Page 9: 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

New testing scheme could work for chips and clinics

Diagnostic testing is big business. The global market for testing semiconductors for defects is estimated at $39 billion in 2025. For medical lab tests, the market is even bigger: $125 billion.

Engineering

'Self-driving' lab learns to grow materials on its own

When scientists make the thin metal films used in electronics, optics, and quantum technologies, they usually spend months tinkering with the temperature, composition and timing of the process, hoping to land on just the ...

Computer Sciences

RiverMamba: New AI architecture improves flood forecasting

Extreme weather events such as heavy rain and flooding pose growing challenges for early warning systems worldwide. Researchers at the University Bonn, the Forschungszentrum Jülich (FZJ), and the Lamarr Institute for Machine ...

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