FOCUS K3D AWG CAD/CAE

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FOCUS K3D is a Coordination Action (CA)which aims at promoting the adoption of best-practices for the use of semantics in 3D content modelling and processing. This slide set gives an overview of the Application Working Group (AWG) CAD/CAE and Virtual Product Modelling.

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http://www.focusk3d.eu/downloads

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FOCUS K3D AWG CAD/CAE

  1. 1. AWG CAD/CAE and Virtual Product Modeling Pedro Santos, Fraunhofer IGD, Germany
  2. 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. 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. 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. 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. 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. 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. 8. Geometry & Knowledge: synergies Source GML Model Semantics Generation rules for Furniture Use Fast Design and reshaping
  9. 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. 10. Geometry & Knowledge: synergies Source GML Model Semantics Generation rules for rims Use Fast Design and reshaping
  11. 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. 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. 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. 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. 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. 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. 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. 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. 19. Scenarios in CAD/CAE and Virtual Product Modeling Samples generated with GML
  20. 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. 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. 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

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