Oak Ridge National Laboratory researchers demonstrated that microchannel heat exchangers in heating, ventilation and air conditioning units can keep refrigerants evenly and continually distributed by inserting a device called a piezoelectric-driven
Oak Ridge National Laboratory researchers demonstrated that an electrochemical sensor paired with a transmitter not only detects propane leaks within seconds, but it can also send a signal to alert emergency services.
Oak Ridge National Laboratory, University of Tennessee and University of Central Florida researchers released a new high-performance computing code designed to more efficiently examine power systems and identify electrical grid disruptions, such as
Oak Ridge National Laboratory researchers have created a technology that more realistically emulates user activities to improve cyber testbeds and ultimately prevent cyberattacks.
Oak Ridge National Laboratory researchers designed and field-tested an algorithm that could help homeowners maintain comfortable temperatures year-round while minimizing utility costs.
A novel approach developed by scientists at ORNL can scan massive datasets of large-scale satellite images to more accurately map infrastructure – such as buildings and roads – in hours versus days.
To better determine the potential energy cost savings among connected homes, researchers at Oak Ridge National Laboratory developed a computer simulation to more accurately compare energy use on similar weather days.
In collaboration with the Department of Veterans Affairs, a team at Oak Ridge National Laboratory has expanded a VA-developed predictive computing model to identify veterans at risk of suicide and sped it up to run 300 times faster, a gain that could profoundly affect the VA’s ability to reach susceptible veterans quickly.
Researchers at Oak Ridge National Laboratory are taking inspiration from neural networks to create computers that mimic the human brain—a quickly growing field known as neuromorphic computing.
A study led by Oak Ridge National Laboratory explored the interface between the Department of Veterans Affairs’ healthcare data system and the data itself to detect the likelihood of errors and designed an auto-surveillance tool