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Human Factors, Instrumentation & Controls
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2025 ANS Annual Conference
June 15–18, 2025
Chicago, IL|Chicago Marriott Downtown
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AI and productivity growth
Craig Piercycpiercy@ans.org
This month’s issue of Nuclear News focuses on supply and demand. The “supply” part of the story highlights nuclear’s continued success in providing electricity to the grid more than 90 percent of the time, while the “demand” part explores the seemingly insatiable appetite of hyperscale data centers for steady, carbon-free energy.
Technically, we are in the second year of our AI epiphany, the collective realization that Big Tech’s energy demands are so large that they cannot be met without a historic build-out of new generation capacity. Yet the enormity of it all still seems hard to grasp.
or the better part of two decades, U.S. electricity demand has been flat. Sure, we’ve seen annual fluctuations that correlate with weather patterns and the overall domestic economic performance, but the gigawatt-hours of electricity America consumed in 2021 are almost identical to our 2007 numbers.
Ruixian Fang, Dan G. Cacuci
Nuclear Science and Engineering | Volume 198 | Number 8 | August 2024 | Pages 1682-1737
Computer Code Abstract | doi.org/10.1080/00295639.2023.2255725
Articles are hosted by Taylor and Francis Online.
This work presents a software module called 4th-Order-SENS, which enables the efficient computation of exactly obtained expressions for all sensitivities, up to and including the 4th order, of a functional of the particle flux (e.g., the leakage of particles out of a body) with respect to nuclear parameters (total, scattering, and fission cross sections; nu, chi, sources; and number densities) for systems modeled by the neutron transport equation. The 4th-Order-SENS module implements the nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Linear Systems (nth-CASAM-L), which is the only practically implementable methodology for obtaining the exact expressions of arbitrarily high-order sensitivities of model responses to model parameters, for response-coupled forward/adjoint large-scale linear systems. In addition to presenting the equations that are solved to obtain the 1st-order through 4th-order sensitivities, this work also describes the components of the module 4th-Order-SENS, including the user interface, input file, output files, and several independent code verification capabilities using symmetries and/or finite-difference formulas. The 4th-Order-SENS module is written in Python and Fortran and runs on Linux platforms. Several illustrative applications involving fixed-source problems in one-dimensional spherical and slab geometries are also presented.