Smart prediction of liquefaction-induced lateral spreading

The prediction of liquefaction-induced lateral spreading/displacement(Dh)is a challenging task for civil/geotechnical engineers.In this study,a new approach is proposed to predict Dh using gene expression programming(GEP).Based on statistical reasoning,individual models were developed for two topographies:free-face and gently sloping ground.Along with a comparison with conventional approaches for predicting the Dh,four additional regression-based soft computing models,i.e.Gaussian process regression(GPR),relevance vector machine(RVM),sequential minimal optimization regression(SMOR),and M5-tree,were developed and compared with the GEP model.The results indicate that the GEP models predict Dh with less bias,as evidenced by the root mean square error(RMSE)and mean absolute error(MAE)for training(i.e.1.092 and 0.815;and 0.643 and 0.526)and for testing(i.e.0.89 and 0.705;and 0.773 and 0.573)in free-face and gently sloping ground topographies,respectively.The overall performance for the free-face topology was ranked as follows:GEP>RVM>M5-tree>GPR>SMOR,with a total score of 40,32,24,15,and 10,respectively.For the gently sloping condition,the performance was ranked as follows:GEP>RVM>GPR>M5-tree>SMOR with a total score of 40,32,21,19,and 8,respectively.Finally,the results of the sensitivity analysis showed that for both free-face and gently sloping ground,the liquefiable layer thickness(T_(15))was the major parameter with percentage deterioration(%D)value of 99.15 and 90.72,respectively.

Spreading speed of a food-limited population model with delay

This paper is concerned with the spreading speed of a food-limited population model with delay.First,the existence of the solution of Cauchy problem is proved.Then,the spreading speed of solutions with compactly supported initial data is investigated by using the general Harnack inequality.Finally,we present some numerical simulations and investigate the dynamical behavior of the solution.

Prospect Theory Based Individual Irrationality Modelling and Behavior Inducement in Pandemic Control

Understanding and modeling individuals’behaviors during epidemics is crucial for effective epidemic control.However,existing research ignores the impact of users’irrationality on decision-making in the epidemic.Meanwhile,existing disease control methods often assume users’full compliance with measures like mandatory isolation,which does not align with the actual situation.To address these issues,this paper proposes a prospect theorybased framework to model users’decision-making process in epidemics and analyzes how irrationality affects individuals’behaviors and epidemic dynamics.According to the analysis results,irrationality tends to prompt conservative behaviors when the infection risk is low but encourages risk-seeking behaviors when the risk is high.Then,this paper proposes a behavior inducement algorithm to guide individuals’behaviors and control the spread of disease.Simulations and real user tests validate our analysis,and simulation results show that the proposed behavior inducement algorithm can effectively guide individuals’behavior.

Simulation modelling of potato virus Y spread in relation to initial inoculum and vector activity

Potato virus Y(PVY)is a non-persistent virus that is transmitted by many aphid species and causes significant damage to potato production.We constructed a spatially-explicit model simulating PVY spread in a potato field and used it to investigate possible effects of transmission efficiency,initial inoculum levels,vector behavior,vector abundance,and timing of peak vector activity on PVY incidence at the end of a simulated growing season.Lower PVY incidence in planted seed resulted in lower virus infection at the end of the season.However,when populations of efficient PVY vectors were high,significant PVY spread occurred even when initial virus inoculum was low.Non-colonizing aphids were more important for PVY spread compared to colonizing aphids,particularly at high densities.An early-season peak in the numbers of noncolonizing aphids resulted in the highest number of infected plants in the end of the season,while mid-and late-season peaks caused relatively little virus spread.Our results highlight the importance of integrating different techniques to prevent the number of PVY-infected plants from exceeding economically acceptable levels instead of trying to control aphids within potato fields.Such management plans should be implemented very early in a growing season.

