Research Article Computational Model for Internal Relative Humidity Distributions in Concrete Wondwosen Ali and Girum Urgessa Volgenau School of Engineering, Department of Civil, Environmental and Infrastructure Engineering, George Mason University, 4400 University Drive MS 6C1, Fairfax, VA 22030, USA Correspondence should be addressed to Wondwosen Ali; wali2@gmu.edu Received 15 December 2013; Revised 29 January 2014; Accepted 4 February 2014; Published 9 March 2014 Academic Editor: Fu-Yun Zhao Copyright © 2014 W. Ali and G. Urgessa. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A computational model is developed for predicting nonuniform internal relative humidity distribution in concrete. Internal relative humidity distribution is known to have a direct effect on the nonuniform drying shrinkage strains. ese nonuniform drying shrinkage strains result in the buildup of internal stresses, which may lead to cracking of concrete. is may be particularly true at early ages of concrete since the concrete is relatively weak while the difference in internal relative humidity is probably high. e results obtained from this model can be used by structural and construction engineers to predict critical drying shrinkage stresses induced due to differential internal humidity distribution. e model uses finite elment-finite difference numerical methods. e finite element is used to space discretization while the finite difference is used to obtain transient solutions of the model. e numerical formulations are then programmed in Matlab. e numerical results were compared with experimental results found in the literature and demonstrated very good agreement. 1. Introduction Cracking is detrimental to the serviceability, durability, and the aesthetic quality of concrete structures. A major driving force behind cracking is the nonuniform early-age drying shrinkage [1]. Drying shrinkage can be defined as the vol- ume reduction that concrete suffers as a consequence of the moisture migration when exposed to a lower relative humidity environment than the initial one in its own pore system. During production of concrete, more water is added to the concrete mix than necessary for hydration for the sake of workability. is leads to having two types of moisture in concrete. e first type is structural water, chemically bound within the cement paste. As the concrete hydrates, some shrinkage takes place in absence of additional water as hydration takes up some free water. is shrinkage is referred to as autogenous shrinkage and is typically about 50 to 100 microstrains [2]. e second type is the excess water that does not take part in the hydration product and as a consequence it will not be chemically bound to the solid phase. is water is contained in the pore structures. Drying shrinkage in concrete is due to drying of the water contained in the pore structures and the associated decrease in moisture content. erefore, it is necessary to estimate the moisture loss as accurately as possible in order to study drying shrinkage in concrete members. Accurate prediction of dry- ing shrinkage in concrete requires knowledge of the concrete moisture content and its variation. Extensive research has been conducted in literature to identify the drying mecha- nisms of water contained in the pore structures and different mechanisms have been proposed in the literature [3–5]. e most prominent drying mechanisms proposed in the literature include surface free energy, capillary tension, movement of interlayer water, and disjoining pressure [6]. ese mechanisms are complex and are oſten interrelated. is is mainly due to the wide range of pore sizes induced in concrete, which determines the different transport mecha- nisms during drying. e pore sizes also keep on changing with time because of the continuing hydration process. Drying shrinkage is better expressed in in terms of internal relative humidity than moisture concentrations since the Hindawi Publishing Corporation Journal of Computational Engineering Volume 2014, Article ID 539850, 7 pages http://dx.doi.org/10.1155/2014/539850