Predicting bending moments with machine learning
Peer reviewed, Journal article
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We investigate the possibility of predicting the bending moment of slender structures based on a limited number of deflection measurements. These predictions can help to estimate the wear and tear of the structures. We compare linear regression and a recurrent neural network on numerically simulated Euler–Bernoulli beam and drilling riser.