• Title/Summary/Keyword: Correlation model

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Numerical Determination of Lateral Loss Coefficients for Subchannel Analysis in Nuclear Fuel Bundles (핵 연료집합체 부수로 해석을 위한 횡 방향 압력손실계수의 수치적 결정)

  • Kim, Sin;Park, Goon-Cherl
    • Nuclear Engineering and Technology
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    • v.27 no.4
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    • pp.491-502
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    • 1995
  • In accurate prediction of cross-flow based on detailed knowledge of the velocity field in subchannels of a nuclear fuel assembly is of importance in nuclear fuel performance analysis. In this study, the low-Reynolds number k-$\varepsilon$ turbulence model has been adopted in too adjacent subchannels with cross-flow. The secondary flow is accurately estimated by the anisotropic algebraic Reynolds stress model. This model was numerically calculated by the finite element method and has been verified successfully through comparison with existing experimental data. Finally, with the numerical analysis of the velocity Held in such subchannel domain, an analytical correlation of the lateral loss coefficient is obtained to predict the cross-flow rate in subchannel analysis codes. The correlation is expressed as a function of the ratio of the lateral How velocity to the donor subchannel axial velocity, recipient channel Reynolds number and pitch-to-diameter.

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Development of monocular video deflectometer based on inclination sensors

  • Wang, Shuo;Zhang, Shuiqiang;Li, Xiaodong;Zou, Yu;Zhang, Dongsheng
    • Smart Structures and Systems
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    • v.24 no.5
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    • pp.607-616
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    • 2019
  • The video deflectometer based on digital image correlation is a non-contacting optical measurement method which has become a useful tool for characterization of the vertical deflections of large structures. In this study, a novel imaging model has been established which considers the variations of pitch angles in the full image. The new model allows deflection measurement at a wide working distance with high accuracy. A monocular video deflectometer has been accordingly developed with an inclination sensor, which facilitates dynamic determination of the orientations and rotation of the optical axis of the camera. This layout has advantages over the video deflectometers based on theodolites with respect to convenience. Experiments have been presented to show the accuracy of the new imaging model and the performance of the monocular video deflectometer in outdoor applications. Finally, this equipment has been applied to the measurement of the vertical deflection of Yingwuzhou Yangtze River Bridge in real time at a distance of hundreds of meters. The results show good agreement with the embedded GPS outputs.

A Generalized Flow Model and Flow Charts for Predicting Mass Flow Rate through Short Tube Orifices (일반화된 오리피스의 유량예측 상관식 및 유량선도)

  • Choi Jong Min;Kim Yongchan;Kwak Jae Su;Kwon Byong Cheol
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.16 no.10
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    • pp.895-900
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    • 2004
  • With the phaseout of CFC and HCFC refrigerants, refrigeration and heat pump systems must be redesigned to match and improve system performance with alternative refrigerants. A generalized flow model for predicting mass flow rate through short tube orifices is derived from a power law form of dimensionless parameters generated by Pi-theorem. The database for developing the correlation includes extensive experimental data for R12, R22, R134a, R407C, R410A, and R502 from the open literature. The correlation yields an average deviation of $0.3\%$ and a standard deviation of $6.1\%$ based on the present database. In addition, rating charts for predicting refrigerant flow rate through short tube orifices are generated for R12, R22, R134a, R407C, R410A, and R502.

Development of a Prediction Model and Correlation Analysis of Weather-induced Flight Delay at Jeju International Airport Using Machine Learning Techniques (머신러닝(Machine Learning) 기법을 활용한 제주국제공항의 운항 지연과의 상관관계 분석 및 지연 여부 예측모형 개발 - 기상을 중심으로 -)

  • Lee, Choongsub;Paing, Zin Min;Yeo, Hyemin;Kim, Dongsin;Baik, Hojong
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.29 no.4
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    • pp.1-20
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    • 2021
  • Due to the recent rapid increase in passenger and cargo air transport demand, the capacity of Jeju International Airport has been approaching its limit. Even though in COVID-19 crisis which has started from Nov 2019, Jeju International Airport still suffers from strong demand in terms of air passenger and cargo transportation. However, it is an undeniable fact that the delay has also increased in Jeju International Airport. In this study, we analyze the correlation between weather and delayed departure operation based on both datum collected from the historical airline operation information and aviation weather statistics of Jeju International Airport. Adopting machine learning techniques, we then analyze weather condition Jeju International Airport and construct a delay prediction model. The model presented in this study is expected to play a useful role to predict aircraft departure delay and contribute to enhance aircraft operation efficiency and punctuality in the Jeju International Airport.

