Artificial Intelligence Applications in Aeronautical and Aerospace Engineering
by K. Sathish Kumar, R. Naren Shankar
13Enhancing Jet Noise Reduction: AI-Powered Predictions of Core Length and Total Pressure Variations in Coaxial Nozzles
R. Naren Shankar1, Irish Angelin S.1*, Bakiya Ambikapathy2, K. Sathish Kumar3 and Parvathy Rajendran4
1 Department of Aeronautical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu, India
2 Department of Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu, India
3 Department of Aeronautical Engineering, Nehru Institute of Engineering and Technology, Coimbatore, India
4 School of Aerospace Engineering, Universiti Sains Malaysia, Nibong Tebal, Pulau Pinang, Malaysia
Abstract
Research into jet noise has been an active field. The coaxial nozzle is one of the passive techniques to reduce jet noise by enhancing the mixing of secondary jet with the primary jet. The core length of the primary jet is significantly influenced by altering the velocity ratio between the primary and secondary jets. Previous efforts have utilized experimental and numerical methods to analyze the core length based on variations in centerline total pressure, which is cost-effective as well as time-consuming approach. Artificial intelligence has emerged as a valuable tool for effectively predicting the core length without disrupting the jet’s flow characteristics. In this study, the Rational Quadratic Gaussian Process Regression method (RQGPR) was ...
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