矿井巷道火灾烟流逆退数值模拟及临界风速研究

为了研究矿井发生火灾后高温烟流的蔓延规律及影响因素,利用COMSOL软件对火区进行数值模拟,建立巷道三维模型,得到火区风流速度与温度分布。通过改变边界条件,分析火风压作用下,火区烟气在不同控制风速、巷道条件作用下蔓延规律,得出不同因素与临界风速的关系,为选取合理的火灾控制风速提供理论依据。研究结果表明:火源温度一定时,巷道入口风速越低,火源下风侧高温烟流越靠近巷道顶部,随着风速增大,向巷道下部蔓延;风速较低时,在火区火风压的作用下,会产生烟流逆退现象,随着风速的增大,逆流层长度和厚度随之减小;巷道入口通风条件不变时,火区温度越高越容易产生烟流的逆退,影响范围越大;巷道高度越高、上行风坡度越小,越易发生逆退现象;不同影响因素与巷道平均温度不成正比关系,其中下行风坡度5~15°时巷道平均温度较高且易于发生烟流滚退现象,影响范围较大;火源温度、巷道条件与临界风速的数据拟合结果对预测巷道的临界风速有较好的参考价值。     

基于人工神经网络的气体泄爆最大超压预测研究

为解决传统经验公式在预测气体泄爆中最大超压出现时的较大偏差或过于保守的问题,提出使用人工神经网络预测气体泄爆最大超压。基于124组实验数据,采用BP与RBF神经网络,通过优化算法计算与迭代循环对泄爆样本中的影响因素进行降维与选择,并确定2类神经网络本身在学习与计算气体泄爆样本时的相关参数。结果表明:PCA（主成分分析法）在当前样本条件下的降维效果较差,而通过迭代对比确认气体泄爆样本中的5类特征全部保留时神经网络的训练模拟效果最好;通过对124组实验数据进行随机挑选训练集与测试集的训练模拟结果发现,神经网络对气体泄爆中最大超压的预测效果较好;通过对比Molkov提出的和经Fakandu等改进的NFPA 68经验公式以及2类神经网络的预测结果表明,神经网络相比于传统气体泄爆经验公式具有明显优势。     

基于事故逆向再现的车辆追尾事故仿真分析研究

为认定车辆碰撞事故的性质及责任,动态还原事故发生过程。提出1种逆向事故分析再现方法,经过坐标系旋转后构建确定方程组的车辆碰撞瞬间解析计算模型,并经过实车碰撞实验数据验证其计算精度与三维再现的准确性。利用Crashview软件对1起车辆追尾事故进行仿真分析,解析计算得出车辆碰撞瞬间车速和碰撞前行驶车速,实现事故二维过程重构和三维模拟再现。结果表明:计算分析车速与VDR记录车速误差在5%以内,模拟再现轨迹与事故现场实测痕迹基本吻合,所构建的方法可有效用于车辆追尾碰撞事故辅助分析鉴定,为事故过程分析提供理论依据。     

缝洞型管道瓦斯爆炸特性数值模拟研究

为探究采空区遗煤、松散破碎岩块对瓦斯爆炸的影响,建立缝洞型管道模型,采用数值模拟与理论分析结合方法研究采空区内缝洞型管道内瓦斯爆炸的传播规律及管道长径比对瓦斯爆炸过程中速度与冲击波的影响。研究结果表明:在缝洞型结构内,随着火焰沿管道向前传播,各监测点速度逐渐变大、压力先增加后降低,而压力上升速率则表现出不规则的变化;缝洞结构加剧了火焰燃烧的剧烈程度,提高了管道内各监测点的温度峰值;在缝洞型管道内随长径比r增加,各监测点最大压力峰值以及速度大小依次降低。     

突发事件下安全舆情的传播与演变——以江苏响水天嘉宜化工有限公司“3.21”特别重大爆炸事故为例

为明确突发事件安全舆情传播与演变路径,提高企业防控突发事件安全舆情传播风险能力,降低衍生灾害发生概率,在文献分析及事故致因理论基础上,构建突发事件安全舆情传播与演变过程的系统动力学（SD）模型,并运用Vensim软件对以江苏响水天嘉宜化工有限公司“3.21”特别重大爆炸事故为例进行仿真实验,模拟安全舆情传播与演变动态过程。结果表明:突发事件安全舆情传播与演变主要受事件自身、媒体、相关企业监管层、相关企业执行层4个主体的共同影响,其中事件自身因素起效时间最早,相关企业监管层影响作用最大、维持时间最持久,相关企业执行层影响最直接。     

