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The path-planning in radioactive environment of nuclear facilities using an improved particle swarm optimization algorithm

机译:改进的粒子群算法在核设施放射性环境中的路径规划

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It is important to ensure the radiation safety of workers in nuclear facilities. The path-planning technology is one of the effective ways to reduce the radiation exposure to the workers in the radioactive environment of nuclear facilities. This work studies the path-planning technology in radioactive environment of nuclear facilities, and proposes an improved particle swarm optimization (PSO) algorithm to solve the path-planning problems. To be specific, particle swarm optimization algorithm is associated with chaos optimization algorithm, and new mathematical dose calculation models for the path-planning problem are built. Then, experimental simulation for 3 cases is carried out and the results are compared to those from traditional PSO method. In the first two cases, the average effective doses from the improved PSO method are similar to those from traditional PSO method, but its possibility that the effective dose value is too large becomes smaller. And this trend is more obvious in Case 3. Specifically, the effective dose value above 800 mu Sv is cut by 25% for the improved PSO method. Besides, the average effective dose decreases about 29 mu Sv in Case 3. Meanwhile, the overall convergence rate isn't affected. Hence, the proposed path-planning method in the radioactive environment of nuclear facilities is demonstrated to be effective through the experiments and analysis.
机译:确保核设施中工人的辐射安全很重要。路径规划技术是减少核设施放射性环境中对工人的辐射暴露的有效方法之一。这项工作研究了核设施放射性环境中的路径规划技术,并提出了一种改进的粒子群优化(PSO)算法来解决路径规划问题。具体而言,粒子群优化算法与混沌优化算法相关联,并针对路径规划问题建立了新的数学剂量计算模型。然后,对3种情况进行了实验仿真,并将结果与​​传统PSO方法的结果进行了比较。在前两种情况下,改进的PSO方法的平均有效剂量与传统PSO方法的平均有效剂量相似,但是有效剂量值太大的可能性变小了。这种趋势在案例3中更加明显。具体地说,对于改进的PSO方法,高于800μSv的有效剂量值降低了25%。此外,案例3的平均有效剂量减少了约29μSv。同时,总体收敛速度不受影响。因此,通过实验和分析证明了所提出的核设施放射性环境中的路径规划方法是有效的。

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