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Application Of Artificial Neural Networks For The Prediction Of Aluminium Agglomeration Processes, Tejasvi K, Y Pydi Setty, Vemana Venkateswara Rao, Kalyan Chakarvarthy

International Journal of Aviation, Aeronautics, and Aerospace

Aluminium is universal and vital constituent in composite propellants and typically used to improve performance. Aluminum agglomeration takes place on the burning surface of aluminized propellants, which leads to reduced combustion efficiency and 2P flow losses. To understand the processes and behaviour of aluminum agglomeration, particles size distribution of composite propellants were studied using a quench particle collection technique, at 2 to 8 MPa and varying quench distances from 5mm to 71mm. To predict the agglomerate diameter of metallized/ultra-fine aluminium of composite propellants, a new artificial neural network (ANN) model was derived. Five Layered Feed Forward Back Propagation Neural Network …