The Classification Scheme of ADHD for children based on the CNN Model (CNN 모델 기반의 소아 ADHD 분류 기법)

  • Kim, Do-Hyun;Park, Seung-Min;Kim, Dong-Hyun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.5
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    • pp.809-814
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    • 2022
  • ADHD is a disorder showing inattentiveness and hyperactivity. Since symptoms diagnosed in childhood continue to the adulthood, it is important to diagnose ADHD and start treatments in early stages. However, it has the problems to acquire enough and accurate data for the diagnosis because the mental state of children is immature using the self-diagnosis method or the computerized test. In this paper, we present the classification method based on the CNN model and execute experiment using the EEG data to improve the objectiveness and the accuracy of ADHD diagnosis. For the experiment, we build the 3D convolutional networks model and exploit the 5-folds cross validation method. The result shows the 97% accuracy on average.

Analytical Study on the Correlation between the Functionality of Virtual Idols and Fan Satisfaction under the Chinese Market

  • Hou, ZhengDong;Kim, KiHong;Ren, YuShi
    • International Journal of Advanced Culture Technology
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    • v.10 no.4
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    • pp.28-38
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    • 2022
  • Virtual idols have aroused wide attention as a novel product of the idol industry in the digital era over the past few years. The population of China determines that virtual idols have a huge fan market. As a digital cultural product closely connected with fans, virtual idols are im-portant to gain insights into the correlation between fan satisfaction and virtual idol functions. In accordance with the KANO demand model, this study first classifies and explains the specific functions of virtual idols into four quadrants, including attractive, must-be, 1D (One-Dimensional), and indifferent. Subsequently, the satisfaction of fans of virtual idols with specific functions in each quadrant are analyzed using a questionnaire. This study suggests that virtual idols have one at-tractive quality, three 1D quality, two must-be quality, and five indifferent quality functional elements. This study qualitatively analyzes the functional elements of virtual idols through fan satisfaction based on the KANO model, which provides valuable help for future research in the field of virtual idols and producers in this field.

Improvement of the subcooled boiling model using a new net vapor generation correlation inferred from artificial neural networks to predict the void fraction profiles in the vertical channel

  • Tae Beom Lee ;Yong Hoon Jeong
    • Nuclear Engineering and Technology
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    • v.54 no.12
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    • pp.4776-4797
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    • 2022
  • In the one-dimensional thermal-hydraulic (TH) codes, a subcooled boiling model to predict the void fraction profiles in a vertical channel consists of wall heat flux partitioning, the vapor condensation rate, the bubbly-to-slug flow transition criterion, and drift-flux models. Model performance has been investigated in detail, and necessary refinements have been incorporated into the Safety and Performance Analysis Code (SPACE) developed by the Korean nuclear industry for the safety analysis of pressurized water reactors (PWRs). The necessary refinements to models related to pumping factor, net vapor generation (NVG), vapor condensation, and drift-flux velocity were investigated in this study. In particular, a new NVG empirical correlation was also developed using artificial neural network (ANN) techniques. Simulations of a series of subcooled flow boiling experiments at pressures ranging from 1 to 149.9 bar were performed with the refined SPACE code, and reasonable agreement with the experimental data for the void fraction in the vertical channel was obtained. From the root-mean-square (RMS) error analysis for the predicted void fraction in the subcooled boiling region, the results with the refined SPACE code produce the best predictions for the entire pressure range compared to those using the original SPACE and RELAP5 codes.

