• Journal of Computational Design and Engineering
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• v.1 no.3
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• pp.187-193
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• 2014

One of the hottest challenges in automotive industry is related to weight reduction in sheet metal forming processes, in order to produce a high quality metal part with minimal material cost. Stamping is the most widely used sheet metal forming process; but its implementation comes with several fabrication flaws such as springback and failure. A global and simple approach to circumvent these unwanted process drawbacks consists in optimizing the initial blank shape with innovative methods. The aim of this paper is to introduce an efficient methodology to deal with complex, computationally expensive multicriteria optimization problems. Our approach is based on the combination of methods to capture the Pareto Front, approximate criteria (to save computational costs) and global optimizers. To illustrate the efficiency, we consider the stamping of an industrial workpiece as test-case. Our approach is applied to the springback and failure criteria. To optimize these two criteria, a global optimization algorithm was chosen. It is the Simulated Annealing algorithm hybridized with the Simultaneous Perturbation Stochastic Approximation in order to gain in time and in precision. The multicriteria problems amounts to the capture of the Pareto Front associated to the two criteria. Normal Boundary Intersection and Normalized Normal Constraint Method are considered for generating a set of Pareto-optimal solutions with the characteristic of uniform distribution of front points. The computational results are compared to those obtained with the well-known Non-dominated Sorting Genetic Algorithm II. The results show that our proposed approach is efficient to deal with the multicriteria shape optimization of highly non-linear mechanical systems.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.537-544
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• 2020

Advances in detection techniques, such as mutation and obfuscation, are being advanced with the development of malware technology. In the malware detection technology, unknown malware detection technology is important, and a method for Malware Authorship Attribution that detects an unknown malicious code by identifying the author through distributed malware is being studied. In this paper, we try to extract the compiler information affecting the binary-based author identification method and to investigate the sensitivity of feature selection, probability and non-probability models, and optimization to classification efficiency between studies. In the experiment, the feature selection method through information gain and the support vector machine, which is a non-probability model, showed high efficiency. Among the optimization studies, high classification accuracy was obtained through feature selection and model optimization through the proposed framework, and resulted in 48% feature reduction and 53 faster execution speed. Through this study, we can confirm the sensitivity of feature selection, model, and optimization methods to classification efficiency.

• Tribology and Lubricants
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• v.20 no.5
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• pp.259-265
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• 2004

The sealing performance of O-rings is affected by working conditions such as applied pressure, operation temperature, pre-compressed ratio and material properties. In this paper, a pressurized and compressed elastomeric bi-polymer O-ring in which is inserted into a rectangular groove is analyzed by non-linear MARC finite element program based on the Taguchi experimental method. O-rings with 9 different profile models are analyzed for design parameters that are related to the diameter ratio between outer diameter and inner one of bi-polymer O-ring, compressive ratio, groove angle and groove depth. The calculated FEM results showed that the affection ratio of design parameter dlD, which may control sealing pressure of O-rings, is the most influential parameter among the groove angle, groove depth and compression ratio.

• Journal of the Society of Naval Architects of Korea
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• v.40 no.4
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• pp.8-15
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• 2003

This paper presents the method for developing an optimum hull form with minimum wave resistance using SQP(sequential quadratic programming) as an optimization technique. The wave resistance is evaluated by a Rankine source panel method with non-linear free surface conditions and the ITTC 1957 friction line is used to predict the frictional resistance coefficient. The geometry of the hull surface is represented and modified using B-spline surface patches. The optimization method is applied to Series 60 hull and KCS(KRISO 3600 TEU Container Ship). The obtained results prove that the method is appropriate for preliminary hull form design.

• Journal of Electrical Engineering and Technology
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• v.3 no.3
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• pp.320-330
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• 2008

This paper presents an improved dynamic programming (IDP) approach to solve the economic power dispatch problem including transmission losses in power systems. A detailed mathematical derivation of recursive dynamic programming approach for the economic power dispatch problem with transmission losses is presented. The transmission losses are augmented with the objective function using price factor. The generalized expression for optimal scheduling of thermal generating units derived in this article can be implemented for the solution of the economic power dispatch problem of a large-scale system. Six-unit, fifteen-unit, and forty-unit sample systems with non-linear characteristics of the generator, such as ramp-rate limits and prohibited operating zones are considered to illustrate the effectiveness of the proposed method. The proposed method results have been compared with the results of genetic algorithm and particle swarm optimization methods reported in the literature. Test results show that the proposed IDP approach can obtain a higher quality solution with better performance.

