• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.221-229
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• 2003

In the early phases of the product life cycle, Life Cycle Assessment (LCA) is recently used to support the decision-making fer the conceptual product design and the best alternative can be selected based on its estimated LCA and its benefits. Both the lack of detailed information and time for a full LCA fur a various range of design concepts need the new approach fer the environmental analysis. This paper suggests a novel approximate LCA methodology for the conceptual design stage by grouping products according to their environmental characteristics and by mapping product attributes into impact driver index. The relationship is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then a neural network approach is developed to predict an approximate LCA of grouping products in conceptual design. Trained learning algorithms for the known characteristics of existing products will quickly give the result of LCA for new design products. The training is generalized by using product attributes for an ID in a group as well as another product attributes for another IDs in other groups. The neural network model with back propagation algorithm is used and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give some useful guidelines fer the design of environmentally conscious products in conceptual design phase.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1144-1158
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• 2016

In this paper, delay-constrained data transmission is considered over error-prone networks. Network coding is deployed for efficient information exchange, and an approximate decoding approach is deployed to overcome potential all-or-nothing problems. Our focus is on determining the cluster size and its impact on approximate decoding performance. Decoding performance is quantified, and we show that performance is determined only by the number of packets. Moreover, the fundamental tradeoff between approximate decoding performance and data transfer rate improvement is analyzed; as the cluster size increases, the data transfer rate improves and decoding performance is degraded. This tradeoff can lead to an optimal cluster size of network coding-based networks that achieves the target decoding performance of applications. A set of experiment results confirms the analysis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.780-783
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• 2002

This paper proposes an approximate LCA methodology fur the conceptual design stage by grouping products according to their environmental characteristics and by mapping product attributes Into impact driver (ID) index. The relationship Is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then an artificial neural network model is developed to predict an approximate LCA of grouping products in conceptual design stage. The training is generalized by using identified product attributes for an ID In a group as well as another product attributes for another IDs in other groups. The neural network model with back propagation algorithm is used and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give an approximate LCA results for design concepts.

• Journal of the Korean Society of Safety
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• v.26 no.4
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• pp.80-86
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• 2011

Structural optimization algorithm of steel box girder bridges using improved higher-order approximate reanalysis technique is proposed in this paper. The proposed approximation method is a generalization of the convex approximation method. The order of the approximate reanalysis for each function is analytically adjusted in the optimization process. This self-adjusted capability makes the approximate structural analysis values conservative enough to maintain the optimum design point of the approximate problem. The efficiency of proposed optimazation algorithm, compared with conventional algorithm, is successfully demonstrated in the steel box girder bridges. The efficiency and robustness of proposed algorithm is also demonstrated in practical steel box girder bridges.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1997.04a
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• pp.192-199
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• 1997

The purpose of this paper is to get a powerful tool for response analysis of a spherical dome subjected to dynamic excitation based on mathematically analytical method, i. e., the Galerkin procedure in modal analysis, with sufficient accuracy and practicality. At first, this paper provides an approximate solution of eigen modes, which has sufficient accuracy and praticallity for response analysis in symmetric and antisymmetric state. In the second stage of this paper, response analysis of a dome subjected to horizontal earthquakes is executed as the application of these approximate modes. Many important response characteristics may manifest themselves through parametric survey of material and geometric properties.

• Water Engineering Research
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• v.4 no.4
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• pp.175-185
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• 2003

A numerical model to analyze dam break flows has been developed based on approximate Riemann solver. The governing equations of the model are the nonlinear shallow-water equations. The governing equations are discretized explicitly by using finite volume method and the numerical flux are reconstructed with weighted averaged flux (WAF) method. The developed model is verified. The first verification problem is about idealized dam break flow on wet and dry beds. The second problem is about experimental data of dam break flow. From the results of the verifications, very good agreements have been observed

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.3
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• pp.206-212
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• 2000

We consider the M/M/1/1 retrial queue where the maximum number of retrials is fixed by a constant. We present an efficient approximate procedure for mean performance measures and the loss probability. The approximate results are satisfactory when compared with simulation results.

• Journal of the Earthquake Engineering Society of Korea
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• v.24 no.3
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• pp.129-139
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• 2020

An approximate analysis method is proposed to predict the dynamic amplification of shear forces in ordinary reinforced concrete shear walls as a preliminary study. First, a seismic design for three groups of ordinary reinforced concrete shear walls higher than 60 m was created on the basis of nonlinear dynamic analysis. Causes for the dynamic amplification effect of shear forces were investigated through a detailed evaluation of the nonlinear dynamic analysis result. A new modal combination rule was proposed on the basis of that observation, in which fundamental mode response and combined higher mode response were summed directly. The fundamental mode response was approximated by nonlinear static analysis result, while higher mode response was computed using response spectrum analysis for equivalent linear structural models with the effective stiffness based on the nonlinear dynamic analysis result. The proposed approximate analysis generally predicted vertical distribution of story shear and shear forces of individual walls from the nonlinear dynamic analysis with comparable accuracy.

• 한국전산유체공학회:학술대회논문집
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• 2005.10a
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• pp.99-104
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• 2005

For the efficient reliability analysis, Bi-direction two-point approximation(BTPA) method is developed which solves shortcomings of conventional two-point approximation(TPA) methods that generate an approximate surface with low accuracy or sometimes do an unstable approximate surface. The conventional reliability based design optimization(RBDO) methods require high computational cost compared with the deterministic design optimization(DO) methods. To overcome the computational inefficiency of RBDO, the approximate reliability analysis approaches on the TPA surface are proposed. Using these FORM and SORM analysis strategies, multi-point aerodynamic-structure interacted shape design optimizations with uncertainty are performed very efficiently.

• Journal of applied mathematics & informatics
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• v.26 no.5_6
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• pp.1021-1035
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• 2008

In this paper, we analyze an N-design call center with skill-based routing, in which one pool of agents handles two types of calls and another pool of agents handles only one type of calls. The approximate analysis is motivated by a computational complexity that has been observed in the direct stochastic approach and numerical method for finding performance measures. The workforce staffing policy is very important to the successful management of call centers. So the allocation scheduling of the agents can be considered as the optimization problem of the corresponding queueing system to the call center. We use a decomposition algorithm which divides the state space of the queueing system into the subspaces for the approximate analysis of the N-design call center with two different types of agents. We also represent some numerical examples and show the impact of the system parameters on the performance measures.