• Title/Summary/Keyword: 기압

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A Study on the Flow Analysis for KP505 Propeller Open Water Test (KP505 프로펠러의 단독성능 시험을 위한 유동해석에 관한 연구)

  • Lee, Han-Seop;Kim, Min-Tae;Kim, Won-Seop;Lee, Jong-Hoon;Park, Sang-Heup
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.9
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    • pp.150-155
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    • 2019
  • Cavitation refers to a phenomenon in which empty spaces occur in a fluid due to changes in pressure and a velocity. When a liquid moves at a high speed, the pressure drops below the vapor pressure, and vapor bubbles are generated in the liquid. This study used CFD to analyze the flow of fluid machinery used in marine and offshore plants. The goals are to ensure the validity of the analysis method for marine propellers in an open water test, to increase the forward ratio, and to use FLUENT to understand the flow pattern due to cavitation. A three-dimensional analysis was performed and compared with experimental data from MOERI. The efficiency was highest at advance ratios of 0.7 - 0.8. Thrust was generated due to the difference between the pressure surface and the suction surface, and it was estimated that bubbles would be generated in the vicinity of the back side surface rather than the face side of the propeller, resulting in more cavitation. The cavitation decreased sharply as the advance ratio increased. The thrust and torque coefficients were comparable to those of the MOERI experimental data except at the advance ratio of 1, which showed a difference of less than 5%. Therefore, it was confirmed that CFD can evaluate an open water propeller test.

Biological Response of Resistant Genes to Korean Brown Planthopper, Nilaparvata lugens Stål (벼멸구 저항성 유전자에 대한 국내 벼멸구의 생물적 반응 연구)

  • Choi, Nak Jung;Kim, Gwang-Ho;Baik, Chai-Hun;Lee, Bong-Choon
    • Journal of Life Science
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    • v.29 no.2
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    • pp.202-208
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    • 2019
  • Brown planthopper (BPH), Nilaparvata lugens Stål (Hemiptera: Delphacidae), is one of the most important migratory pests damaging rice in Korea. It invades annually from tropical and subtropical areas via continental air streams. It is necessary to determine the resistance levels of rice varieties in order to control efficiency. The honeydew excretion, development, and reproduction of the migratory BPH were studied by region in a laboratory at $25{\pm}2^{\circ}C$ and $65{\pm}5%\;RH$ and a 16L: 8D photoperiodism conducted on three BPH resistant genes: Bph1, Bph2, and Bph18. The information obtained was reported using the jackknife method, and we created life table statistics accordingly. The feeding amount of Bph1 resistant gene was lower than that of resistant genes. The developmental periods of immature stages ranged from $13.7{\pm}0.10d$ on Bph2 (Namhae, 2015) to $18.5{\pm}1.06d$ on Bph2 (Sacheon, 2016). Reproductive period and female longevity were longest on the non-resistant genes, Bph2 and Bph18 (except 1980s), and the highest fecundity of N. lugens was observed on the two BPH resistant genes. Highest net reproductive rates ($R_0$) were calculated on Bph2 by region. Intrinsic rates of population increase ($r_m$) showed a difference in resistant genes by region. These population parameters showed that migratory regions and biological characteristics of N. lugens vary annually.

Development of CanSat System for Collecting Weather Information With Autorotating Science Payload Ejection Function (자동회전 과학 탑재체 사출 기능을 갖춘 기상정보 수집용 캔위성 체계 개발)

  • Kim, Youngjun;Park, Junsoo;Nam, Jaeyoung;Lee, Junhyuck;Choi, Yunwon;Yoo, Seunghoon;Lee, Sanghyun;Lee, Younggun
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.50 no.8
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    • pp.573-581
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    • 2022
  • This paper deals with the development of CanSat system, which ejects two maple seed-type autorotating science payloads and collects weather information. The CanSat consists of two autorotating science payloads and a container. The container is equipped with devices for launching science payloads and communication with the ground station, and launches science payloads one by one at different designated altitudes. The science payload consists of a space for loading and a large wing, and rotates to generate lift for slowing down the fall speed. Specifically, after being ejected, it descends at a speed of 20 m/s or less, measures the rotation rate, atmospheric pressure, and temperature, and transmits the measured value to the container at a rate of once per second. The communication system is a master-slave structure, and the science payload transmits all data to the master container, which aggregates both the received data and its own data, and transmits it to the ground station. All telemetry can be checked in real time using the ground station software developed in-house. A simulation was performed in the simulation environment, and the performance of the CanSat system that satisfies the mission requirements was confirmed.

