Tag Archives: Computational particle fluid dynamics

CPFD: Computational particle fluid dynamics

Computational particle fluid dynamics denotes a category of numerical and computational techniques for solving equations of fluid dynamics in which the fluid continuum model is replaced by a finite set of particles. The pioneering developer of these methods, and of commercial software that encapsulates them, is CPFD Software LLC.

“Unequalled accuracy in modeling particle flows”

CPFD describes its mission as “advancing the state-of-the-art in a large but underserved CFD simulation market segment” by building on its proprietary physics-based simulation technologies to “virtualize the chemically reacting particulate flow dynamics of fluidized reactors across all industries, and delivering game-changing economic improvements in output, efficiencies, time-to-market and emissions compliance.”

The company says its clients in senior management “appreciate the cost savings that Barracuda,” its flagship software offering, “can generate for a relatively small investment, and engineers appreciate the competitive edge it provides by revealing scientific insights unavailable with other software.”

The company characterizes Barracuda as “unique among CFD technologies because it was designed exclusively for one purpose: to model particulate-solid flows in fluidized systems. Unlike familiar codes such as ANSYS Fluent, Siemens STAR-CCM+, OpenFoam and others who gradually modified single-phase CFD methods in an attempt to model particle flows, the Barracuda engineering software package was built from the ground up, based on the firm foundation of the multiphase-particle-in cell (MP-PIC) description of the particle phase with strong coupling between fluid and particle phases.”

As a result, the company says, its software “delivers an unequaled level of accuracy that translates to economic value and a competitive advantage” by:

  • Avoiding costly reactor shutdowns and repairs.
  • Lengthening equipment lifecycles.
  • Increasing production of reactor products and yields.
  • Reducing emissions.
  • Ensuring success of scale-up operations.
  • Predicting performance without prototype investment.

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