Computational Fluid Dynamics and Neural Networks for Combustion Systems

This chapter focuses on the use of computational fluid dynamics and neural networks for modeling and optimization of combustion systems. The chapter starts by explaining combustion systems and their uses across different industries, followed by the repetition of the need to critically analyze the combustion process. The chapter continues to introduce the underlying principles of computational fluid dynamics, in addition to modeling fluid dynamics, heat transfer, and chemical reactions in combustion systems. The chapter proceeds to explain the principles of neural networks, such as design and application in modeling complex processes like combustion. The integration of computational fluid dynamics and neural networks illustrates the benefits achieved in using supporting technologies to improve the accuracy and efficiency of combustion system modeling. The chapter ends by scrutinizing future research prospects and challenges in the field, while forecasting potential breakthroughs and supporting areas of research. To conclude, there is discussion of the findings and implications of the use of computational fluid dynamics and neural networks to improve combustion system analysis and design, with attention to the importance of a synergistic approach toward increased combustion efficiency and lower emissions. Case studies on the use of artificial neural networks to model gas turbine combustors, real-time combustion control, and spray combustion modeling are included.