Nonlinear wave dispersion in monoatomic chains with lumped and distributed masses:discrete and continuum models

The main objective of this paper is to investigate the influence of inertia of nonlinear springs on the dispersion behavior of discrete monoatomic chains with lumped and distributed masses.The developed model can represent the wave propagation problem in a non-homogeneous material consisting of heavy inclusions embedded in a matrix.The inclusions are idealized by lumped masses,and the matrix between adjacent inclusions is modeled by a nonlinear spring with distributed masses.Additionally,the model is capable of depicting the wave propagation in bi-material bars,wherein the first material is represented by a rigid particle and the second one is represented by a nonlinear spring with distributed masses.The discrete model of the nonlinear monoatomic chain with lumped and distributed masses is first considered,and a closed-form expression of the dispersion relation is obtained by the second-order Lindstedt-Poincare method(LPM).Next,a continuum model for the nonlinear monoatomic chain is derived directly from its discrete lattice model by a suitable continualization technique.The subsequent use of the second-order method of multiple scales(MMS)facilitates the derivation of the corresponding nonlinear dispersion relation in a closed form.The novelties of the present study consist of(i)considering the inertia of nonlinear springs on the dispersion behavior of the discrete mass-spring chains;(ii)developing the second-order LPM for the wave propagation in the discrete chains;and(iii)deriving a continuum model for the nonlinear monoatomic chains with lumped and distributed masses.Finally,a parametric study is conducted to examine the effects of the design parameters and the distributed spring mass on the nonlinear dispersion relations and phase velocities obtained from both the discrete and continuum models.These parameters include the ratio of the spring mass to the lumped mass,the nonlinear stiffness coefficient of the spring,and the wave amplitude.

Modeling Analysis of Factors Influencing Wind-Borne Seed Dispersal: A Case Study on Dandelion

A weed is a plant that thrives in areas of human disturbance, such as gardens, fields, pastures, waysides, and waste places where it is not intentionally cultivated. Dispersal affects community dynamics and vegetation response to global change. The process of seed disposal is influenced by wind, which plays a crucial role in determining the distance and probability of seed dispersal. Existing models of seed dispersal consider wind direction but fail to incorporate wind intensity. In this paper, a novel seed disposal model was proposed in this paper, incorporating wind intensity based on relevant references. According to various climatic conditions, including temperate, arid, and tropical regions, three specific regions were selected to establish a wind dispersal model that accurately reflects the density function distribution of dispersal distance. Additionally, dandelions growth is influenced by a multitude of factors, encompassing temperature, humidity, climate, and various environmental variables that necessitate meticulous consideration. Based on Factor Analysis model, which completely considers temperature, precipitation, solar radiation, wind, and land carrying capacity, a conclusion is presented, indicating that the growth of seeds is primarily influenced by plant attributes and climate conditions, with the former exerting a relatively stronger impact. Subsequently, the remaining two plants were chosen based on seed weight, yielding consistent conclusion.

Assessing the Impact of Fugitive Dust Emissions from Cement Silos at Cluster of Concrete Batching Facilities Using Air Dispersion Modeling

This research assessed the environmental impact of cement silos emission on the existing concrete batching facilities in M35-Mussafah, Abu Dhabi, United Arab Emirates. These assessments were conducted using an air quality dispersion model (AERMOD) to predict the ambient concentration of Portland Cement particulate matter less than 10 microns (PM10) emitted to the atmosphere during loading and unloading activities from 176 silos located in 25 concrete batching facilities. AERMOD was applied to simulate and describe the dispersion of PM10 released from the cement silos into the air. Simulations were carried out for PM10 emissions on controlled and uncontrolled cement silos scenarios. Results showed an incremental negative impact on air quality and public health from uncontrolled silos emissions and estimated that the uncontrolled PM10 emission sources contribute to air pollution by 528958.32 kg/Year. The modeling comparison between the controlled and uncontrolled silos shows that the highest annual average concentration from controlled cement silos is 0.065 μg/m3, and the highest daily emission value is 0.6 μg/m3;both values are negligible and will not lead to significant air quality impact in the entire study domain. However, the uncontrolled cement silos’ highest annual average concentration value is 328.08 μg/m3. The highest daily emission average value was 1250.09 μg/m3;this might cause a significant air pollution quality impact and health effects on the public and workers. The short-term and long-term average PM10 pollutant concentrations at these receptors predicted by the air dispersion model are discussed for both scenarios and compared with local and international air quality standards and guidelines.

