• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 2001년도 유체기계 연구개발 발표회 논문집
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• pp.143-148
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• 2001

In this study, to investigate the effect of the generalized performance curve on the performance prediction and to find the optimal ones, a systematic study is performed. For this purpose, we compared the influence of the stage performance curves with experimental data in multi-stage axial compressors. As a result, it is discovered that the optimal generalized performance curves vary according to the number of the stages in compressors. And we found that for a low-stage compressors, Muir's pressure coefficient curve gives the best prediction results at design rotational frequency regardless of the efficiency curve. On the other hand, for high-stage compressors, Stone's pressure coefficient curve gives the optimistic results about the performance prediction at design rotational frequency.

• KEPCO Journal on Electric Power and Energy
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• 제7권1호
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• pp.115-123
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• 2021

Through machine learning-based load prediction, it is possible to prevent excessive power generation or unnecessary economic investment by estimating the appropriate amount of facility investment in consideration of the load that will increase in the future or providing basic data for policy establishment to distribute the maximum load. However, in order to secure the reliability of the developed load prediction model in the field, the performance comparison verification between the distribution line load prediction models must be preceded, but a comparative performance verification system between the distribution line load prediction models has not yet been established. As a result, it is not possible to accurately determine the performance excellence of the load prediction model because it is not possible to easily determine the likelihood between the load prediction models. In this paper, we developed a reliability verification system for load prediction models including a method of comparing and verifying the performance reliability between machine learning-based load prediction models that were not previously considered, verification process, and verification result visualization methods. Through the developed load prediction model reliability verification system, the objectivity of the load prediction model performance verification can be improved, and the field application utilization of an excellent load prediction model can be increased.

• International Journal of Naval Architecture and Ocean Engineering
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• 제13권1호
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• pp.102-114
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• 2021

Biofouling represents an important problem in the shipping industry since it causes the increase in surface roughness. The most of ships in the current world fleet do not have good coating condition which represents an important problem due to strict rules regarding ship energy efficiency. Therefore, the importance of the control and management of the hull and propeller fouling is highlighted by the International Maritime Organization and the maintenance schedule optimization became valuable energy saving measure. For adequate implementation of this measure, the accurate prediction of the effects of biofouling on the hydrodynamic characteristics is required. Although computational fluid dynamics approach, based on the modified wall function approach, has imposed itself as one of the most promising tools for this prediction, it requires significant computational time. However, during the maintenance schedule optimization, it is important to rapidly predict the effect of biofouling on the ship hydrodynamic performance. In this paper, the effect of biofilm on the ship hydrodynamic performance is studied using the proposed performance prediction method for three merchant ships. The applicability of this method in the assessment of the effect of biofilm on the ship hydrodynamic performance is demonstrated by comparison of the obtained results using the proposed performance prediction method and computational fluid dynamics approach. The comparison has shown that the highest relative deviation is lower than 4.2% for all propulsion characteristics, lower than 1.5% for propeller rotation rate and lower than 5.2% for delivered power. Thus, a practical tool for the estimation of the effect of biofouling with lower fouling severity on the ship hydrodynamic performance is developed.

• 통합자연과학논문집
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• 제11권4호
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• pp.204-208
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• 2018

Comparison of different optimizer performance in photovoltaic power modeling using artificial neural deep learning techniques is described in this paper. Six different deep learning optimizers are tested for Long-Short-Term Memory networks in this study. The optimizers are namely Adam, Stochastic Gradient Descent, Root Mean Square Propagation, Adaptive Gradient, and some variants such as Adamax and Nadam. For comparing the optimization techniques, high and low fluctuated photovoltaic power output are examined and the power output is real data obtained from the site at Mokpo university. Using Python Keras version, we have developed the prediction program for the performance evaluation of the optimizations. The prediction error results of each optimizer in both high and low power cases shows that the Adam has better performance compared to the other optimizers.

