Understanding the behavior of a structure and its components in the preliminary design phase is important since decisions made at this time can have a significant influence on the quality of the final design. It can also potentially reduce the number of alternative solutions and avoid costly design revisions. However there are few tools available for modeling of a structure and performing qualitative analysis and interpretation of a conceptual design.

We describe a framework QStruc for qualitative structural analysis which combines first principles in structural engineering and experiential knowledge of structural behavior. The purpose of QStruc is to generate refined qualitative models and to infer the qualitative response of a given preliminary structure. The results are expressed by qualitative deflected shape, moments, and reactions. The proposed qualitative analysis strategy is a "greedy" depth-first algorithm that tries to expand the response of behavior as much as possible from known parameter values. This strategy makes use of: (l) causal ordering mechanism, (2) qualitative calculus, and (3) Quantity Lattice to reason about partial ordering among physical parameters.

The paper discusses the following aspects of QStruc: (1) representation of structures, fundamental principles, and experiential knowledge, (2) model generation, and (3) qualitative analysis. We provide a simple example to illustrate the performance of the implemented prototype QStruc. The paper is concluded with a discussion on preliminary findings of this research and future work.

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