• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.3
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• pp.611-623
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• 1998

The delamination fracture of multidirectional carbon-fiber/epoxy laminates under the Mode I condition has been studied using the modified beam analysis for a fracture mechanics approach. It was found that the variation of fracture energy $G_IC$ with increasing length of the propagating crack exhibited a minimum for the pure interlaminar fracture and a maximum for the intraply fracture,i.e. a rising "R-curve", which was strongly affected by the degree of fiber bridging and crack-tip splitting arising in the global delamination. The maximum $G_IC$ value was significantly dependent on such types of delamination as no crack jumping, crack jumping into the adjacent ply and edge-delamination. It was shown also that the value of "effective flexural modulus" estimated from the modified beam analysis increased much with the development of fiber bridging behind the crack tip.ehind the crack tip.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.29-36
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• 2016

Tensairity girder is a light weight inflatable fabric structural concept which can be used in road emergency transportation. It uses low pressure air to stabilize compression elements against buckling. With the purpose of obtaining the comprehensive target of minimum deflection and weight under ultimate load, the cross-section and the inner pressure of tensairity girder was optimized in this paper. The Variable Complexity Modeling (VCM) method was used in this paper combining the Kriging approximate method with the Finite Element Analysis (FEA) method, which was implemented by ABAQUS. In the Kriging method, the sample points of the surrogate model were outlined by Design of Experiment (DOE) technique based on Optimal Latin Hypercube. The optimization framework was constructed in iSIGHT with a global optimization method, Multi-Island Genetic Algorithm (MIGA), followed by a local optimization method, Sequential Quadratic Program (SQP). The result of the optimization gives a prominent conceptual design of the tensairity girder, which approves the solution architecture of VCM is feasible and efficient. Furthermore, a useful trend of sensitivity between optimization variables and responses was performed to guide future design. It was proved that the inner pressure is the key parameter to balance the maximum Von Mises stress and deflection on tensairity girder, and the parameters of cross section impact the mass of tensairity girder obviously.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.6
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• pp.1827-1835
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• 1996

This paper addresses the problem of a torch path generation for the 2D laser cutting of a stock plate nested with resular or irregular parts. Under the constaint of the relative positions of parts enforced by nesting, the developed torch path algorithm generate feasible cutting path. In this paper, the basic object is a polygon( a many-slide figure) with holes. A part may be represented as a number of line segments connected end-to-end in counterclockwise order, and formed a closed contour as requied for cutting paths. The objective is to tranverse this cutting contours with a minimum path length. This paper proposes a simulated annealing based dtorch path algorithm, that is an improved version of previously suggested TSP models. Since everypiercing point of parts is not fixed in advance, the algorithm solves as relazed optimization problem for the constraint, thich is one of the main features of the proposed algorithm. For aolving the torch path optimization problem, an efficient generation mechanism of neighborhood structure and as annealing shedule were introduced. In this way, a global solution can be obtained in a reasonable time. Seveeral examples are represented to ilustrate the method.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.6 s.183
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• pp.136-142
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• 2006

Optimization of the aircraft panel assembly constructed by skin and stringers is investigated. For the design of panel assembly of the aircraft structure, it is necessary to determine the best shape of the stringer which accomplishes lowest weight under the condition of no instability. A panel assembly can fail in a variety of instability modes under compression. Overall modes of flexure or torsion can occur and these can interact in a combined flexural/torsion mode. Flexure and torsion can occur symmetrically or anti-symmetrically. Local instabilities can also occur. The local instabilities considered in this paper are buckling of the free and attached flanges, the stiffener web and the inter-rivet buckling. A program is developed to find out critical load for each instability mode at the specific stringer shape. Based on the developed program, optimization is performed to find optimum stringer shape. The developed instability analysis program is not adequate for sensitivity analysis, therefore RSM (Response Surface Method) is utilized instead to model weight and instability constraints. Since the problem has many local minimum, Genetic algorithm is utilized to find global optimum.

• The Journal of the Acoustical Society of Korea
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• v.13 no.6
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• pp.83-90
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• 1994

In this paper, we propose a new learning algorithm, ASOFM(Adaptive Self Organizing Feature Map), to solve the defects of Kohonen's Self Organiaing Feature Map. Kohonen's algorithm is sometimes stranded on local minima for the initial weights. The proposed algorithm uses an object function which can evaluate the state of network in learning and adjusts the learning rate adaptively according to the evaluation of the object function. As a result, it is always guaranteed that the state of network is converged to the global minimum value and it has a capacity of generalized learning by adaptively. It is reduce that the learning time of our algorithm is about $30\%$ of Kohonen's.

