• Title/Summary/Keyword: Speed Prediction

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A dryout mechanism model for rectangular narrow channels at high pressure conditions

  • Song, Gongle;Liang, Yu;Sun, Rulei;Zhang, Dalin;Deng, Jian;Su, G.H.;Tian, Wenxi;Qiu, Suizheng
    • Nuclear Engineering and Technology
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    • v.52 no.10
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    • pp.2196-2203
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    • 2020
  • A dryout mechanism model for rectangular narrow channels at high pressure conditions is developed by assuming that the Kelvin-Helmholtz instability triggered the occurrence of dryout. This model combines the advantages of theoretical analysis and empirical correlation. The unknown coefficients in the theoretical derivation are supported by the experimental data. Meanwhile, the decisive restriction of the experimental conditions on the applicability of the empirical correlation is avoided. The expression of vapor phase velocity at the time of dryout is derived, and the empirical correlation of liquid film thickness is introduced. Since the CHF value obtained from the liquid film thickness should be the same as the value obtained from the Kelvin-Helmholtz critical stability under the same condition, the convergent CHF value is obtained by iteratively calculating. Comparing with the experimental data under the pressure of 6.89-13.79 MPa, the average error of the model is -15.4% with the 95% confidence interval [-20.5%, -10.4%]. And the pressure has a decisive influence on the prediction accuracy of this model. Compared with the existing dryout code, the calculation speed of this model is faster, and the calculation accuracy is improved. This model, with great portability, could be applied to different objects and working conditions by changing the expression of the vapor phase velocity when the dryout phenomenon is triggered and the calculation formula of the liquid film.

Nondestructive Inspection of Steel Structures Using Phased Array Ultrasonic Technique (위상배열 초음파기법을 이용한 강구조물의 비파괴 탐상)

  • Shin, Hyeon-Jae;Song, Sung-Jin;Jang, You-Hyun
    • Journal of the Korean Society for Nondestructive Testing
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    • v.20 no.6
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    • pp.538-544
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    • 2000
  • A phased array ultrasonic nondestructive inspection system is being developed to obtain images of the interior of steel structures by modifying a medical ultrasound imaging system. The medical system consists of 64 individual transceiver channels that can drive 128 array elements. Several modifications of the system were required mainly due to the change of sound speed. It was necessary to fabricate array transducers for steel structure and to obtain A-scan signal that is necessary for the nondestructive testing. Boundary diffraction wave model was used for the prediction of radiation beam field from array transducers, which provided guidelines to design array transducers. And a RF data acquisition board was fabricated for the A-scan signal acquisition along a selected un line within an image. For the proper beam forming in the transmission and reception for steel structure, delay time was controlled. To demonstrate the performance of the developed system and fabricated transducers, images of artificial specimens and A-scan signals for selected scan lines were obtained in a real time fashion.

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A Study on Predictive Traffic Information Using Cloud Route Search (클라우드 경로탐색을 이용한 미래 교통정보 예측 방법)

  • Jun Hyun, Kim;Kee Wook, Kwon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.4
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    • pp.287-296
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    • 2015
  • Recent navigation systems provide quick guide services, based on processing real-time traffic information and past traffic information by applying predictable pattern for traffic information. However, the current pattern for traffic information predicts traffic information by processing past information that it presents an inaccuracy problem in particular circumstances(accidents and weather). So, this study presented a more precise predictive traffic information system than historical traffic data first by analyzing route search data which the drivers ask in real time for the quickest way then by grasping traffic congestion levels of the route in which future drivers are supposed to locate. First results of this study, the congested route from Yang Jae to Mapo, the analysis result shows that the accuracy of the weighted value of speed of existing commonly congested road registered an error rate of 3km/h to 18km/h, however, after applying the real predictive traffic information of this study the error rate registered only 1km/h to 5km/h. Second, in terms of quality of route as compared to the existing route which allowed for an earlier arrival to the destination up to a maximum of 9 minutes and an average of up to 3 minutes that the reliability of predictable results has been secured. Third, new method allows for the prediction of congested levels and deduces results of route searches that avoid possibly congested routes and to reflect accurate real-time data in comparison with existing route searches. Therefore, this study enabled not only the predictable gathering of information regarding traffic density through route searches, but it also made real-time quick route searches based on this mechanism that convinced that this new method will contribute to diffusing future traffic flow.

