MultiFluidX

Meet the #CORTEX2opencall1 winners! We are incredibly excited to be part of the CORTEX2 ecosystem!  #HorizonEurope #VR #XR

It's been some years since we first deployed machine-learning for accelerating multiphase flow simulations and presented a use-case for liquid hydrogen. Our paper published in the journal Physics of Fluids of #AIP summarises some key features for a new modelling tool within #MPflow to simulate and investigate the complex multi-facet phenomenon of #flashboiling atomisation. This method could save thousand Central Processing Unit hours offering instantaneous #CFD predictions. #AIP #machinelearning #computationalfluiddynamics #CFD #multiphase #openfoam #engineerinnovation https://lnkd.in/ghvZb5aq

The project #vScientist combines #CFD #simulations and the next generation #telecooperation framework based on #XR and #AI for CORTEX2. MultiFluidX and National Technical University of Athens will develop a straightforward workflow for enhanced viewing of #3D physics-based #simulations and associated data in an #immersive virtual environment. The project will enable real-time data transfer, dynamic visualisation and more efficient #RemoteCollaboration in #STEM fields. #CORTEX2 is a unique EU project that sets the basis for future extended collaborative #telepresence to allow for remote cooperation in numerous industries, both for education and training. #VR #XR #AI #CFDsimulation #HorizonEurope #CORTEX2 #Telecooperation #Telepresence #RemoteCollaboration #DigitalWorkplace

Understanding coating physics is critical to the optimisation of any coating process in terms of efficiency and quality. In particular, measurement of paint thicknesses of multilayer structures in the automotive sector is now done by contactless coating thickness measurement technologies that have emerged the last decades. Our work for the #coatML project offers an effective digital twin solution to predict coating-chamber physics and to enable better and faster integration of coating thickness measuring devices into existing industrial coating setups. The feedback gained from ideally integrated measurement devices allows manufacturers to optimise their coating setups reducing resource consumption while increasing coating quality. By using a novel machine learning (ML) method suitable for learning from fluid dynamics simulations and integrating it within the code #MPflow we were able to overcome traditional barriers in the coating industry using Industry 4.0 technologies. This is a combination of cloud computing and machine learning technology which undoubtedly has the potential to democratise Computer Aided Engineering to non-experts in manufacturing engineering and the general public. You can learn more about #coatML and MIND4MACHINES and how their #Industry4.0 solutions are transforming the manufacturing industry at mind4machines.eu. More technical details are included in our article at the journal of Physics of Fluids of #AIP. coatML: Accelerating physics-based simulations for manufacturing

#coatML project, part of the MIND4MACHINES consortium, uses high fidelity computational fluid dynamics (#CFD) simulations for the data-driven models of #MultiFluidX. We have developed a series of simulations for our data-driven model and then tested the our machine learning (ML) approach for obtaining a CFD analysis. The direct benefit of the developed approach is that, the ML-CFD results here, are obtained within a couple of seconds, contrary to the pure CFD approach that generally required 32 CPUh (4 CPUs for 8 hours) for each one of the selected cases. This means that the ML-CFD model can be thousand times faster and can completely bypass the CFD intermediate steps such as meshing. This speed-up in the calculations, makes it possible to use the ML model for predictions in a variety of hardware including devices not necessarily having graphics cards. You can learn more about #coatML and #M4M and how their #Industry4.0 solutions are transforming the manufacturing industry at mind4machines.eu #M4M #Mind4Machines #EITManufacturing #simulations #EuropeanManufacturing #manufacturing #ictsolutions #coatingthickness #measurement

#greenSME is an EU-funded project with the aim to strengthen manufacturing SMEs’ capacity to adopt advanced technologies and social innovation for sustainability through a sustainability assessment tool, an action plan, and financial support to foster projects between manufacturing SMEs and Sustainability and Technology Providers. We are glad to be part as a technology provider for the #greenSMEHub consortium. Learn more here: www.greensmehub.eu #industry4.0 #horizoneurope #industry #smartmanufacturing #supplychain #innovation #sustainability #technology #greendeal #greenerfuture

#coatML project, part of the MIND4MACHINES consortium, uses high fidelity #CFD simulations for the data-driven models of MultiFluidX. First series of testing has led to computing various flow scenarios under various operating conditions using #ML and #CFD. The #MLCFD predictions will provide useful insights for different coating setups. You can learn more about #coatML and #M4M and how their #Industry4.0 solutions are transforming the manufacturing industry at mind4machines.eu #M4M #Mind4Machines #EITManufacturing #simulations #EuropeanManufacturing #manufacturing #ictsolutions #surfaces #coatingthickness #measurement