Katy Bradford: Cassette approach offers compelling construction solution
A new convergent manufacturing platform, developed in only five months at the Department of Energy’s Oak Ridge National Laboratory, is debuting at the International Manufacturing Technology Show, or IMTS, in Chicago, Sept. 9–12, 2024.
A team led by scientists at ORNL identified and demonstrated a method to process a plant-based material called nanocellulose that reduced energy needs by a whopping 21%, using simulations on the lab’s supercomputers and follow-on analysis.
ORNL is working with industry partners to develop a technique that combines 3D printing and conventional machining to produce large metal parts for clean energy applications. The project, known as Rapid Research on Universal Near Net Shape Fabrication Strategies for Expedited Runner Systems, or Rapid RUNNERS, recently received $15 million in funding from DOE.
ORNL is the lead partner on five research collaborations with private fusion companies in the 2024 cohort of the Innovation Network for FUSion Energy, or INFUSE, program. These collaborative projects are intended to resolve technical hurdles and develop enabling technologies to accelerate fusion energy research in the private sector.
Researchers at ORNL recently demonstrated an automated drone-inspection technology at EPB of Chattanooga that will allow utilities to more quickly and easily check remote power lines for malfunctions, catching problems before outages occur.
John joined the MPEX project in 2019 and has served as project manager for several organizations within ORNL.
The award was given in “recognition of his lifelong leadership in fusion technology for plasma fueling systems in magnetically confined fusion systems.”
Two additive manufacturing researchers from ORNL received prestigious awards from national organizations. Amy Elliott and Nadim Hmeidat, who both work in the Manufacturing Science Division, were recognized recently for their early career accomplishments.
Researchers at the Department of Energy’s Oak Ridge National Laboratory and partner institutions have launched a project to develop an innovative suite of tools that will employ machine learning algorithms for more effective cybersecurity analysis of the U.S. power grid.
Power companies and electric grid developers turn to simulation tools as they attempt to understand how modern equipment will be affected by rapidly unfolding events in a complex grid.