Determination of the maximum effective burning velocity of dust–air mixtures in constant volume combustion

The reactivity of a combustible dust cloud is traditionally characterized by the so-called K_St value, defined as the maximum rate of pressure rise measured in constant volume explosion vessels, multiplied with the cube root of the vessel volume. The present paper explores the use of an alternative parameter, called the maximum effective burning velocity (u_eff,max), which also is derived from pressure–time histories obtained in constant volume explosion experiments. The proposed parameter describes the reactivity of fuel–air mixtures as a function of the dispersion-induced turbulence intensity. Procedures for estimating u_eff,max from tests in both spherical and cylindrical explosion vessels are outlined, and examples of calculated values for various fuel–air mixtures in closed vessels of different sizes and shapes are presented. Tested fuels include a mixture of 7.5% methane in air, and suspensions of 500 g/m³ cornstarch in air and 500 g/m³ coal dust in air. Three different test vessels have been used: a 20-l spherical vessel and two cylindrical vessels, 7 and 22 l. The results show that the estimated maximum effective burning velocities are less apparatus dependent than the corresponding K_St values.     

矿井通风系统抗灾变能力评价指标体系

矿井通风系统抗灾变能力的确定和提高对于矿山减灾救灾具有重要意义。在通风系统抗灾变能力评价中，指标体系的选取至关重要。根据矿井火灾、救灾、防灾的具体情况及相关文献，从防火措施、防火管理、指挥救灾和井下工人救火素质4方面选取了22个指标，确定了矿井通风系统抗灾变能力的模糊综合评价指标体系，给出了矿井通风系统抗灾变能力指标分级界定值，并采用层次分析法对各个指标的重要性进行排序，提出了通风系统抗灾变能力层次分析结构模型。     

噪声主观反应模糊隶属函数的AHP计算方法

根据模糊数学层次分析法(AHP)的原理,构造判断矩阵,针对不同的环境功能区域,定量计算各主观烦恼度表述等级的隶属度,求出了相应环境下的模糊隶属函数,并运用于噪声主观烦恼反应阈值的计算.实例计算表明,对不同环境建立不同的烦恼隶属函数,更符合人们对噪声主观反应所作表述的实际,计算得到的烦恼概率和噪声阈值更科学可信.     

Designing environmental monitoring networks to measure extremes

This paper discusses challenges arising in the design of networks for monitoring extreme values over the domain of a random environmental space-time field {X _ij } i = 1, . . . , I denoting site and j = 1, . . . denoting time (e.g. hour). The field of extremes for time span r over site domain i = 1, . . . ,I is given by \(\{Y_{i(r+1)}=\max_{j=k}^{k+n-1} X_{ij}\}\) for k = 1 + rn, r = 0, . . . ,. Such networks must not only measure extremes at the monitored sites but also enable their prediction at the non-monitored ones. Designing such a network poses special challenges that do not seem to have been generally recognized. One of these problems is the loss of spatial dependence between site responses in going from the environmental process to the field of extremes it generates. In particular we show empirically that the intersite covariance Cov(Y _i(r+1),Y _i′(r+1)) can generally decline toward zero as r increases, for site pairs i ≠ i′. Thus the measured extreme values may not predict the unmeasured ones very precisely. Consequently high levels of pollution exposure of a sensitive group (e.g. school children) located between monitored sites may be overlooked. This potential deficiency raises concerns about the adequacy of air pollution monitoring networks whose primary role is the detection of noncompliance with air quality standards based on extremes designed to protect human health. The need to monitor for noncompliance and thereby protect human health, points to other issues. How well do networks designed to monitor the field monitor their fields of extremes? What criterion should be used to select prospective monitoring sites when setting up or adding to a network? As the paper demonstrates by assessing an existing network, the answer to the first question is not well, at least in the case considered. To the second, the paper suggests a variety of plausible answers but shows through a simulation study, that they can lead to different optimum designs. The paper offers an approach that circumvents the dilemma posed by the answer to the second question. That approach models the field of extremes (suitably transformed) by a multivariate Gaussian-Inverse Wishart hierarchical Bayesian distribution. The adequacy of this model is empirically assessed in an application by finding the relative coverage frequency of the predictive credibility ellipsoid implied by its posterior distribution. The favorable results obtained suggest this posterior adequately describes that (transformed) field. Hence it can form the basis for designing an appropriate network. Its use is demonstrated by a hypothetical extension of an existing monitoring network. That foundation in turn enables a network to be designed of sufficient density (relative to cost) to serve its regulatory purpose.     

基于三角模糊技术的河流水环境容量研究

基于河流水环境系统的随机性、模糊性特征,以及资料信息的不足和不精确性,将水环境系统参数定义为三角模糊数。在此基础上,通过将常规的确定性模型参量模糊化,建立了河流水环境容量计算模糊模型。根据该模型,可以计算得到三角模糊数形式的河流水环境容量;再由给定的可信度水平要求,可以进一步将水环境容量由三角模糊数转化为区间值。实例研究表明,相对于常规的确定性方法,所得结果更为科学、合理,而且计算简单、操作方便,具有实用价值。     

堤防工程综合安全模型和风险评价体系研究及应用

为获得荆南长江干堤的安全特性,在层次分析法及模糊一致理论的基础上,考虑堤防工程水、土两相系材料的特点,建立了模糊综合评判系统结构模型。通过正态型模糊隶属函数,结合两种权值理论实现了对堤防工程的安全综合评判。在模糊综合评判结论的基础上,结合模式识别的间接方法,提出了广义多维加权模糊识别模型,实现了对典型堤身段的安全模式识别,并对模型指标体系作了敏感性分析。所得成果比较全面地反映了干堤在复杂运行条件下的综合安全特性,对指导工程现场管理与监测有现实意义。对于复杂堤防系统,模糊综合评判是实现全面风险分析的有效手段,而广义多维加权模糊识别模型可以为工程安全决策提供有力依据。     

