• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.207-220
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• 1999

In this paper, some of the issue about a group sequential method are considered in the Bayesian context. The continuous time optimal stopping boundary can be used to approximate the optimal stopping boundary for group sequential designs. The exact stopping boundary for group sequential design is obtained by using the backward induction method and is compared with the continuous optimal stopping boundary and the corrected continuous stopping boundary.

• Communications for Statistical Applications and Methods
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• v.13 no.1
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• pp.191-204
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• 2006

This paper develops a Bayesian method to derive the optimal sequential preventive maintenance(PM) policy by determining the PM schedules which minimize the mean cost rate. Such PM schedules are derived based on a general sequential imperfect PM model proposed by Lin, Zuo and Yam(2000) and may have unequal length of PM intervals. To apply the Bayesian approach in this problem, we assume that the failure times follow a Weibull distribution and consider some appropriate prior distributions for the scale and shape parameters of the Weibull model. The solution is proved to be finite and unique under some mild conditions. Numerical examples for the proposed optimal sequential PM policy are presented for illustrative purposes.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.10
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• pp.1354-1360
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• 2013

In transmission system, reclosing scheme is very useful method to improve continuity of power supply and reliability of system. Especially, high speed reclosing which is used generally in transmission systems has a benefit improving transient stability. However, the reclosing can jeopardize the stability under the condition having high difference of voltage phase angle between both ends. Thus, this paper proposes optimal sequential reclosing scheme to improve transient stability due to reclosing operation. The optimal sequential reclosing is that each phase is closed sequentially considering transient energy. In this paper, 345kV and 154kV transmission system is modeled using EMTP (ElectroMagnetic Transient Program) to verify the performance and effectiveness of optimal sequential reclosing on transient stability. Also, Integral Square Error(ISE) method is used to assess the transient stability.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.9 s.240
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• pp.1199-1208
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• 2005

Nowadays, it is performed actively to optimize by using an approximate model. This is called the approximate optimization. In addition, the sequential approximate optimization (SAO) is the repetitive method to find an optimum by considering the convergence of an approximate optimum. In some recent studies, it is proposed to increase the fidelity of approximate models by applying the sequential sampling. However, because the accuracy and efficiency of an approximate model is directly connected with the design area and the termination criteria are not clear, sequential sampling method has the disadvantages that could support an unreasonable approximate optimum. In this study, the SAO is executed by using trust region, Kriging model and Optimal Latin Hypercube design (OLHD). Trust region is used to guarantee the convergence and Kriging model and OLHD are suitable for computer experiment. finally, this SAO method is applied to various optimization problems of highly nonlinear mathematical functions. As a result, each approximate optimum is acquired and the accuracy and efficiency of this method is verified by comparing with the result by established method.

• Proceedings of the Korean Reliability Society Conference
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• 2005.06a
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• pp.131-137
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• 2005

In this paper, we propose a Bayesian approach to determine the adaptive preventive maintenance(PM) policy for a general sequential imperfect PM model proposed by Lin, Zuo and Yam(2000) that PM not only reduces the effective age of the system but also changes the hazard rate function. Assuming that the failure times follow Weibull distribution, we adopt a Bayesian approach to update unknown parameters and determine the Bayesian optimal sequential PM policies. Finally, numerical examples of the optimal adaptive PM policy are presented for illustrative purposes.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1919-1922
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• 2003

Bypass anastomosis are frequently adopted for surgical treatments. After the bypass grafting, the bypass artery is often occluded due to restenosis and/or anastomotic neointimal fibrous hyperplasia phenomena. Optimal coronary bypass anastomosis should be investigated to improve the patency for the arterial bypass techniques. The objective of this study is to investigate the influence of bypass with sequential bypass effects in the stenosed coronary artery. Numerical analyses are focused on the understanding of the flow patterns for different sequential anastomosis techniques. Blood flow field is treated as two-dimensional incompressible laminar flow. The finite volume method is adopted for discretization of the governing equations. The Carreau model is employed as the constitutive equation for blood. To find the optimal sequential bypass anastomotic configurations, the mass flow rates at the outlet of different models are compared quantitatively.

• Structural Monitoring and Maintenance
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• v.4 no.1
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• pp.53-68
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• 2017

The response sensitivity method in time domain has been applied extensively for damage identification. In this paper, the relationship between the error of damage identification and the sensitivity matrix is investigated through perturbation analysis. An index is defined according to the perturbation amplify effect and an optimal sensor placement method is proposed based on the minimization of that index. A sequential sub-optimal algorithm is presented which results in consistently good location selection. Numerical simulations with a two-dimensional high truss structure are conducted to validate the proposed method. Results reveal that the damage identification using the optimal sensor placement determined by the proposed method can identify multiple damages of the structure more accurately.

• Progress in Superconductivity and Cryogenics
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• v.23 no.4
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• pp.39-43
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• 2021

This study deals with the ferromagnetic shims design based on the spherical harmonic coefficient reduction method. The design method using the sequential search method is an intuitive method and has the advantage of quickly reaching the optimal result. The study was conducted for a 400 MHz all-REBCO magnet, which had difficulty in shimming due to the problem of SCF (screening current induced field). The initial field homogeneity of the magnet was measured to be 233.76 ppm at 20 mm DSV (Diameter Spherical Volume). In order to improve the field homogeneity of the magnet, the ferromagnetic shim with a thickness of 1 mil to 11 mil was constructed by a design method in which sequential search algorithm was applied. As a result, the field homogeneity of the magnet could be significantly improved to 0.24 ppm at 20 mm DSV and 0.05 ppm at 10 mm DSV.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.12
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• pp.1156-1166
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• 2004

The shape of plate-fin type heat sink is numerically optimized to acquire the minimum pressure drop under the required temperature rise. In constrained nonlinear optimization problems of thermal/fluid systems, three fundamental difficulties such as high computational cost for function evaluations (i.e., pressure drop and thermal resistance), the absence of design sensitivity information, and the occurrence of numerical noise are commonly confronted. Thus, a sequential approximate optimization (SAO) algorithm has been introduced because it is very hard to obtain the optimal solutions of fluid/thermal systems by means of gradient-based optimization techniques. In this study, the progressive quadratic response surface method (PQRSM) based on the trust region algorithm, which is one of sequential approximate optimization algorithms, is used for optimization and the heat sink is optimized by combining it with the computational fluid dynamics (CFD).

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.353-366
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• 1997

In this paper, we derive an approximate optimal Bayes group sequential design for a given loss function. We use the Monte-Carlo method to compare the ASN(average sample size) function and Bayes risk of approximate optimal Bayes group sequential design, Pocock design and O'Brien and Fleming design. Also introduced is the concept of Bayes efficiency and percentage loss of information due to grouping for the group sequential design and use it to measure the loss of information for different group sizes.