A new morphing routine was added to make morphing easier to define,
parametric, and to get smoother morph results. With the new morphing
routine, two new tools were added:
Control Points
A tool to create control points to utilize for morphing. You
can create random or uniform control points on selected
geometries.
Morph
A tool to define active parts, control volumes to define
morph domain, active control points and fixed points to
define fixed regions.
The new morphing tool has the capability to constrain the
scope of morphing by selecting parts, selecting control
volume or by defining impact radius. You can now utilize
symmetrical morphing when all morphs are defined, and morph
definition templates can be created, independent of
geometry.
PhysicsAI
The PhysicsAI ribbon has been added to provide capabilities to train
models with existing simulations and predict KPIs or surface fields.
KPIs prediction
Useful to predict KPIs:
Drag | Lift | Pressure drop | Uniformity
index
No heavy compute resources need to train
Fast to train
No need to decimate result data
Field Prediction:
Useful to predicts surface fields:
Pressure | Wall Shear Stress |
Temperature
Requires consistent set of training data
Requires significant compute resources
Need to decimate the data to reduce node count
Decimate Tool
The new Decimate has been added to reduce geometric complexity of
results to optimize training time and resource usage.
With PhysicsAI and morphing capabilities, you can utilize following workflow.Figure 1.
