Formalization and qualification of models adapted to preliminary design

We propose a procedure for the formalization and qualification of models adapted specifically to the requirements of preliminary design. Using this methodology the current lack of suitable decision support tools for design can be overcome. Following a needs assessment for modeling during this design phase, the approach that we develop here is based on functional decomposition to structure the system to be designed. By applying the formalization procedure defined here, the system can be analyzed using tools that are frequently used to good effect by engineers and the problem of preliminary design is structured to produce a behavior model adapted to making design choices and suitable for use with decision support tools.

[1]  Claudio Lottaz Rewriting Numeric Constraint Satisfaction Problems for Consistency Algorithms , 1999, CP.

[2]  Jean-Pierre Nadeau,et al.  Knowledge Base Formulation for Aided Design Tool , 2007 .

[3]  T. Simpson,et al.  Computationally Inexpensive Metamodel Assessment Strategies , 2002 .

[4]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[5]  Osman Balci,et al.  Verification, Validation, and Testing , 2007 .

[6]  Christian Bessiere,et al.  Non-Binary Constraints , 1999, CP.

[7]  Laurent Granvilliers,et al.  Search heuristics for constraint-aided embodiment design , 2009, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[8]  A. Oustaloup,et al.  Utilisation de modèles d'identification non entiers pour la résolution de problèmes inverses en conduction , 2000 .

[9]  Fouad Bennis,et al.  Model reduction technique for mechanical behaviour modelling: Efficiency criteria and validity domain assessment , 2008 .

[10]  Patrick Sebastian,et al.  Global optimization of a dryer by using neural networks and genetic algorithms , 1999 .

[11]  P. Sébastian,et al.  The embodiment design constraint satisfaction problem of the BOOTSTRAP facing interval analysis and genetic algorithm based decision support tools , 2007 .

[12]  Dominique Scaravetti,et al.  Design space exploration in embodiment design: an application to the design of aircraft air conditioners , 2009 .

[13]  Jean-Pierre Nadeau,et al.  Flash Evaporation: Modelling and Constraint Formulation , 2003 .

[14]  Jerry Banks,et al.  Handbook of simulation - principles, methodology, advances, applications, and practice , 1998, A Wiley-Interscience publication.

[15]  Toby Walsh,et al.  Binary vs. non-binary constraints , 2002, Artif. Intell..

[16]  Jérome Pailhes,et al.  Identification of sensory variables towards the integration of user requirements into preliminary design , 2007 .

[17]  Edward P. K. Tsang,et al.  A Context for Constraint Satisfaction Problem Formulation Selection , 2001, Constraints.

[18]  Pedro Barahona,et al.  PSICO: Solving Protein Structures with Constraint Programming and Optimization , 2002, Constraints.

[19]  T. Diveux,et al.  Horizontal axis wind turbine systems: optimization using genetic algorithms , 2001 .

[20]  Kostas Stergiou On Algorithms for Decomposable Constraints , 2002, SETN.