Machine Learning and Its Application to Reacting Flows: ML and Combustion

This open-access book discusses machine learning algorithms and techniques for simulating chemically reacting turbulent flows, which are crucial for the world's primary energy supply. It covers the current state of the art and outlines challenges and opportunities for improving combustion sciences and technologies using ML. The book is unique in its coverage of topics ranging from big data analysis to combustion science and system design for energy generation.

Format: Paperback / softback
Length: 346 pages
Publication date: 02 January 2023
Publisher: Springer International Publishing AG

This comprehensive open-access book delves into the realm of machine learning (ML) algorithms and techniques, specifically designed for making statistical inferences about complex processes or systems, and their applications in simulating chemically reacting turbulent flows. These two fields, ML and turbulent combustion, possess extensive bodies of work and knowledge on their own, and this book seamlessly brings them together, elucidating the intricacies and challenges involved in applying ML techniques to simulate and study reacting flows. Given the significant role of combustion technologies in the world's total primary energy supply (TPES), accounting for over 90% of this supply, the importance of understanding and improving combustion processes cannot be overstated. While alternative technologies based on renewable energies are emerging, their current market share is less than 5%, indicating a need for a comprehensive paradigm shift to replace combustion sources. However, a pragmatic analysis suggests that the combustion share to TPES is likely to remain more than 70% even by 2070. Thus, it becomes imperative to leverage ML techniques to enhance combustion sciences and technologies, enabling the design of efficient and environmentally friendly combustion systems.

The book comprehensively covers the current state-of-the-art in these two topics, highlighting the challenges and opportunities associated with using ML for turbulent combustion simulations. It provides a detailed discussion of the required mathematical equations and backgrounds, accompanied by ample references for readers seeking further in-depth information. What sets this book apart is its unique perspective, as there currently exists no other book that comprehensively addresses the intersection of ML and turbulent combustion.

In conclusion, this book serves as a valuable resource for researchers, scientists, and engineers interested in advancing the field of combustion simulation and ML. By bridging the gap between these two disciplines, it opens up new avenues for research and development, ultimately contributing to the development of more sustainable and efficient combustion systems.

Weight: 551g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031162503
Edition number: 1st ed. 2023