A Probabilistic Approach to Estimating Hardened Properties of Self-Compacting Concrete

Concrete is the most popular material of construction around the globe. Advancement in structural engineering, architecture, and construction technology has led to the evolution of concrete with superior performance. One of the high-performance concretes is the self-compacting concrete (SCC), which can flow and compact under its own weight. With the need for narrow and sleek structural sections and congestions in the reinforcements, SCC has proved to be a game-changer in the field of concrete technology. The methodology of the present study can be divided into two phases. The first phase is the collection of developed experimental data. Ten different mixes of SCC (with variable amounts of Metakaolin as cement replacement and Nano-silica as additives) are subjected to tests at fresh and hardened states. The set state tests involve compression and split tensile strengths at 7, 28, and 56 days. The study's second phase is the probabilistic assessment of the results obtained from the experimental studies. For this purpose, the Monte-Carlo simulation method of random variable generation is used. The distribution of each mix is established from the Monte Carlo simulation, and strengths corresponding to 5% and 95% probability are shown.