• The KSFM Journal of Fluid Machinery
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• v.6 no.2 s.19
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• pp.41-46
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• 2003

The hydraulic design optimization and performance analysis of mixed-flow pumps for waterjet marine vehicle propulsion has been carried out using mean streamline analysis and three-dimensional computational fluid dynamics (CFD) code. In the present study, the conceptual design optimization has been formulated with a non-linear objective function to minimize the fluid dynamic losses, and then the commercial CFD code was incorporated to allow for detailed flow dynamic phenomena in the pump system. Newly designed mixed-flow model pump has been tested in the laboratory. Predicted performance curves by the CFD code agree very well with experimental data for a newly designed mixed-flow pump over the normal operating conditions. The design and prediction method presented herein can be used efficiently as a unified hydraulic design process of mired-flow pumps for waterjet marine vehicle propulsion.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.9
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• pp.33-42
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• 1997

Fixed-point optimization utility software that can aid scaling and wordlength determination of digital signal processign algorithms written in C or C$\^$++/ language is developed. This utility consists of two programs: the range estimator and the fixed-point simulator. The former estimates the ranges of floating-point variables for automatic scaling purpose, and the latter translates floating-point programs into fixed-point equivalents for evaluating te fixed-point performance by simulation. By exploiting the operator overloading characteristics of C$\^$++/ language, the range estimation and the fixed-point simulation can be conducted just by modifying the variable declaration of the original program. This utility is easily applicable to nearly all types of digital signal processing programs including non-linear, time-varying, multi-rate, and multi-dimensional signal processing algorithms. In addition, this software can be used for comparing the fixed-point characteristics of different implementation architectures.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.315-318
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• 1995

The optimum design problem of a coat-hanger die is solved by the inverse formulation. The flow in the die is analyzed using three-dimensional model. The new model for the manifold geometry is developed for the inverse formulation. The inverse problem for the optimum die geometry is formed as the optimization problem whose objective function is the linear combination of the square sum of pressure gradient deviation at die exit and the penalty function relating to the measure of non-smoothness of solution. From the several iterative solutions of the optimization problem, the optimum solution can be obtained automatically while producing the uniform flow rate distribution at die exit.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.22
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• pp.51-57
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• 1990

A new interactive multiobjective decision making technique, which is called the fuzzy sequential proxy optimization technique, has been proposed. This technique is the revised version the sequential proxy optimization technique that the decision-maker's marginal rates of substitution is interpreted as type of L-R fuzzy numbers. It used to the square of normalized scalar product as the doptimalilry condition. However, this technique ignores the imprecise nature of a decision-maker's judgement of marginal rates of substitution. Also, it have a shortcoming that can be only applied over three objective functions. In this paper, considering the imprecise nature of a decision-maker's judgement, we presents an interactive fuzzy decision-making method on the basis of the decision-maker's MRS presented through the use of five types of membership functions including non-linear functions. FORTRAN programs that run in conversational mode are developed to implement man-machine interactive procedure.

• Proceedings of the KSME Conference
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• 2000.04b
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• pp.144-147
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• 2000

A numerical method for the solution of one-dimensional inverse heat conduction problem is established and its performance is demonstrated with computational results. The present work introduces the maximum entropy method in order to build a robust formulation of the inverse problem. The maximum entropy method finds the solution that maximizes the entropy functional under given temperature measurement. The philosophy of the method is to seek the most likely inverse solution. The maximum entropy method converts the inverse problem to a non-linear constrained optimization problem of which constraint is the statistical consistency between the measured temperature and the estimated temperature. The successive quadratic programming facilitates the maximum entropy estimation. The gradient required fur the optimization procedure is provided by solving the adjoint problem. The characteristic feature of the maximum entropy method is discussed with the illustrated results. The presented results show considerable resolution enhancement and bias reduction in comparison with the conventional methods.