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HyperStudy New Features
What's new with HyperStudy 2017 ?
Watch the video to see what's new in the most recent release of HyperStudy.
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View all HyperWorks 2017 New Features
See all the HyperWorks new features available in this release.
Go to the New Feature Library
HyperStudy 2017 offers exciting new features and enhancements including two new models, a customizable user interface, innovative design exploration methods, and powerful post-processing options. Collectively, the release provides more efficient and effective design exploration, and accessibility to design engineers, analysts, and domain experts as well as non-experts.
HyperStudy Library Includes Two New Models
The Flux model provides seamless integration between HyperStudy and Flux, the low- frequency electromagnetic solver from Altair HyperWorks. Input variables and output responses are calculated automatically.
The Operator model helps modularize complex workflows and reduces the need for scripting.
HyperStudy model library now includes Flux, FEKO, and Operator Models
Added Functionality to Study Setup
HyperStudy handles categorical variables. These can take values from a list of possible values that cannot be ordered by numerical comparison. Material selection and part switching are common use cases where categorical variables are used.
Constraints that are functions of only the input variables can be defined in the study setup. Designs violating these constraints are excluded from the run matrices. By eliminating these designs before the approach evaluation, method sampling efficiency increases while total execution time decreases.
Modified Extensible Lattice Sequence (MELS) is an innovative space-filling method for design of experiments and stochastics approaches. To improve the accuracy of a fit, multiple runs are often required. The extensibility property of the MELS method handles this requirement intelligently by adding runs in locations where the design space is least explored.
D-Optimal is a classical space-filling DOE for sampling data in least-squares regression modeling.
Fractional factorial selection is applied based on desired Resolution. Resolution measures the ability to separate main effects from interactions. Knowing the Resolution of the Fractional factorial DOE helps you understand the efficiency versus accuracy of the DOE results.
Resolution options in fractional DOE
The Adaptive Response Surface Method, ARSM, includes a multi-execute option to run concurrent simulations. This new option shortens the turnaround time for optimization studies using the popular ARSM method.
Pareto plot is added for DOE post-processing. Pareto plots present the ranked effects of the variables on a response in a bar chart. These easy-to-read charts are an effective tool to present the results of a DOE.
Pareto plot for parameter screening
Ordination plot is added to the general post-processing tab. Ordination plots present Principal Component Analysis bi-plots. These plots are used to identify relationships between variables and responses, especially in multi-dimensional problems.
Ordination plot for dimension reduction
Parallel coordinate and correlation plots are enhanced for filtering, which makes identification of the significant relations easier.
Enhanced usability in parallel coordinate and correlation plots via display filtering
The user environment is customizable to show a subset of all available tabs. You can turn Individual tabs on or off, and set the interface to display only the tabs you frequently use.
Customizable User Interface
For each approach specification step, the presentation of the methods has been updated. A subset of all available methods is shown, but all methods are available from an expanded list. This change makes the interface consistent with HyperStudy’s suggested best practices.
Method guidance for increased usability
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