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Division Spotlight
Young Members Group
The Young Members Group works to encourage and enable all young professional members to be actively involved in the efforts and endeavors of the Society at all levels (Professional Divisions, ANS Governance, Local Sections, etc.) as they transition from the role of a student to the role of a professional. It sponsors non-technical workshops and meetings that provide professional development and networking opportunities for young professionals, collaborates with other Divisions and Groups in developing technical and non-technical content for topical and national meetings, encourages its members to participate in the activities of the Groups and Divisions that are closely related to their professional interests as well as in their local sections, introduces young members to the rules and governance structure of the Society, and nominates young professionals for awards and leadership opportunities available to members.
Meeting Spotlight
Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2025)
February 3–6, 2025
Amelia Island, FL|Omni Amelia Island Resort
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!
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Latest News
IAEA’s nuclear security center offers hands-on training
In the past year and a half, the International Atomic Energy Agency has established the Nuclear Security Training and Demonstration Center (NSTDC) to help countries strengthen their nuclear security regimes. The center, located at the IAEA’s Seibersdorf laboratories outside Vienna, Austria, has been operational since October 2023.
Lixun Liu, Han Zhang, Xinru Peng, Qinrong Dou, Yingjie Wu, Jiong Guo, Fu Li
Nuclear Science and Engineering | Volume 198 | Number 10 | October 2024 | Pages 1911-1934
Research Article | doi.org/10.1080/00295639.2023.2284447
Articles are hosted by Taylor and Francis Online.
The Jacobian-free Newton-Krylov (JFNK) method is a widely used and flexible numerical method for solving the neutronic/thermal-hydraulic coupling system. The main property of JFNK is that the Jacobian-vector product is evaluated approximately by finite difference, avoiding the forming and storage of Jacobian explicitly. However, the lack of an efficient preconditioner is a major bottleneck for the JFNK method, leading to poor convergence. The finite difference Jacobian-based Newton-Krylov (DJNK) method is another advanced numerical method, in which the Jacobian matrix is formed and stored explicitly. The DJNK method can provide a better preconditioner for Krylov iteration than JFNK. However, how to compute the Jacobian matrix efficiently and automatically is a key issue for the DJNK method. By fully utilizing the sparsity of the Jacobian matrix and graph coloring algorithm, the Jacobian can be computed efficiently. Unfortunately, when there are dense rows/blocks, a huge computational burden will emerge due to the lack of sparsity, resulting in the extremely poor efficiency of Jacobian computation. In this work, a Jacobian-split Newton-Krylov (JSNK) method is proposed to resolve the dense row/block problem by combining the advantages of JFNK and DJNK. The main feature of the JSNK method is to split the Jacobian matrix into sparse and dense parts. The sparse part of the Jacobian matrix is explicitly constructed using the graph coloring algorithm while for the dense part, the Jacobian-vector product is approximated by finite difference. The computational complexity of the JSNK method is analyzed and compared to the JFNK method and the DJNK method from theoretical and experimental aspects and under different meshes. A simplified two-dimensional (2-D) high-temperature gas-cooled reactor (HTR) model and a simplified 2-D pressurized water reactor model are utilized to demonstrate the superiority of the JSNK method. The numerical results show that the JSNK method successfully resolved the dense rows/blocks. More importantly, its efficiency significantly outperforms the JFNK method and the DJNK method.
