Service life predictions

Even though service life prediction for plastics in terms of aging remains a much discussed and still unsolved issue, phenomenological approximations will be presented in the following, representing a step toward predicting service life. However, it must always be considered that it is scarcely possible to make precise predictions for the service life of plastics products, because the chemical reactions are complex and the physical and geometrical effects overlap (see Section 1.4.1). 

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Mars, W.V., Heuristic approach for approximating energy release rates of small cracks under finite strain, multiaxial loading, in Elastomers and Components—Service Life Prediction Progress and Challenges, Coveney, V., Ed., OCT Science, Philadelphia, 2006, 89. 

Thomas, R. E. Gaines, G. B. "Procedure for Developing Experimental Designs for Service Life Prediction" Thirteenth Institute of Electrical and Electronics Engineers, Inc. Photovoltaic Specialists Conference, Washington, D.C., June 5-8, 1978. 

Figure 12.4 Flow chart for the service life prediction of building components. Simplified from ISO 15686-2 for full details refer to the standard [18].

ISO 15686-2, Buildings and constructed assets - Service life planning - Part 2 Service life prediction procedures, 2001. 

K. Bourke and H. Davies, Factors affecting service life predictions of buildings a discussion paper, BRE Laboratory Report BR 320, Building Research Laboratory, Watford, UK, 1997. 

R336 E. Geiler, N. Eisenreich, A. Geiler and C. Hubner, Analysis and Test Methods for Service Life Prediction of Energetic Materials , Int. Anna. Conf ICT, 2000, 31, 149/1... 

We have demonstrated three techniques that measure the chemical changes associated with the oxidative degradation of polymers. Each of these techniques has the potential to measure very low concentrations of chemical change. The ability to measure slow oxidation rates enable the degradation process to be monitored at the low temperatures more closely related to the material s service conditions. Thus, more accurate service life predictions can be made without relying on extrapolation of high temperature behavior to low temperatures. 

Wei, R. P., and Harlow, D. G., Materials Considerations in Service Life Prediction, Proceedings of DOE Workshop on Aging of Energy Production and Distribution Systems, Rice University, Houston, TX, October 11-12,1992, M. M. Carroll and P. D. Spanos, eds., Appl. Mech. Rev., 46, 5 (1993), 190-193. 

Geotechnical projects Optimal engineering hazard and environmental impact mitigation, service life predictions, cost optimisation... 

Quantitative information on the corrosion rate of steel in concrete is of great importance for the evaluation of repair methods in the laboratory, for service-life prediction and structural assessment of corroding structures as well as control of repair work on site. The only technique available today is the polarization resistance method a RILEM recommendation covering this subject has been published recently [31]. 

Objective of monitoring. A monitoring system, eventually with computerised data acquisition, should meet specifically defined objectives, such as a) to monitor the durability of the structure and its condition in order to make timely decisions for preventive and/or repair actions, b) to monitor the effect of preventative or repair actions, c) to monitor the condition of stmctures based on new materials and/or new technology (including service-life prediction models), d) to follow the time development in areas where access is difficult. 

B. M. Ikeda, M. G. Bailey, M. J. Quinn etal. in Application of Accelerated Corrosion Testing to Service Life Prediction of Materials (Eds. G. Cragnolino, N. Sridhar), American Society for Testing and Materials, Philadelphia, Pa., 1995, Vol. ASTM STP 1194. 

The Life-365 software predicts the initiation period assuming ionic diffusion to be the dominant mechanism. This software differs from other diffusion models in that it accounts for the variability of the diffusion coefficient with age and with temperature. It also attempts to model the impact of various additives. For additives such as silica fume and fly ash it reduces the diffusion coefficient to reflect the lower permeability and for corrosion inhibitors it raises the chloride threshold required to initiate corrosion. To include the impact of sealers and membranes it reduces the rate of accumulation of the surface chloride concentration. The rate of accumulation and the maximum accumulation of surface chloride in this program are based on the type of structure, geographic location and exposure. ACI Committee 365 has also published a state-of-the-art report on service life prediction which is in the process of being updated (ACI 365.1R-00 (2000)). 

Wang, X.M. and Zhao, H.Y. (1993). The residual service life prediction of R.C. structures. Procedding of the 6th International Conference on Durability of Building Materials and Components, S. Nagataki, T. Nireki and F. Tomosawa (eds), Omiya, Japan, October 25-29. 

Pospisil J. Nespurek S. Pilar J. Effect of environmental stress and polymer microenvironment on efficiency trials and fate of stabilizers. In Service Life Prediction of Polymeric Materials Martin, J. W. Ryntz R. A. Chin J. Dickie R. A. Eds. Springer, New York, USA, 2009, pp 493-520. 

Bierwagen, G., et al. 2002. Fundamentals of the measurement of corrosion protection and the prediction of its lifetime in organic coatings. ACS Symp Ser 805 (Service life prediction) 316. 

Guseva, O., S. Brunner, and P. Richner (2003). Service life prediction for aircraft coatings. Polymer degradation and stability S2, 1-13. 

A. R. Azura and A. G. Thomas, Elastomer and components Service life prediction - progress and challenges, Woodhead Publishing in Materials, 2006, 27-38. 

O. Gonenc in Durability and Service Life Prediction of Concrete Reinforcing Materials, University of Wisconsin, Madison, WI, USA, 2001. [MSc Thesis]... 

D. R. Bauer and J. W. Martin, eds.. Service Life Prediction of Organic Coatings (ACS Symposium Series No. 722), Oxford University Press, Oxford, U.K., 1999. 

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

Dickie, R. A., Toward a Unified Strategy of Service Life Prediction, Journal of Coatings Technology, Vol. 64, No. 809, June 1992, pp. 61-64. 

Streicher, M. A., Classification and Application of Corrosion Tests, presented at ASTM Symposium on Application of Accelerated Corrosion Tests to Service Life Prediction of Materials, Miami, FL, 16-17 November 1992. 

W. J. van Ooij and S. K. Jayaseelan, Presented at the Elastomer Service Life Prediction Symposium 98, ARDL, Akron, OH, 1998. 

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