Abstract The Digital Twin (DT) paradigm offers an extension of simulation model utility into
the operational phase of an engineering asset. The goal is a simulation “twinned” with …

After generating a large ensemble of palaeo ice sheet model runs, it is common to either
rank the simulations, or classify each simulation as an acceptable match to observations or …

Unlike some other well-known challenges such as facial recognition, where Machine
Learning and Inversion algorithms are widely developed, the geosciences suffer from a lack …

Abstract The 2010 Deepwater Horizon (DWH) oil spill exposed common bottlenose dolphins
(Tursiops truncatus) in Barataria Bay, Louisiana to heavy oiling that caused increased …

There is increasing concern over anthropogenically driven changes in our oceans and seas,
from a variety of stressors. Such stressors include the increased risk of storms and …

A novel application of a convolutional neural network (CNN) for the identification of mooring
line failure of a turret-moored FPSO is demonstrated. The CNN was trained on images of the …

The Antarctic is a pristine environment inhabited by marine mammal (cetacean and
pinniped) species protected by the Protocol on Environmental Protection to the Antarctic …

Using recent advances in data analytics techniques and tools, this paper proposes a novel
data-centric paradigm for riser fatigue analysis in which practitioners can efficiently make …

Bayesian networks support the probabilistic failure analysis of complex systems, eg, dams
and bridges, needed for a better understanding of the system reliability and for taking …

In the conditions of price reduction in the world energy market, the issue of determining the
priorities of the economic development of hydrocarbons in the Arctic Region of the Russian …