[HTML][HTML] Deep Learning-Based quantifications of methane emissions with field applications
Tackling methane emissions is critical for mitigating climate change, emphasizing the need
to identify, quantify, and mitigate emission sources. Methane emissions can be detected …
to identify, quantify, and mitigate emission sources. Methane emissions can be detected …
Information extraction from historical well records using a large language model
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 …
wells), it is essential to first locate and then plug these wells. Manual reading and digitizing …
Real-time 3D temperature field reconstruction for aluminum alloy forging die using Swin Transformer integrated deep learning framework
Z Hu, Y Wang, H Qi, Y She, Z Lin, Z Hu, L Hua… - Applied Thermal …, 2025 - Elsevier
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 …
prevention, particularly for aluminum alloys. Current methods are limited to discrete points or …
Unlocking solutions: Innovative approaches to identifying and mitigating the environmental impacts of undocumented orphan wells in the united states
In the United States, hundreds of thousands of undocumented orphan wells have been
abandoned, leaving the burden of managing environmental hazards to governmental …
abandoned, leaving the burden of managing environmental hazards to governmental …
Machine learning-based vorticity evolution and super-resolution of homogeneous isotropic turbulence using wavelet projection
A wavelet-based machine learning method is proposed for predicting the time evolution of
homogeneous isotropic turbulence where vortex tubes are preserved. Three-dimensional …
homogeneous isotropic turbulence where vortex tubes are preserved. Three-dimensional …
Journey over destination: dynamic sensor placement enhances generalization
Reconstructing complex, high-dimensional global fields from limited data points is a
challenge across various scientific and industrial domains. This is particularly important for …
challenge across various scientific and industrial domains. This is particularly important for …
Ultra-scaled deep learning temperature reconstruction in turbulent airflow ventilation
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 …
temperature field into a detailed, continuous field. The fluid mechanics application here …
Super-resolution reconstruction of turbulence for Newtonian and viscoelastic fluids with a physical constraint
Y Jiang, Y Liang, XF Yuan - Physics of Fluids, 2024 - pubs.aip.org
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 …
low-resolution turbulence data is a novel and cost-effective way in a turbulence study …
Spatially-aware diffusion models with cross-attention for global field reconstruction with sparse observations
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 …
and incorporate uncertainty, making them ideal for robust predictions in the presence of …
3-D full-field reconstruction of chemically reacting flow towards high-dimension conditions through machine learning
Monitoring chemically reacting flow is crucial for optimizing and controlling the conversion
processes in various chemical engineering scenarios. These processes are often influenced …
processes in various chemical engineering scenarios. These processes are often influenced …