Showing papers by "Timothy J. Ross published in 1986"

DAPS: An Expert System for Damage Assessment of Protective Structures

Abstract: An automated reasoning code for the damage assessment of protective structures (DAPS) is being developed within the Air Force. Protective structures in this context will be synonymous with buried facilities which are designed to withstand intense impulsive pressures. The code is being written for initial implementation on a microcomputer IBM AT. Two inferencing schemes, both involving back-chaining logic, are being investigated for the DAPS code. DAPS combines crisp numerical data with non-crisp linguistic data using the precepts of fuzzy set theory to estimate the uncertainty in the knowledge base. The data base comes from a series of eleven experimental tests on buried reinforced-concrete boxes subjected to explosive pressures. Crisp data in the form of instrumentation waveforms and linguistic data obtained from experts through questionnaires dealing with the experimental tests comprise the knowledge base.

Structural failure determination with fuzzy sets

Abstract: This paper has four objectives. Firstly, modifications are recommended and presented to a well known set of US Army test data representing eleven tests that involve destruction of buried concrete box structures by ground transmitted shock waves. The resultant database is available for failure mode analysis. Secondly, a new approach forfailure mode analysis based on pattern recognition techniques to the structural engineering community is introduced. Thirdly, a comparison is presented of the results of preprocessing, feature extraction, and cluster analysis for failure modes to several previous studies. The objective here is to inform the structural engineering community about data interpretations that can be inferred using this approach; the authors do not claim to have a conclusive or definitive classification of failure modes in these data. Finally, the importance of a priori decisions about data analysis during the planning stages of physical experiments is emphasized by pointing out the many ...

Expert Opinions and Expert Systems

Abstract: The inference mechanism in most current expert (rule-based production) systems is based on exact matching of the antecedent or consequent of a rule with a fact or hypothesis. The rule will not be triggered when there is the slightest discrepancy in matching. However, expert opinions are not always crisp as can be attested by commonly used terms such as large, slight, etc. in the rules. Furthermore, the same term such as large may not have the same meaning when used by different experts. Such fuzziness in expert opinions and rules appears inconsistent with a crisp exact-matching inference mechanism. The paper describes the use of fuzzy sets to model vague and imprecise opinions, the formulation of rules from fuzzy opinions, and an inference mechanism for fuzzy rules. Within this fuzzy set representation framework, matching no longer needs to be exact. Partial matching is possible, and conflicting rules can be accommodated.

Pattern Recognition Techniques for Distinguishing Structural Failure Modes from High Pressure Loading Records

Abstract: Pattern recognition techniques have been successfully employed in a wide variety of fields, such as geophysical exploration, medical diagnosis, radar tracking, and earthquake structural damage classification. To date, two investigations have been attempted in the explosive effects field: one identifying the explosive source based upon ground motion records and the second investigating the phenomenon of ground spall. This paper seeks to describe the utility of pattern recognition methods to help distinguish structural failure modes and also detail the difficulties inherent in a problem of this type. The problem involves the examination of dynamic response and failure of shallow-buried reinforced concrete box structures subjected to impulsive pressures.