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EnSight Announces Case Linking Feature
Posted Tue March 15, 2016 @09:40AM
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News EnSight, the leading post-processor for Computational Fluid Dynamics (CFD) data, has announced a new case linking feature that enables product designers and engineers to dramatically streamline their simulation process.

With EnSight’s new case linking feature, engineers can now instantly visualize the impact of design changes on multiple datasets simultaneously.

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For example, an automotive designer can use EnSight to experiment with how various changes to the shape of a car body will impact aerodynamics and fuel efficiency. In the past, engineers would have to run those visualization scenarios in sequence, which was time consuming, labor intensive and prone to error. The ability to instantly test and experiment with an idea across multiple data sets was just not possible.

Now, using case linking, engineers and product designers can follow a train of thought and instantly see the impact of those changes in four different view ports at the same time. “So far, I’ve found case linking very useful in saving a lot of time when creating duplicate post-processing efforts,” said Jennie Zheng, R&D Modeling and Simulation Process Development Engineer for Proctor and Gamble.

“We’re excited about the impact case linking will have on our users,” said Anders Grimsrud, President of CEI Software. “Since the beginning, EnSight has been about helping engineers make decisions more effectively. I believe that, using this new feature, engineers will not only be able to make faster decisions about their data, but better decisions as well.”

Case linking is available in EnSight version 10.1 and higher. You can find more information on this feature at

EnSight is a visualization software program designed by Computational Engineering International, Inc. (CEI, Inc.) in Apex, North Carolina. Founded in 1994, the employee-owned company has additional offices in Houston, Detroit, Germany, China, Japan and India. EnSight helps design engineers in aerospace, defense, combustion, energy production and high-tech manufacturing better understand their data in environments that require precision. For more information visit

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