Simulating Urban Flow and Dispersion in Beijing by Coupling a CFD Model with the WRF Model

The airflow and dispersion of a pollutant in a complex urban area of Beijing, China, were numerically examined by coupling a Computational Fluid Dynamics （CFD） model with a mesoscale weather model. The models used were Open Source Field Operation and Manipulation （OpenFOAM） software package and Weather Research and Forecasting （WRF） model. OpenFOAM was firstly validated against wind-tunnel experiment data. Then, the WRF model was integrated for 42 h starting from 0800 LST 08 September 2009, and the coupled model was used to compute the flow fields at 1000 LST and 1400 LST 09 September 2009. During the WRF-simulated period, a high pressure system was dominant over the Beijing area. The WRF-simulated local circulations were characterized by mountain valley winds, which matched well with observations. Results from the coupled model simulation demonstrated that the airflows around actual buildings were quite different from the ambient wind on the boundary provided by the WRF model, and the pollutant dispersion pattern was complicated under the influence of buildings. A higher concentration level of the pollutant near the surface was found in both the step-down and step-up notches, but the reason for this higher level in each configurations was different： in the former, it was caused by weaker vertical flow, while in the latter it was caused by a downward-shifted vortex. Overall, the results of this study suggest that the coupled WRF-OpenFOAM model is an important tool that can be used for studying and predicting urban flow and dispersions in densely built-up areas.

A Microscale Model for Air Pollutant Dispersion Simulation in Urban Areas： Presentation of the Model and Performance over a Single Building

A microscale air pollutant dispersion model system is developed for emergency response purposes. The model includes a diagnostic wind field model to simulate the wind field and a random-walk air pollutant dispersion model to simulate the pollutant concentration through consideration of the influence of urban buildings. Numerical experiments are designed to evaluate the model＇s performance, using CEDVAL （Compilation of Experimental Data for Validation of Microscale Disper- sion Models） wind tunnel experiment data, including wind fields and air pollutant dispersion around a single building. The results show that the wind model can reproduce the vortexes triggered by urban buildings and the dispersion model simulates the pollutant concentration around buildings well. Typically, the simulation errors come from the determination of the key zones around a building or building cluster. This model has the potential for multiple applications; for example, the prediction of air pollutant dispersion and the evaluation of environmental impacts in emergency situations; urban planning scenarios; and the assessment of microscale air quality in urban areas.

Comparison between the Chinese EIA Guidelines for Air Dispersion Modelling and the Advanced Air Dispersion Model ADMS

This paper makes comparisons between Chinese Environmental Impact Assessment (EIA) Guidelines for Air dispersion modelling and the advanced air dispersion model ADMS. Since 2001 the ADMS model has been the first and only foreign model that has been approved by the Appraisal Center for Environment and Engineering (ACEE) to be used in EIA projects in China (http://www.china-eia. com/inden_content/rjrz/ rjrz_ADMS/htm). In the paper the following sections provide brief descriptions of the main features of the Chinese Guidelines for Air Dispersion (Section 2) and ADMS (Section 3); Section 4 provides a comparison of the two modelling methods for some simple cases and conclusions and discussion are given in Section 5.

