呼吸效应对矿井封闭火区氧浓度的影响分析

为避免因火区封闭导致重大安全事故发生,通过采集某矿井1 d内3个不同监测点的大气压力变化情况,建立大气压力波动模型并分析计算,同时建立火区内外压差100,750 Pa情形下的氧浓度模型进而获得火区内侧氧气浓度因呼吸效应,在不同压差、体积大小火区、风阻、瓦斯涌出量、封闭时刻等多因素耦合影响下随时间的变化规律,以评估火区危险性。研究结果表明:井下大气随地面大气周期波动,封闭火区内、外侧之间的气压差因外界大气波动呈现16 h的余弦波动和8 h的线性波动周期变化;密闭质量好的火区具有更好地抗干扰性,内侧氧浓度的降低主要依靠瓦斯稀释;密闭质量差的火区,内侧氧浓度易受到火区涌出瓦斯、外界涌入大气双重影响;火区氧浓度在2%~12%之间波动,以至火区存在发生瓦斯爆炸的可能性;火区内外压差较大时,氧浓度波动变化幅度更大,危险作用持续时间更长。结合火区氧浓度波动模型,可有效地对矿井火区采取安全的防范措施,避免瓦斯爆炸事故发生。     

深部煤层钻屑粒度随钻进深度分布规律

为了研究煤层钻屑粒度随钻进深度分布规律,选取具有冲击危险性的平煤八矿己15煤作为研究对象,采取钻屑量测试和孔口瓦斯浓度监测,通过筛分实验煤样并应用Rosin Rammler分布模型,探究了钻屑粒度和钻屑量大小随孔深变化关系,分析不同点钻屑粒度分布特征。结果表明:小于0.075 mm钻屑粒度分布随孔深变化与钻屑量变化规律相吻合;不同钻孔随深度变化分别对应不同Rosin Rammler分布函数,随着应力过渡越平缓,粒径分布宽度系数n值越小,煤体应力越大粒径相关系数D越大;不同范围钻屑粒度占比大小也会影响钻屑量大小;在钻屑量较大时,孔口瓦斯体积分数会出现增高现象。通过对钻屑粒度分布规律分析,更好地了解深部煤体应力分布,有助于冲击危险的预警。     

时间因素对钻屑瓦斯解吸指标K1值测定的影响分析

针对时间因素对钻屑瓦斯解吸指标K1测定结果的影响,采用恒温瓦斯放散试验深入分析钻屑瓦斯解吸指标K1测定理论的准确性,总结因时间因素导致K1值测定误差所带来的现场问题。研究结果表明:K1值的测定误差与时间关系密切,测定启动时间越晚,误差越大;测定启动时间由第1 min延后至第2 min,绝对误差和相对误差最大值分别增加0.081 cm3/(g·min1/2)和2.20%;高瓦斯压力条件矿井或煤层的局部高瓦斯压力区域、构造煤发育区的钻屑瓦斯解吸指标K1值测定结果偏低,测定误差偏大。研究结果可为煤与瓦斯突出预测水平的提升提供技术支撑。     

Mitigating Impact of Devils Lake Flooding on the Sheyenne River Sulfate Concentration

Devils Lake is a terminal lake located in northeast North Dakota. Because of its glacial origin and accumulated salts from evaporation, the lake has a high concentration of sulfate compared to the surrounding water bodies. From 1993 to 2011, Devils Lake water levels rose by ~10 m, which flooded surrounding communities and increased the chance of an overspill to the Sheyenne River. To control the flooding, the State of North Dakota constructed two outlets to pump the lake water to the river. However, the pumped water has raised concerns about of water quality degradation and potential flooding risk of the Sheyenne River. To investigate these perceived impacts, a Soil and Water Assessment Tool (SWAT) model was developed for the Sheyenne River and it was linked to a coupled SWAT and CE‐QUAL‐W2 model that was developed for Devils Lake in a previous study. While the current outlet schedule has attempted to maintain the total river discharge within the confines of a two‐year flood (36 m³/s), our simulation from 2012 to 2018 revealed that the diversion increased the Sheyenne River sulfate concentration from an average of 125 to >750 mg/L. Furthermore, a conceptual optimization model was developed with a goal of better preserving the water quality of the Sheyenne River while effectively mitigating the flooding of Devils Lake. The optimal solution provides a “win–win” outlet management that maintains the efficiency of the outlets while reducing the Sheyenne River sulfate concentration to ≤600 mg/L.     

