A model-driven approach to design engineered physical systems /

• Main Author: Sen, Sagar.
• Format: Others
• Language: en
• Published: McGill University 2006
• Subjects: Engineering design > Mathematical models.; Computer-aided design.
• Online Access: http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=101173

The constant growth in complexity of engineered physical (electrical, mechanical etc.) systems has led to the development of software tools to store and reuse design knowledge to simplify the creation of such systems. Models that encode structure and behaviour of components in the system are currently being developed based on the techniques prescribed by Model Driven Engineering (MDE). We use MDE concepts to develop appropriate modelling formalisms to allow creation of models of a target Engineered Physical System ( EPS) at different levels of abstraction. Each level of abstraction presents a certain view of the EPS to a domain expert in the development team. For instance, a high-level view is suitable for a person in a managerial role. An engineer who deals with the same system at a lower level of abstraction develops a model using idealized physical components. A physicist's concern is the physical meaningfulness of the model. The physicist's model verifies if the model prescribed by the manager via the engineer adheres to the laws of conservation of energy and momentum. Finally, a mathematician or a computer scientist obtains a solution to the constrained equations imposed by the dynamical system by solving it analytically or numerically. This model usually takes the form of a set of Differential Algebraic Equations provided by the physicist. === We design model transformations to transform models from a high-level modelling language to lower-level language. We present visual Graph Grammar rules to perform these transformations. We start with a high-level representation of the physical system which is a model in the High-level Physical System Model modelling language. This model is transformed in subsequent steps to a set of trajectories that describe the state of the physical system over time. We show that this hierarchy of transformations to encode knowledge about physical systems drastically reduces design space size at the high-level of abstraction. We search the space of an example EPS using a design heuristic based randomized algorithm to determine the speedup in search due to reduction in the number of design variables.