An intercomparison study between optimization algorithms for parameter estimation of microphysics in Unified model : Micro-genetic algorithm and Harmony search algorithm (통합모델의 강수물리과정 모수 최적화를 위한 알고리즘 비교 연구 : 마이크로 유전알고리즘과 하모니 탐색 알고리즘)

  • Jang, Jiyeon;Lee, Yong Hee;Joo, Sangwon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.27 no.1
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    • pp.79-87
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    • 2017
  • The microphysical processes of the numerical weather prediction (NWP) model cover the following : fall speed, accretion, autoconversion, droplet size distribution, etc. However, the microphysical processes and parameters have a significant degree of uncertainty. Parameter estimation was generally used to reduce errors in NWP models associated with uncertainty. In this study, the micro- genetic algorithm and harmony search algorithm were used as an optimization algorithm for estimating parameters. And we estimate parameters of microphysics for the Unified model in the case of precipitation in Korea. The differences which occurred during the optimization process were due to different characteristics of the two algorithms. The micro-genetic algorithm converged to about 1.033 after 440 times. The harmony search algorithm converged to about 1.031 after 60 times. It shows that the harmony search algorithm estimated optimal parameters more quickly than the micro-genetic algorithm. Therefore, if you need to search for the optimal parameter within a faster time in the NWP model optimization problem with large calculation cost, the harmony search algorithm is more suitable.

Multiple Linear Regression Analysis of PV Power Forecasting for Evaluation and Selection of Suitable PV Sites (태양광 발전소 건설부지 평가 및 선정을 위한 선형회귀분석 기반 태양광 발전량 추정 모델)

  • Heo, Jae;Park, Bumsoo;Kim, Byungil;Han, SangUk
    • Korean Journal of Construction Engineering and Management
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    • v.20 no.6
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    • pp.126-131
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    • 2019
  • The estimation of available solar energy at particular locations is critical to find and assess suitable locations of PV sites. The amount of PV power generation is however affected by various geographical factors (e.g., weather), which may make it difficult to identify the complex relationship between affecting factors and power outputs and to apply findings from one study to another in different locations. This study thus undertakes a regression analysis using data collected from 172 PV plants spatially distributed in Korea to identify critical weather conditions and estimate the potential power generation of PV systems. Such data also include solar radiation, precipitation, fine dust, humidity, temperature, cloud amount, sunshine duration, and wind speed. The estimated PV power generation is then compared to the actual PV power generation to evaluate prediction performance. As a result, the proposed model achieves a MAPE of 11.696(%) and an R-squred of 0.979. It is also found that the variables, excluding humidity, are all statistically significant in predicting the efficiency of PV power generation. According, this study may facilitate the understanding of what weather conditions can be considered and the estimation of PV power generation for evaluating and determining suitable locations of PV facilities.

Diagnosis and Prognosis of Sepsis (패혈증의 진단 및 예후예측)

  • Park, Chang-Eun
    • Korean Journal of Clinical Laboratory Science
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    • v.53 no.4
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    • pp.309-316
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    • 2021
  • Sepsis is a physiological response to a source of infection that triggers mechanisms that compromise organ function, leading to death if not treated early. Biomarkers with high sensitivity, specificity, speed, and accuracy that could differentiate sepsis from non-infectious systemic inflammatory response syndrome (SIRS) could bring about a revolution in sepsis treatment. Given the limitations and time required for microbial verification of pathogens, the accurate diagnosis of infection before employing antibiotic therapy is important and clinically necessary. Procalcitonin (PCT), lactate, C-reactive protein (CRP), cytokines, and proadrenomedullin (ProADM) are the common biomarkers used for diagnosis. The procalcitonin (PCT)-guided antibiotic treatment in patients with acute respiratory infections effectively reduces antibiotic exposure and side effects while improving survival rates. The evidence regarding sepsis screening in hospitalized patients is limited. Clinicians, researchers, and healthcare decision-makers should consider these findings and limitations when implementing screening tools, future research, or policy on sepsis recognition in hospitalized patients. The use of biomarkers in pediatric sepsis is promising, although such use should always be correlated with clinical evaluation. Biomarkers may also improve the prediction of mortality, especially in the early phase of sepsis, when the levels of certain pro-inflammatory cytokines and proteins are elevated.

Correlation between Microstructure and Mechanical Properties of the Additive Manufactured H13 Tool Steel (적층 제조된 H13 공구강의 미세조직과 기계적 특성간의 상관관계)

  • An, Woojin;Park, Junhyeok;Lee, Jungsub;Choe, Jungho;Jung, Im Doo;Yu, Ji-Hun;Kim, Sangshik;Sung, Hyokyung
    • Korean Journal of Materials Research
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    • v.28 no.11
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    • pp.663-670
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    • 2018
  • H13 tool steels are widely used as metallic mold materials due to their high hardness and thermal stability. Recently, many studies are undertaken to satisfy the demands for manufacturing the complex shape of the mold using a 3D printing technique. It is reported that the mechanical properties of 3D printed materials are lower than those of commercial forged alloys owing to micropores. In this study, we investigate the effect of microstructures and defects on mechanical properties in the 3D printed H13 tool steels. H13 tool steel is fabricated using a selective laser melting(SLM) process with a scan speed of 200 mm/s and a layer thickness of $25{\mu}m$. Microstructures are observed and porosities are measured by optical and scanning electron microscopy in the X-, Y-, and Z-directions with various the build heights. Tiny keyhole type pores are observed with a porosity of 0.4 %, which shows the lowest porosity in the center region. The measured Vickers hardness is around 550 HV and the yield and tensile strength are 1400 and 1700 MPa, respectively. The tensile properties are predicted using two empirical equations through the measured values of the Vickers hardness. The prediction of tensile strength has high accuracy with the experimental data of the 3D printed H13 tool steel. The effects of porosities and unmelted powders on mechanical properties are also elucidated by the metallic fractography analysis to understand tensile and fracture behavior.

