There are many media breaks in data processing, which greatly increases the susceptibility to errors.
Spreadsheets
Curve fittings are often done in spreadsheet programs.
Data leaves the system
Data leaves the protected space of the information system to be evaluated with external tools.
Solution
Material models in Matplus EDA®
Matplus EDA® offers data processing, data compression and data reduction through expandable Scientific Python applications.
Integrate your own mathematical functions without additional programming and use them for visualization and modelling
Visualize multi-dimensional data fields, e.g. flow curves and CCT diagrams
Store and retrieve data in n-dimensional data fields
Parameterize constitutive material models
Modify, extend and parameterize predefined material models such as flow curves or phase transformation models
Integrate existing scripts and programs into a common standard environment based on Scientific Python
Benefits
Traceable modelling in one system
Transparency
Transparent and traceable processing of test data.
System support
Support for complex mathematical calculations.
Documentation
Documentation and traceability of data creation.
Protected environment
Generate models for CAE material cards in a protected system instead of many ‘private’ tools.
Process
From test to material card
Take over test data
Bring test data from the lab together in Matplus EDA®.
Evaluate
Fit curves and reduce data – transparently and documented.
Parameterize the model
Parameterize material models such as flow curves or phase transformation models.
Generate the material card
Generate models for CAE material cards in a protected environment.
JMatPro®
Matplus EDA® for JMatPro®
JMatPro® calculations result in a physically consistent dataset for a specific chemical composition. JMatPro® is typically used by a few employees – Matplus EDA® distributes the results to everyone who needs them via the interface to JMatPro®. JMatPro® is licensed separately.
Data management for JMatPro
Distribute results to engineering teams, access JMatPro data in a web browser and reduce data volume and complexity.
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