MACHINERY | SOFTWARE
Above: Ianus of Germany is part of the EU-based Extra project to develop a simulation- based assistant for plastics extrusion
Eindhoven University of Technology – has developed a numerical model to predict the shape of the extrudate. It allows the shape of the die to be optimised, to produce an extrudate of the correct dimensions. Spanjaards developed a transient 3D finite element model for viscoelastic fluids emerging from complex dies – and combined it with a real-time active control scheme. This solved the inverse problem of three-dimensional die design for extrudate swell. “The results obtained on extrudate swell and die
optimization have shown the potential of the numerical model developed in this thesis,” she wrote in her summary. “The numerical framework has been set up in a general manner and can be used to investigate polymer extrusion for fluids with different rheological properties and different die shapes.”
Material alternatives Researchers in Japan have developed a machine learning method to identify sustainable alternatives for composite materials. Their findings were published in the journal Science and Technology of Advanced Materials: Methods. The researchers, from Konica Minolta and the
Nara Institute of Science and Technology, say that their model “rapidly searches through large numbers of materials” to do this. Their results might be applied to areas within pipe and profile extru- sion, such as finding new materials for composite pipes or wood-plastic composites. “Finding a new composite material that achieves the same performance as the original – using human experience and intuition alone – takes a very long time,” said Michihiro Okuyama, assistant manager at Konica Minolta. “You have to evaluate countless materials while also taking into account the interactions between them.”
26 PIPE & PROFILE EXTRUSION | March/April 2023
The researchers developed a new type of machine learning method – which can quantita- tively evaluate interactions between component materials to reveal how much they contribute to overall composite performance. it then searches for replacements with similar performance to the original material. The researchers tested their method by search- ing for alternative materials for a composite with three components: resin, filler and additive. They experimentally evaluated the performance of the substitute materials and found that them similar to the original material. “Our method removes the need to test large numbers of candidates by trial and error, saving both time and money,” said Okuyama.
Extra data Germany-based Ianus is involved in a European research project called Extra – which will develop a simulation-based assistant for the plastics extrusion process.
It will combine expert knowledge about plastics
processes with live computer simulations to gener- ate data that will help towards process optimisation. The research will use different methods – includ- ing fuzzy-logic, machine learning and deep learning – to interact with data being collected from various equipment, such as extruders and dies. This will help the machine user find the best way of using the data using simulation. This project is being funded by the European Union and the German state of North Rhine-West- phalia.
Damage limitation Researchers in the Philippines have used simulation to estimate the possible extent of earthquake damage to the country’s water distribution network. Quezon City is crossed by the West Valley Fault
System (WVFS) that could generate a magnitude 7.2 earthquake (known as ‘The Big One’). The water distribution network would suffer extensive damage from such an earthquake. The researchers, from the University of the Philippines and the city’s water authority, used line-element modelling to estimate possible damage to the underground PVC water network. They did this by using appropriate empirical
repair rates (RR) and developing ‘fragility curves’. The appropriate empirical RR equation was determined by comparing the results of selected PVC RR equations and the line-element modelling. The PGV ranges from 23.10 cm/s to 64.49 cm/s as determined using the Boore and Atkinson
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IMAGE: IANUS
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