Statistical analysis of concrete transport properties

Abstract

Results of a statistical analysis of transport properties measurements carried out on a number of concrete mixtures are presented. Migration and drying experiments were performed to evaluate the ionic diffusion coefficients and permeability of concrete mixtures. Seven concrete mixtures were tested. The mixtures were either batched under laboratory conditions or sampled from construction sites. For each mixture, approximately eighty concrete samples from a single batch were tested. Ionic diffusion coefficients were calculated by analyzing the evolution of the electrical current passing through concrete samples during the migration tests. Calculations took into account the volume of permeable pores of the materials and the pore solution chemistry. Permeability was calculated from mass loss measured during drying tests. The study indicates that the coefficient of variation of ionic diffusion coefficients is 11.1 % on average, with a maximum of 23.5%, and that the coefficient of variation of permeability is 20.6% on average, with a maximum of 37.3%. Keywords Concrete • Variability •Transport properties • Service life Accordingly, the construction industry started to develop new approaches to increase the service-life of concrete structures. Traditional prescriptive methods, still very much in use today, are in many cases replaced or combined with performance and design specification. In this approach, criteria for durability, such as a targeted service-life duration, are specified. This type of approach was progressively added to construction codes. For example, language for performance specification was incorporated in Canadian standard CSA A23.1-04 1 [9], and defined as a method for specifying a construction product in which the final outcome is given in mandatory language, in a manner that the performance requirements can be measured by accepted industry standards and methods. The Unified Facilities Guide Specification (UFGS), issued by U.S federal agencies in 2010, is another construction guide that incorporates performance-based language for new concrete construction [17]. This new trend in construction methods prompted in recent years the development of numerical tools to support asset management and decision-making to optimize design, service-life, and maintenance of new and existing structures. Reactive transport models dedicated to the prediction of chloride ingress and other deleterious species in reinforced structures became a central element of this new emphasis on long-term service-life predictions [8, 25].

Markov Chain-Based Stochastic Modeling of Chloride Ion Transport in Concrete Bridges

“…The two-point Rosenblueth method for calculating moments of a random variable is used to propagate uncertainty in the transport model and to estimate the mean and variance of chloride ion concentrations as a function of time and depth inside a concrete element. Numerical integration methods or Monte Carlo modeling can be used in theory as an alternative, however, these are computationally too intensive for the transport model (Conciatori et al, 2014). Details of the Rosenblueth point estimators method and comparisons with results from Monte Carlo simulations are presented in Conciatori et al (2014).…”

“…Numerical integration methods or Monte Carlo modeling can be used in theory as an alternative, however, these are computationally too intensive for the transport model (Conciatori et al, 2014). Details of the Rosenblueth point estimators method and comparisons with results from Monte Carlo simulations are presented in Conciatori et al (2014). The Rosenblueth method is used to estimate the mean value of the chloride content and its SD as a function of time and depth into the concrete elements.…”

Updating of chloride ingress models using core data measurements

“…The Rosenblueth point estimation method is used to compute the mean and the variance of the chloride ion concentrations at depths of 25 mm and 50 mm. In both cases, it is assumed that the distributions are lognormal (see Conciatori et al (2014b) for a detailed discussion on the validation of the distribution). The Rosenblueth method is also used to compute the correlation between the chloride ion concentrations at the two depths.…”

Simulation of Humidity Fields in Concrete: Experimental Validation and Parameter Estimation

“…Therefore, knowledge of the moisture distribution within concrete structures since construction and throughout service life can assist a better understanding their actual performance (Conciatori et al 2014), and even support measures to prevent damage and extend the service life. Thus, moisture diffusion in concrete has been studied by many authors in view of several different circumstances and final objectives such as: evaluating the impact of material composition (Bažant and Najjar 1971;Bažant 1972;Kang et al 2012;Persson 1996;Mjörnell 1997;Nilsson 2002), time (Bažant and Najjar 1971;Bažant 1972;Kang et al 2012;Persson 1996;Mjörnell 1997;Nilsson 2002), governing equations or simulation formulations (Zhang et al 2009;Bažant 1972;Kim and Lee 1999;Ishida et al 2007), choice for driving potential for measurement/simulation (e.g.…”