Abstract

Two competing methods were introduced for analyzing the condition of a structural system. The results produced by both were very different. In the weighted average approach, the system condition index will always be somewhere between the condition of the best and worst component in the system. In the traditional reliability approach, the condition index will always be lower than the condition of the worst member in a series system and higher than the condition of the best member in a parallel system. A traditional reliability approach works extremely well for a strength-based system where the importance factors of the components are relatively equal and the consequences of failure are typically catastrophic. In a serviceability context where some failures are more serious than others and some components are clearly more important than others, the information provided is less useful. The extreme values obtained in the traditional approach exaggerate the condition of the structure. A condition index of over 100 for the parallel structure would probably ensure it does not get replaced until every portion of the system is significantly deteriorated. In a multi-tiered series system, such as the spillway gate system presented here, the condition index would be so low that it would appear that every structure was in dire need of replacement. The condition of the worst element in the system, no matter how minor, controls the maintenance decision. If the goal is to use the overall condition of a structure to prioritize and optimize maintenance funding, the weighted average approach seems to provide better decision making information. By combining the condition of components with their importance to the overall system, it is easier to make a distinction between competing priorities. While series and parallel systems are treated in the same manner, a distinction could be made in the assignment of importance factors where a redundant system might receive a lower importance factor.

Disciplines

Architectural Engineering

Number of Pages

11

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URL: https://digitalcommons.calpoly.edu/aen_fac/36