Optimisation of pipes with constant diameter using the heuristic optimality criterion.

Area of Science:

• Fluid dynamics
• Computational fluid dynamics
• Energy efficiency

Background:

• Minimizing internal pressure drop in pipes is crucial for energy efficiency in fluid flow applications.
• Existing heuristic optimization algorithms can reduce pressure drop but may increase pipe diameter, confounding results.
• Constant diameter pipes are favored for ease of manufacturing.

Purpose of the Study:

• To introduce a novel geometrical constraint for heuristic optimization that maintains a constant average pipe diameter.
• To assess pressure drop reduction solely through flow path modification, excluding diameter dilation effects.
• To evaluate the algorithm's applicability in 2D and 3D geometries across various Reynolds numbers.

Main Methods:

• Combined a heuristic optimization algorithm with a novel diameter-preserving constraint.
• Employed numerical simulations using the Lattice Boltzmann method.
• Tested the algorithm on 2D channel and 3D pipe geometries for Reynolds numbers from 40 to 500.

Main Results:

• The diameter-preserving constraint successfully derived improved shapes while maintaining the initial average diameter.
• Shapes optimized at Re=40 unexpectedly outperformed those at higher Reynolds numbers.
• Low-Reynolds number geometries demonstrated fundamental flow features beneficial across a wider range of flow conditions.

Conclusions:

• The developed method effectively modifies flow paths to reduce pressure drop without altering pipe diameter.
• Optimized shapes at low Reynolds numbers show potential for improving energy efficiency in higher Reynolds number and turbulent industrial flows.
• This approach enables a clearer understanding of flow path improvements independent of diameter changes.