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The REVISE-II modeling tool developed at ORNL supports decision-making for electric vehicle charging infrastructure development along interstate highways in support of intercity travel. Credit: Jason Richards/ORNL, U.S. Dept. of Energy

Researchers at Oak Ridge National Laboratory have developed a nationwide modeling tool to help infrastructure planners decide where and when to locate electric vehicle charging stations along interstate highways. The goal is to encourage the adoption of EVs for cross-country travel.

An algorithm developed and field-tested by ORNL researchers uses machine learning to maintain homeowners’ preferred temperatures year-round while minimizing energy costs. Credit: ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers designed and field-tested an algorithm that could help homeowners maintain comfortable temperatures year-round while minimizing utility costs.

Urban climate modeling

Researchers at Oak Ridge National Laboratory have identified a statistical relationship between the growth of cities and the spread of paved surfaces like roads and sidewalks. These impervious surfaces impede the flow of water into the ground, affecting the water cycle and, by extension, the climate.

ORNL has modeled the spike protein that binds the novel coronavirus to a human cell for better understanding of the dynamics of COVID-19. Credit: Stephan Irle/ORNL, U.S. Dept. of Energy

To better understand the spread of SARS-CoV-2, the virus that causes COVID-19, Oak Ridge National Laboratory researchers have harnessed the power of supercomputers to accurately model the spike protein that binds the novel coronavirus to a human cell receptor.

The TRITON model provides a detailed visualization of the flooding that resulted when Hurricane Harvey stalled over Houston for four days in 2017. Credit: Mario Morales-Hernández/ORNL, U.S. Dept. of Energy

A new tool from Oak Ridge National Laboratory can help planners, emergency responders and scientists visualize how flood waters will spread for any scenario and terrain.

An X-ray CT image of a 3D-printed metal turbine blade was reconstructed using ORNL’s neural network and advanced algorithms. Credit: Amir Ziabari/ORNL, U.S. Dept. of Energy

Algorithms developed at Oak Ridge National Laboratory can greatly enhance X-ray computed tomography images of 3D-printed metal parts, resulting in more accurate, faster scans.