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A model for predicting transport velocity in gas fluidized-beds
Kim, Daewook,Won, Yoo Sube,Khurram, Muhammad Shahzad,Joo, Ji Bong,Choi, Jeong-Hoo,Ryu, Ho-Jung Elsevier 2018 Advanced powder technology Vol.29 No.12
<P><B>Abstract</B></P> <P>This study improved the model that used the correlation of the particle entrainment rate to determine the transport velocity. It proposed the new absolute value of the local slope as the criterion of the model for locating the transport velocity in the relationship between dimensionless velocity (U/U<SUB>t</SUB>) and the reciprocal of the entrainment rate (1/K<SUB>i</SUB> <SUP>∗+</SUP>). It indicated that the criterion depended on properties of fluidized particles and increased with Archemedes number. The Archemedes number was modified by substituting the critical diameter, the maximum particle diameter at which the sum of the interparticle adhesion forces gave a dominant influence to the particle entrainment rate, for the diameter of particles in case that the mean diameter of particles was smaller than the critical diameter. A correlation was suggested to calculate the absolute value of the local slope at the transport velocity. The new model was successful covering the effect of particle properties in predicting the transport velocity.</P> <P><B>Highlights</B></P> <P> <UL> <LI> This model determined the transport velocity from the correlation of entrainment rate. </LI> <LI> The criterion for locating the transport velocity was proposed. </LI> <LI> The criterion increased with Archimedes number. </LI> <LI> A correlation for the criterion was successful in predicting the transport velocity. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>Archimedes number versus absolute slope at transport velocity.</P> <P>[DISPLAY OMISSION]</P>
Effects of angle on the transport velocity in an inclined fluidized-bed
Muhammad Shahzad Khurram,최정후,Yoo Sube Won,A Reum Jeong,박영철,류호정,이창근 한국화학공학회 2015 Korean Journal of Chemical Engineering Vol.32 No.12
The transport velocity (utri) in an inclined fluidized-bed was investigated by varying the bed angle relative to the horizontal plane (0o-90o), the particle diameter (0.021-0.925mm), and density (1,272-4,503 kg/m3). This study employed the emptying time method to determine the transport velocity. The transport velocity for the vertical fluidized- bed (utr90) was revealed to increase appreciably with the aspect ratio of the fluidized-bed. The transport velocity decreased as the bed angle increased. The ratio of the transport velocity to that for the vertical bed (utri/utr90) decreased with an increase in either the bed angle or the ratio of the particle diameter (dp) to the critical particle diameter (dp *), i.e., the maximum particle diameter at which the sum of the interparticle adhesion forces had a dominant influence on particle entrainment. Correlations for the transport velocity according to the bed angle relative to the horizontal plane were proposed successfully, based on the experimental data.
A Sectoral Stock Investment Strategy Model in Indonesia Stock Exchange
Defrizal DEFRIZAL,Khomsahrial ROMLI,Agus PURNOMO,Hengky Achmad SUBING 한국유통과학회 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.1
This study aims to obtain a stock investment strategy model based on the industrial sector in Indonesia Stock Exchange (IDX). This study uses IDX data for the period of January 1996 to December 2016. This study uses the Markov Regime Switching Model to identify trends in market conditions that occur in industrial sectors on IDX. Furthermore, by using the Logit Regression Model, we can see the influence of economic factors in determining trends in market conditions sectorally and the probability of trends in market conditions. This probability can be the basis for determining stock investment decisions in certain sectors. The results showed descriptively that the stocks of the consumer goods industry sector had the highest average return and the lowest standard deviation. The trend in sectoral stock market conditions that occur in IDX can be divided into two conditions, namely bullish condition (high returns and low volatility) and bearish condition (low returns and high volatility). Differences in the conditions are mainly due to differences in volatility. The use of a Logit Regression Model to produce probability of market conditions and to estimate the influence of economic factors in determining stock market conditions produces models that have varying predictive abilities.