A novel 4D resolution imaging method for low and medium atomic number objects at the centimeter scale by coincidence detection technique of cosmic-ray muon and its secondary particles

The muon radiography imaging technique for high-atomic-number objects(Z) and large-volume objects via muon transmission imaging and muon multiple scattering imaging remains a popular topic in the field of radiation detection imaging. However, few imaging studies have been reported on low and medium Z objects at the centimeter scale. This paper presents an imaging system that consists of three layers of a position-sensitive detector and four plastic scintillation detectors. It acquires data by co...     

Hydrogen storage comparison of M doped vanadium oxide nanotubes (M = Mo,Zr and W): A molecular simulation study

Zr, Mo and W doped Vanadium oxide nanotube were considered as remarkable materials for hydrogen storage applications. Monte Carlo molecular simulation was performed to study the adsorption behavior of hydrogen molecules on Vanadium oxide nanotubes (VONTs). The effects of temperature, pressure and mole percent of hydrogen on adsorption capacity of VONTs were investigated to provide deep insight of adsorption behavior. The results represented that hydrogen adsorption is an increasing function of pressure and at about 50 MPa all three metal doped VONT has maximum hydrogen capacity. At 5 MPa and room temperature, the hydrogen capacities of Mo, W and Zr doped VONTs were 1.39, 0.88 and 1.43 w% respectively. With temperature increment up to room temperature, more reduction in initial hydrogen capacity were observed in Mo and Zr doped VONTs.Evaluating hydrogen adsorption of Zr doped VONT from pure and hydrogen /nitrogen mixtures at 300 K indicated that under 2 Mpa, modifications in adsorption capacities were insignificant after N2 addition to the environment. Therefore, Zr doped VONT in hydrogen /nitrogen mixture environment can act as a capable adsorbent for Hydrogen storage system in comparison with Mo and W doped VONTs.     

Data quality and uncertainty assessment methodology for pavement LCA

In performing pavement life cycle assessment (LCA), users are facing various reports of energy intensity coefficient (EIC) of pavement materials which differ considerably among data sources and therefore alter the LCA results significantly. Instead of selecting a certain EIC without or of little explanation for the current pavement LCA practices, this study proposed a methodology to build probability density function (PDF) for EIC based on available data-set and their qualities. Each data was first evaluated about the data quality indicator (DQI) through data quality pedigree matrix and converted to PDF in modified Beta distribution form. Three weighting methods, the DQI one, coefficient of variation (COV) one and analytical hierarchy process (AHP) one, were developed to assign weightings for different data. Monte Carlo simulation was run with the weighted PDF of each data as input to obtain the ultimate PDF for EIC. A case study to estimate the bitumen’s EIC with eight data samples were performed using the proposed methodology. It is found (1): the estimates by the proposed methodology is of higher reliability (lower COV) compared to any single data due to utilisation of information of the overall data samples; (2) the AHP weighting method is most favoured despite the results of the three weighting methods are close; (3) the central estimates of bitumen’s EIC are between5.4~5.8 MJ/kg. The proposed methodology is helpful in aiding calculating EICs for pavement materials and capturing uncertainties in LCA results in a statistical sense.     

γ辐照加工用新型工作模体设计研究

本文研究设计了一种用于获取γ辐照装置辐射场和货物剂量场真实分布的新型工作模体。基于真实γ辐照装置参数构建了有效可用的模拟辐射场，提出了新型工作模体的结构和填料设计方法。采用蒙特卡罗方法和随机填充方法（RCS）模拟计算剂量计套管材料与壁厚、填料小球尺寸、空心填料小球尺寸与壁厚、小球填充方式等影响模体剂量学性能的主要因素的分布规律。在满足计算置信度的前提下，参数优化取值范围为：套管采用壁厚为3~5 mm的铝管，对辐射场干扰不超过4.372 23%；填料选择外径为1~4 cm、壁厚为1.1~11.5 mm、材料等效性好、货物密度模拟范围为0.1~0.5 g/cm³的聚丙烯小球，对辐射场干扰不超过9.998 44%；均匀填充和随机填充模式对辐射场干扰基本持平，且均不超过10%。结果表明，当前设计可行有效，投入低、兼顾参数多且量程更宽，适合推广应用。     

Bayesian Inference for ARFIMA Models

This article develops practical methods for Bayesian inference in the autoregressive fractionally integrated moving average (ARFIMA) model using the exact likelihood function, any proper prior distribution, and time series that may have thousands of observations. These methods utilize sequentially adaptive Bayesian learning, a sequential Monte Carlo algorithm that can exploit massively parallel desktop computing with graphics processing units (GPUs). The article identifies and solves several problems in the computation of the likelihood function that apparently have not been addressed in the literature. Four applications illustrate the utility of the approach. The most ambitious is an ARFIMA(2,d,2) model for the Campito tree ring time series (length 5405), for which the methods developed in the article provide an essentially uncorrelated sample of size 16,384 from the exact posterior distribution in under four hours. Less ambitious applications take as little as 4 minutes without exploiting GPUs.     

