Challenges of Modeling and Simulation for Methanol Production
; Tarifa, Enrique Eduardo
; Betti, Carolina Paola
; Dosso, Liza Ainalen 
Otros responsables
Fecha
2024
Editorial
Elsevier
Revista
Título del libro
Comprehensive Methanol Science: Production, Applications, and Emerging Technologies
Nombre del evento
Fecha del evento
Institución organizadora
ISSN
eISSN
ISBN
978-0-443-15741-7
Idioma
Inglés
Tipo del evento
Clasificación temática
Palabras clave
Resumen
Methanol production is a well-established technology, with optimized catalysts and reactor configurations for cost-effective operations. Simulation of methanol plants relies on extensive information on thermodynamics, mass transfer, heat transfer, and momentum transfer equations. While older reactors were simpler to model, modern designs aim to efficiently remove reaction heat and decrease pressure drop through complex internals. Simulating these reactors requires advanced models and computational fluid dynamics. Methanol plant simulation typically utilizes simple reactor models, while approaches based on ANNs (artificial neural networks) enable faster calculations for the entire plant. Downstream separation and purification stages rely on established algorithms. Future simulations may involve compact ANN models and detailed kinetic models, driven by advancements in computer hardware and the expansion of methanol applications.
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