The energy industry worldwide is today confronted with several challenges, including
heightened levels of consumption and inefficiency, volatile patterns in demand and supply …

Heavy machinery allows for the efficient, precise, and safe management of large-scale
operations that are beyond the abilities of humans. Heavy machinery breakdowns or failures …

Monitoring the continuous health status of a Hydraulic Turbine Generator Unit (HTGU) is a
strategic task to prevent any unexpected downtime. In addition to the loss of energy …

The performance of active noise control (ANC) is significantly influenced by the accuracy of
the secondary path estimate. In the case of a vehicle, dynamic environments, which …

Physics-informed neural networks (PINNs) are a promising approach that combines the
power of neural networks with the interpretability of physical modeling. PINNs have shown …

Pipeline systems are crucial in fluid-conveying pipes across diverse engineering disciplines,
including aerospace, oil transportation, deep-sea exploration, and nuclear energy projects …

In this paper we present the Physics-Aware Deep-NMF (PAD-NMF) algorithm and we apply
it to hit detection in mechanical systems from audio mixtures. The algorithm accurately …

Accurate measurement of the working resistance encountered during excavation plays a
vital role in improving production efficiency, reducing energy consumption, and enabling …

In this paper, three state-of-the-art deep learning uncertainty quantification (UQ) methods–
Flipout probabilistic convolutional neural network (CNN), deep ensemble probabilistic CNN …

The current challenges facing data-driven impact localisation methods primarily involve
accurately localising impacts occurring outside the training impact coverage area …