Applications of statistical models in proportioning medium-strength self-consolidating concrete

Self-consolidating concrete (SCC) is generally designed with a relatively higher content of finer - which includes cement and dosage of high-range water-reducing admixture (HRWRA) - than conventional concrete. The design of the current SCC leads to high compressive strength; SCC is already used in special applications where the high cost of materials can be tolerated. Using SCC, which eliminates the need for vibration, leads to increased speed of casting and thus reduces labor requirements, energy consumption, construction time, and cost of equipment. To obtain the maximum benefit from SCC, however, it has to be used for wider applications. The cost of materials will be decreased by reducing the cement content and using a minimum amount of admixtures. This paper reviews statistical models obtained from a factorial design that was carried out to determine the influence of four key parameters on filling ability, passing ability, segregation, and compressive strength. These parameters are important for the successful development of medium-strength SCC (MS-SCC). The parameters considered in the study were the contents of cement and pulverized-fuel ash (PFA), water-powder ratio (W/P), and dosage of HRWRA. The responses of the derived statistical models are slump flow, fluidity loss, rheological parameters, Orimet time, V-funnel time, L-box, JRing combined with Orimet, JRing combined with cone, fresh segregation, and compressive strength at 7, 28, and 90 days. The models are valid for mixtures made with 0.38 to 0.72 W/P, 60 to 216 kg/m³ of coment content, 183 to 317 kg/m³ of PFA, and 0 to 1% of HRWRA, by mass of powder. The utility of such models to optimize concrete mixtures to achieve good balance between filling ability, passing ability, segregation, compressive strength, and cost is discussed. Examples highlighting the usefulness of the models are presented using isoresponse surfaces to demonstrate single and coupled effects of mixture parameters on slump flow, loss of fluidity, flow resistance, segregation, JRing combined with Orimet, and compressive strength at 7 and 28 days. Cost analysis is carried out to show tradeoffs between cost of materials and specified consistency levels and compressive strength at 7 and 28 days that can be used to identify economic mixtures. This paper establishes the usefulness of the mathematical models as tools to facilitate the test protocol required to optimize MS-SCC.