Application of Image Super-Resolution to SDO/HMI magnetograms using Deep Learning

  • Rahman, Sumiaya;Moon, Yong-Jae;Park, Eunsu;Cho, Il-Hyun;Lim, Daye
    • The Bulletin of The Korean Astronomical Society
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    • v.44 no.2
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    • pp.70.4-70.4
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    • 2019
  • Image super-resolution (SR) is a technique that enhances the resolution of a low resolution image. In this study, we use three SR models (RCAN, ProSRGAN and Bicubic) for enhancing solar SDO/HMI magnetograms using deep learning. Each model generates a high resolution HMI image from a low resolution HMI image (4 by 4 binning). The pixel resolution of HMI is about 0.504 arcsec. Deep learning networks try to find the hidden equation between low resolution image and high resolution image from given input and the corresponding output image. In this study, we trained three models with HMI images in 2014 and test them with HMI images in 2015. We find that the RCAN model achieves higher quality results than the other two methods in view of both visual aspects and metrics: 31.40 peak signal-to-noise ratio(PSNR), Correlation Coefficient (0.96), Root mean square error (RMSE) is 0.004. This result is also much better than the conventional bi-cubic interpolation. We apply this model to a full-resolution SDO/HMI image and compare the generated image with the corresponding Hinode NFI magnetogram. As a result, we get a very high correlation (0.92) between the generated SR magnetogram and the Hinode one.

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Dynamic characterization of 3D printed lightweight structures

  • Refat, Mohamed;Zappino, Enrico;Sanchez-Majano, Alberto Racionero;Pagani, Alfonso
    • Advances in aircraft and spacecraft science
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    • v.9 no.4
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    • pp.301-318
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    • 2022
  • This paper presents the free vibration analysis of 3D printed sandwich beams by using high-order theories based on the Carrera Unified Formulation (CUF). In particular, the component-wise (CW) approach is adopted to achieve a high fidelity model of the printed part. The present model has been used to build an accurate database for collecting first natural frequency of the beams, then predicting Young's modulus based on an inverse problem formulation. The database is built from a set of randomly generated material properties of various values of modulus of elasticity. The inverse problem then allows finding the elastic modulus of the input parameters starting from the information on the required set of the output achieved experimentally. The natural frequencies evaluated during the experimental test acquired using a Digital Image Correlation method have been compared with the results obtained by the means of CUF-CW model. The results obtained from the free-vibration analysis of the FDM beams, performed by higher-order one-dimensional models contained in CUF, are compared with ABAQUS results both first five natural frequency and degree of freedoms. The results have shown that the proposed 1D approach can provide 3D accuracy, in terms of free vibration analysis of FDM printed sandwich beams with a significant reduction in the computational costs.

Analysis of Correlation between Respiratory Characteristics and Physical Factors in Healthy Elementary School Childhood (학령기 정상 아동의 호흡 특성과 신체 조건에 관한 상관분석)

  • Lee, Hye Young;Kang, Dong Yeon;Kim, Kyoung
    • The Journal of Korean Physical Therapy
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    • v.25 no.5
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    • pp.330-336
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    • 2013
  • Purpose: Respiratory is an essential vital component for conservation of life in human, which is controlled by respiratory muscles and its related neuromuscular regulation. The purpose of this study is to assess lung capacity and respiratory pressure in healthy children, and to investigate relationship and predictability between respiratory pressure and other related respiratory functions. Methods: A total of 31 healthy children were recruited for this study. Demographic information and respiratory related factors were assessed in terms of body surface area (BSA), chest mobility, lung capacity, and respiratory pressure. Correlation between respiratory pressure and the rested variables was analyzed, and multiple regression using the stepwise method was performed for prediction of respiratory muscle strength, in terms of respiratory pressure as the dependent variable, and demographic and other respiratory variables as the independent variable. Results: According to the results of correlation analysis, respiratory pressure showed significant correlation with age (r=0.62, p<0.01), BSA (r=0.80, p<0.01), FVC (r=0.80, p<0.01), and FEV1 (r=0.70, p<0.01). In results of multiple regression analysis using the backward elimination method, BSA and FVC were included as significant factors of the predictable statistical model. The statistical model showed a significant explanation power of 71.8%. Conclusion: These findings suggest that respiratory pressure could be a valuable measurement tool for evaluation of respiratory function, because of significant relationship with physical characteristics and lung capacity, and that BSA and FVC could be possible predictable factors to explain the degree of respiratory pressure. These findings will provide useful information for clinical assessment and treatment in healthy children as well as those with pulmonary disease.