Modelling of the spread of a potential invasive pest,the Siberian moth (Dendrolimus sibiricus) in Europe

Background： The Siberian moth （Dendrolimus sibiricus） （SM） defoliates several tree species from the genera Larix, Piceo and Abies in northern Asia, east of the Urals. The SM is a potential invasive forest pest in Europe because Europe has several suitable host species and climatic conditions of central and northern Europe are favourable for the SM. Methods： This study developed a grid-based spatio-temporal model for simulating the spread of the SM in case it enters Europe from Russia via border stations. The spread rate was modeled as a function of the spatial distribution of host species, climatic suitability of different locations for the SM, human population density, transportation of moth-carrying material, and flying of moths from tree to tree. Results and conclusions： The simulations showed that the SM is most likely to spread in the forests of northeast Belarus, the Baltic countries, and southern and central Finland. Climatic conditions affected the occurrence of the SM more than human population density and the coverage of suitable host species.

An Overview on Opinion Spreading Model

Research on opinion spreading has received more and more attention in recent years. This paper focus on make a summary of opinion evolution researches, we first review some classical opinion models, and then introduce the existing result of improvement models from the aspect of opinion space, model parameter, social network and so on. The current study’s limitation and further research are also prospected at the end. By in-depth understand the opinion spreading mechanism so as to guide and control the public opinions, which is very useful and meaningful.

Attention-Based and Time Series Models for Short-Term Forecasting of COVID-19 Spread

The growing number of COVID-19 cases puts pressure on healthcare services and public institutions worldwide.The pandemic has brought much uncertainty to the global economy and the situation in general.Forecasting methods and modeling techniques are important tools for governments to manage critical situations caused by pandemics,which have negative impact on public health.The main purpose of this study is to obtain short-term forecasts of disease epidemiology that could be useful for policymakers and public institutions to make necessary short-term decisions.To evaluate the effectiveness of the proposed attention-based method combining certain data mining algorithms and the classical ARIMA model for short-term forecasts,data on the spread of the COVID-19 virus in Lithuania is used,the forecasts of epidemic dynamics were examined,and the results were presented in the study.Nevertheless,the approach presented might be applied to any country and other pandemic situations.The COVID-19 outbreak started at different times in different countries,hence some countries have a longer history of the disease with more historical data than others.The paper proposes a novel approach to data registration and machine learning-based analysis using data from attention-based countries for forecast validation to predict trends of the spread of COVID-19 and assess risks.

Demage Spreading in the Ising Model with a special Metropolis Dynamics Approach

The time evolution of the Hamming distance (damage spreading) for the and Ising models on the square lattice is performed with a special metropolis dynamics algorithm. Two distinct regimes are observed according to the temperature range for both models: a low-temperature one where the distance in the long-time limit is finite and seems not to depend on the initial distance and the system size; a high-temperature one where the distance vanishes in the long-time limit. Using the finite size scaling method, the dynamical phase transition (damage spreading transition) temperature is obtained as for the Ising model.

Simulation of Spread of Infectious Diseases and Population Mobility in a Deterministic Epidemic Patch Model

Computer simulation models are widely applied in various areas of the health care sector, including the spread of infectious diseases. Patch models involve explicit movements of people between distinct locations. The aim of the present work has been designed and explored a patch model with population mobility between different patches and between each patch and an external population. The authors considered a SIR （susceptible-infected-recovered） scheme. The model was explored by computer simulations. The results show how endemic levels are reached in all patches of the system. Furthermore, the performed explorations suggest that the people mobility between patches, the immigration from outside the system and the infection rate in each patch, are factors that may influence the dynamics of epidemics and should be considered in health policy planning.

Modelling the spread of sexually transmitted diseases on scale-free networks

In this paper a new model for the spread of sexually transmitted diseases （STDs） is presented. The dynamic behaviors of the model on a heterogenons scale-free （SF） network are considered, where the absence of a threshold on the SF network is demonstrated, and the stability of the disease-free equilibrium is obtained. Three immunization strategies, uniform immunization, proportional immunization and targeted immunization, are applied in this model. Analytical and simulated results are given to show that the proportional immunization strategy in the model is effective on SF networks.

Modeling the spread of hot-rolled Ni-based alloy plates

The width spread of Ni-based alloy plates in the rolling process is studied. An equation for describing therolling spread of Ni-based alloy plate is proposed based on production data and the Bachtinow equation, which cannot fully account for the compositional variability of Ni-based alloys. To address this, a new coefficient for alloying is added to the equation based on production data. By adding alloying coefficients, it is possible to improve the prediction accuracy for the rolling spread of Ni-based alloy plates and thus better control the width of the rolling spread of different steel grades.

