Issue 38

M. Kepka et alii, Frattura ed Integrità Strutturale, 38 (2016) 82-91; DOI: 10.3221/IGF-ESIS.38.11 83 into a reliability analysis which gives a more accurate description of the risk of fatigue failure in the critical location of the structural detail. S ERVICE LIFE ASSESSMENT USING PROBABILITY APPROACH aterials subjected to time-varying loads suffer damage caused by the fatigue process. Their load response can be described in terms of time-varying strain and stress, and the cumulative fatigue damage can be found using an appropriately chosen rule. In order to evaluate the service fatigue life of a structure, one needs not only information about its service loading but also some data on the structure’s fatigue strength. The resistance of a structure to high-cycle fatigue damage is described by the S - N curve. The S - N curve can be constructed using fatigue data from a sufficient number of test pieces representing the structural detail under examination. However, it can also be determined by estimate or obtained from one of the standards for design of structures. Fatigue life assessment is often based on the deterministic approach which relies on mean values of load-bearing capacity and load, and a set of factors of safety. If, however, the values of the safety factors are not chosen correctly, the load and the fatigue resistance of the material may prove to be mismatched under real-world service conditions, which may lead to fatigue damage or even failure of the part. Probabilistic approach, on the other hand, uses distributions of random input variables for finding the fatigue life distribution function, i.e. the probability that the material enters its limit state with respect to strength after a certain period in service. Fatigue life estimates are based on cumulative fatigue damage rules. Conformity to the life requirement may be formulated as the part’s reliability. This means that over the required life t req the probability of fatigue failure does not exceed the allowable value P allow . Statistical characteristics of input variables are obtained from measurement and tests (service loading measurement, fatigue testing), determined from experience, or derived from standards and codes. Important to the life estimates are the relationships between input variables, e.g. in the form of cumulative fatigue damage rules, and the mean stress of loading cycles. Comparison can be done using several different rules. This, however, enlarges the variance of the lifetime estimate. Structures are normally designed to the guaranteed design life t g and failure probability P g . These values are guaranteed with certain margins Δ t g and Δ P g , and therefore t g > t req , P g < P allow (Fig. 1). Figure 1 : Schematic illustration of the probabilistic approach to life estimation – position of the point of design life of the structural detail with respect to the FLDF While material properties of parts of equipment are given before it is put into operation, the actual service loads can only be estimated for an already-known steady-state process. Changes to the loading conditions or out-of-standard load states affect the form and position of the fatigue life distribution function (FLDF). They may shorten the life margin Δ t g and M P allow 0 P g A damage probability P stress time history t t res, act t res, req Δ t g Δ P g t act t req t g service life t