CPFD Software

CPFD Software advances multiphase simulation and technology for fluid-particle systems.

About CPFD Software

CPFD Software advances multiphase simulation and technology for fluid-particle systems.

Products

  • General purpose software used to simulate the three-dimensional, transient, fluid-particle hydrodynamics, heat transfer, and chemical reactions in industrial fluidized bed react...

  • Arena-flow

    Scientific Models

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    Specialty software used by the metal casting industry to simulate the production of sand cores and molds.

What customers say

  • Arena-flow

    CPFD reports that Fondrémy Inc., working with LAEMPE REICH, used Arena-flow to simulate sand core shooting and gassing for a water pump housing, reducing prototyping and tooling costs and enabling a high-yield,…

    Case study
  • Barracuda Virtual Reactor

    CPFD reports that University of Hull researcher Chinonyelum Udemu used Barracuda Virtual Reactor to simulate and refine larger SE-SR methane reactors using similitude, reducing the need for extensive physical…

    Case study
  • Barracuda Virtual Reactor

    CPFD publishes a University of Hull researcher's account of using Barracuda Virtual Reactor for reactive fluidised-bed simulations, integrating parallel GPU calculations with university HPC and monitoring results during…

    Case study

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Latest updates from CPFD Software

Research

CPFD Software Presents Machine Learning Research for CFD Simulation Acceleration

CPFD Software presented research, titled “Graph Neural Network Reduced-Order Models for Multiphase CFD: Fluidized Bed and Hydraulic Fracturing Applications,” at the ASME 2026 Fluids Engineering Division Summer Meeting. The study introduces a framework that uses machine learning to accelerate high-fidelity multiphase Computational Fluid Dynamics (CFD) simulations generated with the company's Barracuda Virtual Reactor software. The approach demonstrates prediction speedups of 80–105× for transient flow fields and up to three orders of magnitude for isolated snapshot predictions, supporting potential digital twin applications.

MentionedAmerican Society of Mechanical Engineers