• Journal of the Korean Society for Precision Engineering
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• v.30 no.11
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• pp.1179-1185
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• 2013

In this study, the design optimization of the automotive side member is performed to maximize the crash energy absorption efficiency per unit weight. Design parameters which seriously influence on the frontal crash performance are selected through the sensitivity analysis using the Plackett-Burman design method. And also the design variables, which are determined from the sensitivity analysis, are optimized by two methods. One is conventional approximate optimization method which uses the statistical design of experiments (DOE) and response surface method (RSM). The other is a methodology derived from previous work by the authors, which is called sequential design of experiments (SDOE), to reduce a trial and error procedure and to find an appropriate condition for using micro-genetic algorithm. The proposed optimization technique shows that the automotive side member structure can be designed considering the frontal crash performance.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.225-230
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• 2003

Many port states such as New Zealand, the USA, Australia and Canada have strict regulations to prevent ships which arrive in their port from discharging polluted ballast water which contain harmful aquatic organisms and pathogens. They are notified that transfer of polluted ballast water can cause serious injury to public health and damage to property and environment. For this reason, they perceived that the ballast exchange in deep sea is the most effective method, together with submitting the ballast management plan which contains the effective exchange method, ballast system and safety consideration. In this study, we make an effort to develop optimum ballast water exchange management and in result of that, it provide more convenient and stable process for preparing ballast water management plan.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.82-96
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• 2019

A semi-submersible structure has been widely used for offshore drilling and production of oil and gas. The small water plane area makes the structure very sensitive to weight increase in terms of payload and stability. Therefore, it is necessary to lighten the substructure from the early design stage. This study aims at an optimization of hull structure based on a sophisticated yield and buckling strength in accordance with classification rules. An in-house strength assessment system is developed to automate the procedure such as a generation of buckling panels, a collection of required panel information, automatic buckling and yield check and so on. The developed system enables an automatic yield and buckling strength check of all panels composing the hull structure at each iteration of the optimization. Design variables are plate thickness and stiffener section profiles. In order to overcome the difficulty of large number of design variables and the computational burden of FE analysis, various methods are proposed. The steepest descent method is selected as the optimization algorithm for an efficient search. For a reduction of the number of design variables and a direct application to practical design, the stiffener section variable is determined by selecting one from a pre-defined standard library. Plate thickness is also discretized at 0.5t interval. The number of FE analysis is reduced by using equations to analytically estimating the stress changes in gradient calculation and line search steps. As an endeavor to robust optimization, the number of design variables to be simultaneously optimized is divided by grouping the scantling variables by the plane. A sequential optimization is performed group by group. As a verification example, a central column of a semi-submersible structure is optimized and compared with a conventional optimization of all design variables at once.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.6 s.177
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• pp.1616-1623
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• 2000

A diaphragm spring is an important component of a clutch assembly, characteristics of which depends largely on that of a diaphragm spring. A diaphragm spring is subject to high stress concentration in driving condition, which frequently causes cracks and fracture around finger area. In this paper, behavior of a diaphragm spring is analysed by finite element method to calculate sensitivity of design parameters, which is used to perform optimal design of diaphragm spring shape. As an object function, hoop stresses are taken and minimized to improve durability. Characteristics of the diaphragm is used as equality constraint to maintain the original design purpose and sequential linear programming(SLP) is utilized as an optimization tool. With optimized design, it is verified that concentrated stress is decreased maintaining release load characteristic.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.747-752
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• 2011

HMMs (Hidden Markov Models) are widely used for biological signal, such as EEG (electroencephalogram) sequence, analysis because of their ability to incorporate sequential information in their structure. A recent trends of research are going after the biological interpretable HMMs, and we need to control the complexity of the HMM so that it has good generalization performance. So, an automatic means of optimizing the structure of HMMs would be highly desirable. In this paper, we described a procedure of classification of motor imagery EEG signals using HMM. The motor imagery related EEG signals recorded from subjects performing left, right hand and foots motor imagery. And the proposed a method that was focus on the validation of the HSA (Harmony Search Algorithm) based optimization for HMM. Harmony search algorithm is sufficiently adaptable to allow incorporation of other techniques. A HMM training strategy using HSA is proposed, and it is tested on finding optimized structure for the pattern recognition of EEG sequence. The proposed HSA-HMM can performs global searching without initial parameter setting, local optima, and solution divergence.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1418-1423
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• 2004

