Service life predictions examples

Examples of Component Service Life Prediction with Laboratory CF Data... 

The age-old problem of predicting what will happen to any material after it is subjected to service also exists with plastics. Different data on plastics are available, but typical of so-called progress, there is never sufficient or adequate useful information to predict the service life of products being designed. It is suggested that rather than assume that a lack of data exists, one should determine what is logically available and apply it most efficiently. A potential example of improper design with plastics concerns toys. 

In some simple cases an additive approach can be successful. The service life is divided into stages, for example moderate exposure for one year, severe exposure for one month and low exposure for five years. The predicted degradation effects for the three periods can be summed and the condition of the product at the end, and hence residual lifetime, estimated. If it is assumed that degradation is proportional to the time of exposure and that the damage from different exposure conditions can be cumulatively added then the so called Miner s rule could be used ... 

Weathering is an example of where lifetime prediction is based largely on service life experience under normal or severe conditions as well as accelerated testing. If sufficient allowance is made for the variation between accelerated and natural weathering, and in natural weathering itself, the predictions can be regarded as very satisfactory. 

These examples illustrate the application of Weibull plots to service failure data in order to predict the probability of failure before the end of the service life, coupled with a power law to relate time to failure to the applied electric stress (voltage). 

In practice, most lifetime prediction is based on service experience. Depending on the industry concerned, this can take the form of planned examination of components at the end of their service life or be limited to the explanation of warranty returns. Experience with polymers is now sufficiently long for service experience to be a prime source of information for components with lifetimes of up to 35 years. The construction industry provides a good example of systematic listing of component lifetimes, related to minimum quality levels and modified according to the service conditions. The electrical industry applies statistical methods to life components and predict failures. This, however, strays into the general field of engineering component lifetimes. In this book we are concerned with materials rather than components. 

Studies continue on the effects of a polymer host matrix on the excited-state properties of guest molecules. For example, the lifetime of excited singlet-state species may be greatly prolonged through restrictions of molecular motions (Gusten and Meisner, inter alia). Accurate information on the blend miscibility of polymers is provided by studies of excimer emission (Mikes et al.), and George et al. claim that the service life of many polymers can be predicted from their luminescence properties see also Martin. 

Because the fracture toughness depends both on cure time and temperature, the arbitrary selection of time and temperature for accelerated tests may not be appropriate for reliable prediction of longterm service life of joints (J7). In order to reduce test variability and improve the durability prediction of adhesive joints, it would be necessary first to control the cure temperature and time required to produce a level of fracture toughness that does not change further (14). The study is thus an excellent example of a multidisciplinary approach combining chemistry, fracture mechanics, and wood science in the investigation of the adhesive bonding of wood. 

The paper has outlined the problems which can arise when using wear data from laboratory tests or from service trials. The examples illustrate the potential error of wear rates and hence life predictions. It would be inappropriate to conclude this paper without some positive recommendations which may help to reduce this error. 

Requirements specified in this way are deemed-to-satisfy rules. Such rules cannot be used to quantify the performance of the structure in general, specific effects of additional measures (for instance increasing the cover to the steel), or the consequences of sub-standard practice (for example using a higher w/c). In this respect it is important to note that EN 206 also allows the use of alternative performance-related design methods with respect to durability that consider in a quantitative way each relevant deterioration mechanism, the service life of the element or structure, and the criteria that define the end of the service life. Such methods should draw a picture of the characteristics that the concrete must possess to protect the reinforcement for the service life requested from a predictive model of the corrosion attack. These refined methods (as opposed to standard methods) may be based on long-term experience with local practices in local environments, on data from an established performance test method for the relevant mechanism, or on the use of proven predictive models. 

Several examples of application are given in the literature [40], e. g. for predicting the residual service life of a corroding bridge and testing the efficiency of protection with a corrosion inhibitor [44]. 

ABSTRACT A residual reUabiUty radices of particular and structural members of existing structures subjected to extreme service and climate actions are considered. Time-dependent structural safety margins of particular members and their modifications as stochastic finite sequences are discussed. The primary and revised instantaneous and long-term survival probabilities of members exposed to one and two extreme action effects are analyzed. The revised survival probabdity prediction of members during their residual service life is based on the concepts of truncated resistance distributions and Bayesian statistical approaches. The calculation of revised reliability indices of members is demonstrated by the munerical example. 

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