Numerical generation of a database of acousto-ultrasonic signals for predicting the remaining useful life of hydrogen storage tanks

This project tackles the problem of monitoring the health of composite hydrogen‑storage tanks that are repeatedly loaded until they fatigue. Getting experimental data for many different kinds of composite defects takes a lot of time and money, so we propose a purely numerical way to build a large library of acousto‑ultrasonic signals. The method works like this: * A finite‑element model includes a phase‑field fatigue formulation. It simulates how damage spreads in the material when we change the initial flaws, fiber directions, and porosity. * The resulting damage fields – which vary in space and correspond to different numbers of fatigue cycles and stiffness levels – are fed into a

dynamic wave‑propagation model. * The wave model excites and tracks acousto‑ultrasonic waves as they travel through the damaged composite. The output is a set of realistic sensor signals that contain information about the internal damage. The signal database can be used to train algorithms that predict how much useful life remains in a composite pressure vessel. The project also gives step‑by‑step guidance for: * setting up multi‑scale finite‑element simulations, * converting damage variables into wave‑propagation inputs, * analyzing how waves attenuate and scatter because of the damage. These tools aim to improve prognostic and health‑management systems for aerospace and automotive composite structures.

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