Page 16: 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.

Energy & Green Tech

AI paves the way toward green cement

The cement industry produces about 8% of global CO₂ emissions—more than the entire aviation sector worldwide. Researchers at the Paul Scherrer Institute PSI have developed an AI-based model that helps to accelerate the discovery ...

Engineering

Using AI to locate uneven areas within concrete

Researchers at Oak Ridge National Laboratory have developed a tool that gives builders a quick way to measure, correct and certify level foundations. FLAT—the Flat and Level Analysis Tool—examines a 360-degree laser scan ...

Business

AI-powered manufacturing cuts battery defects and costs

A team of researchers affiliated with UNIST has successfully integrated artificial intelligence (AI) technology into the manufacturing process of lithium-ion battery cathode precursors, reducing defect rates and enhancing ...

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