Sprinkler Head biomimicrally optimized
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In this project, a flow channel modelled on the fern leaf and cobra tooth was optimised so that the pressure loss could be reduced by 30% and the cost of the component by 77%.

Project Objectives:

The aim of this project was to reduce the pressure drop and diffusivity of the water jet in a sprinkler system using additive manufacturing and bionic and numerical flow optimisation.

Approach

The biological model was the bundle structure of the leaves of the so-called maidenhair fern. In the course of evolution, this branched structure has turned out to be the optimum. This is because the plant must be able to transport all vital nutrients to the tips of the leaves with minimal energy expenditure. The vascular bundles have a specially formed

Branching tip, which is decisively responsible for the fluidic efficiency. Each branch is geometrically individually adapted to the flow velocity, the branch angle and the diameter ratio.

adapted between the ducts. SinusPro has taken these design guidelines from nature and transferred them to the geometry of the channel.

Combined with a numerical flow optimisation in ANSYS, a model has been created that shows a reduction in pressure loss of 33 % compared to the initial variant. The secondary objective of the project was

increase the compactness of the beam. The spitting cobra is very well suited as a biological model for this problem. There are species of spitting cobra that have specialised in spraying their venom as far as possible. To do this, they need a jet that is as strong and compact as possible. Only in this snake species have two symmetrical ridges been found in the lower third of the tooth. These ridges create a secondary flow field that interacts with the actual liquid flow in such a way that a compact jet is produced. After the exit point, the water jet is therefore more compact by 88 %.

Ein weiteres Ziel in dem Projekt war die Herstellung eines Demonstrators. Allerdings lässt sich die Komplexität bionischer Strukturen in den meisten Fällen nicht mit konventionellen Fertigungsmethoden umsetzen. Nach einem aufwändigen Optimierungsprozess der Druckparameter und der Materialauswahl hat FAM (Fuchshofer Additive Manufacturing) den Prototyp aus Aluminium in einem pulverbasierten 3D-Druckverfahren hergestellt. Die Druckzeit beträgt 8 – 28 Stunden, je nach Druckermodell. Ein besonders wichtiger Faktor bei der Fertigung war die Oberflächenrauigkeit, die zusätzlich zur Geometrie das Strömungsverhalten beeinflussen kann. In einer weiteren Simulation wurden die Oberflächenparameter des realen 3D Drucks mit in das digitale Modell aufgenommen. Das Resultat: Die Oberflächenbeschaffenheit hat einen Einfluss auf den Druck von 0,07 % bei einer geringen Rauigkeit (Ra=8) und 3 %bei einer hohen Rauigkeit (Ra=25). Ein raueres Modell mit größeren Schichtdicken ist also immer noch um 30 % effizienter als die Ausgangsvariante. Noch dazu sinkt bei dieser rauen Variante auch der Bauteilpreis auf etwa 60 €.

In summary, 3D printing is not only 30 % more efficient, but also cheaper than the conventionally manufactured part. With a subsequent FEM (Finite Element Method) calculation by SinusPro, the static strength of the prototype was verified under operational loads. In addition, the FEM enables an analysis of the stress fields on the component and subsequently a topology optimisation of the outer shape, so that material, time and costs can be saved during printing. This project shows very clearly that mechanical engineering is undergoing a transformation. Driven by a growing sustainability mentality and the profitability boom of additive manufacturing methods, completely new possibilities are suddenly opening up. You no longer have to choose between bad performance with a good price and good performance with a bad price. The next generation of mechanical engineering will be organic, flexible, individual and more powerful than ever. Bionics is acting as a catalyst here, because optimised components are no longer one iteration, but one generation ahead.

Results:

  • Pressure drop reduced by 33%
  • Turbulence kinetic energy (unit for compactness) reduced by 88 %
  • Pressure difference between channels reduced from 6 % to 1 %
  • Cost range per nozzle reduced from € 130 to € 30
  • Delivery time reduced from 12 to 2 weeks

Author: Ing. Lukas Reimann, M.Sc.,Bionic Scientist, SinusPro GmbH