波浪与抛石潜堤相互作用的MPS法数值模型研究

为了研究波浪与抛石潜堤相互作用过程中大自由表面变形和堤内渗流等强非线性紊流运动问题,利用改进的MPS法,建立了模拟波浪与抛石潜堤相互作用的MPS法数值计算模型。模型将抛石潜堤假定为均质多孔介质,采用Drew的二相流运动方程描述多孔介质内外的流体运动;通过在动量方程中增加非线性阻力项,并引入亚粒子尺度紊流模型,模拟波浪与可渗结构物相互作用过程中的紊流运动。选取“U”型管中多孔介质内渗流过程和孤立波与可渗潜堤相互作用两个典型的渗流问题,通过将数值计算结果与理论解和实测值的对比分析,对所提出的MPS法紊流渗流模型的模拟精度进行验证。结果表明：基于改进的MPS法构建的垂向二维紊流渗流模型可以很好地再现 “U”型管中多孔介质内渗流以及波浪作用下可渗潜堤内外的复杂流场,显著缓解流-固界面处的压力震荡与粒子分布不均匀问题,实现了较高的模拟精度。     

Spatial and Seasonal Response of Municipal Water Use to Weather across the Contiguous U.S.

Weather variability has the potential to influence municipal water use, particularly in dry regions such as the western United States (U.S.). Outdoor water use can account for more than half of annual household water use and may be particularly responsive to weather, but little is known about how the expected magnitude of these responses varies across the U.S. This nationwide study identified the response of municipal water use to monthly weather (i.e., temperature, precipitation, evapotranspiration [ET]) using monthly water deliveries for 229 cities in the contiguous U.S. Using city‐specific multiple regression and region‐specific models with city fixed effects, we investigated what portion of the variability in municipal water use was explained by weather across cities, and also estimated responses to weather across seasons and climate regions. Our findings indicated municipal water use was generally well‐explained by weather, with median adjusted R² ranging from 63% to 95% across climate regions. Weather was more predictive of water use in dry climates compared to wet, and temperature had more explanatory power than precipitation or ET. In response to a 1°C increase in monthly maximum temperature, municipal water use was shown to increase by 3.2% and 3.9% in dry cities in winter and summer, respectively, with smaller changes in wet cities. Quantifying these responses allows urban water managers to plan for weather‐driven variability in water use.     

Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part II: An Application of Metrics and Adjoints

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

A critical overview of driver recording tools

Introduction: Technological advancements during recent decades have led to the development of a wide array of tools and methods in order to record driving behavior and measure various aspects of driving performance. The aim of the present study is to present and comparatively assess the various driver recording tools that researchers have at their disposal. Method: In order to achieve this aim, a multitude of published studies from the international literature have been examined based on the driver recording methodologies that have been implemented. An examination of more traditional survey methods (questionnaires, police reports, and direct observer methods) is initially conducted, followed by investigating issues pertinent to the use of driving simulators. Afterwards, an extensive section is provided for naturalistic driving data tools, including the utilization of on-board diagnostics (OBD) and in-vehicle data recorders (IVDRs). Lastly, in-depth incident analysis and the exploitation of smartphone data are discussed. Results: A critical synthesis of the results is conducted, providing the advantages and disadvantages of utilizing each tool and including additional knowledge regarding ease of experimental implementation, data handling issues, impacts on subsequent analyses, as well as the respective cost parameters. Conclusions: New technologies provide undeniably powerful tools that allow for seamless data handling, storage, and analysis, such as smartphones and in-vehicle data recorders. However, this sometimes comes at considerable costs (which may or may not pay off at a later stage), while legacy driver recording methods still have their own niches to fill in research. Practical Applications: The present research supports researchers when designing driver behavior monitoring studies. The present work enables better scheduling and pacing of research activities, but can also provide insights for the distribution of research funds.     

CFD simulations of dust dispersion in the 1 m3 explosion vessel

According to standard procedures, flammability and explosion parameters for dusts and dust mixtures are evaluated in 20 L and/or 1 m³ vessels, with equivalent results provided a correct ignition delay time (60 ms in the 20 L vessel; 600 ms in the 1 m³ vessel). In this work, CFD simulations of flow field and dust concentration distribution in the 1 m³ spherical vessel are performed, and the results compared to the data previously obtained for the 20 L. It has been found that in the 1 m³ vessel, the spatial distribution of the turbulent kinetic energy is lower and much more uniform. Concerning the dust distribution, as in the case of the 20 L, dust is mainly concentrated at the outer zones of the vortices generated inside the vessel. Furthermore, an incomplete feeding is attained, with most of the dust trapped in the perforated annular nozzle. Starting from the maps of dust concentration and turbulent kinetic energy, the deflagration index K_St is calculated in both vessels. In the conditions of the present work, the K_St is found to be 2.4 times higher in the 20 L than in the 1 m³ vessel.