Using the OSPM Model on Pollutant Dispersion in an Urban Street Canyon

An observational campaign was conducted in the street canyon of Zhujiang Road in Nanjing city in 2007. Hourly mean concentrations of PM10 were measured at street and roof levels. The Operational Street Pollution Model （OSPM） street canyon dispersion model was used to calculate the street concentrations and the results were compared with the measurements. The results show that there is good agreement between measured and predicted concentrations. The correlation coefficient R2 values （R2 is a measure of the correlation of the predicted and measured time series of concentrations） are 0.5319, 0.8044, and 0.6630 for the scatter plots of PM10 corresponding to light wind speed conditions, higher wind speed conditions, and all wind speed conditions, respectively. PM10 concentrations tend to be smaller for the higher wind speed cases and decrease rapidly with increasing wind speed. The presentations of measured and modelled concentration dependence on wind direction show fairly good agreement. PM10 concentrations measured on the windward side are relatively smaller, compared with the corresponding results for the leeward side. This study demonstrates that it is possible to use the OSPM to model PM10 dispersion rules for an urban street canyon.

Random walk modeling of wake dispersion for the exhaust tower of an underground tunnel in urban area

In this paper, some experimental studies on the impact of effluent from an exhaust tower of an underground tunnel with special construction are reported. By measuring the flow field downstream of the tower in NJU meteorological wind tunnel, some flow characteristics in the make area were established. Based on these, an advanced random\|walk dispersion model was set up and applied successfully to the simulation of dispersion in the wake area. The modelling results were in accordance with wind tunnel measurements. The computed maximum of ground surface concentration in the building case was a factor of 3-4 higher than that in the flat case and appeared much closer to the source. The simulation indicated that random walk modelling is an effective and practical tool for the wake stream impact assessment.

TESTING FOR VARYING DISPERSION OF LONGITUDINAL BINOMIAL DATA IN NONLINEAR LOGISTIC MODELS WITH RANDOM EFFECTS

In this paper, it is discussed that two tests for varying dispersion of binomial data in the framework of nonlinear logistic models with random effects, which are widely used in analyzing longitudinal binomial data. One is the individual test and power calculation for varying dispersion through testing the randomness of cluster effects, which is extensions of Dean(1992) and Commenges et al (1994). The second test is the composite test for varying dispersion through simultaneously testing the randomness of cluster effects and the equality of random-effect means. The score test statistics are constructed and expressed in simple, easy to use, matrix formulas. The authors illustrate their test methods using the insecticide data (Giltinan, Capizzi & Malani (1988)).

Modeling on Residence Time Distribution in Subsurface Flow Constructed Wetlands by Multi Flow Dispersion Model

As an important design factor for constructed wetlands,hydraulic retention time and its distribution will affect the treatment performance.Instantaneously injected sodium chloride tracers were used to obtain residence time distributions of the lab scale subsurface flow constructed wetland.Considering the presence of trailing and multiple peaks of the tracer breakthrough curve,the multi flow dispersion model(MFDM)was used to fit the experimental tracer breakthrough curves.According to the residual sum of squares and comparison between the experimental values and simulated values of the tracer concentration,MFDM could fit the residence time distribution(RTD)curve satisfactorily,the results of which also reflected the layered structure of wetland cells,thus to give reference for application of MFDM to the same kind of subsurface flow constructed wetlands.

A Dynamic Bayesian-Based Comprehensive Trust Evaluation Model for Dispersed Computing Environment

Dispersed computing is a new resourcecentric computing paradigm.Due to its high degree of openness and decentralization,it is vulnerable to attacks,and security issues have become an important challenge hindering its development.The trust evaluation technology is of great significance to the reliable operation and security assurance of dispersed computing networks.In this paper,a dynamic Bayesian-based comprehensive trust evaluation model is proposed for dispersed computing environment.Specifically,in the calculation of direct trust,a logarithmic decay function and a sliding window are introduced to improve the timeliness.In the calculation of indirect trust,a random screening method based on sine function is designed,which excludes malicious nodes providing false reports and multiple malicious nodes colluding attacks.Finally,the comprehensive trust value is dynamically updated based on historical interactions,current interactions and momentary changes.Simulation experiments are introduced to verify the performance of the model.Compared with existing model,the proposed trust evaluation model performs better in terms of the detection rate of malicious nodes,the interaction success rate,and the computational cost.

