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Reactor Physics
The division's objectives are to promote the advancement of knowledge and understanding of the fundamental physical phenomena characterizing nuclear reactors and other nuclear systems. The division encourages research and disseminates information through meetings and publications. Areas of technical interest include nuclear data, particle interactions and transport, reactor and nuclear systems analysis, methods, design, validation and operating experience and standards. The Wigner Award heads the awards program.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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!
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Latest News
Geological work begins on Poland’s first nuclear plant
Project management firm Bechtel started site geological surveys for Poland’s first nuclear power plant project, the company announced on Wednesday.
Bechtel will conduct in-depth geological surveys at the Lubiatowo-Kopalino site in the Pomeranian municipality of Choczewo, in northern Poland. This is a key milestone for the country’s entry into nuclear power production, as the surveys will inform the suitability of the planned site.
Yeni Li, Hany S. Abdel-Khalik, Acacia J. Brunett, Elise Jennings, Travis Mui, Rui Hu
Nuclear Science and Engineering | Volume 195 | Number 5 | May 2021 | Pages 520-537
Technical Paper | doi.org/10.1080/00295639.2020.1840238
Articles are hosted by Taylor and Francis Online.
The System Analysis Module (SAM), developed and maintained by Argonne National Laboratory, is designed to provide whole-plant transient safety analysis capabilities for a number of advanced non–light water reactors, including sodium-cooled fast reactor (SFR), lead-cooled fast reactor (LFR), and molten salt reactor (MSR)/fluoride-salt-cooled high-temperature reactor (FHR) designs. SAM is primarily constructed as a systems-level analysis tool, with the potential to incorporate reduced order models from three-dimensional computational fluid dynamics (CFD) simulations to improve characterization of complex, multidimensional physics. It is recognized that the computational expense associated with CFD can be intractable for various engineering analyses, such as uncertainty quantification, inference, and design optimization. This paper explores the reducibility of a SAM model using recent advances in randomized linear algebra techniques, which attempt to find recurring patterns in the various realizations generated by a model after randomly perturbing all its input parameters. The reduction is described in terms of fewer degrees of freedom (DOFs), referred to as the active DOFs, for the model variables such as input model parameters and model responses. The results indicate that there is significant room for additional reduction that may be leveraged for additional computational gains when employing SAM for engineering-intensive analyses that require repeated model executions. Different from physics-based reduction approaches, the proposed approach allows one to estimate upper bounds on the reduction errors, which are rigorously developed in this work. Finally, different methods for surrogate model construction, such as regression and neural network–based training, are employed to correlate the input and output active DOFs, which are related back to the original variables using matrix-based linear transformations.