• Structural Engineering and Mechanics
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• v.82 no.3
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• pp.271-282
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• 2022

The active learning surrogate model based on adaptive sampling strategy is increasingly popular in reliability analysis. However, most of the existing sampling strategies adopt the trial and error method to determine the size of the Monte Carlo (MC) candidate sample pool which satisfies the requirement of variation coefficient of failure probability. It will lead to a reduction in the calculation efficiency of reliability analysis. To avoid this defect, a new method for determining the optimal size of the MC candidate sample pool is proposed, and a new structural reliability analysis method combining polynomial chaos-based Kriging model (PC-Kriging) with adaptive sampling region is also proposed (PCK-ASR). Firstly, based on the lower limit of the confidence interval, a new method for estimating the optimal size of the MC candidate sample pool is proposed. Secondly, based on the upper limit of the confidence interval, an adaptive sampling region strategy similar to the radial centralized sampling method is developed. Then, the k-means++ clustering technique and the learning function LIF are used to complete the adaptive design of experiments (DoE). Finally, the effectiveness and accuracy of the PCK-ASR method are verified by three numerical examples and one practical engineering example.

• Journal of the Korean Society of Marine Environment & Safety
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• v.3 no.2
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• pp.93-103
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• 1997

This paper develops a new heuristic, the Excursion Algorithm(EA), for constructing optimal designs for the experiments related with marine environment. The proposed EA consists of three parts: 1) construction of an initial feasible solution, 2) excursions over a bounded region, and 3) stopping rules. It is the second part that distinguishes the EA from the other existing heuristic methods. It turns out that excursions over a bounded feasible and/or infeasible region is effective in alleviating the risks of being trapped at a local optimum. Since this problem is formulated for the first time thesis, other heuristic algorithms do not exist. Therefore, global optimal solutions are obtained by complete enumeration for some cases, and the performance of the EA is evaluated in terms of solution quality. Computational results show that the proposed EA is effective in finding good(or, in many cases, global) solutions to the constrained optimal experimental design problems.

• Journal of computational fluids engineering
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• v.8 no.3
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• pp.41-49
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• 2003

The spatial accuracy becomes first-order when second-order conservation schemes including the non-conservative interpolation in general Chimera method are used. To ensure the solution accuracy, the discontinuities must be located away from the overlapped regions, and the length of overlapped region also must be proportional to the grid spacing. In this paper, a proposed method, cut-paste algorithm, is used to satisfy above constraints. The cut-paste algorithm can generate the optimal mesh inteface region automatically, To validate the spatial and temporal accuracy due to the non-conservative interpolation, inviscid and viscous problems are tested.

• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.5
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• pp.463-469
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• 2014

This paper proposes a maximum torque operation strategy for the direct torque control of a surface-mounted permanent-magnet synchronous motor (SPMSM). The proposed method analyzes the available operation region of the stator flux of the SPMSM under voltage and current constraints. Based on this analysis, the optimal stator flux trajectory that yields the maximum torque is obtained across the entire operation region, including constant torque and constant power regions. The proposed strategy is also applicable in the flux-weakening region II operation of the SPMSM, which has no speed limit. The validity of the proposed method is verified through experiments conducted on an 800 W SPMSM drive system.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.549-552
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• 1996

The tolerance approach to the sensitivity analysis in linear programming considers simultaneous and independent variations in the coefficients of the objective funciton or of the right-hand side terms and gives a region in which the coefficients and terms and gives a region in which the coefficients and terms can be changed and still the current optimal basis B for the original problem remains as an optimal basis for the perturbed problem. In this paper we describe a procedure that expands a region S obtained by the tolerance approch into a larger region R, so that more variations in the objective function coefficients or the right-hand side terms are permissible.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.529-532
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• 1988

This paper proposes a graph matching algorithm based on simulated annealing, which assures the globally optimal solution for circuit partitioning for the placement in the rectilinear region occurring as a result of the pre-placement of some macro cells, or onto the nonplanar surface in some military or space applications. The circuit graph ($G_{C}$) denoting the circuit topology is formed by a hierarchical bottom-up clustering of cells, while another graph called region graph ($G_{R}$) represents the geometry of a planar rectilinear region or a nonplanar surface for circuit placement. Finding the optimal many-to-one vertex mapping function from $G_{C}$ to $G_{R}$, such that the total mismatch cost between two graphs is minimal, is a combinatorial optimization problem which was solved in this work for various examples using simulated annealing.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.3
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• pp.232-238
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• 2011

In the present study, Taguchi method is used to determine the rough region first, followed by RSM technique to determine the exact optimum value during milling on a machining center. A region reducing algorithm is applied to narrow down the region of the Taguchi method for RSM. The result from the Taguchi method is fed to train the artificial neural network (ANN), whose optimum value is used to drive the region reducing algorithm. The proposed algorithm is tested under different cutting condition and results show that the introduced algorithm works well during milling process. It is also shown that theoretically obtained optimal cutting condition is very close to experimentally obtained result.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.1
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• pp.99-106
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• 1990

With two-class-based storage assignment policy and dual command cycle in Automated Storage/Retrieval Systems(AS/RS), the problem of determining the region dedicated for class-one item is considered. First, the expected travel time of the S/R machine is derived when the boundary of the class-one region is square. Secondly, a heuristic procedure is proposed which determines sequentially the class-one region in a discrete rack. An application of the procedure generates leaf shape region which confirms that the L-shape partition is not necessarily optimal.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.659-664
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• 2000

Fuel-consumption and catalyst-out emissions of a parallel hybrid electric vehicle are affected by operating region of an engine. In many researches, It is generally known that it is profitable in fuel- consumption to operate engine in OOL(Optimal Operating Line). We established the mathematical model of a parallel hybrid electric vehicle, which is linear time-invariant. To operate an engine in OOL, we applied RHC(Receding Horizon Control) to the driving control of a parallel hybrid electric vehicle. And it is known that the RHC has advantages such as good tracking performance under state and control constraints. This RHC is obtained by using linear matrix inequality (LMI) optimization. In this paper, there are three main topics. First, without state and control constraints, the optimal tracking of OOL was simulated. Second, with state and control constraints by engine and motor performances, the optimal tracking of OOL was simulated. In the last, we studied on the optimal gear ratio. That is to say, we combined the RHC and the iterative simulation to extract the optimal gear ratio. In this simulation, the vehicle is commanded to track the reference vehicle trajectory and the engine is operated in the optimal operating region which is made by the state constraints.

• Journal of Biomedical Engineering Research
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• v.25 no.4
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• pp.235-242
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• 2004

In this paper, we proposed the algorithm for detection of microtalcification by automatic threshold decision based on region growing method. The region for optimal threshold is grown from local maximum pixel by increasing repeatedly threshold in microralcification candidate region. Then, the optimal threshold is automatically decided at the maximum value of the contrast and edge sharpness in this region. Microcalcifications could be efficiently detected as satisfied result that true positive ratio is 81.5% and average false positive numbers are 1.1 about total 299 microcalcifirations in real image. In a result, we showed that this algorithm can be used to aid diagnostic-radiologist for the diagnosis of the early phase of breast cancer.