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Members focus on the dissemination of knowledge and information in the area of power reactors with particular application to the production of electric power and process heat. The division sponsors meetings on the coverage of applied nuclear science and engineering as related to power plants, non-power reactors, and other nuclear facilities. It encourages and assists with the dissemination of knowledge pertinent to the safe and efficient operation of nuclear facilities through professional staff development, information exchange, and supporting the generation of viable solutions to current issues.
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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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Prepare for the 2025 Nuclear PE Exam with ANS guides
The next opportunity to earn professional engineer (PE) licensure in nuclear engineering is this fall, and now is the time to sign up and begin studying with the help of materials like the online module program offered by the American Nuclear Society.
R. R. Coveyou, V. R. Cain, and K. J. Yost
Nuclear Science and Engineering | Volume 27 | Number 2 | February 1967 | Pages 219-234
Technical Paper | doi.org/10.13182/NSE67-A18262
Articles are hosted by Taylor and Francis Online.
The use of the Monte Carlo method for the study of deep penetration of radiation into and through shields entails the use of sophisticated methods of variance reduction to make such calculations economical or even feasible. This paper presents an exposition of the most useful methods of variance reduction. The exposition is unified by consistent exploitation of adjoint formulations to estimate expected values, as in previous work, and further to evaluate the variance of the resulting estimates., The connection between adjoint formulations and the choice of biasing schemes is also investigated. In particular, it is shown that the value function (the solution of the integral equation of the adjoint formulation) is always a good choice for importance function biasing; a sharp upper bound, independent of the particular problem, is found for the resulting variance. Predicted (analytic) and experimental (Monte Carlo) results are also given for a simple one-dimensional problem.