To reduce environmental risks and impacts from orphaned wells (abandoned oil and gas
wells), it is essential to first locate and then plug these wells. Manual reading and digitizing …

Tackling methane emissions is critical for mitigating climate change, emphasizing the need
to identify, quantify, and mitigate emission sources. Methane emissions can be detected …

Temperature field distribution in forging dies is crucial for quality control and defect
prevention, particularly for aluminum alloys. Current methods are limited to discrete points or …

In the United States, hundreds of thousands of undocumented orphan wells have been
abandoned, leaving the burden of managing environmental hazards to governmental …

A wavelet-based machine learning method is proposed for predicting the time evolution of
homogeneous isotropic turbulence where vortex tubes are preserved. Three-dimensional …

Reconstructing complex, high-dimensional global fields from limited data points is a
challenge across various scientific and industrial domains. This is particularly important for …

A deep learning super-resolution scheme is proposed to reconstruct a coarse, turbulent
temperature field into a detailed, continuous field. The fluid mechanics application here …

Super-resolution reconstruction (SR) of turbulent flow fields with high physical fidelity from
low-resolution turbulence data is a novel and cost-effective way in a turbulence study …

Diffusion models have gained attention for their ability to represent complex distributions
and incorporate uncertainty, making them ideal for robust predictions in the presence of …

Monitoring chemically reacting flow is crucial for optimizing and controlling the conversion
processes in various chemical engineering scenarios. These processes are often influenced …