ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Division Spotlight
Education, Training & Workforce Development
The Education, Training & Workforce Development Division provides communication among the academic, industrial, and governmental communities through the exchange of views and information on matters related to education, training and workforce development in nuclear and radiological science, engineering, and technology. Industry leaders, education and training professionals, and interested students work together through Society-sponsored meetings and publications, to enrich their professional development, to educate the general public, and to advance nuclear and radiological science and engineering.
Meeting Spotlight
ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
Latest Magazine Issues
Apr 2025
Jan 2025
Latest Journal Issues
Nuclear Science and Engineering
May 2025
Nuclear Technology
April 2025
Fusion Science and Technology
Latest News
General Kenneth Nichols and the Manhattan Project
Nichols
The Oak Ridger has published the latest in a series of articles about General Kenneth D. Nichols, the Manhattan Project, and the 1954 Atomic Energy Act. The series has been produced by Nichols’ grandniece Barbara Rogers Scollin and Oak Ridge (Tenn.) city historian David Ray Smith. Gen. Nichols (1907–2000) was the district engineer for the Manhattan Engineer District during the Manhattan Project.
As Smith and Scollin explain, Nichols “had supervision of the research and development connected with, and the design, construction, and operation of, all plants required to produce plutonium-239 and uranium-235, including the construction of the towns of Oak Ridge, Tennessee, and Richland, Washington. The responsibility of his position was massive as he oversaw a workforce of both military and civilian personnel of approximately 125,000; his Oak Ridge office became the center of the wartime atomic energy’s activities.”
Christine Latten, Dan G. Cacuci
Nuclear Science and Engineering | Volume 178 | Number 2 | October 2014 | Pages 156-171
Technical Paper | doi.org/10.13182/NSE13-110
Articles are hosted by Taylor and Francis Online.
This work illustrates reactor physics applications of the predictive modeling of coupled multiphysics systems (PMCMPS), formulated by Cacuci (2014), by means of the benchmarks Godiva (a bare uranium sphere) and Jezebel-239 and Jezebel-240 (bare plutonium spheres). The PMCMPS methodology was ab initio developed in the response space, to reduce as much as possible the computational memory requirements for predictive modeling of very large systems involving not only many model parameters but also many model responses. The model parameters considered in this work include individual cross sections for each material, nuclide, reaction type, and energy group, giving the following totals: 2241 parameters for Jezebel-239, 1458 parameters for Jezebel-240, and 2916 parameters for Godiva. Eight responses were considered for Jezebel-239 (the effective multiplication factor; the center core fission rates for 233U, 238U, 237Np, and 239Pu; and the center core radiative capture rates for 55Mn, 93Nb, and 63Cu). Three responses (the effective multiplication factor and the center core fission rates for 233U and 237Np) were selected for Jezebel-240, and eleven responses were selected for Godiva (the reaction rate types listed for Jezebel-239, along with the radiative capture rates for 107Ag, 127I, and 81Br). The PMCMPS methodology ensures that increasing the amount of information yields more accurate predictions, with smaller predicted uncertainties, as long as the considered information is consistent. This fact is amply illustrated in this work, which shows that the interdependence of responses that were measured in more than one benchmark is stronger than for responses that were measured in a single benchmark. More generally, the consideration of the complete information, including couplings, provided jointly by all three benchmarks (as opposed to consideration of the benchmarks as separate systems) leads to more accurate predictions of nominal values for responses and model parameters, yielding larger reductions in the predicted uncertainties that accompany the predicted mean values of responses and model parameters.