Radiation situation dynamics at the Andreeva Bay site for temporary storage of spent nuclear fuel and radioactive waste over the period 2002-2016

摘要

The Coastal Technical Base (CTB) N (o) under bar 569 at Andreeva Bay was established in the early 1960s and intended for the refueling of nuclear submarine reactors and temporary storage of spent nuclear fuel (SNF) and radioactive waste (RW). In 2001, the base was transferred to the Russian Ministry for Atomic Energy and the site remediation began. The paper describes in detail the radiation situation change at the technical site in Andreeva Bay from 2002-2016, the period of preparation for the most critical phase of remedial work: removal of spent fuel assemblies. The analysis of aggregated indicators and data mining were used. The article suggests the best number and location of checkpoints needed to ensure sufficient accuracy of the radiation situation description. The fractal properties of the radiation field are studied using the Hurst index. The relationship between checkpoints was assessed using the method of searching for checkpoint communities. The decrease in the integral of the ambient dose equivalent rate (ADER) at the technical site was evaluated by the method of time series decomposition. Three components of time series were identified: trend, seasonal and residual. The trend of the ADER integral over the technical site is a monotonic decreasing function, where the initial and final values differ tenfold. Taking into account that Cs-137 dominates the radiation situation on-site, it is clear that the ADER due to the radionuclide decay will have decreased by 1.4 times. It is estimated that only a small proportion of Cs-137 has migrated off-site. Therefore, approximately a sevenfold decrease in dose rate is mainly due to remediation activities of personnel. During the year, the seasonal component varies the ADER integral by a factor of two, due to snowfall. The residual component reflects the uncertainty of the ADER integral calculation and phases of active SNF and RW management. The methods developed are used to support the optimization of remediation wo