Artificial neural networks and noncontact microwave NDT for evaluation of polypropylene fiber concrete

Abstract

Polypropylene fibers are extensively incorporated into reinforced concrete to enhance performance aspects such as crack resistance, flexural and tensile strength, fire resistance, and overall durability. However, current methods for evaluating factors like fiber inclusion percentage, distribution, and orientation within the concrete matrix are often limited, destructive, and time-consuming. This study explores developing and applying a non-contact microwave non-destructive method (NMNDT) for assessing polypropylene fiber-reinforced concrete. The NMNDT system measures the reflection and transmission characteristics of microwave signals through the concrete, correlating these properties with the physical and mechanical characteristics of the material. Key findings indicate a strong correlation between microwaves’ reflection and transmission properties, the quality of fiber distribution, and the fiber content within the concrete. For instance, the study found that the reflection coefficient (S₁₁) increased from 0.36 to 0.39, with fiber content varying from 0.5 to 1.5 kg/m³, while the transmission coefficient (S₂₁) decreased from 0.46 to 0.38 over the same range. The compressive strength of fiber-reinforced concrete was predicted with a correlation coefficient (R) of 0.98 using artificial neural networks (ANN). These microwave properties can predict mechanical properties such as tensile and compressive strength, with the ANN model achieving more than 97% accuracy. The study highlights the innovative potential of microwave technology as a non-invasive evaluation technique for polypropylene fiber-reinforced concrete, offering a promising avenue for rapid and non-destructive quality control and performance assessment. The integration of ANN further enhances the predictability of the strength properties of polypropylene fiber-reinforced concrete, significantly contributing to advancements in the field of fiber-reinforced concrete evaluation and quality control.