Nuclear magnetic resonance(NMR) microscopic simulation based on random-walk: Theory and parameters analysis

The microscopic response characteristics of nuclear magnetic resonance(NMR) are widely used for characterizing complex pore structures of rocks. Due to the prohibitive NMR experiment cost, numerical simulation was employed as an alternative approach to verify some theoretical aspects of NMR responses. Firstly, the basic principles of pore-scale NMR simulation based on random-walk method(RWM) were introduced. The RWM-simulated results were benchmarked with the analytical results for an ideal spherical pore model. Then, the effects of two numerical parameters, namely diffusion radius and walk numbers, were studied on the simulation accuracy. The simulation method is then applied to various pore models with different pore sizes and pore shapes filled with different fluids to study the microscopic NMR response characteristics. The numerical experiments are useful for understanding and interpreting NMR measurements and the simulation code provides a numerical tool to perform pixel-based digital rock analysis.

One-step random-walk process of nanoparticles in cement-based materials

Efficient modelling approaches capable of predicting the behavior and effects of nanoparticles in cement-based materials are required for conducting relevant experiments.From the microstructural characterization of a cement-nanoparticle system,this paper investigates the potential of cell-based weighted random-walk method to establish statistically significant relationships between chemical bonding and diffusion processes of nanoparticles within cement matrix.LaSr_(0.5)C_(0.5)O_(3)(LSCO)nanoparticles were employed to develop a discrete event system that accounts for the behavior of individual cells where nanoparticles and cement components were expected to interact.The stochastic model is based on annihilation(loss)and creation(gain)of a bond in the cell.The model considers both chemical reactions and transport mechanism of nanoparticles from cementitious cells,along with cement hydration process.This approach may be useful for simulating nanoparticle transport in complex 2D cement-based materials systems.

基于随机行走介数的级联失效模型

将随机行走介数引入级联失效模型,提出了基于随机行走介数的级联失效模型,该模型较基于介数的级联失效模型更加符合实际情况。为了研究该模型的特性,针对无标度网络和随机网络,运用仿真方法,将其与基于介数的级联失效模型进行了比较。通过对两组共4个无标度网络模型和两个随机网络模型的仿真,发现基于随机行走介数的级联失效模型的节点介数相对较小,不同节点间介数大小的差距也较小,并分析了得到上述仿真结果的原因。

An Improved Walk Model for Train Movement on Railway Network

In this paper, we propose an improved walk model for simulating the train movement on railway network. In the proposed method, walkers represent trains. The improved walk model is a kind of the network-based simulation analysis model. Using some management rules for walker movement, walker can dynamically determine its departure and arrival times at stations. In order to test the proposed method, we simulate the train movement on a part of railway network. The numerical simulation and analytical results demonstrate that the improved model is an effective tool for simulating the train movement on railway network. Moreover, it can well capture the characteristic behaviors of train scheduling in railway traffic.

Bayesian Computation for the Parameters of a Zero-Inflated Cosine Geometric Distribution with Application to COVID-19 Pandemic Data

A new three-parameter discrete distribution called the zero-inflated cosine geometric(ZICG)distribution is proposed for the first time herein.It can be used to analyze over-dispersed count data with excess zeros.The basic statistical properties of the new distribution,such as the moment generating function,mean,and variance are presented.Furthermore,confidence intervals are constructed by using the Wald,Bayesian,and highest posterior density(HPD)methods to estimate the true confidence intervals for the parameters of the ZICG distribution.Their efficacies were investigated by using both simulation and real-world data comprising the number of daily COVID-19 positive cases at the Olympic Games in Tokyo 2020.The results show that the HPD interval performed better than the other methods in terms of coverage probability and average length in most cases studied.

Construction of Clonal Growth Models in Trifolium repens

The suitability of models for describing the clonal growth of Trifolium repens population was discussed. The results showed that deterministic models were inadequate for describing its clonal growth, but the diffusion models and the randomwalk models suited for the clonal growth characteristics of the population. And it was found that random-walk models were better than diffusion models for describing a population in an environment with rich natural resources, and the latter was better in a poor environment.

Effect of Correlations on the Exponents for the Power-Law Distributions in Self-Organized Criticality

The origin of power-law distributions in self-organized criticality is investigated by treating the variation of the number of active sites in the system as a stochastic process. An avalanche is mapped to a first-return random-walk process in a one-dimensional lattice. In order to understand the reason of variant exponents for the power-law distributions in different self-organized critical systems, we introduce the correlations among evolution steps. Power-law distributions of the lifetime and spatial size are found when the random walk is unbiased with equal probability to move in opposite directions. It is found that the longer the correlation length, the smaller values of the exponents for the power-law distributions.