Imputation of Missing SST Observation Data Using Multivariate Bidirectional RNN (다변수 Bidirectional RNN을 이용한 표층수온 결측 데이터 보간)

  • Shin, YongTak;Kim, Dong-Hoon;Kim, Hyeon-Jae;Lim, Chaewook;Woo, Seung-Buhm
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.34 no.4
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    • pp.109-118
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    • 2022
  • The data of the missing section among the vertex surface sea temperature observation data was imputed using the Bidirectional Recurrent Neural Network(BiRNN). Among artificial intelligence techniques, Recurrent Neural Networks (RNNs), which are commonly used for time series data, only estimate in the direction of time flow or in the reverse direction to the missing estimation position, so the estimation performance is poor in the long-term missing section. On the other hand, in this study, estimation performance can be improved even for long-term missing data by estimating in both directions before and after the missing section. Also, by using all available data around the observation point (sea surface temperature, temperature, wind field, atmospheric pressure, humidity), the imputation performance was further improved by estimating the imputation data from these correlations together. For performance verification, a statistical model, Multivariate Imputation by Chained Equations (MICE), a machine learning-based Random Forest model, and an RNN model using Long Short-Term Memory (LSTM) were compared. For imputation of long-term missing for 7 days, the average accuracy of the BiRNN/statistical models is 70.8%/61.2%, respectively, and the average error is 0.28 degrees/0.44 degrees, respectively, so the BiRNN model performs better than other models. By applying a temporal decay factor representing the missing pattern, it is judged that the BiRNN technique has better imputation performance than the existing method as the missing section becomes longer.

A Study on The Effects of Long-Term Tidal Constituents on Surge Forecasting Along The Coasts of Korean Peninsula (한국 연안의 장주기 조석성분이 총 수위 예측에 미치는 영향에 관한 연구)

  • Jiha, Kim;Pil-Hun, Chang;Hyun-Suk, Kang
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.34 no.6
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    • pp.222-232
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    • 2022
  • In this study we investigated the characteristics of long-term tidal constituents based on 30 tidal gauge data along the coasts of Korea and its the effects on total water level (TWL) forecasts. The results show that the solar annual (Sa) and semiannual (Ssa) tides were dominant among long-term tidal constituents, and they are relatively large in western coast of Korea peninsula. To investigate the effect of long-term tidal constituents on TWL forecasts, we produced predicted tides in 2021 with and without long-term tidal constituents. The TWL forecasts with and without long-term tidal constituents are then calculated by adding surge forecasts into predicted tides. Comparing with the TWL without long-term tidal constituents, the results with long-term tidal constituents reveals small bias in summer and relatively large negative bias in winter. It is concluded that the large error found in winter generally caused by double-counting of meteorological factors in predicted tides and surge forecasts. The predicted surge for 2021 based on the harmonic analysis shows seasonality, and it reduces the large negative bias shown in winter when it subtracted from the TWL forecasts with long-term tidal constituents.

A Study on the Improvement of Wave and Storm Surge Predictions Using a Forecasting Model and Parametric Model: a Case Study on Typhoon Chaba (예측 모델 및 파라미터 모델을 이용한 파랑 및 폭풍해일 예측 개선방안 연구: 태풍 차바 사례)

  • Jin-Hee Yuk;Minsu Joh
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.35 no.4
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    • pp.67-74
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    • 2023
  • High waves and storm surges due to tropical cyclones cause great damage in coastal areas; therefore, accurately predicting storm surges and high waves before a typhoon strike is crucial. Meteorological forcing is an important factor for predicting these catastrophic events. This study presents an improved methodology for determining accurate meteorological forcing. Typhoon Chaba, which caused serious damage to the south coast of South Korea in 2016, was selected as a case study. In this study, symmetric and asymmetric parametric vortex models based on the typhoon track forecasted by the Model for Prediction Across Scales (MPAS) were used to create meteorological forcing and were compared with those models based on the best track. The meteorological fields were also created by blending the meteorological field from the symmetric / asymmetric parametric vortex models based on the MPAS-forecasted typhoon track and the meteorological field generated by the forecasting model (MPAS). This meteorological forcing data was then used given to two-way coupled tide-surge-wave models: Advanced CIRCulation (ADCIRC) and Simulating Waves Nearshore (SWAN). The modeled storm surges and waves correlated well with the observations and were comparable to those predicted using the best track. Based on our analysis, we propose using the parametric model with the MPAS-forecasted track, the meteorological field from the same forecasting model, and blending them to improve storm surge and wave prediction.

