Corrections to the 148Nd method of evaluation of burnup for the PIE samples from Mihama-3 and Genkai-1 reactors

Suyama, Kenya; Mochizuki, Hiroki

doi:10.1016/j.anucene.2005.11.009

Cited by 10 publications

(1 citation statement)

References 11 publications

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“…where N Nd148 is the number of 148 Nd atoms and Y Nd148 is the effective fission yield of 148 Nd. The effective fission yield of 148 Nd has to be calculated by weighting the yields for 148 Nd from the four main fissionable nuclides ( 235 U, 238 U, 239 Pu, 241 Pu) with the contributions of these nuclides for the corresponding fuel type (UO 2 or MOX) for each individual fuel sample [42]. The effective fission yields increase slightly with burn-up for both UO 2 and MOX, mostly because of the increasing contribution of 241 Pu.…”

Section: Burn-up Determination By Hplc-mc-icp-msmentioning

confidence: 99%

Characterization of nuclear fuels by ICP mass-spectrometric techniques

et al. 2007

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Isotopic analyses of radioactive materials such as irradiated nuclear fuel are of major importance for the optimization of the nuclear fuel cycle and for safeguard aspects. Among the mass-spectrometric techniques available, inductively coupled plasma mass spectrometry (ICP-MS) and thermal ionization mass spectrometry are the most frequently applied methods for nuclear applications. Because of the low detection limits, the ability to analyze the isotopic composition of the elements and the applicability of the techniques for measuring stable as well as radioactive nuclides with similar sensitivity, both mass-spectrometric techniques are an excellent amendment to classical radioactivity counting methods. The paper describes selected applications of multicollector ICP-MS in combination with chromatographic separation techniques and laser ablation for the isotopic analysis of irradiated nuclear fuels. The advantages and limitations of the selected analytical technique for the characterization of such a heterogeneous sample matrix are discussed.

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Section: Burn-up Determination By Hplc-mc-icp-msmentioning

confidence: 99%