CFD-based optimisation of base pressure behaviour on suddenly expanded flows at supersonic Mach numbers
by Jaimon Dennis Quadros; S.A. Khan; T. Prashanth
Progress in Computational Fluid Dynamics, An International Journal (PCFD), Vol. 22, No. 3, 2022

Abstract: The base pressure developed in a suddenly expanded flow process majorly depends on Mach number (M), nozzle pressure ratio (NPR), area ratio (AR), and length to diameter ratio (L/D). Numerical analysis of the flow process was carried out using the computational fluid dynamics (CFD) technique, and was validated by experiments. The input-output test cases for CFD analysis were developed by two statistical methods, namely central composite design (CCD) and Box-Behnken design (BBD). The BBD model yielded better prediction accuracy and was used for generating data that trained the recurrent and backpropagation neural networks. The recurrent neural network outperformed both the backpropagation neural network and Box-Behnken design. Furthermore, to assess the right range of conditions for maximising base pressure, the genetic algorithm (GA), desirability function approach (DFA), and particle swarm optimisation (PSO) techniques were implemented. The PSO and GA techniques were found to be better, as they carried out search operations in many directions at multi-dimensional space simultaneously.

Online publication date: Wed, 01-Jun-2022

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