On the sampling distribution of Allan factor estimator for a homogeneous Poisson process and its use to test inhomogeneities at multiple scales

The Allan factor (AF) is a statistic widely used to assess if the rate of occurrences of an event tends to cluster and show persistence in a range of space and/or time scales. For a homogeneous Poisson process, the relationship between AF and the space/time is expected to be constant, thus denoting the lack of clustering and persistence in the occurrence process. However, in time series analysis, conclusions about the persistence of the underlying process have been usually drawn by visual inspection of the diagrams of AF estimates versus scale, without applying any formal statistical test. This study investigates the sampling distribution function of the AF estimator when the underlying process is homogeneous Poissonian. Monte Carlo simulations show that the distribution of the AF estimator is described by a gamma distribution whose mean and variance can be deduced by the delta method. Therefore, the derived analytical distribution of the AF estimator can be used to build a formal statistical test to evaluate the significance of the AF fluctuation against the Poissonian hypothesis across a range of space/time scales. As an example, we apply the AF-based test to analyse the time series of the number of rainfall observations exceeding fixed high thresholds in order to study the properties of the rate of occurrence of the extreme values over a wide range of time scales.     

充模过程中熔接痕的改进光滑粒子动力学方法模拟与预测

提出了一种黏弹性流体的改进光滑粒子动力学(SPH)方法以试探性地模拟和预测黏弹性FENE-P熔体充模过程中熔接痕的形态演化. 首先基于SPH方法建立了聚合物流动的宏微观耦合模型, 同时提出了黏弹性流体的改进SPH离散格式. 随后, 通过模拟一些基准算例验证了改进的SPH方法模拟聚合物宏微观耦合问题的有效性及收敛性, 以及所提出的黏弹性温度模型的有效性. 最后, 模拟了环型腔内的充模过程, 试探性地展示了充模过程中微观分子的变形过程. 同时采用顺序热流道技术模拟了多浇口C形腔内的充模过程, 并与其他数值结果做比较. 数值结果表明: 对于大制件多浇口充模过程, 顺序热流道技术能够改善甚至消除充模过程中的熔接痕.