Multi-use is effected through a Compositional Modeling Interchange Language (CMIL), an extension of the earlier CML. CMIL is a declarative language for composable, multi-use domain theories and ontologies. One can represent the structural and behavioral properties of engineered artifacts via algebraic and/or ordinary differential equations, along with applicable constraints. In particular, behavior is encapsulated in model fragments, with structured annotations that explicitly define the applicability conditions for invoking the model fragment and the modeling assumptions that underlie it, thus enhancing its reusability.
CMIL is the language used in the Collaborative Device Modeling Environment (CDME), which consists of libraries of domain theories, ontologies and component device models; a CMIL editor and browser for assembling, extending, and customizing the libraries; a model composer that composes a mathematical model of a physical system from the domain theory and a scenario (the scenario defines the relations among the physical components, initial conditions, stopping conditions, etc.). CDME is accessible via an HTML/Java web user interface.
At the request of DARPA, we focused attention on the domain of jet propulsion systems. Starting with the model described by John A. Reed of Toledo University [Reed97], we modeled the basic components of a gas turbine engine: bleed duct, combustor, compressor, stored mass duct, nozzle, bleed cooled turbine, and rotor shaft. We also modeled the outside environment as described in Reed's paper. The components were modeled as entities, with their behavior (i.e., the mathematical equations) described as CML model fragments. A scenario describing a prototype turbine engine was defined, and CDME composed a model of the system.
CDME was also applied in two other domains during the past year. In collaboration with the Stanford Center for Design Research and Toshiba Corporation, a CML model of a pickup head (as found in CD players) was developed and its behavior simulated successfully. A second application was a (simplified) model of the Boeing 777 hydraulics system, a joint project with Boeing Information and Support Services, which illustrated the advantages of an explicit representation of the components and behavior of a physical system that CDME affords.
The work on safety verification is described in [Loeser98, Neller97, Neller98]. Two approaches to the verification of hybrid systems were examined. Neller's approach is to search for a trajectory that would lead a system from an initial state to an unsafe state. Verification that such a trajectory does not exist is transformed into a global optimization problem. Loeser took the complementary approach of proving that there is no trajectory from a given initial state to an unsafe state.
We also developed a practical framework for characterizing, evaluating, and selecting reformulation techniques for reasoning about physical systems, with the long-term goal of automating the selection and application of these techniques [Choueiry98]. We take the view that problems are solved by the application of a sequence of reformulations to an initial encoding to produce a final encoding that is solvable. The framework provides the terminology to specify the conditions under which a particular reformulation technique is applicable, the cost associated with performing the reformulation, and the effects of the reformulation with respect to the problem encoding. Several reformulation techniques are characterized within this framework.
This project is sponsored by DARPA as part of the Rapid Design and Exploration Optimization (RaDEO) program, and is supported under NIST Cooperative Agreement 70NANB6H0075-04.
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