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Smarter waste strategies: Helping deliver on the promise of advanced nuclear
At COP28, held in Dubai in 2023, a clear consensus emerged: Nuclear energy must be a cornerstone of the global clean energy transition. With electricity demand projected to soar as we decarbonize not just power but also industry, transport, and heat, the case for new nuclear is compelling. More than 20 countries committed to tripling global nuclear capacity by 2050. In the United States alone, the Department of Energy forecasts that the country’s current nuclear capacity could more than triple, adding 200 GW of new nuclear to the existing 95 GW by mid-century.
Chin-Jen Chang, Samim Anghaie
Nuclear Technology | Volume 124 | Number 3 | December 1998 | Pages 265-275
Technical Paper | Radiation Measurements and Instrumentation | doi.org/10.13182/NT98-A2925
Articles are hosted by Taylor and Francis Online.
A high-definition gamma scanning method for the near-field measurement of radionuclide inventories in a large nuclear waste barrel is presented. The method introduced is especially accurate for radionuclides with multiple gamma energy peaks. Multiple detectors positioned as closely as possible to the waste barrel are used to measure the radiation field emanating from the distributed radiation sources. The total source activity is reconstructed by using the conjugate gradient with nonnegative constraint method or the maximum likelihood expectation maximum method based on measured detector responses. The maximum measurement error bond and its associated confidence level for the developed gamma scanning system are determined statistically by performing a large number of numerical experiments that take into consideration the counting statistics, the nonuniformity of source distribution, and the heterogeneous density of the self-absorbing medium. The accuracy and reliability of the system are verified through a series of real measurements with randomly distributed 192Ir sources in a 208-litre waste barrel. The results of these measurements are in full agreement with the estimated error and the confidence level that are predicted by the numerical simulation.