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The mission of the Decommissioning and Environmental Sciences (DES) Division is to promote the development and use of those skills and technologies associated with the use of nuclear energy and the optimal management and stewardship of the environment, sustainable development, decommissioning, remediation, reutilization, and long-term surveillance and maintenance of nuclear-related installations, and sites. The target audience for this effort is the membership of the Division, the Society, and the public at large.
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Neutron Vision at Los Alamos: Exploring the Frontiers of Nuclear Materials Science
In materials science, understanding the unseen—how materials behave internally under real-world conditions—has always been key to developing new materials and accelerating innovative technologies to market. Moreover, the tools that allow us to see into this invisible world of materials have often been game-changers. Among these, neutron imaging stands out as a uniquely powerful method for investigating the internal structure and behavior of materials without having to alter or destroy the sample. By harnessing the unique properties of neutrons, researchers can uncover the hidden behavior of materials, providing insights essential for advancing nuclear materials and technologies.
Shaopeng Xia, Maosong Cheng, Zhimin Dai
Nuclear Science and Engineering | Volume 194 | Number 12 | December 2020 | Pages 1143-1161
Technical Paper | doi.org/10.1080/00295639.2020.1776057
Articles are hosted by Taylor and Francis Online.
Burnup calculations play a very important role in nuclear reactor design and analysis, and solving burnup equations is an essential topic in burnup calculations. In the last decade, several high-accuracy methods, mainly including the Chebyshev rational approximation method (CRAM), the quadrature-based rational approximation method, the Laguerre polynomial approximation method, and the mini-max polynomial approximation method, have been proposed to solve the burnup equations. Although these methods have been demonstrated to be quite successful in the burnup calculations, limitations still exist in some cases, one of which is that the accuracy becomes compromised when treating the time-dependent polynomial external feed rate. In this work, a new method called the Padé rational approximation method (PRAM) is proposed. Without directly approximating the matrix exponential, this new method is derived by using the Padé rational function to approximate the scalar exponential function in the formula of the inverse Laplace transform of burnup equations. Several test cases are carried out to verify the proposed new method. The high accuracy of the PRAM is validated by comparing the numerical results with the high-precision reference solutions. Against CRAM, PRAM is significantly superior in handling the burnup equations with time-dependent polynomial external feed rates and is much more efficient in improving the accuracy by using substeps, which demonstrates that PRAM is the attractive method for burnup calculations.