Tracking methods are used in particle transport Monte Carlo simulations to simulate the particle movements in models with multiple materials. However, as Monte Carlo simulations are becoming increasingly sophisticated, the most widely used tracking method, ray-tracing, exposes serious disadvantages in dealing with continuously varying materials and needs to be improved. Delta-tracking, the most common alternative, is not stable enough as its efficiency strongly depends on the models. After comparing the two methods, this paper presents an improved tracking method called hybrid-tracking that integrates the advantages of these two tracking methods. Hybrid-tracking significantly improves the computational efficiency by merging cells in complex geometric models. For the model in this paper, the time cost of cross-boundary judgments is significantly lower using hybrid-tracking with the computational efficiency increasing by 20%. Hybrid-tracking is then used in an advanced on-the-fly cross-section temperature treatment—Target Motion Sample (TMS) method, after the biasness of TMS method in ray-tracing is proved. Hybrid-tracking method extends the application range of the TMS method from a single material to multiple materials. The efficiency and validity of the TMS method in hybrid-tracking are illustrated using the VERA benchmark Problem 3A. These methods are easily implemented in the Monte Carlo codes based on ray-tracing and are compatible with the original functions.

粒子传输蒙特卡洛模拟中使用了跟踪方法，以模拟具有多种材料的模型中的粒子运动。但是，随着蒙特卡洛模拟变得越来越复杂，最广泛使用的跟踪方法（光线跟踪）在处理连续变化的材料时暴露出严重的缺点，需要加以改进。Delta跟踪是最常见的替代方法，它的效率在很大程度上取决于模型，因此不够稳定。在比较这两种方法之后，本文提出了一种改进的跟踪方法，称为混合跟踪，它结合了这两种跟踪方法的优点。混合跟踪通过合并复杂几何模型中的单元大大提高了计算效率。对于本文中的模型，使用混合跟踪时，跨边界判断的时间成本大大降低，计算效率提高了20％。在证明了TMS方法在光线跟踪中的偏差之后，将混合跟踪用于先进的动态横截面温度处理-目标运动样本（TMS）方法。混合跟踪方法将TMS方法的应用范围从单一材料扩展到了多种材料。使用VERA基准测试问题3A说明了TMS方法在混合跟踪中的效率和有效性。这些方法很容易在基于光线跟踪的蒙特卡洛代码中实现，并且与原始功能兼容。在证明了TMS方法在光线跟踪中的偏差之后，将混合跟踪用于先进的动态横截面温度处理-目标运动样本（TMS）方法。混合跟踪方法将TMS方法的应用范围从单一材料扩展到了多种材料。使用VERA基准测试问题3A说明了TMS方法在混合跟踪中的效率和有效性。这些方法很容易在基于光线跟踪的蒙特卡洛代码中实现，并且与原始功能兼容。在证明了TMS方法在光线跟踪中的偏差之后，将混合跟踪用于先进的动态横截面温度处理-目标运动样本（TMS）方法。混合跟踪方法将TMS方法的应用范围从单一材料扩展到了多种材料。使用VERA基准测试问题3A说明了TMS方法在混合跟踪中的效率和有效性。这些方法很容易在基于光线跟踪的蒙特卡洛代码中实现，并且与原始功能兼容。使用VERA基准测试问题3A说明了TMS方法在混合跟踪中的效率和有效性。这些方法很容易在基于光线跟踪的蒙特卡洛代码中实现，并且与原始功能兼容。使用VERA基准测试问题3A说明了TMS方法在混合跟踪中的效率和有效性。这些方法很容易在基于光线跟踪的蒙特卡洛代码中实现，并且与原始功能兼容。