• Proceedings of the Korea Concrete Institute Conference
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• 1994.10a
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• pp.267-272
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• 1994

This work presents a method of optimum design for reinforced concrete building frames with rectangular cross sections. The optimization techniques used is based on the principle of divided parameters. The design variable parameters are divided into two groups, external and internal, and the optimization is also divided into external and internal procedure. This principle overcomes difficulties arising from the presence of two materials in one element, the property peculiar to reinforced concrete. Several search algorithms are tested to verify their accuracy for the external optimization. Among them pattern search algorithms has been found consistent. This work proposes a new method, modified pattern search, and a number of sample problems prove its accuracy and usefulness. Exhaustive search for all local minima in the design spaces for two sample problems has been carried out to understand the nature of the problem. The number of local minima identified is quite more than expected and it has become understood that the researcher's task in this field is to find a better local minimum if not global. The designs produced by the method preposed have been found better than those from other method, and they are in full accord with ACI Building Code Requirments(ACI 318-89).

• Korean Journal of Cognitive Science
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• v.4 no.2
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• pp.181-200
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• 1994

In the learning phase of multilyer feedforword neural network,there are problems such that local minimum,learning praralysis and slow learning speed when backpropagation algorithm used.To overcome these problems, the genetic algorithm has been used as learing method in the multilayer feedforword neural network instead of backpropagation algorithm.However,because the genetic algorith, does not have any mechanism for fine-tuned local search used in backpropagation method,it takes more time that the genetic algorithm converges to a global optimal solution.In this paper,we suggest a new GA-BP method which provides a fine-tunes local search to the genetic algorithm.GA-BP method uses gradient descent method as one of genetic algorithm's operators such as mutation or crossover.To show the effciency of the developed method,we applied it to the 3-parity bit problem with analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.767-778
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• 2003

This paper presents a method for generating optimal fuzzy rules using a genetic algorithm. Fuzzy rules are generated from the training data in the first stage. In this stage, fuzzy c-Means clustering method and cluster validity are used to determine the structure and initial parameters of the fuzzy inference system. A cluster validity is used to determine the number of clusters, which can be the number of fuzzy rules. Once the structure is figured out in the first stage, parameters relating the fuzzy rules are optimized in the second stage. Weights and variance parameters are tuned using genetic algorithms. Variance parameters are also managed with left and right for asymmetrical Gaussian membership function. The method ensures convergence toward a global minimum by using genetic algorithms in weight and variance spaces.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1059-1063
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• 2010

Shimming is an important technique in development of nuclear magnetic resonance (NMR) magnets where image resolution is highly dependent on magnetic field homogeneity. Classically, shimming may be categorized into two types: 1) active shimming that incorporates with extra coils and precise tuning of their currents; and 2)passive shimming that incorporates with pieces of steel placed in a bore of a main magnet and their uniform magnetization under homogeneous external fields. Additional magnetic fields, produced by the coils and/or the steel sheets, compensate original magnetic field from the main magnet in such a way that the total field becomes more homogeneous. In this paper, we developed a passive shimming method based on linear programming optimization. Linear programming is well known to be highly efficient to find a global minimum in various linear problems. We firstly confirmed the linearity of magnetization of ferromagnetic pieces under a presence of external magnetic fields. Then, we adopted the linear programming to find optimized allocation of the steel pieces in the inner bore of a main magnet to improve field homogeneity.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1057-1064
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• 2009

This paper introduces a new approach based on a quantum-inspired evolutionary algorithm (QEA) to solve unit commitment (UC) problems. The UC problem is a complicated nonlinear and mixed-integer combinatorial optimization problem with heavy constraints. This paper proposes a bounded quantum evolutionary algorithm (BQEA) to effectively solve the UC problems. The proposed BQEA adopts both the bounded rotation gate, which is simplified and improved to prevent premature convergence and increase the global search ability, and the increasing rotation angle approach to improve the search performance of the conventional QEA. Furthermore, it includes heuristic-based constraint treatment techniques to deal with the minimum up/down time and spinning reserve constraints in the UC problems. Since the excessive spinning reserve can incur high operation costs, the unit de-commitment strategy is also introduced to improve the solution quality. To demonstrate the performance of the proposed BQEA, it is applied to the large-scale power systems of up to 100-unit with 24-hour demand.