• 시스템엔지니어링학술지
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• 제19권1호
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• pp.107-113
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• 2023

For one-shot systems such as 81mm high-explosive ammunition, research on performance prediction is insignificant due to research manpower infrastructure and lack of interest and difficulties in securing field data, which can only be done by special task workers. In order to evaluate the actual range of ammunition, the storage ammunition reliability evaluation checks the range by firing actual ammunition through a functional test. Test evaluation is a method of extracting a sample from the population, launching it, and recording the results accordingly. As a result of these tests, the range, which is an indicator of ammunition performance, can be measured differently according to meteorological factors such as temperature, atmospheric pressure, and humidity according to the location of the test site. In this study, various environmental factors generated at the test site and storage period analyze the correlation with the range, which is the performance of ammunition, and analyze the priority of importance for each factor and the numerical standards that environmental factors affect range. Through this, a new approach to one-shot system performance prediction was presented.

• 대한임베디드공학회논문지
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• 제8권5호
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• pp.285-293
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• 2013

The procedure of the arbitration which is the tag collision is essential because the multiple tags response simultaneously in the same frequency to the request of the Reader. This procedure is known as Anti-collision and it is a key technology in the RFID system. In this paper, we propose the Bit Pattern Prediction Algorithm(BPPA) for the efficient identification of the multiple tags. The BPPA is based on the tree algorithm using the time slot and identify the tag quickly and efficiently using accurate bit pattern prediction method. Through mathematical performance analysis, We proved that the BPPA is an O(n) algorithm by analyzing the worst-case time complexity and the BPPA's performance is improved compared to existing algorithms. Through MATLAB simulation experiments, we verified that the BPPA require the average 1.2 times query per one tag identification and the BPPA ensure stable performance regardless of the number of the tags.

• 한국유체기계학회 논문집
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• 제8권2호
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• pp.31-38
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• 2005

A low NPSH and high pressure fuel pump has been designed for a turbopump system. The fuel pump has an axial inducer and a centrifugal impeller. A meanline method has been established for the preliminary design and performance prediction of pumps at design or off-design points. KeRC(Kelyish Research Center) carried out a model testing of the fuel pump with water as a working fluid at the reduced speed. Predicted performances by the method are shown to be in good agreement with experimental results for cavitating and non-cavitating conditions. The established meanline method can be used for the performance prediction and preliminary design of high speed pumps which have a inducer, impeller and volute. In the current study, the three dimensional viscous flow in the fuel pump was investigated through numerical computation. A modified design of the fuel pump was generated to improve pump performance by utilizing CFD results. The modified fuel pump was experimentally tested by ROTEM and KARI(Korea Aerospace Research Institute). The measured non-cavitating and cavitating performance showed a good agreement with designed performance.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 2004년도 유체기계 연구개발 발표회 논문집
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• pp.341-346
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• 2004

A low NPSH and high pressure fuel pump has been designed for a turbopump system. The fuel pump has an axial inducer and a centrifugal impeller. A meanline method has been established for the preliminary design and performance prediction of pumps at design or off-design points. KeRC carried out a model testing of the fuel pump with water as a working fluid at the reduced speed. Predicted performances by the method are shown to be in good agreement with experimental results for cavitating and non-cavitating conditions. The established meanline method can be used for the performance prediction and preliminary design of high speed pumps which have a inducer, impeller and volute. In the current study, the three dimensional viscous flow in the fuel pump was investigated through numerical computation. A modified design of the fuel pun was generated to improve pump performance by utilizing CFD results. The modified fuel pump was experimentally tested by ROTEM and KARI. The measured non-cavitating and cavitating performance showed a good agreement with designed performance.

• Transactions on Electrical and Electronic Materials
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• 제13권5호
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• pp.256-261
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• 2012

Recently, many photovoltaic systems (PV systems) including solar parks and PV farms have been built to prepare for the post fossil fuel era. To investigate the degradation process of the PV systems and thus, efficiently operate PV systems, there is a need to visually monitor PV systems in the range of infrared ray through the Internet. For efficient visual monitoring, this paper explores a multithreaded implementation of a recently developed HEVC standard whose compression efficiency is almost two times higher than H.264. For an efficient parallel implementation under a meshbased 64 multicore system, this work takes into account various design choices which can solve potential problems of a two-dimensional interconnects-based 64 multicore system. These problems may have not occurred in a small-scale multicore system based on a simple bus network. Through extensive evaluation, this paper shows that, for an efficient multithreaded implementation of HEVC intra prediction in a mesh-based multicore system, much effort needs to be made to optimize communications among processing cores. Thus, this work provides three design choices regarding communications, i.e., main thread core location, cache home policy, and maximum coding unit size. These design choices are shown to improve the overall parallel performance of the HEVC intra prediction algorithm by up to 42%, achieving a 7 times higher speed-up.