Steady-State Analysis of SECIR Rumor Spreading Model in Complex Networks

In this paper, the SECIR rumor spreading model is formulated and analyzed, in which the social education level and the counterattack mechanism are taken into consideration. The results show that improving education level and increasing the ratio of counter are effective in reducing the risk of rumor propagation and enhancing the resistance to rumor propagation.

Mathematical Modeling of Crown Forest Fire Spread

Mathematical model of forest fire was based on an analysis of known experimental data and using concept and methods from reactive media mechanics. In this paper the assignment and theoretical investigations of the problems of crown forest fire spread in windy condition were carried out. In this context, a study—mathematical modeling—of the conditions of forest fire spreading that would make it possible to obtain a detailed picture of the change in the temperature and component concentration fields with time, and determine as well as the limiting condition of fire propagation in forest with fire break.

Temperature-Dependent Newtonian Rheology in Advection-Convection Geodynamical Model for Plate Spreading in Eastern Volcanic Zone, Iceland

Geodynamic process as advection-convection of the Mid-Atlantic Ocean Ridge (MAR), that is exposed on land in Iceland is investigated. Advection is considered for the plate spreading velocity. Geodetic GPS data during 2000-2010 is used to estimate plate spreading velocity along a profile in the Eastern Volcanic Zone (EVZ), Iceland striking N102。E, approximately parallel to the NUVEL-1A spreading direction between the Eurasian and North American plates. To predict subsurface mass flow patterns, temperature-dependent Newtonian rheology is considered in the finite-element models (FEM). All models are considered 2-D with steady-state, incompressible rheology whose viscosity depends on the subsurface temperature distribution. The thickness of lithosphere along the profile in the EVZ is identified by 700。C isotherm and 1022 Pa s iso-viscosity, those reach 50 ± 3 km depth at distance of 100 km from rift axis. Geodetic observation and model prediction results show the ~90% of spreading is accommodated within ~45 km of the rift axis in each direction. Model predicts ~8.5 mm.yr-1 subsidence at the surface of rift center when magmatic plumbing is inactive. The rift center (the highest magmatic influx is ~11 mm.yr-1) in model shifts ~10 - 20 km west to generate observed style surface deformation. The spreading velocity, isotherm and depth of isotherm are the driving forces resulting in the surface deformation. These three parameters have more or less equal weight. However, as the center of deformation in the EVZ shifts and most of the subsidence takes place in the volcanic system that is currently the active which is the located of plate axis.

Modified Ceiling Bounce Model for Computing Path Loss and Delay Spread in Indoor Optical Wireless Systems

This paper proposes modifications to the tradional Ceiling Bounce Model and uses it to characterize diffuse indoor optical wireless channel by analyzing the effect of transceiver position on signal propagation properties. The modified approach uses a combination of the tradional ceiling bounce method and a statistical approach. The effects of different transmitter-receiver separations and height of the ceiling on path loss and delay spread are studied in detail.

Utilization of Oil Properties to Develop a Spreading Rate Regression Model for Nigerian Crude Oil

The target of this study is to develop a spreading rate regression model capable of predicting rate of spread of Nigerian crude oil spills on water. The major factors responsible for spreading rate of crude oil on water were considered, namely surface tension, viscosity, and specific gravity/American Petroleum Institute degree (0API), all at specified temperature values. The surface tension, viscosity and density parameters were interactively measured under controlled factorial analysis. The spreading rate of each crude oil was determined by artificially spilling them on laboratory calm/stagnant water in a rectangular tank and their averages were also computed. These averages were used to develop a regression model equation for spreading rate. The model developed indicated that an average spreading rate was 3.3528 cm/s at 37.5°C and the predictive regression model is evaluated with the interactions of specific gravity, viscosity and surface tension. It is convenient to state that the model will predict the spread rate of crude oils which possess imputed physicochemical properties having pour point averaged 15.5°C on calm seawater.

