矿井火区启封安全性分析及判别准则

矿井火区启封时火区状态判断失误会导致火区复燃或火区内瓦斯爆炸。为此,本文在分析矿井火区启封的安全性的基础上,从气体信息采集和火区燃烧状态的判断技术两方面,提出了相关准则。气体信息采集准则含气样代表火区状态真实性、提高气样代表火区大气状态的真实性、正确的气样采集方法十六项内容,主要论及钻孔取样、孔内测压、火区气体采样地点、倾斜巷道密闭取样、取样地点对气样准确度的影响、气样采集时间、采集钻孔封堵、混合气样分段采集方法、取样时间间隔、气样分析方式等。火区燃烧状态的判断技术准则含十二项内容,主要论及不同火区气体浓度条件和环境条件下正确判断火区燃烧状态技术。准则可为矿井火区治理中正确分析判断火区状态和启封条件提供参考。     

机器人在人机交互过程中的安全性研究进展

为全面准确地掌握人机交互作业过程中人与机器人在安全性方面的研究进展,把提高机器人安全性的策略归纳为3种方法,分别称为事前预防主动控制、关节柔顺设计和用黏弹性材料包裹连杆,阐述了每种方法评价机器人安全性的主要性能指标。通过对比各种实现方法的设计思想和结构组成方案,总结出各种方法的优缺点和存在的主要问题。事前控制的关键在于信息的全面性和控制的实时性;事后控制方法的主要问题则只能在一定程度上减缓撞击的伤害程度,而无法从根本上保证人的安全性。结果表明,到目前为止仅靠单一手段和方法还不能彻底解决机器人安全性问题,要多种手段相结合,高度重视影响安全性的主客观因素,把提高机器人安全性的理念贯穿于机器人设计的各个环节。     

基于模糊均生函数和最优子集回归的飞行事故率预测

为有效预防飞行事故的发生,针对飞行事故率具有随机波动性和趋势性的特点,采用模糊均生函数(FMGF)和最优子集回归(OSR)建立飞行事故率预测模型。该方法把FMGF延拓序列作为预测因子加入OSR方程,将FMGF分析和因子筛选相结合作OSR,进而对飞行事故率进行预测。通过对美国空军1988—2004年的飞行事故率进行拟合预测,结果表明:将FMGF模型和OSR模型有机结合,能够有效刻画飞行事故率的随机波动特性,并且其预测结果的相对误差也较小。     

实验室煤与瓦斯突出模拟试验回顾及展望

为借鉴国内外煤与瓦斯突出模拟试验研究成果,查阅大量相关文献,进行分析和总结。以人们对煤与瓦斯突出试验研究的深入程度为主线,将实验室煤与瓦斯突出模拟试验的研究历程进行阶段划分。研究表明:20世纪50—60年代,成功诱导了突出,初步考察诸因素对突出的影响;70—90年代,深入探究突出发生的力学判据及突出过程,并提出数十种有关突出机理方面的假说;21世纪初,以组建三维模拟试验台进行试验为特点,大大提高了模拟试验条件与现场的相似度,但在力学加载系统的稳定性和可调性、模型的整体密封性、测试探头的精度等方面仍需改进。     

Translating habitat class to land cover to map area of habitat of terrestrial vertebrates

Area of habitat (AOH) is defined as the “habitat available to a species, that is, habitat within its range” and is calculated by subtracting areas of unsuitable land cover and elevation from the range. The International Union for the Conservation of Nature (IUCN) Habitats Classification Scheme provides information on species habitat associations, and typically unvalidated expert opinion is used to match habitat to land-cover classes, which generates a source of uncertainty in AOH maps. We developed a data-driven method to translate IUCN habitat classes to land cover based on point locality data for 6986 species of terrestrial mammals, birds, amphibians, and reptiles. We extracted the land-cover class at each point locality and matched it to the IUCN habitat class or classes assigned to each species occurring there. Then, we modeled each land-cover class as a function of IUCN habitat with (SSG, using) logistic regression models. The resulting odds ratios were used to assess the strength of the association between each habitat and land-cover class. We then compared the performance of our data-driven model with those from a published translation table based on expert knowledge. We calculated the association between habitat classes and land-cover classes as a continuous variable, but to map AOH as binary presence or absence, it was necessary to apply a threshold of association. This threshold can be chosen by the user according to the required balance between omission and commission errors. Some habitats (e.g., forest and desert) were assigned to land-cover classes with more confidence than others (e.g., wetlands and artificial). The data-driven translation model and expert knowledge performed equally well, but the model provided greater standardization, objectivity, and repeatability. Furthermore, our approach allowed greater flexibility in the use of the results and uncertainty to be quantified. Our model can be modified for regional examinations and different taxonomic groups.     