Inversion of dispersion coeffcient in water quality model using optimal perturbation algorithm

As a primary parameter in the water quality model for shallow bays, the dispersion coefficient is traditionally determined with a trial-and-error method, which is time-consuming and requires much experience. In this paper, based on the measured data of chemical oxygen demand （COD）, the dispersion coefficient is calculated using an inversion method. In the process, the regularization method is applied to treat the ill-posedness, and an operator identity perturbation method is used to obtain the solu- tion. Using the model with an inverted dispersion coefficient, the distributions of COD, inorganic nitrogen （IN）, and inorganic phosphorus （IP） in Bohai Bay are predicted and compared with the measured data. The results indicate that the method is feasible and the inverted dispersion coefficient can be used to predict other pollutant distribution. This method may also be further extended to the inversion of other parameters in the water quality model.

Derivation the Schemes of Lateral and Vertical Dispersion Parameters: Application in Gaussian Plume Model

The main objective of this paper is to estimate the plume dispersion parameters in lateral direction (σy) and vertical direction (σz) by using power law wind speed and the scheme of eddy diffusivity in unstable condition. Comparison among our model and algebraic [1] and integral [2] formulations were held. We find that our model and two other models are in agreement with observed data.

Review of Air Dispersion Modelling Approaches to Assess the Risk of Wind-Borne Spread of Foot-and-Mouth Disease Virus

Foot-and-mouth disease virus (FMDV) is one of the most economically serious veterinary pathogens due to its negative effects on livestock and its highly infectious nature via a variety of transmission paths through oral and inhalation routes. Measures to enhance outbreak management can be designed according to analytical results predicted by mathematical models for wind-borne dispersion, an important path of virus transmission. Accurate atmospheric dispersion models are useful tools for properly determining risk management plans, while inaccurate models may conversely lead to accidental loss in two possible ways. Overly strict measures, e.g., slaughter for too wide an area, can cause severe economic difficulties, including irreversible loss of business operations for a number of farms. On the contrary, inestimable loss potentially caused by lax controls is a persistent threat. In this paper, available modelling procedures for forecasting the spread of FMDV, which have been used since the 1970s, each having its advantages and limitations, are reviewed for the purpose of ensuring suitable application in various conditions of any future emergency cases.

An Environmental Risk Evaluation Method Employing Atmospheric Dispersion Models and GIS

This study aims to develop a method for evaluating the environmental risk of harmful chemical substances released from specific sources, using two atmospheric dispersion models and GIS (Geographic Information Systems). In the first stage of evaluation, ADMER was used to conduct a wide-area evaluation which covered the entire area of the evaluation target region. In the second stage, METI-LIS was used to conduct a detailed limited-area evaluation which targeted the vicinity of sources. In this study, incinerators were selected as sources and dioxins were selected as harmful chemical substances. The area selected for evaluation was the Tokyo Metropolis in Japan, and the evaluation method proposed in this study was used to evaluate environmental risk. Through the use of atmospheric dispersion models and GIS, the behavior of dioxins emitted into the atmosphere from incinerators was estimated. By superimposing atmospheric levels and population data, the amounts of dioxins that humans exposed to were found. Additionally, by superimposing deposition amounts and land use data, the amounts of dioxins accumulated in each land environment were found. Conducting these steps enabled the impact of dioxins on humans and the environment to be grasped quantitatively and visually, and the risk that dioxins emitted from incinerators pose to the environment to be evaluated.

Plug-flow/dispersion model of longitudinal dispersion

A modified Fickian plug-flow/dispersion model (P/D model) is developed in this study. In P/D model, the flow process is divided into two belts, plug flow belt and dispersion belt. P/D model is very similar to Fickian model and rather perfect. The prediction by P/D model can be always consistent with experimental data in river, flume, and pond, even though the data are much skew. Therefore, P/D model is better than Fickian model and other dispersion models.