Measurements of Void Concentration Parameters in the Drift-Flux Model (상대유량 모델내의 기포분포계수 측정에 관한 연구)

  • Yun, B.J.;Park, G.C.;Chung, C.H.
    • Nuclear Engineering and Technology
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    • v.25 no.1
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    • pp.91-101
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    • 1993
  • To predict accurately the thermal hydraulic behavior of light water reactors during normal or abnormal operation, the accurate estimation of the void distribution is required. Up to date, many techniques for predicting void fraction of two-phase flow systems have been suggested. Among these techniques, the drift-flux model is widely used because of its exact calculation ability and simplicity. However, to get more accurate prediction of void fraction using drift-flux model, slip and flow regime effects must be considered more properly In the drift-flux method, these two effects are accounted for by two drift-flux parameters ; $C_{o}$ and (equation omitted). At earlier stage, $C_{o}$ is measured in a circular tube. In this study, $C_{o}$ is experimentally determined by measuring local void fraction and vapor velocity distribution in a rectangular subchannel having 4 heating rods which simulates nuclear subchannels. The measurements are peformed with two-electrical conductivity probes which are known to be adequate for measuring local parameters. The experiments are performed at low flow rate and the system pressure less than 3 atmo spheric pressure. In this experiment, (equation omitted), is not measured, but quoted from well-known empirical correlation to formulate $C_{o}$. Finally, $C_{o}$ is expressed as a function of channel averaged void fraction. fraction.

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Effects of Fiber Orientations and Hybrid Ratios on Lubricant Tribological Characteristics of $Al_2O_{3f}/SiC_p$ Reinforced MMCs ($Al_2O_{3f}/SiC_p$ 금속복합재료의 섬유방향과 혼합비가 윤활마모특성에 미치는 영향)

  • Wang, Yi-Qi;Song, Jung-Il
    • Composites Research
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    • v.22 no.5
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    • pp.15-23
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    • 2009
  • The lubricant tribological characteristics of $Al_2O_3$ fiber and SiC particle hybrid metal matrix composites (MMCs) fabricated by squeeze casting method was investigated using a pin-on-disk wear tester. The wear tests of the MMCs were performed according to fiber/particle hybrid ratio in the planar-random (PR) and normal (N) orientations sliding against a counter steel disk at a fixed speed and $25\;kg_f$ loading under different sliding distances and temperatures. The test results showed that the wear behavior of MMCs varied with fiber orientation and hybrid ratio. At room temperature, the lubricant wear behavior of F20P0 unhybrid PR-MMCs was superior to that of N-MMCs while the hybrid composites exhibited the reverse lubricant wear behavior. It was also revealed that the wear resistance of PR-MMCs was superior to that of the N-MMCs due to the joint action of reinforcements and lubricant film between the friction surfaces at an elevated temperature of $100^{\circ}C$ for both fiber only and hybrid cases. In case of $150^{\circ}C$, although the trend of weight loss was similar to that of others, the wear resistance of PR-MMCs was better than that of N-MMCs for hybrid MMCs.

Predicting Probability of Precipitation Using Artificial Neural Network and Mesoscale Numerical Weather Prediction (인공신경망과 중규모기상수치예보를 이용한 강수확률예측)

