AI-Powered Ultrasonic Identification of Cracks in Rocks
This project focuses on identifying crack locations in sedimentary, igneous, and metamorphic rocks using advanced ultrasonic testing. The process involves creating precise cracks using water jet technology, followed by ultrasonic wave analysis to extract key features. By integrating Artificial Intelligence, the system can accurately detect the presence and location of structural defects.
Durability Performance of Impermeable Self-Consolidating Concrete
This research evaluates the high impermeability of SCC under 12-bar water pressure and its long-term durability after 300 freeze-thaw cycles. Through the assessment of Relative Dynamic Elastic Modulus (RDEM) and mechanical properties, we ensure the stability and low penetration depth of concrete specimens in extreme environmental conditions.
AI and Machine Learning Models for Concrete and Advanced Materials
Artificial Intelligence is revolutionizing concrete technology by analyzing thousands of experimental data points to improve the accuracy of strength and workability predictions. Our services include UPV signal processing for damage prediction, automated mix design optimization to minimize waste, and long-term durability forecasting under various environmental conditions.
Data-Driven Accuracy and Smart Mix Optimization
By analyzing thousands of experimental and field data points, Artificial Intelligence significantly improves the accuracy of predicting concrete strength, workability, and setting behavior. Our AI-powered algorithms automatically design and adjust complex concrete mix proportions to achieve optimal performance, minimize waste, and reduce material costs. Furthermore, through machine learning models, we forecast long-term durability, cracking potential, and environmental resistance of concrete under various exposure conditions to ensure structural longevity.