高应力条件下尾矿破碎特性及坝体稳定性研究*

高应力条件下尾矿破碎特性与坝体稳定性研究是高尾矿坝避免溃坝事故的重要参考。分析尾矿颗粒破碎过程中级配曲线的演化规律,提出采用BET测试颗粒比表面积以定量化表征颗粒破碎指标;在室内高应力三轴试验的基础上,阐述高应力条件下尾矿的力学行为,提出高应力条件下尾矿强度准则,并基于该准则对工程实例进行应用分析。结果表明:相比于常用破碎指标,从能量观点出发的BET法比表面积表征尾矿颗粒破碎更为合理;采用线性Mohr-Coulomb准则计算尾矿在低应力阶段的内摩擦角,采用幂函数Mohr强度准则计算尾矿在高应力阶段的内摩擦角;提出1套考虑高应力条件下尾矿强度折减的坝体稳定性分析方法,以供实际工程参考。     

建筑结构活荷载标准与灾害荷载设防水平 --使用年限的影响

旨在提供不同使用年限建筑结构对应的活荷载水平.分析了结构可靠度理论的特点,揭示了设计使用年限是结构可靠度的时间特征.应根据不同设计使用年限活荷载的超越概率等于常规设计荷载超越概率的原则确定活荷的载标准;通过建立不同设计使用期、不同设计基准期与活荷载取值的关系,给出了不同使用年限对应活荷载与灾害荷载设防水平.     

确立灾害评估标准是我国“国际减灾十年”目标的重要问题

本文通过许多实例.从测、报、抗、防、救等几个方面论述灾害评估标准的重要性,进而说明了灾害评估与减灾管理以及灾情统计的密切关系.文中还根据我国近几年灾害经济损失的情况对90年代的减灾目标提出了看法.     

Uncertainty propagation in vegetation distribution models based on ensemble classifiers

Ensemble learning techniques are increasingly applied for species and vegetation distribution modelling, often resulting in more accurate predictions. At the same time, uncertainty assessment of distribution models is gaining attention. In this study, Random Forests, an ensemble learning technique, is selected for vegetation distribution modelling based on environmental variables. The impact of two important sources of uncertainty, that is the uncertainty on spatial interpolation of environmental variables and the uncertainty on species clustering into vegetation types, is quantified based on sequential Gaussian simulation and pseudo-randomization tests, respectively. An empirical assessment of the uncertainty propagation to the distribution modelling results indicated a gradual decrease in performance with increasing input uncertainty. The test set error ranged from 30.83% to 52.63% and from 30.83% to 83.62%, when the uncertainty ranges on spatial interpolation and on vegetation clustering, respectively, were fully covered. Shannon’s entropy, which is proposed as a measure for uncertainty of ensemble predictions, revealed a similar increasing trend in prediction uncertainty. The implications of these results in an empirical distribution modelling framework are further discussed with respect to monitoring setup, spatial interpolation and species clustering.     

在环境保护中开展环境审计的重要作用

工业革命把人类推向工业文明,工业文明刺激人类对资源的无限需求,创造出大量消耗资源、严重污染环境的生产方式,产生了大量的环境污染和生态危机。于是,提高环境质量、开展环境保护、保证经济发展的可持续性的呼声越来越高。环境审计作为环境保护的一种有力工具,在当代经济活动中会越来越发挥其重要作用。本文就环境审计的有关问题作一阐述,以其推动环境审计在我国的发展。