Motion Monitoring using Mask R-CNN for Articulation Disease Management (관절질환 관리를 위한 Mask R-CNN을 이용한 모션 모니터링)

  • Park, Sung-Soo;Baek, Ji-Won;Jo, Sun-Moon;Chung, Kyungyong
    • Journal of the Korea Convergence Society
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    • v.10 no.3
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    • pp.1-6
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    • 2019
  • In modern society, lifestyle and individuality are important, and personalized lifestyle and patterns are emerging. The number of people with articulation diseases is increasing due to wrong living habits. In addition, as the number of households increases, there is a case where emergency care is not received at the appropriate time. We need information that can be managed by ourselves through accurate analysis according to the individual's condition for health and disease management, and care appropriate to the emergency situation. It is effectively used for classification and prediction of data using CNN in deep learning. CNN differs in accuracy and processing time according to the data features. Therefore, it is necessary to improve processing speed and accuracy for real-time healthcare. In this paper, we propose motion monitoring using Mask R-CNN for articulation disease management. The proposed method uses Mask R-CNN which is superior in accuracy and processing time than CNN. After the user's motion is learned in the neural network, if the user's motion is different from the learned data, the control method can be fed back to the user, the emergency situation can be informed to the guardian, and appropriate methods can be taken according to the situation.

Analytic study on thermal management operating conditions of balance of 100kW fuel cell power plant for a fuel cell electric vehicle (100kW급 연료전지 열관리 시스템 실도로 운전조건 해석적 연구)

  • Lee, Ho-Seong;Lee, Moo-Yeon;Cho, Choong-Won
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.2
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    • pp.1-6
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    • 2019
  • The objective of this study was to investigate performance characteristics of thermal management system(TMS) in a fuel cell electric vehicle with 100kW Fuel Cell(FC) system. In order to build up analytic modelling for TMS, each component was installed and tested under various operating conditions, such as water pump, radiator, 3-Way valve, COD heater, and FC stack etc. and as the results of them, correlations reflecting component's characteristics with flow rate, air velocity were developed. Developed analytic modelling was carried out under various operating conditions on the road. To verify modelling's accuracy, after prediction for optimum coolant flow rate was fulfilled under certain operating conditions, such as FC system, water pump speed, opening of 3-way valve, and pipe resistance, analytic and experimental values were compared and good agreement was shown. In order to predict cold-start operating performance for analytic modelling, coolant temperature variation was analyzed with $-20^{\circ}C$ ambient temperature and duration was predicted to rise in optimum temperature for FC. Because there is appropriate temperature difference between inlet and outlet of FC stack to operate FC system properly, related analysis was performed with respect to power consumption for TMS and heat rejection rate and performance map was depicted along with FC operating conditions.

Development of a Coupled Eulerian-Lagrangian Finite Element Model for Dissimilar Friction Stir Welding (Coupled Eulerian-Lagrangian기법을 이용한 이종 마찰교반용접 해석모델 개발)

  • Lim, Jae-Yong;Lee, Jinho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.2
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    • pp.7-13
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    • 2019
  • This study aims to develop a FE Model to simulate dissimilar friction stir welding and to address its potential for fundamental analysis and practical applications. The FE model is based on Coupled Eulerian-Lagrangian approach. Multiphysics systems are calculated using explicit time integration algorithm, and heat generations by friction and inelastic heat conversion as well as heat transfer through the bottom surface are included. Using the developed model, friction stir welding between an Al6061T6 plate and an AZ61 plate were simulated. Three simulations are carried out varying the welding parameters. The model is capable of predicting the temperature and plastic strain fields and the distribution of void. The simulation results showed that temperature was generally greater in Mg plates and that, as a rotation speed increase, not the maximum temperature of Mg plate increased, but did the temperature of Al plate. In addition, the model could predict flash defects, however, the prediction of void near the welding tool was not satisfactory. Since the model includes the complex physics closely occurring during FSW, the model possibly analyze a lot of phenomena hard to discovered by experiments. However, practical applications may be limited due to huge simulation time.