DYNAMIC MODEL FOR OIL SLICK DISPERSION INTO A WATER COLUMN- A WINDDRIVEN WAVETANK EXPERIMENT

A dynamic experiment for oil dispersion into a water column was performed with a 21 m long, 0.5 m wide, and 1 m high wind-driven wave tank. At wind velocity between 6-12 m/s and with the oil slide kept constant (about 1 um), the rate of the oil content increase in the water column could be approximated from the difference between the dispersion rate (R) of the oil slick and the coagulation rate (R’) of the dispersed oil slick. Assuming the coagulation rate is directly proportional to the concentration of the water dispersed oil slick (i. e. R’ =KC),, the integral form of the dynamic model can be expressed as C=R*[1-exp(-K*t)]/K and parameters R and K can be regressed with a computer. The relative deviation of model results from the experimental data was mainly less than 10%. The oil slick dispersion rate (R) had exponential relationship with the wind velocity (V), and can be fitted with a formula R=A*(U+1)B.The fitted constant of the coagulation rate, K(0.8-3.0* 10-3 min-1) did not have significant

Unified Data Model of Urban Air Pollution Dispersion and 3D Spatial City Model:Groundwork Assessment towards Sustainable Urban Development for Malaysia

Understanding the behavior of urban air pollution is important en route for sustainable urban development (SUD). Malaysia is on its mission to be a developed country by year 2020 comprehends dealing with air pollution is one of the indicators headed towards it. At present monitoring and managing air pollution in urban areas encompasses sophisticated air quality modeling and data acquisition. However, rapid developments in major cities cause difficulties in acquiring the city geometries. The existing method in acquiring city geometries data via ground or space measurement inspection such as field survey, photogrammetry, laser scanning, remote sensing or using architectural plans appears not to be practical because of its cost and efforts. Moreover, air monitoring stations deployed are intended for regional to global scale model whereby it is not accurate for urban areas with typical resolution of less than 2 km. Furthermore in urban areas, the pollutant dispersion movements are trapped between buildings initiating it to move vertically causing visualization complications which imply the limitations of existing visualization scheme that is based on two-dimensional (2D) framework. Therefore this paper aims is to perform groundwork assessment and discuss on the current scenario in Malaysia in the aspect of current policies towards SUD, air quality monitoring stations, scale model and detail discussion on air pollution dispersion model used called the Operational Street Pollution Model (OSPM). This research proposed the implementation of three-dimensional (3D) spatial city model as a new physical data input for OSPM. The five Level of Details (LOD) of 3D spatial city model shows the scale applicability for the dispersion model implementtation. Subsequently 3D spatial city model data commonly available on the web, by having a unified data model shows the advantages in easy data acquisition, 3D visualization of air pollution dispersion and improves visual analysis of air quality monitoring in urban areas.

Study on Conventional Atmospheric Dispersion Models in China,America and Canada

The conventional atmospheric dispersion models used in China (CRADM), America (HPDM) and Canada (AMS) are investigated. The main differences between the three models are described, and the various aspects of CRADM, HPDM and AMS for same input are compared and discussed. Some problems in application of atmospheric dispersion models to environmental impact assessment are analyzed and suggestions for rivision are proposed. Results show that the Briggs plume rise formula in neutral condition overestimates the real rise due to the fact that the accumulative effect of ambient turbulence on plume is not considered in his model.

Mathematical modeling of the bellows dispersion system of submunitions

A mathematical model of the bellows dispersion system is developed by combining the interior ballistic theory with structural dynamics theory to describe the deformation course of bellows. By analyzing the physical model of the bellows dispersion system, the dispersion course is divided into three stages. For each stage, mathematical model is built and its terminal conditions are given. The numerical simulation is based on the Runge-Kutta method and differential quadrature method. Simulation results of the model agree with those of the model built by only interior ballistics theory. However, this model is congruous with the actual dispersion course and can more easily determine the dispersion time and submunition displacement.