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2026 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
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A closer look at the initial NLIC selections—Part 2
In January, the Department of Energy announced its new Nuclear Lifecycle Innovation Campus (NLIC) program, inviting states via a request for information to express their interest in hosting a facility supporting work from the front to the back end of the nuclear fuel cycle.
By April, 26 states had expressed interest in hosting such a facility. At the end of July, the DOE signed memorandums of understanding with five states—Idaho, Louisiana, Oklahoma, Tennessee, and Utah—to more closely explore the possibilities of state-federal partnerships. These MOUs are not firm commitments from either the federal or state governments. Time will tell which—if any—of the five states develop projects through the program. In the meantime, today, we are taking a close look at what Utah, Idaho, Tennessee can offer in terms of a preexisting nuclear sector that could support new fuel cycle developments.
Executive Session|Panel|Sponsored by Executive Track
Thursday, December 2, 2021|3:05–4:50PM EST |International Ballroom East
Session Chairs:
Todd S. Palmer (Professor, School of Nuclear Science and Engineering Oregon State University)
Ryan G. McClarren (Associate Professor of Aerospace and Mechanical Engineering University of Notre Dame)
Student Assistant:
Keenan Hoffman
Computation and simulation have a rich history in the nuclear enterprise. When combined with modern theory and informed by experimental data, virtual scientific exploration can lead to unparalleled technological advances. But while simulations can be predictive, they can also be dead wrong, leading to the potential for devastating errors in judgment. In this panel session we will explore some of the triumphs of computation and dissect those instances when overreliance on simulation has led us astray. With real-world examples, we will show how the nuclear professional community has been at the forefront of computation and how nuclear science remains at the cutting edge today by using high-performance computing, machine learning, and other methods.
Todd Palmer
Oregon State University
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