Computational Fluid Dynamics Suite with Innovative AI Models For Industry Application


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Computational Fluid Dynamics (CFD), one form of advanced engineering simulation is widely used to design and model complex industrial applications. Examples of the use of CFD include modelling occupant’s thermal comfort in buildings design, studying aerodynamic effect for vehicle design and analysing energy distribution in industrial processes. In industrial processes, small amount of optimisation can provide large energy savings. While CFD provides high accuracy, the simulation time requires long hours that could sometimes take weeks to produce the result. As such, it is pertinent to find alternative simulation techniques which offers faster simulation time while achieving good accuracy.

The technology provider described herein has developed a collection of AI models which can replace CFD solvers to obtain faster results without increasing more computer power. Used case applied thus far includes chemical mixing processes and motorbike simulation. The technology provider is seeking for partners to collaborate through applying this simulation technique in more industry applications.


Technology Features:

  • CFD solvers acceleration, that is beyond what is achievable with hardware upgrades or adaptation to hardware accelerators
  • Replacement of numerical solvers with equivalent AI models
  • Use case specific AI models
  • Digital twin ready

Technology Specifications:

  • Replacement of solvers with AI models – 2D, 3D domains
  • Interactive AI models – Use case specific solutions, interacting with solvers
  • Custom AI model generator – Tool to generate AI models to replace CFD solvers on demand
  • “Unleashed” version of the suite – Growing collection of innovate AI models for CFD


Applications include but are not limited to:

  • characterize the sub-grid scales effect in global numerical simulations of turbulent stellar interiors
  • compare anelastic and compressible convection-permitting weather forecasts
  • biomechanical modeling of brain injuries within the Voigt model
  • simulation of gravity wave turbulence in the Earth’s atmosphere
  • simulation of geophysical turbulence in the Earth’s atmosphere
  • ocean modeling: simulation of three-dimensional solitary wave generation and propagation using EULAG coupled to the barotropic NCOM (Navy Coastal Ocean Model) tidal model
  • seismic analysis, reservoir modeling and basin modeling (Oil & Gas)
  • models to track and predict various environmental impacts on crop yield such as weather changes (AgriTech)
  • modeling the prediction of forest fire spread
  • flood simulations


  • Ultra fast results. Faster prototyping and parametrization
  • Replacing solvers with AI models (use case targeted calculators)
  • AI models training much faster than adapting solvers for field programmable gate arrays (FPGAs) / graphics processing units (GPUs) for accelerating the results
  • Real-time simulations for ever-increasing amounts of data
  • Acceleration beyond hardware capabilities
  • Lowering entry barrier for new adopters of CFD simulations
  • Democratization of CFD - AI CFD Models act as “CFD Calculators”, designed to address specific use cases and make it easy and straight forward to run simulations.
  • Money savings by lowering TCO radically
  • Increase complexity of simulations (AI predicting intermediate steps, allowing more advanced simulations with the same hardware)
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