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A hierarchical systems knowledge representation framework

We present the design and implementation of a framework for storing and analysing knowledge about engineering systems. The hierarchical entity-relation-attribute model is useful for large data sets, in which it can abstract details so that human users are able to reason about the data. The time-series extension to the model abstracts temporal details. Finally, the implementation of the model includes an execution engine that can simulate the model in one time-slice or as a function of time. Thesis Supervisor: Daniel Hastings Title: Professor