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Author
Bentz, D. P. | Ehlen, M. A. | Ferraris, C. F. | Garboczi, E. J.
Title
Sorptivity-Based Service Life Predictions for Concrete Pavements.
Coporate
National Institute of Standards and Technology, Gaithersburg, MD
Book or Conf
Concrete Pavements, 7th International Conference. Proceedings. Volume 1. International Society for Concrete Pavements. September 9-13, 2001, Orlando, FL, 181-193 p., 2001
Keywords
concretes | degradation | service life | simulation | sorption
Abstract
The degradation of concrete pavements is often controlled by the transport of a deleterious species (chloride or sulfate ions, or water in the case of freeze/thaw) into the concrete. With this in mind, a three-year research project, funded by the Federal Highway Administration, has culminated in the development of sorptivity-based service life models for concrete pavements and bridge decks. To develop a service life model, one needs to identify and model the suspected degradation mechanism, develop laboratory tests to evaluate the critical material properties, and adequately characterize the exposure environment. For this project, degradation mechanisms for sulfate attack (ettringite-induced expansion) and freeze/thaw degradation (critical saturation of the air void system) have been postulated. To evaluate sorptivity, a laboratory-based testing protocol for conditioning and assessing the sorption properties of field concrete cores has been developed and submitted to ASTM committee C09 for standardization. To characterize the exposure environment, a one-dimensional finite difference computer model which utilizes typical meteorological year weather data supplied by the National Renewable Energy Laboratory has been developed to predict the concrete pavement surface temperature and time-of-wetness history for a wide variety of geographical locations thoughout the United States. Finally, these methods and computational tools have been integrated into a Windows-based computer software package, CONCLIFE, which provides sorptivity-based service life predictions.