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New PumpLinx Improves Pump Design Simulation
Posted Thu October 04, 2007 @01:52PM
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News Simerics Inc. is proud to announce the release of Version 2.2 of its CFD simulation tool PumpLinx.

PumpLinx is developed specifically for the analysis and design of pumps and other fluid devices with rotating or sliding components. Version 2.2 includes many improvements in capability and ease-of-use.

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Features of the new release include additional pump/motor templates. These templates, listed below, can be used by the designer to improve efficiency, minimize cavitation, control pressure ripple, and reduce noise.

PumpLinx 2.2: Templates
PumpLinx 2.2: Available Templates

In addition, new features include advanced capabilities such as multiple reference frames and new engineering output in the Graphical User Interface.

PumpLinx Graphical User Interface (GUI)

Version 2.2 also includes automated grid generation for each template, for example as shown below. Starting with a prototype pump geometry in CAD format, this automated mesh generation enables complete problem set-up in less than an hour.

Automated Grid Generation
PumpLinx Binary Tree Automated Grid Generation (Gerotor Ports)


Structured Grid Generation
Template Specific Automated Structured Grid Generation (Gerotor)

PumpLinx has been specially developed for design engineers. Starting with CAD-CAM file, the code enables the design engineer to create a virtual pump or motor. The code predicts the flow, pressures, and cavitation throughout the device.

Three-dimensional spatial and temporal results are output graphically and in spreadsheet format to enable engineers to use them as they would use empirical data to improve a design.

Key advantages of PumpLinx are automated grid generation, robust and accurate cavitation modeling, ease-of-use, very fast turn-around time, and reliable results. The PumpLinx cavitation module has been throughly validated against real engineering test cases.

For more information, please visit Simerics' website at

PumpLinx Prediction
PumpLinx Prediction vs Empirical Data.

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