Makarenko Nikolay, Karimova Lyailya, Novak Miroslav M
Institute of Mathematics, 480100 Almaty, Kazakhstan.
Health Phys. 2003 Sep;85(3):330-42. doi: 10.1097/00004032-200309000-00009.
Effective management of radioactive contamination requires comprehensive knowledge of pollutants' characteristics. The complicated character of the problem is due to a number of issues, such as the very wide range of contamination, the presence of a mixture of radioactive isotopes, the highly variable diffusion of radionuclides in soil, water, and air, and the effect of climatic conditions. The resultant field has an irregular mosaic structure, which restricts the choice of measurement methods and data processing. In view of this, application of classical statistics techniques is often inappropriate in modeling such an environment. Application of the tools of fractal and stochastic geometry provides a good insight and helps to distinguish between distribution characteristics of natural and man-made isotopes. Several techniques are implemented to determine scaling aspects of contaminated fields. The discovery of multifractal scaling leads to the hierarchical structure of contamination spots on different scales and intensity and places restrictions on the measurement net for detecting anomalies. The method of stochastic geometry further demonstrates that topological characteristics of contamination fields differ from those of the Gaussian fields and the topology of man-made isotopes differs from natural ones.
有效管理放射性污染需要全面了解污染物的特性。该问题的复杂性源于诸多因素，例如污染范围极广、存在放射性同位素混合物、放射性核素在土壤、水和空气中的扩散高度可变以及气候条件的影响。由此产生的场具有不规则的镶嵌结构，这限制了测量方法和数据处理的选择。鉴于此，经典统计技术在模拟此类环境时往往并不适用。分形几何和随机几何工具的应用提供了很好的见解，并有助于区分天然同位素和人造同位素的分布特征。实施了多种技术来确定污染场的标度方面。多重分形标度的发现揭示了不同尺度和强度下污染点的层次结构，并对检测异常的测量网络设置了限制。随机几何方法进一步表明，污染场的拓扑特征不同于高斯场，人造同位素的拓扑结构也不同于天然同位素。
