A novel approach for sustainable construction based on mathematical simulation and a machine learning algorithm: Smart concrete structures with piezoelectric patch

This paper presents a new mathematical simulation using data validation through machine learning for the sustainable construction of smart concrete structures equipped with piezoelectric patches. The framework leverages the selfsensing characteristics of piezoelectric materials to meet the pressing demands for sustainable, intelligent, and resilient infrastructure. The dynamic electromechanical behavior of concrete elements under different working conditions and environmental influences is simulated based on a detailed mathematical model. These simulations are then validated by the use of machine learning algorithms that have been trained on experimental and synthetic data in order to improve the accuracy and robustness for future real-world applications. Simulation of the mathematics along with supervised learning models reveals how the system can support in detection of an anomaly and help make decisions proactively. The research also contributes towards smart infrastructure domain by offering a sustainable nd globally conformable, scalable, and adaptive framework. When applied in combination, power of simulation and data-driven validation supports a revolution in civil engineering design and maintenance pipeline towards an efficient, long-lasting, and intelligent built world.