• Title/Summary/Keyword: Temperature prediction model

Search Result 1,360, Processing Time 0.026 seconds

Prediction of the Summer Effective Sky Temperatrure during the Clear Day on Osan City (오산시의 맑은날 하절기 등가 하늘온도 예측)

  • Byun, Ki-Hong
    • Journal of the Korean Solar Energy Society
    • /
    • v.30 no.5
    • /
    • pp.100-106
    • /
    • 2010
  • The purpose of this study is to predict the effective sky temperature on Osan City during the summer. The north latitude, east longitude of Osan City is $37^{\circ}06'$ and $127^{\circ}02'$. The altitude from the sea level is 48m. Empirical relations of the effective sky temperature suggested by Duffie and Beckman are compared on clear days. For the effective sky temperature prediction, data measured by the Korea Meteorological Administration is used as an input to the Bliss model. Both Hottel and Krondratyev model are used to calculate the water vapor emissivity. The results using Hottel's model match well with the empirical relation proposed by Bliss. The results show maximum, minimum, and average values depending on water vapor emissivity model. The maximum deviation is about 10K and is due to total emissivity model.

The development and application of on-line model for the prediction of strip temperature in hot strip rolling (열간 사상 압연중 판 온도예측 모델 개발 및 적용)

  • Lee J. H.;Choi J. W.;Kwak W. J.;Hwang S. M.
    • Proceedings of the Korean Society for Technology of Plasticity Conference
    • /
    • 2004.08a
    • /
    • pp.336-345
    • /
    • 2004
  • Investigated via a series of finite-element(FE) process simulation is the effect of diverse process variables on some selected non-dimensional parameters characterizing the thermo-mechanical behavior of the roll and strip in hot strip rolling. Then, on the basis of these parameters, on-line models are derived for the precise prediction of the temperature changes occurring in the bite zones as well as in the inter-stand zones in a finishing mill. The prediction accuracy of the proposed models is examined through comparison with predictions from a FE process model.

  • PDF

Prediction model for the hydration properties of concrete

  • Chu, Inyeop;Amin, Muhammad Nasir;Kim, Jin-Keun
    • Computers and Concrete
    • /
    • v.12 no.4
    • /
    • pp.377-392
    • /
    • 2013
  • This paper investigates prediction models estimating the hydration properties of concrete, such as the compressive strength, the splitting tensile strength, the elastic modulus,and the autogenous shrinkage. A prediction model is suggested on the basis of an equation that is formulated to predict the compressive strength. Based on the assumption that the apparent activation energy is a characteristic property of concrete, a prediction model for the compressive strength is applied to hydration-related properties. The hydration properties predicted by the model are compared with experimental results, and it is concluded that the prediction model properly estimates the splitting tensile strength, elastic modulus, and autogenous shrinkage as well as the compressive strength of concrete.

Development of Road Surface Temperature Prediction Model using the Unified Model output (UM-Road) (UM 자료를 이용한 노면온도예측모델(UM-Road)의 개발)

  • Park, Moon-Soo;Joo, Seung Jin;Son, Young Tae
    • Atmosphere
    • /
    • v.24 no.4
    • /
    • pp.471-479
    • /
    • 2014
  • A road surface temperature prediction model (UM-Road) using input data of the Unified Model (UM) output and road physical properties is developed and verified with the use of the observed data at road weather information system. The UM outputs of air temperature, relative humidity, wind speed, downward shortwave radiation, net longwave radiation, precipitation and the road properties such as slope angles, albedo, thermal conductivity, heat capacity at maximum 7 depth are used. The net radiation is computed by a surface radiation energy balance, the ground heat flux at surface is estimated by a surface energy balance based on the Monin-Obukhov similarity, the ground heat transfer process is applied to predict the road surface temperature. If the observed road surface temperature exists, the simulated road surface temperature is corrected by mean bias during the last 24 hours. The developed UM-Road is verified using the observed data at road side for the period from 21 to 31 March 2013. It is found that the UM-Road simulates the diurnal trend and peak values of road surface temperature very well and the 50% (90%) of temperature difference lies within ${\pm}1.5^{\circ}C$ (${\pm}2.5^{\circ}C$) except for precipitation case.

Development of the Permanent Deformation Prediction Model of 19mm Dense Grade Asphalt Mixtures (19mm 밀입도 아스팔트 혼합물의 소성변형 예측 모델 개발)

  • Park, Hee-Mun;Choi, Ji-Young;Park, Seong-Wan
    • International Journal of Highway Engineering
    • /
    • v.7 no.4 s.26
    • /
    • pp.1-8
    • /
    • 2005
  • Permanent Deformation is one of the most important load-related pavement distresses in asphalt pavements. The Korean Pavement Design Guide currently being developed adopted the mechanistic-empirical approach and needed the pavement distress prediction models. This study intends to develop the model for prediction of permanent deformation in the asphalt layer and estimate the pavement performance. The objectives of this paper are to figure out the factors affecting the permanent deformation and then develop the permanent deformation prediction model for asphalt mixtures. The repeated triaxial load test was Performed on the 19mm dense graded asphalt mixture with variation of temperature and air void. Results from the laboratory tests showed that temperature and air void in asphalt mixtures have significantly influenced on the factors in prediction model. The permanent deformation prediction model for 19m dense grade asphalt mixtures has been developed using the multiple regression approach and validated the proposed permanent deformation prediction model.

