铀尾矿堆覆盖材料混合智能优化选择研究

Hybrid Intelligent Optimal Selection Research of Cover Materials in Uranium Tailing Pile

根据铀尾矿堆放射性污染物特性,建立了覆盖条件下铀尾矿堆氡迁移的动力学模型。在覆盖材料的优化选择过程中,建立了以氡析出率和成本为决策目标的多目标决策模型,该模型有效融合了免疫遗传算法与TOPSIS排优方法的优点求解多目标决策模型。通过该模型可得到氡析出率最小时,覆盖材料物理性能参数的最优值及最优覆盖材料。参数优化结果表明,氡析出率与覆盖材料孔隙度及扩散系数呈正比,与覆盖材料厚度呈反比。方案排优结果证实,使用可行解沥青进行覆盖能取得很好的环境及经济效益。

Under the condition of covering,a radon migration dynamics model of the uranium tailing pile was developed according to the characteristics of radioactive pollutants.In the process of the optimization of cover material selection,the multi-objective decision model was established which considered the radon exhalation rate and cost as decision objective.The model effectively integrated advantages of immune genetic algorithm and TOPSIS to solve the multi-objective decision model.The optimal values of physical property parameters of cover materials are obtained when the radon exhalation rate is minimal,and the optimal cover material is got by this model.The results of parameter optimization show that the radon exhalation rate is proportional to the porosity and diffusion coefficient of cover materials and inversely proportional to the thickness of cover material.The results of multi-objective optimization confirm that using the fea-sible solution-asphalt can obtain the best benefit of environment and economy.