Page 7: 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.

Automotive

An AI system for real-time fault detection in rail transport

Railway infrastructure could be made safer and more reliable using AI, artificial intelligence, according to research published in the International Journal of Information and Communication Technology. The research outlines ...

Computer Sciences

Enhancing navigability for tributaries

Inland waterway transportation has played a limited role in Europe so far, with a share of about 6%. Together with 15 partners, Fraunhofer researchers are seeking to change this with the EU project CRISTAL.

Electronics & Semiconductors

Preventing faults in electronics induced by radiation

Telephone and television reception, GPS navigation systems, broadband internet via satellite—none of this would be possible without electronics in space. However, cosmic radiation in particular can damage components, lead ...

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