The Mathematical Model of Short-Term Forest Fire Spread

In this paper, we establish a mathematical model of the forest fire spread process based on a partial differential equation. We describe the distribution of time field and velocity field in the whole two-dimensional space by vector field theory. And we obtain a continuous algorithm to predict the dynamic behavior of forest fire spread in a short time. We use the algorithm to interpolate the fire boundary by cubic non-uniform rational B-spline closed curve. The fire boundary curve at any time can be simulated by solving the Eikonal equation. The model is tested in theory and in practice. The results show that the model has good accuracy and stability, and it’s compatible with most of the existing models, such as the elliptic model and the cellular automata model.

Simulation and Experimental Research on Liquid Spreading in a Wire-Sawn Kerf

The significance of liquids in abrasive wire sawing has been demonstrated in several studies.However,the perfor-mance of its spreading behavior is limited by the current development trend,where the wafer has a larger area and the kerf is narrower.Moreover,there are very few studies on the liquid spreading behavior in wire-sawn kerfs.Therefore,a 3D CFD(computational fluid dynamics)model is presented in this paper and used to simulate the liquid spreading behavior in a kerf based on a VOF(volume of fluid)method with a CSF(continuum surface force)model,which is used to simulate multiphase flow,and an empirical correlation for characterizing the liquid dynamic contact angle using UDF(user defined functions).Subsequently,parametric simulations are performed on the kerf area,kerf width,liquid viscosity,liquid surface tension,and liquid velocity at the inlet area of the kerf,and verification experi-ments are conducted to determine the validity of the simulation model.From the simulation and experimental results,three typical liquid spreading regimes that exhibit different effects on wire sawing in the kerfs are found,and their limiting conditions are identified using non-dimensional analysis.Subsequently,a prediction model is pro-posed for the liquid spreading regime based on a set of Weber and Capillary numbers.For wire sawing,an increase in the wafer area does not change the liquid spreading regime in the kerf;however,a reduction in the kerf width sig-nificantly hinders the liquid spreading behavior.Thereby,the spreading regime can be effectively converted to facili-tate wire sawing by adjusting the physical properties and supply conditions of the liquid.

森林火灾中使用细水雾进行灭火仿真方法研究

森林火灾作为一种极具危害性的自然灾害,其发生和蔓延过程通常受到气候、地形、植被、可燃物等多种复杂因素的影响,导致很难准确地对森林火灾的蔓延与灭火过程进行仿真。对森林火灾的蔓延和细水雾灭火过程进行物理建模,蔓延模型采用树形模块结构来模拟树木燃烧的热解反应,并考虑了温度、风场、质量损失率等因素对树木燃烧蔓延的影响。在使用细水雾进行灭火仿真实验时,重点关注细水雾穿透火焰区域形成水膜以及水分蒸发导致的灭火作用,从而阻止森林火灾的蔓延,成功实现了交互灭火的仿真平台,可以让用户沉浸式地体验森林火灾的蔓延过程,并通过水枪、消防车和无人机进行细水雾灭火仿真实验。该研究成果对消防仿真领域方面的应用具有重要意义。

重庆两场森林火灾蔓延特征的数值模拟

为了深入认识同时段内发生的两场森林火灾蔓延特征以及大气、地形等对不同林火行为的影响,进而为多起林火扑灭火工作提供科学支撑,选取2022年8月17日发生在涪陵两场森林火灾,利用高分辨率地理信息、植被数据和气象数据对两场林火行为进行分析研究,同时运用林火大气耦合WRF-Fire(Weather Research and Forecasting Model with Fire Module)模式进行数值模拟。研究发现:①受深厚高压控制,两场林火是在持续高温、干燥背景下发生的,气象干旱等级达到重旱,火险气象等级高。②模式模拟风向风速变化与实况较为一致,基本体现出火场风向和风速突变,表明WRF-Fire模式可以较准确地再现火场蔓延情况。③基于林火蔓延特征时间和空间变化可将大梁山林火发展分为6个阶段、北山坪林火分为4个阶段,造成直线距离相隔4.4 km两个火场蔓延发展程度不同的原因在于地形差异造成的局地风场差异。