• 전기학회논문지
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• 제67권1호
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• pp.96-102
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• 2018

For efficient operating strategy of electric power system, forecasting of daily peak electric load is an important but difficult problem. Therefore a daily peak electric load forecasting system using a neural network and fuzzy system is presented in this paper. First, original peak load data is interpolated in order to overcome the shortage of data for effective prediction. Next, the prediction of peak load using these interpolated data as input is performed in parallel by a neural network predictor and a fuzzy predictor. The neural network predictor shows better performance at drastic change of peak load, while the fuzzy predictor yields better prediction results in gradual changes. Finally, the superior one of two predictors is selected by the rules based on rough sets at every prediction time. To verify the effectiveness of the proposed method, the computer simulation is performed on peak load data in 2015 provided by KPX.

• International Journal of Internet, Broadcasting and Communication
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• 제13권4호
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• pp.135-142
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• 2021

Estimating the locations of workers in a shipyard is beneficial for a variety of applications such as selecting potential forwarders for transferring data in IoT services and quickly rescuing workers in the event of industrial disasters or accidents. In this work, we propose a human movement stream processing system for estimating worker locations in shipyards based on Apache Spark and TensorFlow serving. First, we use Apache Spark to process location data streams. Then, we design a worker location prediction model to estimate the locations of workers. TensorFlow serving manages and executes the worker location prediction model. When there are requirements from clients, Apache Spark extracts input data from the processed data for the prediction model and then sends it to TensorFlow serving for estimating workers' locations. The worker movement data is needed to evaluate the proposed system but there are no available worker movement traces in shipyards. Therefore, we also develop a mobility model for generating the workers' movements in shipyards. Based on synthetic data, the proposed system is evaluated. It obtains a high performance and could be used for a variety of tasksin shipyards.

• 한국지능시스템학회논문지
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• 제14권5호
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• pp.533-538
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• 2004

본 논문은 뉴로-퍼지 모델의 구조 학습을 이용하여 단기 전력 수요 예측시스템을 개발하기 위한 체계적인 방법을 제안한다. 제안된 단기 수요 예측시스템은 1시간, 24시간, 168시간의 예측 리드 타임을 갖고 예측을 수행하기 위해서 요일 유형과 시간 별로 총 96개의 초기 구조를 미리 생성하고, 이를 초기 구조 뱅크에 저장한다. 예측이 수행되는 시점에 해당하는 초기구조를 선택하여 뉴로-퍼지 모델을 초기화하고, 학습하고, 예측을 수행한다. 제안된 예측시스템은 단지 2개의 입력 변수만을 이용하기 때문에 간단한 모델 구조를 가질 뿐 아니라 학습된 퍼지 규칙을 해석하는 것이 매우 용이하다는 장점을 갖는다. 제안된 방법의 실효성을 검증하기 위해 1996년과 1997년의 한극전력의 실제 전력 수요 데이터를 이용하여 1시간, 24시간, 168시간 앞의 전력 수요를 예측하는 모의 실험을 수행한다. 실험 결과 제안된 방법은 단지 2개의 입력 변수를 사용함에도 불구하고, 기존의 예측 방법과 비교하여 예측의 정확도와 신뢰도 측면에서 우수한 성능을 얻는다.

• 오토저널
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• 제14권6호
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• pp.48-59
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• 1992

This study is on the performance of the perforated tube muffler when it operates as an exhaust silencer with through-flow, steady or pulsating. Theoretical estimation of the insertion loss was made by means of transfer matrix and by using the impedance equation for the perforated tube obtained for the case of low-speed steady through-flow. Experiment was performed for the measurement of the insertion loss at two flow conditions. The one is a steady flow from the exhaust pipe of an idling diesel engine. The effect of the through-flow velocity and steadiness on the muffler performance was obtained. By comparing the theoretical prediction with the experimental result, the validity of the impedance equation in the theoretical model was discussed. It has been found that steadiness as well as magnitude of the through-flow has a significant effect on the performance of the perforated tube muffler. Especially, the self-noise due to the pulsating flow in the engine exhaust system must be taken into account for the prediction of the muffler performance.

• 한국전기전자재료학회논문지
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• 제14권3호
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• pp.241-245
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• 2001

In this paper, we present parameter optimization technique for GaAs/AlGaAs multiple quantum well avalanche photodiodes used for image capture mechanism in high-definition system. Even under flawless environment in semiconductor manufacturing process, random variation in process parameters can bring the fluctuation to device performance. The precise modeling for this variation is thus required for accurate prediction of device performance. The precise modeling for this variation is thus required for accurate prediction of device performance. This paper will first use experimental design and neural networks to model the nonlinear relationship between device process parameters and device performance parameters. The derived model was then put into genetic algorithms to acquire optimized device process parameters. From the optimized technique, we can predict device performance before high-volume manufacturign, and also increase production efficiency.