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Web-based forecasting system for the airborne spread of livestock infectious disease using computational fluid dynamics

机译:基于网络的牲畜传染病传播传播的预报系统使用计算流体力学

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摘要

Livestock infectious diseases, such as foot-and-mouth disease (FMD), cause substantial economic damage to livestock farms and their related industries. Among various causes of disease spread, airborne dispersion has previously been considered to be an important factor that could not be controlled by preventive measures to stop the spread of disease that focus on direct and indirect contact. Forecasting and predicting airborne virus spread are important to make time for developing strategies and to minimise the damage of the disease. To predict the airborne spread of the disease a modelling approach is important since field experiments using sensors are ineffective because of the rarefied concentrations of virus in the air. The simulation of airborne spread during past outbreaks required improvement both for farmers and for policy decision makers. In this study a free license computational fluid dynamics (CFD) code was used to simulate airborne virus spread. Forecasting data from the Korea Meteorological Administration (KMA) was directly connected in the developed model for real-time forecasting for 48 h in three-hourly intervals. To reduce computation time, scalar transport for airborne virus spread was simulated based on a database for the CFD computed airflow in the investigated area using representative wind conditions. The simulation results, and the weather data were then used to make a database for a web-based forecasting system that could be accessible to users.
机译:诸如口蹄疫(FMD)等牲畜传染病对畜牧场及其相关产业造成重大经济损失。在疾病传播的各种原因中,以前认为空中传播是一个重要因素,不能通过集中于直接和间接接触的预防措施来阻止疾病传播而加以控制。预测和预测机载病毒的传播对于腾出时间制定策略并最大程度地减少疾病的损害非常重要。为了预测疾病的空气传播,建模方法很重要,因为使用传感器的现场实验是无效的,因为空气中的病毒浓度很少。对过去暴发期间的空中传播进行模拟需要农民和决策者进行改进。在这项研究中,免费许可证计算流体动力学(CFD)代码用于模拟机载病毒传播。来自韩国气象局(KMA)的预报数据直接连接到已开发的模型中,用于每三个小时间隔进行48小时的实时预报。为了减少计算时间,基于CFD计算出的风量,利用代表风条件的数据库,通过空气传播病毒的标量运输进行了模拟。然后,将模拟结果和天气数据用于为用户可以访问的基于Web的预报系统建立数据库。

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