Creep prediction techniques

This chapter is a review of practical and easily accessible techniques in physicochemical property prediction. It is not intended to be comprehensive, or be a guide to every kind of approach that can be adopted. The scientific basis of the various methods has been reviewed frequently and recently (Boethling and Mackay, 2000 Fisk 1995). The intention is to set out approaches that can be readily applied, and to give guidance on good practice. The very fact of the ready availability of computerized methods of well-established reliability can give a false sense of security. The examples show that the off-the-peg methods are remarkably effective, which, somewhat ironically, increases the risk of bad practice creeping in. 

It can be said that the design of a product involves analytical, empirical, and/or experimental techniques to predict and thus control mechanical stresses. Strength is the ability of a material to bear both static (sustained) and dynamic (time-varying) loads without significant permanent deformation. Many non-ferrous materials suffer permanent deformation under sustained loads (creep). Ductile materials withstand dynamic loads better than brittle materials that may fracture under sudden load application. As reviewed, materials such as RPs can exhibit changes in material properties over a certain temperature range encountered by a product. 

Temperature or humidity fluctuations can be accelerated only to the point of maintaining uniform penetration that is likely in the end use environment. If creep or vibration is expected in service, time-temperature superposition may often be applied to accelerate laboratory testing. This technique mathematically predicts the material s response in service, based on laboratory characterization of the material over a... 

All voids described so far have been formed at, or released from, the metal-oxide interface. Birchenal has discussed the formation and growth of voids within the oxide scale by condensation of vacancies. For this to occur anions must be removed in some way and he has suggested creep and slip in the anion lattice as possible mechanisms. More recently, Cox has used a sensitive porosimeter as well as special metallographic techniques to study strings of voids formed in zirconium oxide as a result of recrystallisation—the work is discussed in more detail below. Although Birchenal s model predicted greater deviations from the parabolic rate law than were in fact found, the phenomenon of pore growth within the scale seems to be real and it is as well to keep the implications for anion movement in mind. 

The difficulty in using the R-W technique or any other method to predict time dependent failure is subject to the variability of experimental data. It is well known that large variability in creep rupture data is the norm. One obvious reason for the variability is that the slope of a stress vs. failure time plot of data is quite small and, for this reason, a small change in failure stress can translate into a large change in time. It is for this rea-... 

The tests were performed to check how close the predictions from the master curve are to the actual data of viscosity versus shear rate. For most polymers, the error in the predicted value was limited to a maximum of 20%. The minimum deviation was less than 3%, as in the case of PET. For some polymers, however, the maximum enor in the case of some data was within a broader band of 40%. The reason for this is that the master rheogram itself had a broad bandwidth. Because most of the data were coalesced from existing literature data, the errors in the original data naturally creep into the predictions from the master curve. It is known that, even with the most sophisticated equipments, errors to the extent of 50% can creep in if proper care is not taken when generating the data. Thus, the blame for the broader error band in the case of some polymers, that too only in the low-medium shear-rate ranges, does not rest entirely with the master curve. If the original data which are used for forming the master curve are error-free, then automatically the master curve predictions would be very accurate, as the unification technique itself is very reliable. 

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