Multiphysical Characterization for Predicting Compressive Strength of Portland Cement Concrete using Synthetic Aperture Radar, Ultrasonic Testing, and Rebound Hammer

Abstract

Portland cement concrete (PCC) is a versatile and widely used construction material renowned for its strength and durability. The mechanical properties of PCC, including compressive strength, flexural strength, and splitting tensile strength, play a pivotal role in ensuring the safety and sustainability of structures such as buildings, bridges, and dams. Traditionally, the determination of PCC's compressive strength involves destructive testing of standard-size concrete cylinders until they fail. While nondestructive evaluation (NDE) techniques are available for assessing these properties, they often require direct contact between the sensor and the concrete surface, making them less efficient and practical compared to remote sensing techniques. In this paper, we applied three NDE techniques for estimating the mechanical properties of concrete, including synthetic aperture radar (SAR), ultrasonic testing (UT), and a rebound hammer (RH). We manufactured a total of 48 laboratory concrete cylinders (diameter = 3", height = 6"). These cylinders were created with different water-to-cement ratios (0.4, 0.45, 0.5, and 0.55) with a mix design ratio of 1:2:3 for cement: sand: gravel (by mass). Before these cylinders were tested by destructive compression test, they were measured by three NDE techniques. A 10GHz SAR system, a 54kHz UT system, and a RH sensor were used to inspect those cylinders at different concrete ages (7, 14, 28, and 96 days). From our result, the performance ranking among three NDE techniques was individually UT, SAR, and RH. When combining two NDE techniques, SAR with UT delivered the best performance. Multiphysical NDE (SAR with UT) outperformed uniphysical NDE (UT with RH) on the prediction of compressive strength of concrete. This research demonstrates the promising potential of multiphysical NDE for other engineering problems.