Page 2: Research news on AI-enabled digital twins

AI-enabled digital twins combine high-fidelity virtual replicas of physical assets with machine learning and sensing technologies to monitor condition, predict failures, and support operational decision-making. Applications span bridges, railways, nuclear reactors, wind turbines, manufacturing equipment, and urban infrastructure, integrating structural health monitoring, non-destructive evaluation, and high-resolution imaging. Data-driven models enable real-time fault diagnosis, risk-informed maintenance, and optimization of performance, often incorporating robotics, remote sensing, and time-series domain adaptation for robust, continuous infrastructure management.

Engineering

AI could prevent construction delays before they happen

What if a construction project could rewrite its own schedule the moment a problem appears? A new peer-reviewed study from the University of East London (UEL) suggests that artificial intelligence could make this possible—detecting ...

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