基于遗传-模拟退火算法的源项反演方法研究

Research of Source Term Inversion Based on Genetic Simulated Annealing Algorithms

核事故发生后,在事故工况信息无法获取的情况下,通过环境监测数据进行源项反演是一种有效的源项估计方法。文章设计并实现了一种遗传-模拟退火源项反演方法,仿真计算结果表明:在监测数据无误差这种理想情况下,利用该方法可以得到准确的源项反演结果。为了更好地应用于实际,进一步研究了监测数据误差对反演结果的影响,以及监测数据存在误差的情况下,监测点布点方式和监测点数量对反演结果的影响。

After nuclear accident , if the accident conditions information cannot be obtained directly , it will be an effective method to evaluate source term by reconstructing source term with environmental monitoring data . The article describes the design and the realization of a source term inversion method based on genetic simulated annealing algorithms .The results of simulation show that in the ideal situation that the monitoring data has no error, accurate inversion results can be obtained with this method .In order to apply well in practical applica-tion, the article does further study about the impact of monitoring data error on the inversion results , and the impact of monitoring point distribution mode and the number of monitoring points in the situation that the moni -toring data have errors .