• 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.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2377-2386
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• 2021

To model the atmospheric dispersion of radionuclides released from nuclear accident is very important for nuclear emergency. But the uncertainty of model parameters, such as source term and meteorological data, may significantly affect the prediction accuracy. Data assimilation (DA) is usually used to improve the model prediction with the measurements. The paper proposed a parameter bias transformation method combined with Lagrangian puff model to perform DA. The method uses the transformation of coordinates to approximate the effect of parameters bias. The uncertainty of four model parameters is considered in the paper: release rate, wind speed, wind direction and plume height. And particle swarm optimization is used for searching the optimal parameters. Twin experiment and Kincaid experiment are used to evaluate the performance of the proposed method. The results show that the proposed method can effectively increase the reliability of model prediction and estimate the parameters. It has the advantage of clear concept and simple calculation. It will be useful for improving the result of atmospheric dispersion model at the early stage of nuclear emergency.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.12
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• pp.1464-1470
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• 2009

RBDO approach based on a sampling method with the Kriging metamodel and Constraint Boundary Sampling (CBS), which is sequential sampling method to generate metamodels is proposed. The major advantage of the proposed RBDO approach is that it does not require Most Probable failure Point (MPP) which is essential for First-Order Reliability Method (FORM)-based RBDO approach. The Monte Carlo Sampling (MCS), most well-known method of the sampling methods for the reliability analysis is used to assess the reliability of constraints. In addition, a Cumulative Distribution Function (CDF) of the constraints is approximated using Moving Least Square (MLS) method from empirical distribution function. It is possible to acquire a probability of failure and its analytic sensitivities by using an approximate function of the CDF for the constraints. Moreover, a concept of inactive design is adapted to improve a numerical efficiency of the proposed approach. Computational accuracy and efficiency of the proposed RBDO approach are demonstrated by numerical and engineering problems.

• Journal of Korea Multimedia Society
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• v.12 no.1
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• pp.31-40
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• 2009

Call centers have become the prevalent contact points between companies and their customers. By virtue of recent advances in communication technology, the number and size of call centers have grown dramatically. As a large portion of the operating costs are related to the labor costs, efficient design and workforce staffing are crucial for the economic success of call centers. Therefore it is very important to determine the adequate number of agents. In this context, the workforce staffing level can be modeled as mathematical optimization problem using queueing theory. In this paper, we deal with an approximate analysis of an N-design call center with two finite queues and two types of reneging customers by using the state decomposition method. We also represent some numerical examples and show the impact of the system parameters on the performance measures of the call center.

• Computational Structural Engineering
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• v.9 no.1
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• pp.141-149
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• 1996

Efficient approximate reanalysis techniques based on substructuring are presented. In most optimal design problems, the analysis precedure must be repeated many times. In particular, one of the main obstacles in the structural optimization systems is high computational cost and time required for the repeated analysis of large-scale structural systems. The purpose of this paper is to show how to evaluate efficiently the sturctural behavior of new designs using information from the previous ones, instead of the multiple repeated analysis of basic equations for successive modification in the optimal design. The proposed reanalysis method is a combined Taylor series expansion and reduced basis method based on substructuring. Several numerical examples illustrate the effectiveness of the method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1333-1353
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• 2012

The robustness of a network is usually measured by error tolerance and attack vulnerability. Significant research effort has been devoted to determining the network design with optimal robustness. However, little attention has been paid to the problem of how to improve the robustness of existing networks. In this paper, we investigate how to optimize attack tolerance and communication efficiency of an existing network under the limited link addition. A survival fitness metric is defined to measure both the attack tolerance and the communication efficiency of the network. We show that network topology reconfiguration optimization with limited link addition (NTRLA) problem is NP-hard. Two approximate solution methods are developed. First, we present a degree-fitness parameter to guide degree-based link addition method. Second, a preferential configuration node-protecting cycle (PCNC) method is developed to do trade-off between network robustness and efficiency. The performance of PCNC method is demonstrated by numerical experiments.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.8
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• pp.398-402
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• 2002

The ELD computation has been based upon the so-called B-coefficient which uses a quadratic approximation of system loss as a function of generation output. Direct derivation of system loss sensitivity based on the Jacobian-based method was developed in early 1970s', which could eliminate the dependence upon the approximate loss formula. However, both the B-coefficient and the Jacobian-based method require a complicated Procedure for calculating the system loss sensitivity included in the constraints of the optimization problem. In this paper, an ELD formulation in which only the bus power equations are defined as the constraints has been introduced. Derivation of the partial derivatives of the system loss with respect to the generator output and calculation of the penalty factors for individual generators are not required anymore in proposed method. A comprehensive solution procedure including calculation of the Jacobians and Hessians of the formulation has been presented in detail. Proposed ELD formulation has been tested on a sample system and the simulation indicated a satisfactory result.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.10
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• pp.1079-1086
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• 2013

Optimal mount position of a front pillar trim considering heat resistant characteristics can be determined by two methods. One is conventional approximate optimization method which uses the statistical design of experiments (DOE) and response surface method (RSM). Generally, approximated optimum results are obtained through the iterative process by a trial and error. The quality of results depends seriously on the factors and levels assigned by a designer. 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 artificial neural network (ANN) systematically. An appropriate condition is determined from the iterative process based on the analysis of means. With this new technique and ANN, it is possible to find an optimum design accurately and efficiently.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.5
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• pp.597-604
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• 2010

This study focuses on the design of a mechanical joint for a zero moment crane (ZMC), which is a specialized loading/unloading system used in a mobile harbor (MH). The mechanical joint is based on the concept of zero moment point (ZMP), and it plays an important role in stabilizing a ZMC. For effective stabilization, it is necessary to ensure that the mechanical joint is robust to a wide variety of loads; further, the joint must allow the structures connected to it to perform rotational motion with two degrees of freedom By adopting a traditional design process, we designed a new mechanical joint; in this design, a universal joint is coupled with a spherical joint, and then, deformable rolling elements are incorporated. The rolling elements facilitate load distribution and help in decreasing power loss during loading/unloading. Because of the complexity of the proposed system, Kriging-based approximate optimization method is used for enhancing the optimization efficiency. In order to validate the design of the proposed mechanical joint, a structural analysis is performed, and a small-scale prototype is built.

• Journal of the Korean Society of Propulsion Engineers
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• v.16 no.1
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• pp.25-35
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• 2012

An endwall boundary layer fence technique was adapted to improve the aerothermal environment of a gas turbine passage. The shape optimization of the fence was performed to maximize the improvement. The turbine passage was simulated by a $90^{\circ}$ turning duct (ReD=360,000). The main purpose of the present investigation was to focus on finding a endwall boundary layer fence with minimum total pressure loss in the passage and heat transfer coefficient on the endwall of the duct. Anothor objective function was to minimize the area on the endwall of the duct. An approximate optimization method was used for the investigation to secure the computational efficiency. Results indicated that a significant improvement in aerodynamic environment can be achieved through the application of the fence. Improvement of the thermal environment was smaller than that of the aerodynamic enviroment.