  • Kang, Boosik;Lee, Bongki
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.5B
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    • pp.485-493
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    • 2008
  • The Artificial Neural Network (ANN) model was suggested for predicting probability of precipitation (PoP) using RDAPS NWP model, observation at AWS and upper-air sounding station. The prediction work was implemented for flood season and the data period is the July, August of 2001 and June of 2002. Neural network input variables (predictors) were composed of geopotential height 500/750/1000 hPa, atmospheric thickness 500-1000 hPa, X & Y-component of wind at 500 hPa, X & Y-component of wind at 750 hPa, wind speed at surface, temperature at 500/750 hPa/surface, mean sea level pressure, 3-hr accumulated precipitation, occurrence of observed precipitation, precipitation accumulated in 6 & 12 hrs previous to RDAPS run, precipitation occurrence in 6 & 12 hrs previous to RDAPS run, relative humidity measured 0 & 12 hrs before RDAPS run, precipitable water measured 0 & 12 hrs before RDAPS run, precipitable water difference in 12 hrs previous to RDAPS run. The suggested ANN has a 3-layer perceptron (multi layer perceptron; MLP) and back-propagation learning algorithm. The result shows that there were 6.8% increase in Hit rate (H), especially 99.2% and 148.1% increase in Threat Score (TS) and Probability of Detection (POD). It illustrates that the suggested ANN model can be a useful tool for predicting rainfall event prediction. The Kuipers Skill Score (KSS) was increased 92.8%, which the ANN model improves the rainfall occurrence prediction over RDAPS.

A study on the precise prediction of tides using long-term tidal observation data at the Nakdong River Estuary (낙동강 하구 장기조석관측 자료를 이용한 조위의 정밀예측 연구)

  • Park, Byeong Woo;Kang, Tae Soon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.269-269
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    • 2022
  • 최근 낙동강 하구 기수생태 복원에 있어서 중요한 요소 중 하나는 하굿둑 외해측의 보다 높은 정도를 가지는 조석예보치 산정과 이를 통해 하굿둑 방류량과 해수 유입량을 추정하여 주변 환경 등을 예측할 수 있다. 기수생태 복원이 본격으로 논의가 진행 전인 2016년까지는 하구에서 수km 떨어진 기존 조위관측소(부산 및 가덕도)를 활용하여 하류수위를 예측하여 왔지만 조위 높이와 위상 차이로 인하여 활용이 용이하지 않다. 따라서, 낙동강 하굿둑 인접 외해역에서 조석 영향을 받는 수위관측치를 이용하여 조석조화분해를 통해 조위 예측을 보다 정밀하게 산정하는 것이 필요하다. 연구방법으로는 낙동강 하굿둑 외해역에서 관측된 2016년, 2017년 각각 1년간 10분간격으로 관측자료의 저장상태 및 이상자료 유무를 확인하고, 조석조화분해 프로그램인 TASK2000(Tidal Analysis Software Kit) Package를 이용하여 2016년, 2017년 낙동강 하굿둑 인접 외해역에서 관측된 조위자료를 각각 조석조화분해한 결과로 관측조위와 예측조위 비교하였고, 관측조위와 예측조위를 뺀 성분인 조석잔차성분을 구했다. 조화분해결과, 낙동강 하굿둑 외해역은 일반적인 연안역의 조석과는 달리 하천수의 유출, 배수갑문의 조작, 연안사주지형에 의한 조석변형 등 매우 복잡하고 불규칙적인 특성인 기상성분(기압, 바람 등)에 의한 교란을 고려한다면 예측정확도가 상당부분 확보되는 것으로 나타났다. 또한 장주기 성분과 비선형 조석성분의 크기를 비교해 볼 때 거의 편차가 없이 나타나 조석조화상수를 이용한 예보 가능성을 확인할 수 있었다. 조위검증은 2016년의 1년치의 조석자료를 이용하여 조화분해된 조화상수 63개를 이용하여 2017년의 조석 예보치를 산정하였으며, 이를 2017년의 낙동강 하굿둑 외해역의 조석관측치와 조석예측치를 1대 1 비교하는 방식으로 검증하였고, 이들의 상관관계를 파악하기 위하여 두 성분에 대하여 Regression Analysis를 수행하여 예측조위와 관측조위 사이에는 Pre=0.9535×Obs+0.396과 같은 관계식이 성립하는 것으로 분석되었다. 또한, 두 성분간의 상관도는 0.9535로 높게 나타났다. 조위예측 프로그램인 TASK2000 Package 중 MARIE를 이용한 조위예측 프로그램의 신뢰도가 매우 높은 것으로 판단되고, 해당년도 조위예측 시에는 가능하면 직전년도의 1년 조석관측자료를 조화분해하고 얻어진 조화상수를 이용하여 조위예측을 실시하면 보다 정확한 자료를 얻을 수 있다.

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