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

This is 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 techniques to improve combustion sciences and technologies so that efficient and "greener" combustion systems that are friendlier to the environment can be designed.

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. The required mathematical equations and backgrounds are discussed with ample references for readers to find further detail if they wish. This book is unique since there is not any book with similar coverage of topics, ranging from big data analysis and machine learning algorithm to their applications for combustion science and system design for energy generation.

這本開放存取的書介紹和解釋了機器學習（ML）算法和技術，這些技術是為了對複雜的過程或系統進行統計推斷而開發的，並將它們應用於模擬化學反應的湍流流動。機器學習和湍流燃燒這兩個領域都有自己的大量工作和知識，而這本書將它們結合起來，解釋了應用機器學習技術模擬和研究反應流動時所涉及的複雜性和挑戰。這對於全球的主要能源供應（TPES）非常重要，因為超過90％的能源供應來自燃燒技術，而燃燒對環境的影響也不可忽視。儘管基於可再生能源的替代技術正在出現，但它們目前在TPES中的份額不到5％，需要完全改變範式才能取代燃燒能源。這是否切實可行完全是另一個問題，並且對這個問題的回答取決於回答者。然而，實用的分析表明，到2070年，燃燒在TPES中的份額可能超過70％。因此，明智的做法是利用機器學習技術來改進燃燒科學和技術，以設計出對環境更友好、更高效的燃燒系統。

這本書涵蓋了這兩個主題的最新研究現狀，並概述了應用機器學習進行湍流燃燒模擬所涉及的挑戰、優點和缺點，包括可以探索的解決挑戰的途徑。書中討論了所需的數學方程和背景知識，並提供了豐富的參考文獻，供讀者進一步了解。這本書獨特之處在於它涵蓋了從大數據分析和機器學習算法到它們在燃燒科學和能源生成系統設計中的應用的相關主題，沒有其他類似的書籍。

Nedunchezhian Swaminathan is a Professor of Mechanical Engineering in Cambridge University, UK, and Fellow and Director of Studies in Robinson College, Cambridge. He is a Fellow of The Combustion Institute since 2018. Swaminathan holds visiting Professorships in many overseas Universities and consults to a number of industries in Transport and Energy Sectors. He has 25 years of research and teaching experiences in the fields of Combustion, Turbulence, Combustion Noise and Instabilities, and Simulations of Flows with Multi-physics occurring in engineering applications and geophysics.
Alessandro Parente is Professor of Thermodynamics, Fluid Mechanics and Combustion at the Aero-Thermo-Mechanical Department of Université Libre de Bruxelles, as well as director of the Combustion and Robust Optimisation research center (BURN, burn-research.be). In this capacity, he also serves as vice-president of the Belgian Section of the Combustion Institute. The research interests of Dr. Parente are in the field of turbulent/chemistry interaction in turbulent combustion and reduced-order models, non-conventional fuels and pollutant formation in combustion systems, novel combustion technologies, numerical simulation of atmospheric boundary layer flows, and validation and uncertainty quantification.

Nedunchezhian Swaminathan是英國劍橋大學機械工程學教授，也是劍橋羅賓遜學院的研究員和導師。他自2018年起成為燃燒學會的會士。Swaminathan在許多海外大學擔任客座教授，並為運輸和能源行業的多個企業提供諮詢服務。他在燃燒、湍流、燃燒噪音和不穩定性以及工程應用和地球物理學中出現的多物理流動模擬等領域擁有25年的研究和教學經驗。

Alessandro Parente是布魯塞爾自由大學航空熱力機械系的熱力學、流體力學和燃燒學教授，也是燃燒和強健優化研究中心（BURN, burn-research.be）的主任。在這個職位上，他還擔任比利時燃燒學會的副主席。Parente博士的研究興趣包括湍流/化學反應在湍流燃燒中的相互作用和簡化模型、非傳統燃料和燃燒系統中的污染物生成、新型燃燒技術、大氣邊界層流動的數值模擬以及驗證和不確定性量化。