沭河水质模糊综合评价评价模型建立与应用

根据模糊数学原理,建立了水质模糊综合评价模型,利用该模型对2006年-2009年山东省临沂市沭河水质进行了水质评价。结果表明,（1）该模型计算方法简便且能比较客观的反映评价对象的客观实际和水质变化规律,评价结果更为可靠,是水质综合评价的一种理想、有效的方法;（2）沭河流域水质总体状况良好,一年中I级水的天数为50％、Ⅱ级水的天数为8．3％、Ⅲ级水的天数为41．7％,评价结果与实际相符;评价方法有实用价值。     

Water quality evaluation of Haihe River with fuzzy similarity measure methods

Fuzzy similarity measures, which are used to judge the closeness of two fuzzy sets, are presented to evaluate the water quality of the Haihe River. Based on the membership functions and coefficient of variation as the weights, four fuzzy similarity measures （including Lattice similarity measure, Hamming similarity measure, Euclidean similarity measure and the max-min similarity measure） are used to classify the 299 samples into the proper water quality standard ranks. The results are compared with the traditional distance discriminant methods. The calculation of two traditional distance discriminant methods （both Euclidean distance and absolute value distance） is also based on the use of coefficients of variation as the weights. Without the Lattice similarity measure, for this method loses some information, the correct assignment of samples classified into the same water quality ranks is 75.92% with the other three similarity measures and two distance discriminant methods. This result shows the reliability of the five methods. Only considering the three similarity measures, there were only 1.01% of the samples that did not classify to the same ranks, while the corresponding ratio of the two distance discriminant methods was 5.69%. The results of leave-one-out cross validation show that more than 88% of the samples are classified to the proper ranks, which demonstrates that the similarity measures are suitable to evaluate the water quality of the Haihe River.     

延安新造贫瘠耕地适生农作物及其高产品种筛选

2013?—?2017年延安市实施了治沟造地工程,总投资约50亿,新造耕地3.33万hm2,但是研究发现新造耕地土壤贫瘠,改良需要较长时间.因此筛选新造耕地适生农作物及其高产品种,指导农业生产实践显得尤为重要和迫切.为此,本研究开展延安新造耕地适生农作物筛选实验,发现马铃薯为新造耕地适生农业作物,进而从甘肃等地选择有代表性的抗性强、产量高的11个马铃薯品种,在延安安塞区高桥镇南沟村开展了最适马铃薯品种筛选的大田实验.结果表明:(1)从产量、产值以及对土壤改良角度综合考虑,马铃薯为延安新造耕地适生作物,其产量和产值均显著高于其他农作物,且马铃薯有利于降低土壤pH值,改善土壤团粒结构,提升有机质与氮磷含量,适宜于新造贫瘠耕地种植.(2)"新大坪"、"青薯168"、"克新1号"产量均显著高于本地马铃薯品种(P<0.01),且出苗率、水分利用效率、净光合效率、气孔导度、蒸腾速率和胞间CO2浓度均高于本地马铃薯品种(P<0.05);"陇薯7号"出苗率、气孔导度、蒸腾速率和胞间CO2浓度也高于本地品种(P<0.05),其水分利用效率低(P>0.05),限制了其光合效率(P>0.05),没有表现出高产效果(P>0.05),但是个头大、表面光滑、卖相好.(3)进一步大田验证实验发现,"新大坪"不但产量高,而且出苗率、株高、净光合速率、气孔导度、淀粉、还原糖、蛋白质均优于本地马铃薯品种;"青薯168"产量也显著高于本地马铃薯品种,其胞间CO2浓度、蒸腾速率、PSⅡ实际光化学效率、最大光化学量子产量、PSⅡ潜在活性均优于本地品种;"陇薯7号"与"克新1号"产量也高于本地品种,但无显著性差异(P>0.05).利用模糊数学隶属函数方法综合评价发现,"新大坪"隶属度值最大,为新造耕地最适宜种植推广的品种,其次为"陇薯7号"与"青薯168",而"克新1号"综合评价劣于本地品种.     

Explosibility of micron- and nano-size titanium powders

Explosibility of micron- and nano-titanium was determined and compared according to explosion severity and likelihood using standard dust explosion equipment. ASTM methods were followed using a Siwek 20-L explosion chamber, MIKE 3 apparatus and BAM oven. The explosibility parameters investigated for both size ranges of titanium include explosion severity (maximum explosion pressure (P_max) and size-normalized maximum rate of pressure rise (K_St)) and explosion likelihood (minimum explosible concentration (MEC), minimum ignition energy (MIE) and minimum ignition temperature (MIT)). Titanium particle sizes were ?100 mesh (<150 μm), ?325 mesh (<45 μm), ≤20 μm, 150 nm, 60–80 nm, and 40–60 nm. The results show a significant increase in explosion severity as the particle size decreases from ?100 mesh with an apparent plateau being reached at ?325 mesh and ≤20 μm. Micron-size explosion severity could not be compared with that for nano-titanium due to pre-ignition of the nano-powder in the 20-L chamber. The likelihood of an explosion increases significantly as the particle size decreases into the nano range. Nano-titanium is very sensitive and can self-ignite under the appropriate conditions. The explosive properties of the nano-titanium can be suppressed by adding nano-titanium dioxide to the dust mixture. Safety precautions and procedures for the nano-titanium are also discussed.