  • PDF

Two-dimensional attention-based multi-input LSTM for time series prediction

  • Kim, Eun Been;Park, Jung Hoon;Lee, Yung-Seop;Lim, Changwon
    • Communications for Statistical Applications and Methods
    • /
    • v.28 no.1
    • /
    • pp.39-57
    • /
    • 2021
  • Time series prediction is an area of great interest to many people. Algorithms for time series prediction are widely used in many fields such as stock price, temperature, energy and weather forecast; in addtion, classical models as well as recurrent neural networks (RNNs) have been actively developed. After introducing the attention mechanism to neural network models, many new models with improved performance have been developed; in addition, models using attention twice have also recently been proposed, resulting in further performance improvements. In this paper, we consider time series prediction by introducing attention twice to an RNN model. The proposed model is a method that introduces H-attention and T-attention for output value and time step information to select useful information. We conduct experiments on stock price, temperature and energy data and confirm that the proposed model outperforms existing models.

A Study on Effect of Process Parameters and Development of Prediction Model for Prepolymer Mass Production (대용량 프리폴리머 중합공정의 영향인자 평가 및 예측모델 개발에 관한 연구)

  • Ha, Kyong-Ho;Kang, Dae-Min
    • Journal of the Korean Society of Manufacturing Process Engineers
    • /
    • v.13 no.2
    • /
    • pp.81-88
    • /
    • 2014
  • Synthetic products such as casting tape and splints are rapidly replacing conventional plaster casts to treat orthopedic patients. Most synthetic products are produced through a polymerization process with related chemical agents. In this study, the effect of the process parameters on the residual NCO content within a prepolymer for casting tape and the hardening temperature for casting tape were experimentally evaluated. In order to verify the effects of the process parameters, an experimental method was adopted. From an S/N ratio analysis, optimal parameter combinations were determined to produce a pre-polymer with a suitable residual NCO content and alower hardening temperature. Prediction models for the NCO content and the hardening temperature were developed and confirmed.

Development of the Numerical Model for Temperature Prediction of Fruits (청과물의 품온예측모델 개발)

  • 김의웅;김병삼;남궁배;정진웅;김동철;금동혁
    • Journal of Biosystems Engineering
    • /
    • v.20 no.4
    • /
    • pp.343-350
    • /
    • 1995
  • In order to design efficient and effective pressure cooling system for fruits and vegetables, a numerical model for temperature prediction of fruits was developed. This model was extended to study the various factors affecting product cooling time, such as product depth, approach air temperature, entering air velocity and initial product temperature. Also, selection of these factors were examined with respect to the efficiency of the pressure cooling system, the overall precooling cost and the final quality of the product. When designing a pressure cooling system for a particular product, the range of the factors must be selected carefully according to the thermal and physiological properties.

  • PDF

Temporal and Spatial correlation of Meteorological Data in Sumjin River and Yongsan River Basins (섬진강 및 영산강 유역 기상자료의 시.공간적 상관성)

  • 김기성
    • Magazine of the Korean Society of Agricultural Engineers
    • /
    • v.41 no.6
    • /
    • pp.44-53
    • /
    • 1999
  • The statistical characteristics of the factors related to the daily rainfall prediction model are analyzed . Records of daily precipitation, mean air temperature, relative humidity , dew-point temperature and air pressure from 1973∼1998 at 8 meteorological sttions in south-western part of Korea were used. 1. Serial correlatino of daily precipitaiton was significant with the lag less than 1 day. But , that of other variables were large enough until 10 day lag. 2. Crosscorrelation of air temperature, relative humidity , dew-point temperature showed similar distribution wiht the basin contrours and the others were different. 3. There were significant correlation between the meteorological variables and precipitation preceded more than 2 days. 4. Daily preciption of each station were treated as a truncated continuous random variable and the annual periodic components, mean and standard deviation were estimated for each day. 5. All of the results could be considered to select the input variables of regression model or neural network model for the prediction of daily precipitation and to construct the stochastic model of daily precipitation.

  • PDF

Development and Evaluation of Predictive Model for Microstructures and Mechanical Material Properties in Heat Affected Zone of Pressure Vessel Steel Weld (압력용기강 용접 열영향부에서의 미세조직 및 기계적 물성 예측절차 개발 및 적용성 평가)

  • Kim, Jong-Sung;Lee, Seung-Gun;Jin, Tae-Eun
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.26 no.11
    • /
    • pp.2399-2408
    • /
    • 2002
  • A prediction procedure has been developed to evaluate the microtructures and material properties of heat affected zone (HAZ) in pressure vessel steel weld, based on temperature analysis, thermodynamics calculation and reaction kinetics model. Temperature distributions in HAE are calculated by finite element method. The microstructures in HAZ are predicted by combining the temperature analysis results with the reaction kinetics model for austenite grain growth and austenite decomposition. Substituting the microstructure prediction results into the previous experimental relations, the mechanical material properties such as hardness, yielding strength and tensile strength are calculated. The prediction procedure is modified and verified by the comparison between the present results and the previous study results for the simulated HAZ in reactor pressure vessel (RPV) circurnferential weld. Finally, the microstructures and mechanical material properties are determined by applying the final procedure to real RPV circumferential weld and the local weak zone in HAZ is evaluated based on the application results.