Concrete Workability

Concrete workability, a crucial factor influencing concrete's performance and the efficiency of construction processes, is being extensively researched to improve its prediction and control. Current research focuses on leveraging machine learning, particularly deep neural networks (including CNNs and physics-informed neural networks), and advanced image analysis techniques (like Vision Mamba) to analyze concrete properties from images and sensor data, enabling more precise and automated workability assessment. These advancements aim to optimize concrete mix design, reduce material waste, and enhance the overall efficiency and sustainability of concrete construction. The ultimate goal is to transition from subjective, human-based assessments to objective, data-driven methods for ensuring optimal concrete workability.