Study of Phase Distribution of a Liquid-Solid Circulating Fluidized Bed Reactor Using Abductive Network Modeling Approach

2013 ◽  
Vol 8 (2) ◽  
pp. 77-91 ◽  
Author(s):  
Shaikh A. Razzak
Keyword(s):  
Fluidized Bed ◽  
Network Model ◽  
Circulating Fluidized Bed ◽  
Phase Distribution ◽  
Network Modeling ◽  
Absolute Error ◽  
Pilot Scale ◽  
Cross Sectional ◽  
Modeling Approach ◽  
Abductive Network

Abstract This communication deals with the Abductive Network modeling approach to investigate the phase holdup distributions of a liquid–solid circulating fluidized bed (LSCFB) system. The Abductive Network model is developed/trained using experimental data collected from a pilot scale LSCFB reactor involving 500-μm size glass beads and water as solid and liquid phases, respectively. The trained Abductive Network model successfully predicted experimental phase holdups of the LSCFB riser under different operating parameters. It is observed that the model predicted cross-sectional average of solids holdups in the axial directions and radial flow structure are well agreement with the experimental values. The statistical performance indicators including the mean absolute error (~4.67%) and the correlation coefficient (0.992) also show favorable indications of the suitability of Abductive Network modeling approach in predicting the solids holdup of the LSCFB system.

Application of Support Vector Machine Modeling on Phase Distribution in the Riser of an LSCFB Reactor

2014 ◽  
Vol 12 (1) ◽  
pp. 123-134 ◽  
Author(s):  
Shaikh A. Razzak ◽  
Muhammad I. Hossain ◽  
Syed M. Rahman ◽  
Mohammad M. Hossain
Keyword(s):  
Support Vector Machine ◽  
Circulating Fluidized Bed ◽  
Phase Distribution ◽  
Solid Phase ◽  
Correlation Coefficients ◽  
Absolute Error ◽  
Pilot Scale ◽  
Support Vector ◽  
Cross Sectional ◽  
Machine Modeling

Abstract Support vector machine (SVM) modeling approach is applied to predict the solids holdups distribution of a liquid–solid circulating fluidized bed (LSCFB) riser. The SVM model is developed/trained using experimental data collected from a pilot-scale LSCFB reactor. Two different size glass bead particles (500 μm (GB-500) and 1,290 μm (GB-1290)) are used as solid phase, and water is used as liquid phase. The trained model successfully predicted the experimental solids holdups of the LSCFB riser under different operating parameters. It is observed that the model predicted cross-sectional average of solids holdups in the axial directions and radial flow structure are well agreement with the experimental values. The goodness of the model prediction is verified by using different statistical performance indicators. For the both sizes of particles, the mean absolute error is found to be less than 5%. The correlation coefficients (0.998 for GB-500 and 0.994 for GB-1290) also show favorable indications of the suitability of SVM approach in predicting the solids holdup of the LSCFB system.

Applications of Feed-Forward Neural Network to Study Irregular-Shape Particle Effects on Hydrodynamics Behavior in a Liquid–Solid Circulating Fluidized Bed Riser

2013 ◽  
Vol 11 (1) ◽  
pp. 443-452 ◽  
Author(s):  
Shaikh Abdur Razzak
Keyword(s):  
Neural Network ◽  
Experimental Data ◽  
Fluidized Bed ◽  
Circulating Fluidized Bed ◽  
Phase Distribution ◽  
Flow Behavior ◽  
Pilot Scale ◽  
Irregular Shape ◽  
Feed Forward Neural Network ◽  
Feed Forward

Abstract Feed-forward neural network (FFNN) modeling techniques are applied to study the flow behavior of different-size irregular-shape particles in a pilot scale liquid–solid circulating fluidized bed (LSCFB) riser. The adequacy of the developed model is examined by comparing the model predictions with experimental data obtained from the LSCFB using lava rocks (dmean 500 and 920 µm) and water as solids and liquid phases, respectively. Axial and radial solid holdup profiles are measured in the riser at four axial locations (H 1, 2, 3 and 3.8 m above the distributor) above the liquid distributor for different operating liquids. In the model training, the effects of various auxiliary and primary liquid velocities, superficial liquid velocities and superficial solid velocities on radial phase distribution at different axial positions are considered. For model validation along with other experimental parameters, dimensionless normalized superficial liquid velocities and net superficial liquid velocities are also introduced. The correlation coefficient values of the predicted output and the experimental data are found to be 0.95 and 0.94 for LR-500 and LR-920 particles, respectively which reflects the competency of the developed FFNN model.

