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Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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GRETA, sensitive and flexible, heads to Michigan State to study the nucleus
Researchers announced earlier this month that they have completed major construction of the Gamma-Ray Energy Tracking Array (GRETA), a precision tool for gamma ray spectroscopy that, according to Paul Fallon, a researcher at University of California–Berkeley and GRETA’s project director, will be 10 to 100 times more sensitive than previous nuclear science experiments. Fallon was quoted in an August 8 article published by Lawrence Berkeley National Laboratory (Berkeley Lab)—where GRETA’s project leaders are based and GRETA was assembled.
Michio Murase, Yoichi Utanohara, Takayoshi Kusunoki, Yasunori Yamamoto, Dirk Lucas, Akio Tomiyama
Nuclear Technology | Volume 197 | Number 2 | February 2017 | Pages 140-157
Technical Paper | doi.org/10.13182/NT16-96
Articles are hosted by Taylor and Francis Online.
We proposed prediction methods for countercurrent flow limitation (CCFL) in horizontal and slightly inclined pipes with one-dimensional (1-D) computations and uncertainty of computed CCFL. In this study, we applied the proposed methods to a full-scale pressurizer surge line [inclination angle θ = 0.6 deg, diameter D = 300 mm, and ratio of the length to the diameter (L/D) = 63] in a specific pressurized water reactor, performed 1-D computations and three-dimensional (3-D) numerical simulations, and found that uncertainties caused by effects of the diameter and fluid properties on CCFL were small. We also applied the proposed methods to experiments for hot-leg and surge line models (θ = 0 and 0.6 deg, D = 0.03 to 0.65 m, and L/D = 4.5 to 63) to generalize them, performed 1-D computations, and found that uncertainties caused by effects of θ and L on CCFL were large due to the setting error for θ and differences among experiments. This shows that a small-scale air-water experiment with the same θ and L/D as those in an actual plant is effective to reduce the uncertainty of CCFL prediction.