Machine learning and its application to reacting flows: ml and combustion
- Author
- Nedunchezhian Swaminathan & Alessandro Parente
- Publication Year
- 2023
- Publisher
- Springer
- Language
- English
- Document Type
- Book
- Faculty / Subject Heading
- Computer Science
- Download Book Read book
These two fields, ML and turbulent combustion, have large body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the world’s total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges.
Keywords: Artificial intelligence / Machine learning / Combustion Modelling / Big Data Analysis / Dimensionality reduction / Reduced-order modelling / Neural Networks / Turbulent Combustion / Physics-based modelling / Data-driven modelling / Deep learning / Thermoacoustics and its modelling / Reactive molecular dynamics / Simulations of reacting flows
