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Geostatistics for radiological evaluation: study of structuring of extreme values

机译:用于放射学评估的地统计学:极值结构的研究

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摘要

Geostatistics applied to radiological evaluation of nuclear premises provides sound methods to estimate radiological activities, together with their uncertainty. Quantification and risk analysis of contaminated areas are initially performed by applying geostatistical methods relying on the multi-Gaussian assumption. However, the application of the classical bi-Gaussian model for disjunctive kriging proves sub-optimal due to the spatial structuring of high and low values. The beta model which pertains to the class of Hermitian isofactorial models is potentially better suited to radiological evaluation as it allows a continuous evolution from a mosaic to a pure diffusive model. In the test case, disjunctive kriging estimates are obtained by applying in turn the beta model and the pure diffusive model. The comparison of estimation outcomes shows rather limited differences, primarily located in and around the homogeneous contaminated areas.
机译:应用于核场所放射性评估的地统计学提供了评估放射性活动及其不确定性的合理方法。污染区域的量化和风险分析最初是通过基于多高斯假设的地统计学方法进行的。然而,由于高值和低值的空间结构,经典双高斯模型在析取克里金法上的应用证明是次优的。属于Hermitian等因子模型类别的beta模型可能更适合于放射学评估,因为它允许从镶嵌图到纯扩散模型的连续演变。在测试案例中,通过依次应用beta模型和纯扩散模型来获得析取克里金法估计。估算结果的比较显示出相当有限的差异,主要位于均质污染区域内和周围。

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