Graphene nanoengineered fiber reinforced concrete compressive strength dataset
Description
This dataset accompanies the article titled "Assessment of Hybrid Fiber Reinforced Graphene Nano-Engineered Concrete Composites: From Experimental Testing to Explainable Machine Learning Modeling". It includes experimental data on the properties of concrete composites that incorporate hybrid fibers and graphene nano-engineering. The dataset contains key parameters such as: Material Composition: Quantities of cement, sand, aggregate, and supplementary cementitious materials (SCM). Additives: Information on water-to-binder ratio (W/B), superplasticizer (SP), and types of fibers used, including steel fiber (SF), polypropylene fiber (PP), and glass fiber (GF). Experimental Conditions: The age of the concrete samples (in days) and the corresponding compressive strength (CS) values. References: A column for source references providing additional details on the experimental setups. This data supports the development and validation of machine learning models to predict the behavior of hybrid fiber reinforced graphene nano-engineered concrete composites.