• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.30 no.5
• /
• pp.118-126
• /
• 2002

The Altitude Engine Test Facility(AETF) was built at the Korea Aerospace Research Institute and has been being operated for the gas turbine engines in the class of 3,000 lbf thrust. To enhance the confidence level of AETF to the international level, a series of studies and facility modification have been conducted to improve the measurement uncertainty and reliability. In this paper, some part of the facility evaluation tests performed with a single spool turbojet engine are introduced. Tests were performed simulating the flight conditions as steady state, sea level for various flight speeds (i.e., Mn=0.3, 0.5, 0.7, 0.9). The obtained test results are compared with the predicted values of the engine DECK. The measurement uncertainties of airflow, net thrust, fuel flow and SFC showed 0.791~0.914%, 0.851~1.706%, 1.372~7.348% and 1.642~5.205%, respectively. Thus, from this research, the improvement methods of uncertainties on AETF has been confirmed.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.2
• /
• pp.178-185
• /
• 2011

In this paper, we propose the position estimation algorithm based on the multisensor fusion using equalization of state variables and feedback structure. First, the state variables measured from INS of main sensor with large error and DVL of assistance sensor with small error are measured before prediction phase. Next, the equalized state variables are entered to each filter and fused the enhanced state variables for prediction and update phases. Finally, the fused state variables are returned to the main sensor for improving the position estimation of UUV. For evaluation, we create the moving course of UUV by simulation and confirm the performance of position estimation by applying the proposed algorithm. The evaluation results show that the proposed algorithm is the best for position estimation and also possible for robust position estimation at the change period of moving courses.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2020.06a
• /
• pp.88-88
• /
• 2020

수심평균 2차원 혼합모형은 하천환경에서 다양한 용존성 오염물질의 혼합현상을 모의하기 위해 널리 활용되어왔다. 2차원 혼합모형에서 분산계수는 하천의 전단 흐름에 의해 야기되는 오염물질의 퍼짐 현상을 표현하는 중요한 인자로서 작용하기 때문에 정교한 오염물질 혼합거동을 모의하기 위해서는 적합한 분산계수를 산정하는 것이 필수적이다. 분산계수를 실험적으로 산정하는 방법으로는 크게 모멘트법과 추적법으로 나뉘며, 비정상상태의 혼합거동에 대해 종방향 및 횡방향 분산계수를 동시에 산정할 수 있는 방법은 추적법 계열의 2차원 유관추적법(2D STRP)이 유일하다. 본 연구에서는 하천에 유입된 오염물질의 2차원 혼합해석을 위한 수치모형을 개발하였으며, 개발된 모형의 수치해를 바탕으로 다양한 Peclet 수의 범위에 대해 기존연구에서 제시된 2D STRP의 적용범위 및 성능을 정량적으로 분석하였다. 분석된 정보를 바탕으로 기존 2D STRP의 한계를 극복하기 위한 개선된 2차원 유관추적법(2D STRP-i)을 개발하고, 사행하천을 모형화한 실규모 하천실험시설에서 검증하였다. 기존 2D STRP의 성능평가 결과, Peclet 수가 낮은 조건일수록 농도분포의 예측 정확도가 감소하는 경향을 보였으며, 하안 경계에 도달하는 농도가 증가할수록 부정확한 결과를 초래하는 것으로 나타났다. 본 연구에서는 기존 2D STRP의 한계를 보완하여 더욱 정확한 분산계수를 산정하고자 하안 경계면 조건을 고려한 2차원 유관추적법(2D STRP-i)을 개발하였다. 2D STRP-i는 직교-곡선좌표계 기반의 2차원 이송-분산 방정식을 바탕으로 횡방향 유속분포 및 하안 경계조건을 고려할 수 있도록 개선되었다. 2D STRP-i는 공간적으로 상이한 이송효과 및 하안경계 조건을 적절히 반영함으로써 농도분포의 예측 정확도를 개선 시키는 것으로 평가되었으며, 하안경계면에서 농도가 증가하는 구간에서 기존 2D STRP의 결과와 비교하여 더욱 정확한 농도분포 및 분산계수를 제공하는 것으로 밝혀졌다.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.6B
• /
• pp.579-587
• /
• 2010

