Hybrid Intelligent Optimal Control Research Of Radioactive Contaminants In Uranium Tailings Pile

The extraction process of Uranium resource can cause large quantities of radioactive pollution, while the uranium tailings pile is the main source of radon and its daughter in the environment. Therefore, the key point that solving the environmental radioactive pollution is to take reasonable measures to reduce the emission of radon gas of uranium tailings. Studies have shown that covering is an important means to reduce the radon exhalation of uranium tailings. At first, it establishes the dynamic migration models of radon in the Uranium tailings pile separately under the ideal situation and situation that considering the coupling effect of temperature and pressure. Through comparative analyzing, it concludes that the coupling of temperature and pressure may have important influence on the diffusion of radon gas. And on this basis,the one-dimensional migration mathematical equation of radon gas in the covering and constructed multi-objective decision model which considered the radon exhalation rate and cost as decision objective is built.Finally, a hybrid intelligent optimization algorithm, which took Immune genetic optimization algorithm and TOPSIS method as its' theoretical basis, has been used to achieve the optimal choice of cover material. The main results of this project are as follows:(1)It establishes mathematical model of gas migration in the uranium tailings pile under the ideal situation, basing on the diffusion mechanism of radon. The visual display of model results indicates that the radon density in the upper uranium tailings pile increases with time and finally tends to steady state. The radon density is proportional to the displacement.(2)Under the coupling effect of temperature and pressure, a mathematical model of gas migration in the uranium tailings pile is established. The results of numerical analysis shows that the increasing temperature of external environment can exacerbate the diffusion of radon gas molecule and affect the distribution of internal pressure of medium, thus, accelerating the radon exhalation on the surface of uranium tailings pile.(3)It built the dynamic migration model of radon in the covering and got the relational expression between radon exhalation rate and the thickness of the cover, the material porosity and the diffusion coefficient of radon.(4)Using the immune genetic optimization algorithm optimize the material parameters. The results points out that the exhalation rate of radon decreases with the reduction of cover material porosity and the diffusion coefficient.(5)It constructs a multi-objective decision model which considers the radon exhalation rate and cost as decision objective and uses hybrid intelligent optimization method to select asphalt as its optimal cover material.