Extensive pipeline location data resource: Integrating reported incidents, past environmental loadings, and potential geohazards for integrity evaluations in the U.S. Gulf of Mexico.

The U.S. Gulf of Mexico contains a complex network of existing, decommissioned, and abandoned oil and gas pipelines, which are susceptible to a number of stressors in the natural-engineered offshore system including corrosion, environmental hazards, and human error.

Critical mineral source potential from oil & gas produced waters in the United States.

The volume of produced water, a by-product of oil & gas operations and other energy processes, has been growing across the United States (U.S.) along with the need to manage or recycle this wastewater.

Uncertainty quantification for Bayesian active learning in rupture life prediction of ferritic steels.

Three probabilistic methodologies are developed for predicting the long-term creep rupture life of 9-12 wt%Cr ferritic-martensitic steels using their chemical and processing parameters. The framework developed in this research strives to simultaneously make efficient inference along with associated risk, i.e.

A machine learning aided interpretable model for rupture strength prediction in Fe-based martensitic and austenitic alloys.

The class of 9-12% Cr ferritic-martensitic alloys (FMA) and austenitic stainless steels have received considerable attention due to their numerous applications in high temperature power generation industries. To design high strength steels with prolonged service life requires a thorough understanding of the long-term properties, e.g.