• Journal of Ship and Ocean Technology
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• v.11 no.4
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• pp.55-71
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• 2007

The primary objective of this work is to develop methodologies for virtual model basin and to demonstrate the capabilities for generic multi-hull ship geometry. A computational fluid dynamics approach is used to simulate various model basin tests for steady resistance, maneuvering and seakeeping. For a catamaran hull configuration, the methodologies are used for solving these problems and the results are discussed. Computational results are compared with the results of a benchmarked potential flow theory method for calm water resistance.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.2
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• pp.197-205
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• 2017

During the sea trial, we discovered EMI between MOSCOS and ES DF antenna. CW emitted by MOSCOS raised the threshold level of ES DF antenna. As a result, direction finding rate of ES has been decreased. This is a study for the improvement of EMI between the antennas mounted on a surface ship. An analysis is accomplished for MOSCOS, ES DF antenna and Jamming transmitter. This paper presents the method how to solve EMI based on the measurements and calculations about the ES DF antenna receiving level, MOSCOS radiation pattern and Jamming transmitter thermal noise. The test was performed with optimal deployment of MOSCOS on a surface ship. After changing the position of MOSCOS, EMI has been decreased significantly.

• Journal of the Korean Society of Systems Engineering
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• v.4 no.1
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• pp.35-43
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• 2008

Generally, in analysis of reliability of Design and Development Phase, reliability of electrical components is analyzed based on standards such as MIL-HDBK-217F, Bellcore Issue 4,5,6 by analyzing stress of architectural side (Power, Voltage, Current and quality level of components) of weapon system and stress of operational side (operational environment, operational temperature, Operational Profile). But the reliability of mechanical components is analyzed based on the data book of failure history of mechanical parts called NPRD-95(Nonelectronic Parts Reliability Data-95) without any analysis of above stress. However, even if it's the same mechanical parts, it might have different failure rate(fatigue, wear, corrosion) during operation depending on how weary(stress : pressure, vibration, temperature during operation) the parts are. Therefore, analyzing reliability using just data book can cause big difference in reliability instead of analyzing based upon stressfulness that parts might have, operational concept, and other various factors. Thus, This paper will guide the way of predicting reliability by organizing ways of predicting reliability for system organization and adopt ing NSWC-98/LE1(Naval Surface Warfare Center-98/LE1) for mechanical components.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.1
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• pp.9-16
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• 2021

Modern combat has been extended to the concept of real-time response to a variety of threats simultaneously occurring in vast areas. In order to quick command determination and accurate engagement in these threats, the combat system has emerged in frigate. Frigates conduct anti-surface, anti-submarine, and anti-aircraft as the core forces of the fleet. In this study, the combat effectiveness measures naval frigates using AHP (analytic hierarchy process) method. A hierarchical structure for measuring the combat effectiveness was developed, and weights of criteria were calculated by expert surveys and pair-wise comparisons. In addition, the combat effectiveness of frigates was synthesized and compared. The weights for each attribute were calculated, and the weights for the three main attributes were in the order of act (0.594), evaluate (0.277), and see (0.129). As a result of calculating the weight, anti surface warfare (0.203) was the highest. The combat effectiveness of FFG Batch-III, which has advanced hardware and software and improved combat system capabilities, see (1.73 to 2.56 times), evaluate (1.68 to 2.08 times), and act (1.31 to 3.80 times) better than the comparative frigate. In summarizing the combat effects of the frigate, FFG Batch-III was 1.41~2.95 times superior to the comparative frigate. In particular, a group of experts evaluated the act importantly, resulting in better combat effectiveness.

• Advances in Computational Design
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• v.1 no.3
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• pp.235-251
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• 2016

We have performed a design optimization of a stiffened panel with curvilinear stiffeners using an artificial neural network (ANN) residual kriging based surrogate modeling approach. The ANN residual kriging based surrogate modeling involves two steps. In the first step, we approximate the objective function using ANN. In the next step we use kriging to model the residue. We optimize the panel in an iterative way. Each iteration involves two steps-shape optimization and size optimization. For both shape and size optimization, we use ANN residual kriging based surrogate model. At each optimization step, we do an initial sampling and fit an ANN residual kriging model for the objective function. Then we keep updating this surrogate model using an adaptive sampling algorithm until the minimum value of the objective function converges. The comparison of the design obtained using our optimization scheme with that obtained using a traditional genetic algorithm (GA) based optimization scheme shows satisfactory agreement. However, with this surrogate model based approach we reach optimum design with less computation effort as compared to the GA based approach which does not use any surrogate model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.12
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• pp.1379-1385
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• 2014

Even the rough prediction of the product test time before the lifetime test of mechanical component begins would be of use in estimating cost and deciding how to keep up with the test. The reliability predictions of mechanical components are difficult because failure or degradation mechanisms are complicated, and few plausible databases are available for lifetime prediction. Therefore, this study conducted lifetime predictions of elastomeric U seals that were respectively installed in a hydraulic actuator and a pneumatic actuator using lifetime models and a field database based on failure physics and an actual test database obtained from the NSWC handbook. To validate the results, the predicted failure rates were compared with the actual lifetime test results acquired in the lab durability tests. Finally, this study discussed an engineering procedure to determine the coefficients in the failure rate models and analyzed the sensitivity of each influential parameter on the seal lifetime.

• The Journal of the Acoustical Society of Korea
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• v.37 no.2
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• pp.118-128
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• 2018

In this paper, we have studied how to search an underwater object by learning the image generated by the side scan sonar in the convolution neural network. In the method of human side analysis of the side scan image or the image, the convolution neural network algorithm can enhance the efficiency of the analysis. The image data of the side scan sonar used in the experiment is the public data of NSWC (Naval Surface Warfare Center) and consists of four kinds of synthetic underwater objects. The convolutional neural network algorithm is based on Faster R-CNN (Region based Convolutional Neural Networks) learning based on region of interest and the details of the neural network are self-organized to fit the data we have. The results of the study were compared with a precision-recall curve, and we investigated the applicability of underwater object detection in convolution neural networks by examining the effect of change of region of interest assigned to sonar image data on detection performance.