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Published on: June 9, 2023
Optimisation of pipes with constant diameter using the heuristic optimality criterion
David Blacher1, Michael Harasek2
1LKR Light Metals Technologies, AIT Austrian Institute of Technology, Lamprechtshausener Straße 61, Ranshofen, 5282, Austria.
Background:
Minimising internal pressure drop in pipes is crucial for energy efficiency of fluid flow applications. Numerous computational optimisation tools that are capable of modifying flow geometries to reduce the pressure drop have been developed. Among these is a comparably simple heuristic optimisation al- gorithm which mimics erosion and sedimentation processes based on the shear stress in the vicinity of the domain boundaries. Although this method succeeds in modifying flow geometries for reduced pressure drop, it allows the fluid domain to widen during the reshaping process. Therefore, a reported reduction of pressure drop is not only caused by an improvement of the flow path, but also by an increase in the domain width. However, pipes with a constant circular diameter are favoured in many applications because they can be easily manufactured.
Methods:
Here we combine the heuristic optimisation approach with a novel geometrical constraint that maintains constant average diameter throughout the reshaping process. To our knowledge, this is the first application of a diameter-preserving constraint to the heuristic optimality criterion, enabling assessment of pressure drop reduction achieved solely through flow path modification without diameter dilation effects. We determined the applicability of the new algorithm for 2D channel and 3D pipe ge- ometries, conducting numerical simulations using the Lattice Boltzmann method with Reynolds numbers ranging from 40 to 500.
Results:
For the novel constant diameter constraint, the method successfully derived improved shapes across most tested Reynolds numbers while maintaining the initial average diameter. Notably, shapes derived at Re = 40 unexpectedly outperformed those derived at higher Reynolds numbers across all tested flow conditions, suggesting that low-Re geometries may capture fundamental flow features beneficial across wider Reynolds number ranges.
Conclusions:
This finding suggests applicability to higher Reynolds number flows, potentially even at turbulent industrial flows to be investigated in fu- ture research.
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