The mid-range streamflow forecast was performed using NWP(Numerical Weather Prediction) provided by KMA. The NWP consists of RDAPS for 48-hour forecast and GDAPS for 240-hour forecast. To enhance the accuracy of the NWP, QPM to downscale the original NWP and Quantile Mapping to adjust the systematic biases were applied to the original NWP output. The applicability of the suggested streamflow prediction system which was verified in Geum River basin. In the system, the streamflow simulation was computed through the long-term continuous SSARR model with the rainfall prediction input transform to the format required by SSARR. The RQPM of the 2-day rainfall prediction results for the period of Jan. 1~Jun. 20, 2006, showed reasonable predictability that the total RQPM precipitation amounts to 89.7% of the observed precipitation. The streamflow forecast associated with 2-day RQPM followed the observed hydrograph pattern with high accuracy even though there occurred missing forecast and false alarm in some rainfall events. However, predictability decrease in downstream station, e.g. Gyuam was found because of the difficulties in parameter calibration of rainfall-runoff model for controlled streamflow and reliability deduction of rating curve at gauge station with large cross section area. The 10-day precipitation prediction using GQPM shows significantly underestimation for the peak and total amounts, which affects streamflow prediction clearly. The improvement of GDAPS forecast using post-processing seems to have limitation and there needs efforts of stabilization or reform for the original NWP.

• Food Science of Animal Resources
• /
• v.31 no.1
• /
• pp.115-121
• /
• 2011

The objective of this study was to develop models to predict freshness factors (total viable counts (TVC), pH, volatile basic nitrogen (VBN), trimethylamine (TMA), and thiobarbituric acid (TBA) values) and the storage period in beef using a visible and near-infrared (NIR) spectroscopic technique. A total of 216 beef spectra were collected during the storage period from 0 to 14 d at a $10^{\circ}C$ storage. A spectrophotometer was used to measure reflectance spectra from beef samples, and beef freshness spectra were divided into a calibration set and a validation set. Multi-linear regression (MLR) models using the stepwise method were developed to predict the factors. The MLR results showed that beef freshness had a good correlation between the predicted and measured factors using the selected wavelength. The correlation of determination ($r^2$), standard error of prediction (SEP), and ratio of standard deviation to SEP (RPD) of the prediction set for TVC was 0.74, 0.64, and 2.75 Log CFU/$cm^2$, respectively. The $r^2$, SEP, and RPD values for pH were 0.43, 0.10, and 1.10; those for VBN were 0.73, 1.45, and 2.00 mg%; those for TMA were 0.70, 0.19, and 2.58 mg%; those for TBA values were 0.73, 0.13, and 2.77 mg MA/kg; and those for storage period were 0.77, 1.94, and 2.53 d, respectively. The results indicate that visible and NIR spectroscopy can predict beef freshness during storage.

• Journal of Korea Water Resources Association
• /
• v.57 no.2
• /
• pp.73-85
• /
• 2024

Predicting water quality of rivers and reservoirs is necessary for the management of water resources. Artificial Neural Networks (ANNs) have been used in many studies to predict water quality with high accuracy. Previous studies have used Gradient Descent (GD)-based optimizers as an optimizer, an operator of ANN that searches parameters. However, GD-based optimizers have the disadvantages of the possibility of local optimal convergence and absence of a solution storage and comparison structure. This study developed improved optimizers to overcome the disadvantages of GD-based optimizers. Proposed optimizers are optimizers that combine adaptive moments (Adam) and Nesterov-accelerated adaptive moments (Nadam), which have low learning errors among GD-based optimizers, with Harmony Search (HS) or Novel Self-adaptive Harmony Search (NSHS). To evaluate the performance of Long Short-Term Memory (LSTM) using improved optimizers, the water quality data from the Dasan water quality monitoring station were used for training and prediction. Comparing the learning results, Mean Squared Error (MSE) of LSTM using Nadam combined with NSHS (NadamNSHS) was the lowest at 0.002921. In addition, the prediction rankings according to MSE and R² for the four water quality indices for each optimizer were compared. Comparing the average of ranking for each optimizer, it was confirmed that LSTM using NadamNSHS was the highest at 2.25.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.12A
• /
• pp.1182-1188
• /
• 2006

Adaptive OFDM(Orthogonal Frequency Division Multiplexing) improves data capacity and system performance over multipath fading by adaptively changing modulation schemes according to channel state information(CSI). To achieve a good performance in adaptive OFDM systems, CSI should be transmitted from receiver to transmitter in real time through feedback channel. However, practically, the CSI feedback delay d which is the sum of the data processing delay and the propagation delay is not negligible and damages to the reliability of CSI such that the performance of adaptive OFDM is degraded. This paper presents an adaptive OFDM system with a multistep predictor on the frequency axis to effectively compensate the multiple feedback delays $d(\geq2)$. Via computer simulation we compare the proposed scheme and existing adaptive OFDM schemes with respect to data capacity and system performance.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.47 no.11
• /
• pp.59-68
• /
• 2010

