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Access anywhere, anytime: Nuclear power, Ice Camp, and Rickover’s enduring standard of excellence
Admiral William Houston
As U.S. Navy submarines surface through Arctic ice during Ice Camp 2026, they demonstrate more than operational proficiency in one of the harshest environments on Earth. They reaffirm a technological truth first proven in August 1958, when the USS Nautilus completed its submerged transit of the North Pole: nuclear power enables access anywhere, anytime.
The Arctic is unforgiving, with vast distances, extreme cold, shifting ice, and no logistical infrastructure. Conventional propulsion is constrained by fuel, air, and endurance. Nuclear propulsion removes those constraints. Only a nuclear-powered submarine can operate anywhere in the world’s oceans, including under the polar ice, undetected and at maximum capability for extended periods. Nuclear power provides sustained high speed and the endurance to reposition across the globe without refueling.
Hany S. Abdel-Khalik, Paul J. Turinsky
Nuclear Technology | Volume 151 | Number 1 | July 2005 | Pages 22-34
Technical Paper | Advances in Nuclear Fuel Management - Core Physics and Fuel Management Methods, Analytical Tools, and Benchmarks | doi.org/10.13182/NT05-A3628
Articles are hosted by Taylor and Francis Online.
Use of adaptive simulation is intended to improve the fidelity and robustness of important core attribute predictions such as core power distribution, thermal margins, and core reactivity. Adaptive simulation utilizes a selected set of past and current reactor measurements of reactor observables, i.e., in-core instrumentation readings, to adapt the simulation in a meaningful way. The companion paper, "Adaptive Core Simulation Employing Discrete Inverse Theory - Part I: Theory," describes in detail the theoretical background of the proposed adaptive techniques. This paper, Part II, demonstrates several computational experiments conducted to assess the fidelity and robustness of the proposed techniques. The intent is to check the ability of the adapted core simulator model to predict future core observables that are not included in the adaption or core observables that are recorded at core conditions that differ from those at which adaption is completed. Also, this paper demonstrates successful utilization of an efficient sensitivity analysis approach to calculate the sensitivity information required to perform the adaption for millions of input core parameters. Finally, this paper illustrates a useful application for adaptive simulation - reducing the inconsistencies between two different core simulator code systems, where the multitudes of input data to one code are adjusted to enhance the agreement between both codes for important core attributes, i.e., core reactivity and power distribution. Also demonstrated is the robustness of such an application.