fraction with globally continuous bilinear function in order to enforce the continuity of volume fraction distributions.

• Steel and Composite Structures
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• v.24 no.2
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• pp.227-237
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• 2017

This paper presents optimization of a long-span portal steel frame under dynamic wind loads using a surrogate-assisted evolutionary algorithm. Long-span portal steel frames are often used in low-rise industrial and commercial buildings. The structure needs be able to resist the wind loads, and at the same time it should be as light as possible in order to be cost-effective. In this work, numerical model of a portal steel frame is constructed using structural analysis program (SAP2000), with the web-heights at five locations of I-sections of the columns and rafters as the decision variables. In order to evaluate the performance of a given design under dynamic wind loading, the equivalent static wind load (ESWL) is obtained from a database of wind pressures measured in wind tunnel tests. A modified formulation of the problem compared to the one available in the literature is also presented, considering additional design constraints for practicality. Evolutionary algorithms (EA) are often used to solve such non-linear, black-box problems, but when each design evaluation is computationally expensive (e.g., in this case a SAP2000 simulation), the time taken for optimization using EAs becomes untenable. To overcome this challenge, we employ a surrogate-assisted evolutionary algorithm (SAEA) to expedite the convergence towards the optimum design. The presented SAEA uses multiple spatially distributed surrogate models to approximate the simulations more accurately in lieu of commonly used single global surrogate models. Through rigorous numerical experiments, improvements in results and time savings obtained using SAEA over EA are demonstrated.