Optimization of a heat exchanger with internally finned circular tubes has been performed for three-dimensional periodically fully developed turbulent flow and heat transfer. The design variables of fin number N, fin width ($d_1,d_2$) and fin height(H), are numerically optimized for the limiting conditions of $N=22{\sim}37$, $d_1=0.5{\sim}1.5$ mm, $d_2=0.5{\sim}1.5$ mm, $H=0.1{\sim}1.5$. Due to the periodic boundary conditions along main flow direction, the three layers of meshes are considered. The CFD and the mathematical optimization are coupled to optimize the heat exchanger. The flow and thermal fields are predicted using the finite volume method and the optimization is carried out by using the sequential quadratic programming (SQP) method which is widely used in the constrained nonlinear optimization problem.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.4 s.235
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• pp.460-468
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• 2005

Analyses of flow and heat transfer characteristics and shape optimization of internally finned circular tubes have been performed for three-dimensional periodically fully developed turbulent flow and heat transfer. CFD and mathematical optimization are coupled in order to optimize the shape of heat exchanger. The design variables such as fin widths $(d_{1},\;d_{2})$ and fin height (h) are numerically optimized by minimizing the pressure loss and maximizing the heat transfer rate for limiting conditions of $d_{1}=0.2\~1.5\;mm,\;d_{2}=0.2\~1.5\;mm,$ and $h=0.2\~1.5mm$. Due to the periodic boundary conditions along main flow direction, the three layers of meshes are considered. The flow and thermal fields are predicted using the finite volume method and the optimization is carried out by means of the sequential quadratic programming (SQP) method which is widely used in the constrained nonlinear optimization problem.

• Korean Journal of Computational Design and Engineering
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• v.21 no.4
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• pp.389-396
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• 2016

The necessity for environment-friendly material development has emerged in the recent automotive field due to stricter regulations on fuel economy and environmental concerns. Accordingly, the automotive industry is paying attention to carbon fiber reinforced plastic (CFRP) material with high strength and stiffness properties while the lightweight. In this study, we determine a shape of lower control arm (LCA) for maximizing the strength and stiffness by optimizing the thickness of each layer when the stacking angle is fixed due to the CFRP manufacturing problems. Composite materials are laminated in the order of $0^{\circ}$, $90^{\circ}$, $45^{\circ}$, and $-45^{\circ}$ with a symmetrical structure. For the approximate optimal design, we apply a sequential two-point diagonal quadratic approximate optimization (STDQAO) and use a process integrated design optimization (PIDO) code for this purpose. Based on the physical properties calculated within a predetermined range of laminate thickness, we perform the FEM analysis and verify whether it satisfies the load and stiffness conditions or not. These processes are repeated for successive improved objective function. Optimized CFRP LCA has the equivalent stiffness and strength with light weight structure when compared to conventional aluminum design.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.4
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• pp.217-224
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• 2020

In this study, a framework for optimizing the opening in an outrigger wall is proposed. To solve a constrained bounded optimization problem, an in-house finite element program and SQP algorithm in Python SciPy library are utilized. The openings of the outrigger wall are located according to the strut-tie behavior of the outrigger wall deep beam. A linear interpolation method is used to obtain differentiable continuous functions required for optimization, whereas a database is used for the efficiency of the optimization program. By comparing the result of the two-variable optimization through the moving path of the search algorithm, it is confirmed that the algorithm efficiently determines the optimized result. When the size of each opening is set to individual variables rather than the same width of all openings, the value of the objective function is minimized to obtain better optimization results. It was confirmed that the optimization time can be effectively reduced when using the database in the optimization process.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.510-518
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• 2014

In this study, in order to improve and optimize the performance of the turning mechanism for a fish robot in the fluid, we propose the tail joint trajectories using neural networks to mimic the CST(C-shape Sharp Turn) patterns of a real fish which is optimized in the natural environment. In order to mimic the CST patterns of a fish, we convert the sequential recording CST patterns into the coordinate data, and change the numerical coordinate data into a functions. We change the motion functions to the relative joint angles which is adapted to suit robot's shape and data. However, these relative joint trajectories obtained by the sequential recording of the carp have low-precision. It is difficult to apply to the control of a fish robot. Therefore, the relative joint trajectories are interpolated using neural networks with superior generalization ability and applied to the fish robot. we have found that the proposed method using neural networks is superior to ones using high-order polynomial equation through the computer simulations.