A KNOWLEDGE REPOSITORY FOR BEHAVIORAL MODELS IN ENGINEERING DESIGN

Computer simulations and behavioral modeling are becoming increasingly important in product development processes. Simulations can result in better decisions in less time by providing the designers with greater understanding of the product’s behavior. However, behavior model creators (i.e. analysts) and behavior model users (i.e. designers) often do not have the same level of understanding of the model, thus limiting the reuse of a model. Our goal in this research is to develop a clean interface that reduces the knowledge gap between engineering design and analysis by facilitating reuse of behavioral models. To achieve a higher level of reuse in the product design process, we propose a meta-data representation for formally characterizing behavioral models. The meta-data representation captures the assumptions, limitations, accuracy, and context of engineering behavioral models. Based on this knowledge representation, a proof-of-concept repository is implemented for archiving and exchanging reusable behavioral models. The knowledge representation and implementation is illustrated with a simple cantilever beam example.

[1]  Donal Finn,et al.  An Intelligent Modelling Assistant for Preliminary Analysis in Design , 1992 .

[2]  Christiaan J. J. Paredis,et al.  Composable Models for Simulation-Based Design , 2001, Engineering with Computers.

[3]  Steven J. Fenves,et al.  A product information modeling framework for product lifecycle management , 2005, Comput. Aided Des..

[4]  Donal Finn,et al.  A physical modeling assistant for the preliminary stages of finite element analysis , 1993, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[5]  Gregory M. Mocko,et al.  A Survey of Design ? Analysis Integration Issues , 2003 .

[6]  D. C. Barton,et al.  Towards integrated design and analysis , 1991 .

[7]  E. A. Avellone,et al.  Marks' Standard Handbook for Mechanical Engineers , 1916 .

[8]  Steven J. Fenves,et al.  Master Product Model for the Support of Tighter Integration of Spatial and Functional Design , 2003 .

[9]  Ram D. Sriram,et al.  Design Repositories: Next-Generation Engineering Design Databases , 2000 .

[10]  M. Shephard,et al.  Toward the implementation of automated analysis idealization control , 1994 .

[11]  Timothy J. Tautges,et al.  The generation of hexahedral meshes for assembly geometry: survey and progress , 2001 .

[12]  B. Gurumoorthy,et al.  Automatic propagation of feature modification across domains , 2000, Comput. Aided Des..

[13]  Sharon J. Kemmerer,et al.  STEP: The Grand Experience , 1999 .

[14]  Hilding Elmqvist,et al.  Physical system modeling with Modelica , 1998 .

[15]  Christiaan J. J. Paredis,et al.  Behavioral model composition in simulation-based design , 2002, Proceedings 35th Annual Simulation Symposium. SS 2002.

[16]  Mark S. Shephard,et al.  Framework for the reliable generation and control of analysis idealization , 1990 .

[17]  N. K. Shaw,et al.  Steps towards CAD-FEA integration , 1993, Engineering with Computers.

[18]  Timothy J. Tautges,et al.  THE WHISKER WEAVING ALGORITHM: A CONNECTIVITY‐BASED METHOD FOR CONSTRUCTING ALL‐HEXAHEDRAL FINITE ELEMENT MESHES , 1996 .

[19]  Ram D. Sriram,et al.  The NIST Design Repository Project , 1999 .

[20]  V. Prabhakar,et al.  A knowledge-based approach to model idealization in FEM , 1994, Proceedings of the Tenth Conference on Artificial Intelligence for Applications.

[21]  Lockheed Martin,et al.  CAD/FEA INTEGRATION WITH STEP AP209 TECHNOLOGY AND IMPLEMENTATION , 1997 .

[22]  Alla Sheffer,et al.  Model simplification for meshing using face clustering , 2001, Comput. Aided Des..

[23]  Russell S. Peak,et al.  Integrating engineering design and analysis using a multi-representation approach , 1998, Engineering with Computers.

[24]  Donal Finn,et al.  Introduction: Preliminary stages of engineering analysis and modeling , 1993, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.