SENSITIVITY ANALYSIS FOR URANIUM SOILS DECONTAMINATION USING A MONTE CARLO SIMULATION

被引:3
|
作者
Woinaroschy, Alexandru [1 ]
Radu, Aura Daniela [1 ,2 ]
机构
[1] Univ Politehn Bucuresti, Dept Chem & Biochem Engn, Bucharest 011061, Romania
[2] Natl Res & Dev Inst Radioact Met & Resourses, Bucharest 020917, Romania
来源
关键词
artificial neural networks; Monte Carlo simulation; sensitivity analysis; soils decontamination; uranium; REMEDIATION TECHNOLOGIES; CONTAMINATED SOILS; NEURAL NETS; OPTIMIZATION; GROUNDWATER; EXTRACTION;
D O I
10.30638/eemj.2014.202
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The washing method for uranium contaminated soils using three different reagents was investigated. Experimental data have been obtained for four types of soils, which have been characterized in terms of particle size distribution, as well as structure and chemical composition. Thus, the decontamination degree for each type of soil and reagent respectively has been measured. Subsequently, the decontamination process has been simulated using an artificial neural network. Based on this neural network, within the frame of a sensitivity analysis study, and after more than 1,000,000 Monte Carlo simulations it has been established that the most significant parameter (with a contribution to variance of 83.7%) is the soil granulometry. Clay concentration has a significant non-negligible negative influence on the fractional decontamination degree. This means that higher values of clay concentration correspond to a decreasing of the fractional decontamination degree. A similar effect, however smaller, is sludge concentration. Sand concentration in soil, due to their penetration properties, promote in a relative small proportion the decontamination process. These results are common for all three decontamination reagents which have been used.
引用
收藏
页码:1817 / 1825
页数:9
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