基于VB6.0的供水管网震害预测方法和软件

为了提高供水管网震害预测的效率,修订了现有供水管网震害预测模型,应用Visual Basic 6.0软件平台,开发了供水管网震害预测软件。震害预测软件提供了两方面的预测功能,分别为不同地震烈度下供水管段基于三态的破坏等级预测和供水管网基于五态的破坏等级预测。软件实现了批量供水管段及整个管网的震害预测,且可以进行管网在设定地震下的震害预测,提高了预测效率。经算例分析,验证了软件的可靠性。     

西南山地区域森林火险综合预报模型研究——以重庆市为例

森林火灾严重破坏森林生态系统的结构和功能,针对其风险预报开展研究具有重要的理论意义和应用价值。通过融合气象、地表覆盖和人类活动等要素的方式构建森林火险综合预报模型,是西南山地区域森林火险综合预报业务化应用的重要发展方向。基于《森林火险气象等级》国家标准(GB/T 36743-2018),本文研究首先构建了重庆市森林火险气象风险预报模型。然后通过融合可燃物因素和人为因素的方式,进一步构建重庆市森林火险综合预报模型。最后利用历史火点数据针对上述两类模型的精度进行对比和分析。研究结果表明:重庆市森林火灾发生次数较多,且呈现出季节性规律;重庆市森林火灾的发生不仅受到气象条件的影响,而且受到地表覆盖和人类活动等多种要素条件的共同影响;与森林火险气象风险预报结果相比,森林火险综合预报结果在空间分布上具有更高的精细程度;森林火险综合预报模型能有效提高森林火险等级预报精度。     

An Analysis of Secondary Pollutants in Buenos Aires City

Air pollutant concentrations from a monitoring campaign in Buenos Aires City, Argentina, are used to investigate the relationships between ambient levels of ozone (O₃), nitric oxide (NO) and nitrogen dioxide (NO₂) as a function of NO _x (=NO + NO₂). This campaign undertaken by the electricity sector was aimed at elucidating the apportionment of thermal power plants to air quality deterioration. Concentrations of carbon monoxide (CO) and sulphur dioxide (SO₂) were also registered. Photo stationary state (PSS) of the NO, NO₂, O₃ and peroxy radicals species has been analysed. The ‘oxidant’ level concept has been introduced, OX (=O₃ + NO₂), which varies with the level of NO _x . It is shown that this level is made up of NO _x -independent and NO _x -dependent contributions. The former is a regional contribution that equates the background O₃ level, whereas the latter is a local contribution that correlates with the level of primary pollution. Furthermore, the anticorrelation between NO₂ and O₃ levels, which is a characteristic of the atmospheric photo stationary cycle has been verified.The analysis of the concentration of the primary pollutants CO and NO strongly suggests that the vehicle traffic is the principal source of them. Levels of continuous measurements of SO₂ for Buenos Aires City are reported in this work as a complement of previously published results.     

Cancer and Non-Cancer Health Risk from Eating Cassava Grown in Some Mining Communities in Ghana

Food crops such as cassava, cocoyam and other tuber crops grown in mining communities uptake toxic or hazardous chemicals such as arsenic, and cadmium, from the soil. Cassava is a stable food for Ghanaians. This study evaluated human health risk from eating cassava grown in some mining communities in Ghana such as Bogoso, Prestea, Tarkwa and Tamso, which are important mining towns in the Western Region of Ghana. The study evaluated cancer and non-cancer health effects from eating cassava grown in the study areas in accordance with US Environmental Protection Agency’s Risk Assessment guidelines. The results of the study revealed the following: cancer health risk for Tamso, 0.098 (RME – Reasonable Maximum Exposure) and 0.082 (CTE – Central Tendency Exposure). This means that approximately 10 and 8 out of 100 resident adults are likely to suffer from cancer related cases by RME and CTE parameters respectively. For Prestea, we have 0.010 and 0.12, which also means that approximately 1 out of 100 and 10 resident adults out of 100 are also likely to suffer from cancer related diseases by RME and CTE parameters. The results of the study obtained were found to be above the acceptable cancer risk range of 1× 10⁻⁶ to 1× 10⁻⁴, i.e., 1 case of cancer out of 1 million or 100,000 people respectively.     

基于改进的非线性GM(1,1)模型的职业病预测研究

为了更准确地预测职业病,在传统GM(1,1)模型的基础上,提出改进的非线性GM(1,1)模型,在传统的GM(1,1)模型中引入弱化算子,将紧邻均值与原始数据之间的线性假设改为非线性假设,提高曲线的拟合度。以2005—2014年的全国职业病例数为研究对象,进行数据拟合和预测分析,其中以2014年职业病例数作为验证数据,并利用后验差比值和小误差概率2个参数,检验该改进模型的预测精度。由应用实例的分析结果可知:在职业病发病趋势的预测方面,改进的非线性GM(1,1)模型的预测精度提高到一级,曲线拟合度较高,预测得到2015年的职业病例数为34 900例。     

基于SVM的矿井通风阻力系数影响因素分析与预测

矿井通风阻力系数是通风安全最重要的基础参数之一,为了实现矿井通风阻力系数简单准确地预测,提出了利用支持向量机（SVM）来预测矿井通风阻力系数的方法。通过分析影响因子与矿井通风阻力系数的相关性关系,并利用MATLAB逐步建立单影响因素与矿井通风阻力系数、多影响因素与矿井通风阻力系数之间的SVM预测模型,对比分析各预测模型的相对误差,确定最佳矿井通风阻力系数预测模型,即当输入模型影响因素为巷道断面积、周长和支护方式时,预测相对误差小于10%的样本数占测试样本的76%,相对误差小于20%的样本数占测试样本的90%。结果表明:该预测方法在矿井通风阻力系数预测中是可行的,并具较高的准确性。