At NIST, there is an ongoing program with the goal of predicting the rheological performance of concrete from its mix design. The prediction is based on several steps:
1. measuring the rheological properties of cement paste to determine the influence of chemical admixtures and supplementary cementitious materials;
2. measuring the rheological properties of mortar to determine the influences of air and sand contents; and
3. predicting concrete properties through computer simulation coupled with experimental rheological measurements on mortar and/or cement paste (Ferraris, 1999a; Ferraris and Martys, 2001; Ferraris, de Larrard, and Martys, 2001a).
This approach is justified by the fact that most chemical admixtures and supplementary cementitious materials will have negligible interactions with coarse aggregate. Mortar measurements provide a representative and stable amount of air, as well as a wide range of sand size distributions and shapes. The scientific progression from mortar to concrete then entails only the addition of the coarse aggregates. A novel computational materials science approach allows us to take the rheological properties measured on mortar, add the coarse aggregates with their shape and size distribution, and predict concrete rheological properties. The advantage of this approach is that mortar rheology is much easier and quicker to perform experimentally, and uses much less material than do concrete rheological measurements.
This hierarchical approach obviously needs to be validated at all stages. The rheological properties of cement pastes containing different supplementary cementitious materials (SCM) and high range water-reducing admixtures (HRWRA) were measured and the results were compared to concrete data (Ferraris, Obla, and Hill, 2001). The results showed that the rank of the cement paste mixtures was found to match the concrete performance as characterized by the conventional slump test. A methodology to measure the rheology of mortars was developed and tests are underway with ideal aggregates (spherical glass beads) in mortar and concrete to validate the model (in collaboration with the Center for Advanced Cement-Based Materials).
The cement paste and mortar measurements are performed using a parallel plate rheometer with different size plates depending on whether cement paste or mortar is to be measured. The materials are mixed using a high shear mixer with controlled speed and temperature (Helmuth and others, 1995) to ensure that the material tested experiences conditions typically found in concrete.
The computational materials science model is based on dissipative particle dynamics (DPD) theory (Groot and Warren, 1997 Hoogerbrugge and Koelman, 1992; Koelman and Hoogerbrugge, 1993). This model combines the concepts of cellular automata and molecular dynamics. The fluid phase is modeled by a collection of discrete particles. These particles may represent an agglomeration of molecules or a finite volume of fluid. The DPD algorithm tracks the particle positions at all times. Koelman and Hoogerbrugge (1993) developed an algorithm for modeling the movement of solid objects of arbitrary shape. A rigid body is represented by "freezing together" a group of particles in the volume occupied by the object, which then move together. This method is being modified for application to the flow of concrete. The shape of real aggregates can be described easily by this method (see Figure 10.3.3 for an example). Therefore, it will be possible, knowing the mortar rheological properties, to "virtually" add the aggregates with the correct shape and size distribution. This will allow the simulation of the rheological properties of a concrete of known composition.
Because this computational approach requires powerful computers beyond the range of those readily available to the cement and concrete community, NIST is building a database that will catalog the viscosity of concrete with a coarse aggregate defined by its shape and size distribution for various aggregate contents. The VCCTL user may search the database for aggregates similar in shape and size distribution to those being used. Once the mortar properties are measured, the database will provide the relative viscosity1 of the concrete. Obviously, this will allow the reduction of time-consuming and expensive concrete testing by guiding the VCCTL user to the correct concrete composition having the desired rheological properties.
Figure 10.3.3. Showing a model concrete, where the matrix is mortar (transparent in the picture) and there are 45% by volume coarse aggregates. The four different kinds of aggregates are similar in size and are taken from real aggregates.
1 The relative viscosity is the ratio between the viscosity of the concrete and that of the mortar with the same composition as the mortar component in the concrete.