Researchers at Tianjin University have developed LineGen, a physics-guided method combining ordinary differential equations and a time-embedded U-Net, to generate super-resolution load data (SRLD) for power distribution systems. Published in Engineering, the approach addresses limitations in high-frequency data collection by achieving a 1000-fold resolution enhancement—significantly surpassing prior deep learning methods—while offering traceable physical interpretability for improved grid management and reliability.

Researchers at Shenzhen University have developed a novel self-sensing steel fiber-reinforced polymer  composite bar (SFCB) that integrates distributed fiber-optic sensors (DFOS) for real-time monitoring of cracks and mechanical behavior in reinforced concrete members. This innovative approach, detailed in a recent study published in Engineering, aims to enhance the durability and safety of civil infrastructure by providing a more accurate and reliable method for structural health monitoring.