2023
DOI: 10.1016/j.dche.2023.100095
|View full text |Cite
|
Sign up to set email alerts
|

Evaluation of dynamic responses of a BFB boiler furnace by means of CFD modelling

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 28 publications
0
1
0
Order By: Relevance
“…The introduction of digital tools such as machine learning, artificial neural networks, and other modelling tools. in real-time process monitoring and optimization, product yield prediction, production metering, life-cycle assessment, and techno-economic analysis will accelerate scalability, and bridge the knowledge gaps in the autothermal pyrolysis technology [79,80]. Table 4 summarizes the production of green hydrogen from diverse crop residues using advanced thermochemical conversion technologies.…”
Section: Autothermal Pyrolysismentioning
confidence: 99%
“…The introduction of digital tools such as machine learning, artificial neural networks, and other modelling tools. in real-time process monitoring and optimization, product yield prediction, production metering, life-cycle assessment, and techno-economic analysis will accelerate scalability, and bridge the knowledge gaps in the autothermal pyrolysis technology [79,80]. Table 4 summarizes the production of green hydrogen from diverse crop residues using advanced thermochemical conversion technologies.…”
Section: Autothermal Pyrolysismentioning
confidence: 99%