In this paper, we present a new method to complete Dynamic Spectrum Access by modifying the reward function. Partially Observable Markov Decision Process (POMDP) is an eligible algorithm to predict the upcoming spectrum opportunity. In POMDP, Reward function is the last portion and very important for prediction. However, the Reward function has only two states (Busy and Idle). When collision happens in the channel, reward function indicates busy state which is responsible for the throughput decreasing of secondary user. In this paper, we focus the difference between busy and collision state. We have proposed a new algorithm for reward function that indicates an additional state of collision which brings better communication opportunity for secondary users. Secondary users properly utilize opportunities to access Primary User channels for efficient data transmission with the help of the new reward function. We have derived mathematical belief vector of the new algorithm as well. Simulation results have corroborated the superior performance of improved reward function. The new algorithm has increased the throughput for secondary user in cognitive radio network.

• Food Science and Preservation
• /
• v.19 no.1
• /
• pp.95-103
• /
• 2012

The objective of this study was to develop models for the predict of the milk properties (fat, protein, SNF, lactose, MUN) of unhomogenized milk using the visible and near-infrared (NIR) spectroscopic technique. A total of 180 milk samples were collected from dairy farms. To determine optimal measurement temperature, the temperatures of the milk samples were kept at three levels ($5^{\circ}C$, $20^{\circ}C$, and $40^{\circ}C$). A spectrophotometer was used to measure the reflectance spectra of the milk samples. Multilinear-regression (MLR) models with stepwise method were developed for the selection of the optimal wavelength. The preprocessing methods were used to minimize the spectroscopic noise, and the partial-least-square (PLS) models were developed to prediction of the milk properties of the unhomogenized milk. The PLS results showed that there was a good correlation between the predicted and measured milk properties of the samples at $40^{\circ}C$ and at 400~2,500 nm. The optimal-wavelength range of fat and protein were 1,600~1,800 nm, and normalization improved the prediction performance. The SNF and lactose were optimized at 1,600~1,900 nm, and the MUN at 600~800 nm. The best preprocessing method for SNF, lactose, and MUN turned out to be smoothing, MSC, and second derivative. The Correlation coefficients between the predicted and measured fat, protein, SNF, lactose, and MUN were 0.98, 0.90, 0.82, 0.75, and 0.61, respectively. The study results indicate that the models can be used to assess milk quality.

• 전기의세계
• /
• v.46 no.1
• /
• pp.19-27
• /
• 1997

본 고는 전력연구원 연구과제인 "배전케이블 수명예측 기준결정 및 열화진단 시스템 구축"의 연구 수행중 전력케이블의 반도전층내에 들어 있는 불순물 또는 외부로부터 침투된 불순물이 전력케이블의 수명에 미치는 영향에 관한 총설로서, 그 동안 문헌조사 및 해외출장을 통하여 수집한 자료를 정리한 원고이다. 본 총설은 전력케이블에 사용되는 반도전층 재료의 변천, 반도전층의 역할 및 반도전층내에 들어 있는 불순물의 역할 등에 관한 내용이 정리되어 있다. 본 고를 통하여 반도전층내에 들어 있는 불순물은 전력케이블의 수명에 심각한 영향을 미칠 수 있다는 점을 강조하여 국내 지중배전 케이블에서도 불순물이 제거된 반도전 컴파운드를 사용해야 한다는 점을 강조하였다. 최근 반도전 재료의 개선을 통하여 전력케이블의 성능을 크게 개선시킬 수 있다는 연구결과 및 실용화 연구가 이루어지고 있는데, 이 새로운 개선방법은 반도전층으로부터 불순물을 제거한다는 단순한 방법이 아니라 반도전층을 이루는 반도전 컴파운드의 조성을 변화시키는 방법이다. 이는 단순히 전도성 카본블랙의 종류만을 바꾸는 것이 아니라 반도전 컴파운드에 사용하는 고분자 수지를 개질하거나 또는 일정 종류의 첨가제를 첨가하는 방법으로서, 본 고에서는 이들 방법에 대하여 간략하게 소개하였다. 이와 같은 고찰을 통하여 본 고에서는 전력케이블에 있어서 절연재료에 관한 연구도 물론 중요하지만 반도전층도 매우 중요한 역할을 하며, 나아가서 전력케이블의 성능을 현저히 향상시키기 위해서는 절연재료 뿐만 아니라 반도전층 재료에 관한 연구도 필요하다는 점을 강조하고자 한다. 본 고를 통하여 전력케이블에서의 반도전층의 역할 및 중요성에 과하여 좀 더 정확하게 인식되었으면 한다.