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Division Spotlight
Fuel Cycle & Waste Management
Devoted to all aspects of the nuclear fuel cycle including waste management, worldwide. Division specific areas of interest and involvement include uranium conversion and enrichment; fuel fabrication, management (in-core and ex-core) and recycle; transportation; safeguards; high-level, low-level and mixed waste management and disposal; public policy and program management; decontamination and decommissioning environmental restoration; and excess weapons materials disposition.
Meeting Spotlight
Utility Working Conference and Vendor Technology Expo (UWC 2024)
August 4–7, 2024
Marco Island, FL|JW Marriott Marco Island
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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Nuclear Technology
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Latest News
ARPA-E announces $40 million to develop transmutation technologies for UNF
The Department of Energy’s Advanced Research Projects Agency–Energy (ARPA-E) announced $40 million in funding to develop cutting-edge technologies to enable the transmutation of used nuclear fuel into less-radioactive substances. According to ARPA-E, the new initiative addresses one of the agency’s core goals as outlined by Congress: to provide transformative solutions to improve the management, cleanup, and disposal of radioactive waste and spent nuclear fuel.
Nadish Saini, Igor A. Bolotnov
Nuclear Technology | Volume 208 | Number 8 | August 2022 | Pages 1244-1265
Technical Paper | doi.org/10.1080/00295450.2021.1974279
Articles are hosted by Taylor and Francis Online.
Spacer grids and mixing vanes exhibit a significant role in the thermal hydraulics of pressurized water reactors (PWRs), especially in the post loss-of-coolant accident regimes. A detailed analysis of the contrasting upstream and downstream turbulent flow features is of great importance to both system codes and computational fluid dynamics (CFD)–Reynolds-averaged Navier–Stokes (RANS) modeling. Further, with the advent of supercomputing resources and machine learning research, a data-driven approach to turbulence modeling is gaining popularity. However, owing to the complexities associated with large-scale, high-fidelity data collection capabilities, the application of machine learning–based turbulence models has been limited to simple geometries. In this work, using a highly scalable CFD code PHASTA, we have collected data from direct numerical simulations of a PWR subchannel with high spatial and temporal resolution. From the collected data we extract key turbulent flow features, including mean velocities and Reynolds stresses that highlight the effects of spacer grids and mixing vanes on downstream turbulence in a typical PWR subchannel. An invariant analysis of the anisotropic stress tensor is also presented, which further elucidates their effect on the nature of turbulence in the immediate upstream and downstream vicinity. The high-resolution data from the simulations are archived and intended for the development of data-driven RANS closure models that are capable of capturing the evolution of anisotropy in PWR subchannels.