Improved CCM for variable causality detection in complex systems

Convergent cross-mapping (CCM), has been largely implemented for variable causality detection in complex systems like chemical process. However, this method is susceptible to problems regarding parameter selection and threshold determination. The synchronization phenomenon and the Moran effect, which are two interference terms in causality detection, must also be addressed. Therefore, an improved CCM is proposed to overcome these limitations in this paper. In the improved CCM, the optimal embedding dimension is selected based on the pseudo-nearest-neighbor theory. Also, Monte Carlo simulation is adopted to evaluate the convergence threshold. Next, by using the defined time delay detection function, the synchronization phenomenon and the Moran effect are identified to reduce the interference terms and further improve the accuracy. Finally, the improved CCM method is applied in a numerical example and a hydrocracking process to demonstrate its feasibility and superior performance than other methods.     

乙苯和对二甲苯在ZSM-5分子筛上吸附的蒙特卡罗模拟

采用巨正则统计系综蒙特卡罗模拟方法研究了高温条件下乙苯和对二甲苯在不同硅铝比ZSM-5分子筛上的吸附行为，并结合工业样品的催化反应进行了验证。GCMC模拟结果表明：在不同硅铝比ZSM-5上乙苯的吸附能均高于对二甲苯，乙苯和对二甲苯的吸附位在两种孔道的交叉处，随Al含量的增加，吸附状态多样化；温度623 K下，压力在200 kPa左右时吸附量已达到平稳。催化反应评价结果表明，乙苯生成苯的反应比对二甲苯生成甲苯的反应更容易进行，与吸附扩散的规律一致。     

Monitoring process variation using modified EWMA

A new control chart, namely, modified exponentially weighted moving average (EWMA) control chart, for monitoring the process variance is introduced in this work by following the recommendations of Khan et al.¹⁵ The proposed control chart deduces the existing charts to be its special cases. The necessary coefficients, which are required for the construction of modified EWMA chart, are determined for various choices of sample sizes and smoothing constants. The performance of the proposed modified EWMA is evaluated in terms of its run length (RL) characteristics such as average RL and standard deviation of RL. The efficiency of the modified EWMA chart is investigated and compared with some existing control charts. The comparison reveals the superiority of proposal as compared with other control charts in terms of early detection of shift in process variation. The application of the proposal is also demonstrated using a real-life dataset.     

基于染色体畸变的细胞存活模型研究

为评估质子和重离子的辐射生物效应，建立了基于染色体畸变的细胞存活机理模型。开发了纳剂量生物物理蒙特卡罗模拟程序（NASIC）的DNA损伤修复模块，用于模拟不同射线类型、不同传能线密度（LET）辐射所致细胞核内染色体畸变产额。在分析辐射所致染色体畸变产额规律的基础上，建立了基于染色体畸变的细胞存活机理模型，并根据细胞存活实验数据拟合模型参数。以V79细胞为例，对于X射线和不同LET的质子，细胞存活分数的模型计算值与实验数据符合得很好，相关系数为0.985 3。采用⁴He离子的实验数据对模型及参数进行了验证，模型计算值与实验数据的相关系数为0.931 1。可见，模型能较好地区分不同射线类型、不同LET辐射在细胞致死效应上的差异。     

Magnetic properties and magnetoresistance effect of SnFe2O4 spinel nanoparticles: Experimental,ab initio and Monte Carlo simulation

In this contribution, SnFe₂O₄ nanoparticles were prepared by the solvothermal method, the structural properties were performed using X-Ray Diffraction (DRX) to prove the success of tin ferrite formation and to determine de crystals parameters. The size and morphological study were build using Scanning Electron Microscopy (SEM) and Transmission Electron microscopy (TEM), the results showed that the size of particles is uniform with a range of particles (5–7 nm). The magnetic properties were carried out using the SQUID device, the SnFe2O4 nanoparticles have a magnetic transition at 750 K. In addition, the hysteresis loops at low temperature displayed Ms and Mr equals to 23 emu/g and 6 emu/g, respectively. The magnetoresistance properties were investigated, the SnFe₂O₄ nanoparticles present a large magnetoresistance effect (80%). The experimental results are supplemented by model calculations utilizing density functional theory and Monte-Carlo simulations.