Reply To: Adjoint Method for Optimising Diodicity of Tesla Valve

[Jason Sum]

Yes Rob, I am thinking to create a ratio (forward flowrate / reverse flowrate) - like diodicity, as the observable under the adjoint setup on Fluent.
But because of the two cases of discrete flow direction (forward & reverse) as shown similarly to the screenshot below, if I work on the adjoint setting in the Reverse's Fluent solver, it seems not to be able to obtain flow data and solutions from Foward's Fluent solver, making me unable to relate the observable defined with the "forward flowrate" simulated from Forward's Fluent solver.  

Also, as far as i know, in gradient-based optimiser, flow solving and adjoint solving are iteratively solved. If I just work on the adjoint setting in the Reverse's Fluent solver, flow and adjoint solving of foward flow case are not included in the iterations. 

I tried to import the sensitivity data from Forward's Fluent solver to Reverse's Fluent solver, but it seems the sensitivity of foward flow did not contribute to the objective in the gradient-based optimiser.

Therefore I am still figuring out the way to take both flow cases into account for adjoint optimisation, and seeking for insights thanks!