MSC ONE APPLICATIONS
MACHINE LEARNING & AI
Access CAE design space exploration to broaden your horizons.
ODYSSEE is a powerful portfolio of modules (Lunar, Quasar and Nova) from CADLM. It is a unique and powerful CAE-centric innovation platform that allows users to apply modern Machine Learning, Artificial Intelligence, Reduced Order Modelling (ROM) and Design Optimization to workflows.
ODYSSEE includes:- Machine Learning & AI
- Statistics, Data Mining, Data Fusion
- Optimization and Robustness
- Process Discovery
- Image Recognition and Compression
BenefitsSimulation in Real Time
With Lunar, you can manage the main steps of your project in real time with parametric design and optimization based on very few simulations
- Concept Design: Parametric Studies, Trial and error
- Detailed Modeling: Optimization, Model Fitting
- Validation: Reliability Studies, Robustness
Key Aspects of Lunar
Intelligent DOE (Design of Experiment)- Adapted DOE tool.
- Improve an existing DOE tool.
- DOE can include simulation models, tests or the two.
Real-time computing- Zero-computing effort for parametric studies and optimization.
- Corridor / Population generation.
Software and physics independent- Works with Structural, Thermal, CFD, Acoustics (MSC Nastran, Marc, Adams, Cradle CFD & Actran)
Automation/Parser- Automatic post-preprocessing.
Reduces CAE computing effort- Allows for a few wisely selected sampling points.
- Adaptive learning that allows you to improve as you learn.
Precision & completeness- Full time history output (not only scalars).
- Physical domain decomposition and not fitting (it is NOT a Response Surface Method!).
Can produce 3D animations- No interpolations but reconstructions.
- Stress/displacement iso value reconstruction.
Evaluation tools included- Quality of parameters.
- Quality of DOE.
- Best method for your application...
MSCOneXT is an extension to MSCOne, providing access to an ever-evolving suite of software tools that have been developed by MSC Software’s technology partners to complement the solution portfolio within the MSCOne token system. One such software is SmartUQ which has tools useful for uncertainty quantification (UQ) which allows the user to interpret the variability in the design lifecycle.
Predictive Analytics Software for Working in the Uncertain World
SmartUQ is a powerful predictive analytics and uncertainty quantification (UQ) software tool that incorporates real world variability and probabilistic behaviour into engineering and systems analyses. It was built from the ground up to solve some of the most challenging analytics problems faced by manufacturing companies, in industries like Automotive, Aerospace & Defense, Turbomachinery, Heavy Equipment, Medical Device, Semiconductors, Energy, Oil & Gas, Heating, Ventilation, and Air Conditioning and Consumer Products.
Applications- Acceleration of simulation efforts
- Testing and evaluation planning
- Optimize decision making under uncertainty
- Real system applications
- Model calibration and validation
- Digital Twins/Thread
- Additive manufacturing
- Root cause analysis
Easy to use software- User-Friendly GUI - Powerful, yet intuitive, SmartUQ is designed for Engineers and Data Scientists alike. SmartUQ’s clean, straightforward user interface, including software wizards, makes performing complex analyses easier than ever before.
- Integration - Analytics software is only as powerful as it is compatible with other systems. SmartUQ has built-in integrations with MSC Software products like Adams, Digimat, and Nastran. Additionally, with SmartUQ’s application programming interface (API), you can seamlessly integrate SmartUQ tools into your workflow. SmartUQ’s API significantly reduces time spent on performing analyses while still providing the full benefits of its GUI.
- Automated Predictive Modelling - With an existing data set or a connected simulation model, SmartUQ runs, builds, and compares predictive models until it meets your accuracy requirements.
- Reduce duration of simulation and testing
- Catch problems early, reducing development time
- Prevent unnecessary design iterations
- Increased utility of simulations
- Fewer tests & prototypes
- Reduce cost associated with unexpected failures
Improve Quality and Reduce Risk
- Validate that the simulation agrees with reality
- Maximize Product Reliability and Durability
- Meet oversight requirements (FAA, FDA, DoD)
UQ Goes Beyond Uncertainty Propagation
In addition to propagating input uncertainties, Uncertainty Quantification provides a more comprehensive framework, including several key analytics techniques:
- Modern Design of Experiment tools designed to efficiently collect data from simulation, physical testing, or digital twins.
- Unique Data Sampling tools for subsampling or dividing large data sets into evenly distributed batches to build large-scale machine learning models.
- Flexible Predictive Modelling and Machine Learning tools to cover a wide range of scenarios including high dimensional problems, large sample sizes, spatial data, and functional/transient responses.
- Statistical Calibration tools to determine model calibration parameters even with limited simulation and test data and provide model discrepancy to improve simulation and perform model validation.
- Inverse Analysis tool to calculate the probability distribution of inputs based on a set of outputs from a system, helping verify hard-to-measure system properties.
- Sensitivity Analysis library to rapidly determine which factors have a relatively low or high impact on the outputs, allowing engineers to focus efforts appropriately.
- Optimization library handles multiple objectives and accommodates very large numbers of inputs.