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In nuclear and industrial facilities, fine particles, including radioactive residues—can accumulate on the interior surfaces of ventilation ducts and equipment, posing serious safety and operational risks.
Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.
Among the methods for point source carbon capture, the absorption of CO2 using aqueous amines (namely MEA) from the post-combustion gas stream is currently considered the most promising.
A novel approach is presented herein to improve time to onset of natural convection stemming from fuel element porosity during a failure mode of a nuclear reactor.
The technologies provide a system and method of needling of veiled AS4 fabric tape.
ORNL will develop an advanced high-performing RTG using a novel radioisotope heat source.
This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.