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Because materials and structures cannot be made to always be perfect, they are inspected to determine if they contain flaws or defects large enough to influence their strength, reliability, or economic life. Inspection methods and procedures depend upon the part configuration, possible flaw type, orientation, location, and accessibility. The procedure will depend upon prior knowledge of possible defects and whether or not the inspector is to decide if a single flaw is at a specific location or if no significant flaws exist anywhere in some distributed area or volume.
Long-lived structures require that initial flaws be small so that the flaws will not grow to a critical size during the structure's life or between inspections. Consequently, nondestructive inspection methods are commonly pushed to their limits. For example, the size of a permitted flaw might be just less than the size flaw which will be detected 90 percent of the time. As a result, nondestructive engineering (NDE) methods are not infallible, and some flawed parts might pass inspection. The question, then, is how to calculate the reliability of a part or a structure that has passed inspection.
Three analyses have been developed to calculate this a posteriori reliability. Each handles an increasingly complex situation. The first and simplest gives the reliability based upon the efficiency of the detection method and the probability that the part was unflawed when it reached the inspector (a priori reliability).
The second deals with the problem where flaws are distributed over an area or throughout a volume. Here, the mean number of flaws per unit area or volume (a priori) is a parameter; the actual number in a part is assumed to be Poisson distributed.
The third analysis predicts the a posteriori reliability for a structure with distributed flaws but where some portions are inaccessible and cannot be inspected.
composite materials, nondestructive tests, inspection, reliability
Head, Structural Integrity Branch, NASA-Langley Research Center, Hampton, Va.