Automated Modelling of Visco-elastic Materials

To build model-based systems capable of emulating the scientist's or engineer's way of reasoning about a given physical domain requires methods for automating the formulation or selection of a model, which adequately captures the knowledge needed for solving a specific problem. To find and exploit such models requires the use and integration of different kinds of knowledge, formalisms and methods. This paper describes a system which aims at reasoning automatically about visco-elastic materials from a mechanical point of view. It integrates both domain specific and domain independent knowledge in order to classify and analyse the mechanical behaviours of materials. The classification task is grounded on qualitative knowledge while the analysis of a material is performed at a quantitative level and is grounded on numerical simulation. The key ideas of our work are: to generate automatically a library of models of ideal materials and their corresponding qualitative responses to standard experiments, to classify an actual material by selecting within the library a class of models whose simulated qualitative behaviours to standard loads match the observed ones, to identify a quantitative model of the material, and then to analyse the material by simulating its behaviour upon any load. Each model in the library is automatically generated in two different forms: at the lowest level, as a symbolic description and then, at a mathematical level, as an ordinary differential equation. This paper mainly concentrates on the methods and algorithms of model generation and of qualitative simulation.