The document discusses the evolution of 3D shape modeling in CAD/CAE, emphasizing the need for semantic recognition and self-awareness of shapes beyond mere geometry. It introduces generative modeling language (GML) as a transformative approach that allows for high-level shape design by defining operations rather than static objects. Key challenges identified include the lack of links between 3D models and product properties, the complexity of mechatronic systems, and the necessity for better interoperability in simulation frameworks.

1. AWG CAD/CAE and Virtual Product Modeling
Pedro Santos,
Fraunhofer IGD,
Germany

2. 3D and knowledge in CAD/CAE and
Virtual Product Modeling
What do we currently do with 3D shapes ?
Currently 3D shapes come as geometry – most of
the times as CAD model or triangle mesh
3D shapes are modeled, modified and visualized.
We use them for simulation (virtual wind tunnels,
structural analysis, clash and clearance, …)
What is the next step of evolution ?
Semantic Recognition and Interpretation of shapes
Self-awareness of shapes
More than “just’’ geometry

3. 3D and knowledge in CAD/CAE and
Virtual Product Modeling
visualizing
recognizing and interacting and
interpreting modifying
analysing
simulating
3D Geometry
representing and
and converting Semantic Properties
measuring
modeling
esp. properties

4. 3D and knowledge in CAD/CAE and
Virtual Product Modeling
The evolution of 3D shapes – the next level
Semantic technologies can help 3D shapes
becoming more than “just’’ geometry
3D shapes become self-aware of their function in a
model
A model becomes an entity on which reasoning
may be performed
3D shapes do no longer just contain a geometric
description (CAD, mesh) but also contain meta
information (such as kinematic constraints,
function in the model, performance factors,
parametric dependencies)

5. 3D and knowledge in CAD/CAE and
Virtual Product Modeling
How do we retrieve and embed additional meta
information on 3D shapes ?
Alternative 1: Semantic meta-information is
gathered from the raw data of the model
capturing process, which analyses the structure of
the model and identifies inter-dependencies such
as constraints in a semi-automatic process
Alternative 2: Existing models are analysed for
characteristic structures or patterns. Meta-
information is extracted from perceived inter-
dependencies and additional user-provided
information

6. Geometry & Knowledge: synergies
GML - Generative Modeling Language
Traditionally, 3D objects and virtual worlds are
defined by lists of geometric primitives as can be
found in CAD or mesh models.
GML is a paradigm change in shape description
=> the generalization from objects to operations.
A shape is described by a sequence of processing
steps, rather than just the end result of applying
these operations.
Shape design becomes rule design.

7. Geometry & Knowledge: synergies
GML - Generative Modeling Language
High-level shape operators can be gained from
low-level shape operators.
Any sequence of processing steps can be grouped
together to create a new combined operator.
Concrete values can easily be replaced by
parameters, which makes it possible to separate
data from operations: The same processing
sequence can be applied to different input data
sets. The same data can be used to produce
different shapes.
This makes it possible to create very complex
objects from only a few high-level input
parameters, such as for instance a style library.

8. Geometry & Knowledge: synergies
Source
GML Model
Semantics
Generation rules for Furniture
Use
Fast Design and reshaping

9. Geometry & Knowledge: synergies
Drag to
Drag to
change Resi
ze se change Resize leg
seat at le
ngth seat length
length
height
Drag to Resize Resize chair
change backrest breadth
backrest length
length
Drag to
change
seat
breadth

10. Geometry & Knowledge: synergies
Source
GML Model
Semantics
Generation rules for rims
Use
Fast Design and reshaping

11. Geometry & Knowledge: synergies
Drag to Drag to Drag to
change change change
spoke length spoke quantity spoke quantity
(again)
Change rim style Change several
parameters

12. Contacts and Key Players
# Contacts: 53
# Questionnaires: 25
Categories
Applications:
e.g Industrial Design, Mechanical Engineering,
Research Engineering, Simulation Engineering
Methodology:
Visualization, simulation, testing, analysis, optimization,
verification of shapes, validation
Integration
Supplier Industry, Prototyping Service Provider, IT
developer

13. Contacts and Key Players
Volkswagen AG, Germany
Siemens AG, Germany
LogiTech, Switzerland
Dassault Systems, USA
Ceetron, Norway
Technische Universität Darmstadt, Interactive
Graphics Systems Group, Germany
Think3, Italy
AUTODESK, USA
Lumiscaphe, France
EDF Group – R&D Direction
Pininfarina Extra S.r.l, Italy

14. Contacts and Key Players
Jotne EPM Technology, Norway
ItalDesign Giugiaro, Italy
Institute of Computer Graphics, TU Graz, Austria
Det Norske Veritas Industries, Norway
Intergraph Deutschland, Germany
Hella KgaA Hueck & Co, Germany
Adam Opel GmbH, Germany
ANSALDO RICERCHE, Italy
ALESSI S.p.A, Italy

15. Scenarios in CAD/CAE and Virtual Product
Modeling
FDMU – Functional Digital Mock-Up
Industry sees a need for higher inter-operability
and integration of simulation frameworks
Modeling and Simulation of large electronical and
mechanical components of a product within a
single application overcoming format and I/O
boundaries
Seamless interfaces
Better and faster visualization of potential hazards
Mechatronics as a new field of research

16. Scenarios in CAD/CAE and Virtual Product
Modeling
Specific problems
Rapidly growing share of mechatronic systems in
products
Products getting increasingly complex
Continuing competitive pressure
Reduction of time and costs
Increase in quality and reliability
Time-to-market

17. Scenarios in CAD/CAE and Virtual Product
Modeling
mechanic electronic
simulation: simulation:
results results
visualization visualization
of e.g. of e.g. EMI
flow
system view:
functions
and control
software simulation:
function control,
system
behaviour/validation

18. Scenarios in CAD/CAE and Virtual Product
Modeling
Semantic procedural models - what is it?
…are for 3D what pdf is for text pages
Characteristics and potentials
High reusabilbity
Paradigm shift towards
generic models
Inherent semantics
Rules and reasoning
Procedural matching

19. Scenarios in CAD/CAE and Virtual Product
Modeling
Samples generated with GML

20. Conclusion
Open issues / major problems
Non-existent links between 3D models and product
properties/characteristics/behaviour
Re-use for geometric components
Less knowledge about interfaces and kinematic of
cybernetics
Visualization of production technologies’ shape
constraints
Global shape modeling
Creation/Re-use of surface/volume CAD models
containing partitions

21. Conclusion
More Open issues / major problems
Unfold geometries for surface parametrization
PDM for the whole product life cycle
Effective similarity search methods
Structural similarity as a concept
Effective querying controls
Contextualize 3D objects

22. Conclusion
More Characteristics of a framework for
handling 3D content:
Scalable result visualization
Powerful user interface for query specification
Extensibility with respect to new shape
representations