BCLH2Pro: A novel computational tools approach for hydrogen production prediction via machine learning in biomass chemical looping processes

BCLH2Pro: A novel computational tools approach for hydrogen production prediction via machine learning in biomass chemical looping processes

This study optimizes biomass chemical looping processes (BCLpro), a technique for converting biomass to energy, through machine learning (ML) for sustainable energy production. The study proposes an integrated Fe2O3-based ฺBCLpro combining steam gasification for H2 production. Aspen Plus is used as...

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Bibliographic Details
Main Authors: Thanadol Tuntiwongwat, Sippawit Thammawiset, Thongchai Rohitatisha Srinophakun, Chawalit Ngamcharussrivichai, Somboon Sukpancharoen
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Energy and AI
Subjects:
Artificial intelligence
Supervised learning
Process simulation
Chemical looping
Agricultural waste
Online Access:http://www.sciencedirect.com/science/article/pii/S2666546824000806
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