| 书目名称 | Machine Learning and Its Application to Reacting Flows |
| 副标题 | ML and Combustion |
| 编辑 | Nedunchezhian Swaminathan,Alessandro Parente |
| 视频video | |
| 概述 | Contains the latest developments in machine learning methods (ML) for reacting flow applications.Includes machine learning algorithms.Points the way to future application of ML in new technologies.Thi |
| 丛书名称 | Lecture Notes in Energy |
| 图书封面 |  |
| 描述 | .This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows..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. Whether this is practical or not is entirely a different question, and an answer to this question depends on the respondent. However, a pragmatic analysis suggests that the combustion share to TPES is likely to be more than 70% even by 2070. Hence, it will be prudent to take advantage of ML tech |
| 出版日期 | Book‘‘‘‘‘‘‘‘ 2023 |
| 关键词 | Machine Learning; Combustion Simulations; Combustion Modelling; Big Data Analysis; Dimensionality reduct |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-16248-0 |
| isbn_softcover | 978-3-031-16250-3 |
| isbn_ebook | 978-3-031-16248-0Series ISSN 2195-1284 Series E-ISSN 2195-1292 |
| issn_series | 2195-1284 |
| copyright | The Editor(s) (if applicable) and The Author(s) 2023 |
发表于 2025-3-21 17:10:32
