A Neural Network Study of Blasius Equation
This is an incremental application of neural networks to a specific fluid dynamics problem.
The authors tackled solving the Blasius equation, a third-order nonlinear differential equation for boundary layer flow, using a feed-forward neural network without reducing it to first-order equations, and found that the numerical results were in good agreement with existing studies.
In this work we applied a feed forward neural network to solve Blasius equation which is a third-order nonlinear differential equation. Blasius equation is a kind of boundary layer flow. We solved Blasius equation without reducing it into a system of first order equation. Numerical results are presented and a comparison according to some studies is made in the form of their results. Obtained results are found to be in good agreement with the given studies.