Do particle-related parameters influence circulating fluidized bed (CFB) riser flux and elutriation?
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Do particle-related parameters influence circulating fluidized bed (CFB) riser flux and elutriation?
Authors
Keywords
circulating fluidized bed (CFB) riser, Mass flux, Elutriation, Machine learning, Geldart Group B, Particle properties
Journal
CHEMICAL ENGINEERING SCIENCE
Volume 227, Issue -, Pages 115935
Publisher
Elsevier BV
Online
2020-07-03
DOI
10.1016/j.ces.2020.115935
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Application of machine learning methods to understand and predict circulating fluidized bed riser flow characteristics
- (2020) Jia Wei Chew et al. CHEMICAL ENGINEERING SCIENCE
- A machine learning approach for electrical capacitance tomography measurement of gas-solid fluidized beds
- (2019) Qiang Guo et al. AICHE JOURNAL
- Hydrodynamic characteristics in a cold model of the dual fluidized bed with mixed particles
- (2019) Xin Yang et al. POWDER TECHNOLOGY
- Computer vision for real-time monitoring of shrinkage for peas dried in a fluidized bed dryer
- (2019) Anthony Iheonye et al. DRYING TECHNOLOGY
- Effects of Operating Parameters on Solids Flux in a High-Density/-Flux Circulating Fluidized Bed Riser Reactor
- (2019) Xin Su et al. ENERGY & FUELS
- Uncertainty quantification of fluidized beds using a data-driven framework
- (2019) V.M. Krushnarao Kotteda et al. POWDER TECHNOLOGY
- Coarse grid simulation of the hydrodynamics of binary gas-solid flow in CFB risers
- (2018) Zhiyuan Qin et al. CANADIAN JOURNAL OF CHEMICAL ENGINEERING
- Evaluation of correlations for minimum fluidization velocity ( Umf ) in gas-solid fluidization
- (2018) Aditya Anantharaman et al. POWDER TECHNOLOGY
- An artificial intelligence based approach to predicting syngas composition for downdraft biomass gasification
- (2018) Ali Yener Mutlu et al. ENERGY
- The promise of artificial intelligence in chemical engineering: Is it here, finally?
- (2018) Venkat Venkatasubramanian AICHE JOURNAL
- Comparison of solid phase closure models in Eulerian-Eulerian simulations of a circulating fluidized bed riser
- (2018) Markku Nikku et al. CHEMICAL ENGINEERING SCIENCE
- Annulus flow behavior of Geldart Group B particles in a pilot-scale CFB riser
- (2017) Aditya Anantharaman et al. POWDER TECHNOLOGY
- Model NOx emission and thermal efficiency of CFBB based on an ameliorated extreme learning machine
- (2017) Peifeng Niu et al. SOFT COMPUTING
- Interpreting Differential Pressure Signals for Particle Properties and Operating Conditions in a Pilot-Scale Circulating Fluidized Bed Riser
- (2016) Aditya Anantharaman et al. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
- Gas–solid flow in a high-density circulating fluidized bed riser with Geldart group B particles
- (2016) Jian Chang et al. Particuology
- Review of entrainment correlations in gas–solid fluidization
- (2015) Jia Wei Chew et al. CHEMICAL ENGINEERING JOURNAL
- Deep learning in neural networks: An overview
- (2015) Jürgen Schmidhuber NEURAL NETWORKS
- Comparative study of Transport Disengaging Height (TDH) correlations in gas–solid fluidization
- (2015) Andy Cahyadi et al. POWDER TECHNOLOGY
- Challenge problem: 1. Model validation of circulating fluidized beds
- (2014) Rupen Panday et al. POWDER TECHNOLOGY
- Species segregation of binary mixtures and a continuous size distribution of Group B particles in riser flow
- (2011) Jia Wei Chew et al. CHEMICAL ENGINEERING SCIENCE
- Cluster characteristics of Geldart group B particles in a pilot-scale CFB riser. II. Polydisperse systems
- (2011) Jia Wei Chew et al. CHEMICAL ENGINEERING SCIENCE
- Cluster characteristics of Geldart Group B particles in a pilot-scale CFB riser. I. Monodisperse systems
- (2011) Jia Wei Chew et al. CHEMICAL ENGINEERING SCIENCE
- Impact of material property and operating conditions on mass flux profiles of monodisperse and polydisperse Group B particles in a CFB riser
- (2011) Jia Wei Chew et al. POWDER TECHNOLOGY
- Reverse core-annular flow of Geldart Group B particles in risers
- (2011) Jia Wei Chew et al. POWDER TECHNOLOGY
- Variable selection using random forests
- (2010) Robin Genuer et al. PATTERN RECOGNITION LETTERS
- Estimate of solid flow rate from pressure measurement in circulating fluidized bed
- (2010) Esmail R. Monazam et al. POWDER TECHNOLOGY
- Particle clusters in and above fluidized beds
- (2010) Ray Cocco et al. POWDER TECHNOLOGY
- Empirical characterization of random forest variable importance measures
- (2007) Kellie J. Archer et al. COMPUTATIONAL STATISTICS & DATA ANALYSIS
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started