• ETRI Journal
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• 제42권5호
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• pp.686-699
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• 2020

In this paper, we propose a supervised-learning-based spatial performance prediction (SLPP) framework for next-generation heterogeneous communication networks (HCNs). Adaptive asset placement, dynamic resource allocation, and load balancing are critical network functions in an HCN to ensure seamless network management and enhance service quality. Although many existing systems use measurement data to react to network performance changes, it is highly beneficial to perform accurate performance prediction for different systems to support various network functions. Recent advancements in complex statistical algorithms and computational efficiency have made machine-learning ubiquitous for accurate data-based prediction. A robust network performance prediction framework for optimizing performance and resource utilization through a linear discriminant analysis-based prediction approach has been proposed in this paper. Comparison results with different machine-learning techniques on real-world data demonstrate that SLPP provides superior accuracy and computational efficiency for both stationary and mobile user conditions.

• Journal of Advanced Marine Engineering and Technology
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• 제35권2호
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• pp.189-195
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• 2011

본 논문은 R744-R404A용 캐스케이드 냉동시스템의 기초 설계자료를 제공하기 위해서 COP 예측 상관식을 제안하고 그 결과를 타 상관식과 비교하였다. 작동변수로는 R404A용 고온사이클과 R744용 저온사이클의 과냉각도와 과열도, 압축기효율, 응축과 증발온도이다. 이에 대한 주요결과를 요약하면 다음과 같다. 다중회귀 분석을 통해 R744-R404A용 캐스케이드 냉동시스템의 성능 예측식을 제안하였고, 그 결과를 타 연구자들의 상관식과 비교하였다. 그 결과 본 연구에서 제안한 성능 예측식은 타 연구자들의 상관식과 일치하지 않았다. 따라서 향후 R744-R404A용 캐스케이드 냉동시스템에 대한 추가 실험 데이터와 본 연구에서 제안한 COP 예측 상관식을 비교하여 그 신뢰성을 확보할 필요가 있다.

• Journal of information and communication convergence engineering
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• 제19권4호
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• pp.241-247
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• 2021

Particulate matter has emerged as a serious global problem, necessitating highly reliable information on the matter. Therefore, various algorithms have been used in studies to predict particulate matter. In this study, we compared the prediction performance of neural network models that have been actively studied for particulate matter prediction. Among the neural network algorithms, a deep neural network (DNN), a recurrent neural network, and long short-term memory were used to design the optimal prediction model using a hyper-parameter search. In the comparative analysis of the prediction performance of each model, the DNN model showed a lower root mean square error (RMSE) than the other algorithms in the performance comparison using the RMSE and the level of accuracy as metrics for evaluation. The stability of the recurrent neural network was slightly lower than that of the other algorithms, although the accuracy was higher.

• Journal of Mechanical Science and Technology
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• 제18권8호
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• pp.1428-1434
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• 2004

This paper presents the mean streamline analysis using the empirical loss correlations for performance prediction of cross-flow fans. Comparison of overall performance predictions with test data of a cross-flow fan system with a simplified vortex wall scroll casing and with the published experimental characteristics for a cross-flow fan has been carried out to demonstrate the accuracy of the proposed method. Predicted performance curves by the present mean streamline analysis agree well with experimental data for two different cross-flow fans over the normal operating conditions. The prediction method presented herein can be used efficiently as a tool for the preliminary design and performance analysis of general-purpose cross-flow fans.

• 한국유체기계학회 논문집
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• 제2권2호
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• pp.46-56
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• 1999

This study is on the performance prediction and design of a sirocco fan. Slip coefficient is very important factor for the performance analysis of a centrifugal-type fan. Because generally used slip coefficient equations of backward curved centrifugal fan are not appropriate for forward curved sirocco fan, in this study a proper slip coefficient equation for a sirocco fan is suggested. Using this equation performance prediction program for sirocco fan is composed of and also included the total noise prediction that include the turbulent noise at the fan inlet and boundary layer noise. A comparison between the values obtained from performance prediction program and experimental values shows that the program predicts the sirocco fan performance in a practical rate.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 1998년도 강연회 및 연구개발 발표회 논문집
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• pp.63-72
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• 1998

This study Is on the performance prediction and design of sirocco fan. Slip coefficient is very important factor for the performance analysis of centrifugal-type fan. Because generally used slip coefficient equations of backward curved centrifugal fan are not appropriate for forward curved sirocco fan, in this study a proper slip coefficient equation for sirocco fan is suggested. Using this equation performance prediction program for sirocco fan is composed and also included the total noise prediction that include turbulent noise at the fan Inlet and boundary layer noise. A comparison between the values obtained from performance prediction program and experimental values shows that the program predicts the sirocco fan performance in a practical rate.