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HyperStudy New Features

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What's New in HyperStudy 2019? Watch the video to see what's new in the most recent release of HyperStudy.

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View All HyperStudy New Features Videos See all the HyperStudy new features available in the 2019 release. Go to the New Features Page
Get Best Predictive Models Automatically

The data fitting process now has a simple, new method - Fit Automatically Selected by Training (FAST) - to save time by avoiding manual tuning of predictive models. It automatically compares the Fit results, then selects the best method and adjusts settings to match the data with its highest quality predictive model. Suitable for both noisy and non-noisy data, FAST is applied by default and returns automatically the highest fidelity results delivering predictive models for use in trade-off studies, or to replace costly simulations within optimization and stochastic studies.

Automated data fitting with the new FAST algorithm

Visualize Scatter Data in 4 Dimensions

Bubble plots are available in Scatter and Optima tabs to learn more and take better decisions during studies.

The sized and colored bubbles enable visualization of 4 pieces of information on standard 2D plots.

Whilst very useful in many situations, Bubbles are particularly helpful when reviewing trade-offs from a multi-objective optimization.

Additional clarity over simulation data with Bubble Plots

Connect Quickly To Tabular Data

Lookup Table has been added in Setup to provide easy import of data, such as measurement data sets, aiding data exploration and its use when building predictive models for trade-off studies by leveraging HyperStudy.

Export and Re-Use Fit Models

Fit models can now be exported in Python format (*.pyfit file) or imported using a new HyperStudy Fit model added in Setup.

Using these functions, Fit models can be easily shared between users and re-used for different studies. As an example, those developed in different domains (NVH, durability, etc.) are readily available for multi-domain exploration within one study.

Link Models into a Workflow

Model Resources now allows files and the entire contents of a directory to be assigned as resources. It also enables defining and visualizing dependencies between models, for instance, by setting up a file transfer workflow from one model into another for Multiphysics analysis and Optimization.

Assigning an entire set of files as resources for a Multiphysics analysis or optimization

Meet System Reliability Requirements Efficiently

A new Reliability Based Design Optimization (RBDO) method - System Reliability Optimization (SRO) – now features in the list of optimization methods. Reliability constraints are for the entire system rather than on individual constraints, which is an inherently better approach to the problem. Impractical designs are identified regardless of the underlying failure mode. Additionally, its robust design option results in a natural trade-off between performance and sensitivity.

And Many Others

  • SimLab model now supports automatic detection and import of variables and responses

  • Models from FluxMotor motor predesign tool now connect to HyperStudy

  • Mode Tracking using Modal Assurance Criteria (MAC)


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