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Full-Text Articles in Aerospace Engineering
Ultrafine Aluminium: Quench Collection Of Agglomerates, Tejasvi K, Y Pydi Setty, Vemana Venkateswara Rao
Ultrafine Aluminium: Quench Collection Of Agglomerates, Tejasvi K, Y Pydi Setty, Vemana Venkateswara Rao
International Journal of Aviation, Aeronautics, and Aerospace
Combustion of aluminized solid propellants exhibits phenomena associated with accumulation, agglomeration, ignition, and combustion of ultra-fine aluminium particles. In this study, agglomeration phenomenon of ultra-fine aluminium in solid propellant combustion is investigated using quench collection experimental technique over the pressure ranges from 2MPa to 8MPa. The ultra-fine aluminium powder synthesized by Radio Frequency Induction Plasma technique having harmonic mean size of 438nm is used for agglomeration study. The quenching distance is varied from 5mm to 71mm from the propellant burning surface to estimate the effect on agglomerate size. The morphology and chemical compositions of the collected products were then studied …
Application Of Artificial Neural Networks For The Prediction Of Aluminium Agglomeration Processes, Tejasvi K, Y Pydi Setty, Vemana Venkateswara Rao, Kalyan Chakarvarthy
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 …