Modified model of the aggregated dead zone on examples of radionuclide transfer in natural hydrodynamic systems
Abstract
This paper presents the results obtained during a detailed study of the aggregate dead zone model designed to describe the longitudinal transport and dispersion of dissolved substances in a channel flow. This model is based on a new approach to the description of advection and dispersion, which allows to adequately reproduce the concentrations of solutes observed in natural hydrodynamic systems with a high degree of accuracy. Instead of modelling the dissolved solute concentration continuously in both distance and time along the watercourse, the aggregate dead zone model uses a black box approach and considers the concentration at the chamber outlet (from the aggregate dead zone) as a function of the concentration at the chamber inlet and the current time. This approach significantly reduces the computational time and reduces the requirements for the amount of initial and boundary data. The mathematical apparatus of the extended model of the aggregated dead zone is presented, designed to analyse the transport of non-conservative radioactive contamination in real water bodies, taking into account the possible interaction of the radionuclide with suspended sediments and a layer of bottom sediments. The equations of the proposed model are a system of ordinary differential equations with a delayed argument. The results of modelling the distribution of 3 H as a result of releases from 14 nuclear reactors in the Russian section of the Loire River for six months with an hourly discreteness are presented. The results of modelling the propagation of sudden 90Sr releases in the Kyiv reservoir, which occurred in 1999 as a result of the Chornobyl disaster, are presented. The modelling was carried out with a daily discreteness. A comparison of the obtained model values of radionuclide concentrations and measurement data was carried out. The proposed model has a comparative simplicity, much lower requirements for the amount of initial and boundary data, and very little time required for calculations.
Prombles in programming 2024; 2-3: 45-52
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