The process of reviewing test data for anomalies after a firing of the Space Shuttle Main Engine (SSME) is a complex, time-consuming task. A project is under way to provide the team of SSME experts with a knowledge-based system to assist in the review and diagnosis task. A model-based approach was chosen because it can be adapted to changes in engine design, is easier to maintain, and can be explained more easily. A complex thermodynamic fluid system like the SSME introduces problems during modeling, analysis, and diagnosis which have as yet been insufficiently studied. We developed a qualitative constraint-based diagnostic system inspired by existing qualitative modeling and constraint-based reasoning methods which addresses these difficulties explicitly. Our approach combines various diagnostic paradigms seamlessly, such as the model-based and heuristic association-based paradigms, in order to better approximate the reasoning process of the domain experts. The end-user interface allows expert users to actively participate in the reasoning process, both by adding their own expertise and by guiding the diagnostic search performed by the system.