Carbon dioxide purity and combustion characteristics of oxy firing compared to air firing in a pilot-scale circulating fluidized bed

Energy ◽  
2019 ◽  
Vol 166 ◽  
pp. 183-192 ◽  
Author(s):  
Ji-Hong Moon ◽  
Sung-Ho Jo ◽  
Sung Jin Park ◽  
Nguyen Hoang Khoi ◽  
Myung Won Seo ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Fluidized Bed ◽  
Circulating Fluidized Bed ◽  
Pilot Scale ◽  
Combustion Characteristics

Pilot-Scale Study on Improving SNCR Denitrification Efficiency by Using Gas Additives

2018 ◽  
Vol 17 (3) ◽  
Author(s):  
Zhou Weiqing ◽  
Liu Meng ◽  
Huang Baohua ◽  
Qiu Xiaozhi
Keyword(s):  
Low Temperature ◽  
Fluidized Bed ◽  
Reaction Temperature ◽  
Temperature Region ◽  
Circulating Fluidized Bed ◽  
Catalytic Reduction ◽  
Pilot Scale ◽  
Incomplete Oxidation ◽  
Optimal Value

Abstract The experiment of improving Selective Non-Catalytic Reduction (SNCR) denitrification efficiency with gas additives (CH4 and C3H8) was carried out in the 50 kW circulating fluidized bed (CFB) pilot-scale equipment. The results show that the denitrification efficiency can reach 20 % when the reaction temperature is 650 °C, and the optimum mole ratio of C3H8/NH3 is 0.5. The denitrification efficiency can exceed 50 % when the mole ratio of C3H8/NH3 is 0.4 and the reaction temperature is 720 °C. However, the CH4 additive does not promote denitrification at this temperature. When the reaction temperature is 760 °C, the optimum denitrification efficiency of CH4 is 60 %, and the required CH4/NH3 is 0.8. Once the amount of CH4 exceeds the optimal value, the denitrification efficiency is suppressed. In addition, the concentrations of N2O and CO in the gas increase significantly with an increase of gas additives. Due to the incomplete oxidation of C3H8, a large amount of C2H4 is produced in the low-temperature region (< 750 °C) of SNCR.

scholarly journals Predicting mobile apps spread: An epidemiological random network modeling approach

SIMULATION ◽  
2017 ◽  
Vol 94 (2) ◽  
pp. 123-130 ◽  
Author(s):  
Juan Alegre-Sanahuja ◽  
Juan-Carlos Cortés ◽  
Rafael-Jacinto Villanueva ◽  
Francisco-José Santonja
Keyword(s):  
Network Model ◽  
Mobile Applications ◽  
Mobile Apps ◽  
Random Network ◽  
Network Modeling ◽  
Numerical Results ◽  
Business Managers ◽  
Short Term ◽  
Modeling Approach ◽  
Proposed Model

The mobile applications business is a really big market, growing constantly. In app marketing, a key issue is to predict future app installations. The influence of the peers seems to be very relevant when downloading apps. Therefore, the study of the evolution of mobile apps spread may be approached using a proper network model that considers the influence of peers. Influence of peers and other social contagions have been successfully described using models of epidemiological type. Hence, in this paper we propose an epidemiological random network model with realistic parameters to predict the evolution of downloads of apps. With this model, we are able to predict the behavior of an app in the market in the short term looking at its evolution in the early days of its launch. The numerical results provided by the proposed network are compared with data from real apps. This comparison shows that predictions improve as the model is fed back. Marketing researchers and strategy business managers can benefit from the proposed model since it can be helpful to predict app behavior over the time anticipating the spread of an app.

Nonintrusive Particle Motion Studies in the Near-Wall Region of a Pilot-Scale Circulating Fluidized Bed

2004 ◽  
Vol 43 (18) ◽  
pp. 5582-5592 ◽  
Author(s):  
Preetanshu Pandey ◽  
Richard Turton ◽  
Paul Yue ◽  
Lawrence Shadle
Keyword(s):  
Fluidized Bed ◽  
Particle Motion ◽  
Circulating Fluidized Bed ◽  
Pilot Scale ◽  
Wall Region ◽  
Motion Studies ◽  
Near Wall
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