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systems. The project will integrate electrochemical degradation models with advanced estimation methods, including Kalman filtering and observer-based techniques, to enable real-time prediction of internal
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models of steel structures with emphasis on fatigue hot-spot modelling, building on existing in-house methods Load and stress estimation using virtual sensing techniques (e.g., Kalman Filters) combined
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will consider techniques like flow matching, and use ideas from optimal transport and neural (stochastic) differential equations, invariant Kalman filtering and geometric numerical integration
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models of steel structures with emphasis on fatigue hot-spot modelling, building on existing in-house methods Load and stress estimation using virtual sensing techniques (e.g., Kalman Filters) combined
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transport and neural (stochastic) differential equations, invariant Kalman filtering and geometric numerical integration. The application areas will be chosen among the use cases of the aiD canter