Mathematical and Statistical Approaches for Anaerobic Digestion Feedstock Optimization

This book examines biomass mixture modeling and optimization. The book discusses anaerobic digestion and related fermentative processes and explains their compositional dynamics. Early chapter examine macromolecules, elemental fractions, and their direct influence on methane production. Supported by...

Full description

Bibliographic Details
Main Authors: Moretta, Federico, Bozzano, Giulia (Author)
Format: eBook
Language:English
Published: Cham Springer Nature Switzerland 2024, 2024
Edition:1st ed. 2024
Series:SpringerBriefs in Energy
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Description
Summary:This book examines biomass mixture modeling and optimization. The book discusses anaerobic digestion and related fermentative processes and explains their compositional dynamics. Early chapter examine macromolecules, elemental fractions, and their direct influence on methane production. Supported by an extensive data bank of substrates obtained from research, the book points out correlations that enable the estimation of global methane production for diverse biomass mixtures. Furthermore, it provides valuable insights into discerning the optimal composition capable of yielding the utmost methane output. The book integrates cutting-edge machine learning techniques and shows how the programming language Python and Julia can be used for analysis and to optimize processes. It has many graphs, figures, and visuals.
Physical Description:VIII, 69 p. 25 illus., 16 illus. in color online resource
ISBN:9783031564604