• Structural Engineering and Mechanics
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• v.30 no.1
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• pp.37-66
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• 2008

This paper focuses on the nonlinear vibrations of stay cables and evaluates the dynamic characteristics of stay cables by using the nonlinear enhanced MECS approach and the approximate approach. The nonlinear enhanced MECS approach is that both the girder-tower vibrations and the cable vibrations including parametric cable vibrations are simultaneously considered in the numerical analysis of cable-stayed bridges. Cable finite element method is used to simulate the responses including the parametric vibrations of stay cables. The approximate approach is based on the assumption that cable vibrations have a small effect on girder-tower vibrations, and analyzes the local cable vibrations after obtaining the girder-tower responses. Under the periodic excitations or the moderate ground motion, the differences of the responses of stay cables between these two approaches are evaluated in detail. The effect of cable vibrations on the girder and towers are also discussed. As a result, the dynamic characteristics of the parametric vibrations in stay cables can be evaluated by using the approximate approach or the nonlinear enhanced MECS approach. Since the different axial force fluctuant of stay cables in both ends of one girder causes the difference response values between two approach, it had better use the nonlinear enhanced MECS approach to perform the dynamic analyses of cable-stayed bridges.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.2
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• pp.35-51
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• 2016

This paper proposes a new approximate approach to calculate the order fill rate and the probability of filling an entire customer order immediately from the shelf in a business environment under purchase dependence characterized by customer purchase patterns observed in such areas as marketing, manufacturing systems, and distribution systems. The new approximate approach divides customer orders into item orders and calculates fill rates of all order types to approximate the order fill rate. We develop a greed iterative search algorithm (GISA) based on the Gauss-Seidel method to avoid dimensionality and prevent the solution divergence for larger instances. Through the computational analysis that compares the GISA with the simulation, we demonstrate that the GISA is a dependable algorithm for deriving the stationary joint distribution of on-hand inventories in the type-K pure system. We also present some managerial insights.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.4
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• pp.811-825
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• 1998

An approximate line search is presented for dynamic response optimization with Augmented Lagrange Multiplier(ALM) method. This study empolys the approximate a augmented Lagrangian, which can improve the efficiency of the ALM method, while maintaining the global convergence of the ALM method. Although the approximate augmented Lagragian is composed of only the linearized cost and constraint functions, the quality of this approximation should be good since an approximate penalty term is found to have almost second-order accuracy near the optimum. Typical unconstrained optimization algorithms such as quasi-Newton and conjugate gradient methods are directly used to find exact search directions and a golden section method followed by a cubic polynomial approximation is empolyed for approximate line search since the approximate augmented Lagrangian is a nonlinear function of design variable vector. The numberical performance of the proposed approach is investigated by solving three typical dynamic response optimization problems and comparing the results with those in the literature. This comparison shows that the suggested approach is robust and efficient.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.15-15
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• 2003

We provide some recent results of approximation algorithms for solving Markov Games and discuss their applications to problems that arise in Computer Science. We consider a receding horizon approach as an approximate solution to two-person zero-sum Markov games with an infinite horizon discounted cost criterion. We present error bounds from the optimal equilibrium value of the game when both players take “correlated” receding horizon policies that are based on exact or approximate solutions of receding finite horizon subgames. Motivated by the worst-case optimal control of queueing systems by Altman, we then analyze error bounds when the minimizer plays the (approximate) receding horizon control and the maximizer plays the worst case policy. We give two heuristic examples of the approximate receding horizon control. We extend “parallel rollout” and “hindsight optimization” into the Markov game setting within the framework of the approximate receding horizon approach and analyze their performances. From the parallel rollout approach, the minimizing player seeks to combine dynamically multiple heuristic policies in a set to improve the performances of all of the heuristic policies simultaneously under the guess that the maximizing player has chosen a fixed worst-case policy. Given $\varepsilon$>0, we give the value of the receding horizon which guarantees that the parallel rollout policy with the horizon played by the minimizer “dominates” any heuristic policy in the set by $\varepsilon$, From the hindsight optimization approach, the minimizing player makes a decision based on his expected optimal hindsight performance over a finite horizon. We finally discuss practical implementations of the receding horizon approaches via simulation and applications.

• Structural Engineering and Mechanics
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• v.57 no.6
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• pp.1039-1049
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• 2016

In this research, an approximate analytical solution has been presented for nonlinear problems of vibratory systems in mechanical engineering. The new method is called Variational Approach (VA) which is applied in two different high nonlinear cases. It has been shown that the presented approach leads us to an accurate approximate analytical solution. The results of variational approach are compared with numerical solutions. The full procedure of the numerical solution is also presented. The results are shown that the variatioanl approach can be an efficient and practical mathematical tool in field of nonlinear vibration.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.05a
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• pp.117-121
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• 2005

In this paper, an approximate time-effective approach to rigid-plastic finite element method is presented with its solution scheme and a volume compensation method is proposed to simulate rotary forging processes. The applicability is examined by comparing the results obtained by the presented approach with those by the conventional approach. The approach is applied to simulation of a rotary forging process fur a wheel bearing assembly. The analyzed results are compared with the experimental results.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.6
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• pp.57-65
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• 2006

An approximate function approach has been developed using the subsystem synthesis method for real-time multibody vehicle dynamics models. In this approach, instead of solving loop closure constraint equations of the suspension linkage, approximate functions are used. The approximate function represents the functional relationship between dependent coordinates and independent coordinates of the suspension subsystem. This kinematic relationship is also included in the suspension subsystem equations of motion. Different order of polynomial functions are tried to find out the best candidate functions. The proposed method is also compared with the conventional subsystem synthesis method to verify its efficiency and accuracy.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.1
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• pp.143-159
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• 1998

This paper proposes a new type of fuzzy approximate reasoning method that combines a self organizing feature map and a fuzzy logic. Previous methods considered only input part to determine the number of fuzzy rules, while this paper considers both input and output parts simultaneously. Our approach proved to improve the inference performance. We also developed a new index for avoiding overlearning which guarantees more accurate results. Experimental results showed that our approach surpasses the performance of Takagi & Hayashi (1991) approach.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.248-251
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• 1997

In this paper, We propose the concept of approximate Classification in the field of two group discriminan analysis. In our approach, an attribute space is divided into three subspaces. Two subspaces are for given two group and one subspace is for a boundary area between the two groups. We propose Approximate Pattern Classification with Rough set. We also propose learning procedures of neural networks for approximate classification. We propose two weighting methods which lead to possibility analysis and necessity analysis. We illustrate the proposed methods by numerical examples.

• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1969-1976
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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 for the product concepts, and the best alternative can be selected based on its estimated LCA and benefits. Both the lack of detailed information and time for a full LCA for a various range of design concepts need a new approach for the environmental analysis. This paper explores a new approximate LCA methodology for the product concepts by grouping products according to their environmental characteristics and by mapping product attributes into environmental impact driver (EID) 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 newly designed products. The training is generalized by using product attributes for an EID in a group as well as another product attributes for the other EIDs 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 for the design of environmentally conscious products in conceptual design phase.