企业建设项目竣工环境保护自主验收工作初探

简述了企业建设项目竣工环境保护自主验收政策的出台背景,介绍了自主验收目前取得的成效。针对现阶段工作中存在的自主验收缺乏有效监管及配套的技术支撑、企业主体责任意识不强等问题,提出了完善监督管理制度、提高企业主体责任意识、加强第三方验收监测机构管理、开展验收技术培训、规范建设项目变动认定管理等建议。     

响应面法优化预氧化强化混凝处理铁锰地下水

以KMnO_4为氧化剂,Al_2(SO_4)_3·18H_2O为混凝剂,含铁锰离子地下水为模拟用水,考察预氧化强化混凝法的效果。利用响应面设计试验,分析氧化剂投加量、混凝剂投加量和pH值对铁锰去除的交互作用。模型优化结果显示,在氧化剂投加量4.16 mg/L,混凝剂投加量263.68 mg/L,pH值为7.54的最佳工艺参数下,铁锰去除率分别可达98.22%和97.49%。     

关于锅炉烟气脱硫除尘技术的探讨

目前国内能源结构仍以煤炭为主,大气污染非常的严重,尤其是酸雨和粉尘危害相对较大。在生态文明建设的时代背景下,我们应当加强锅炉脱硫以及除尘技术创新与改造,对燃煤烟尘以及二氧化硫等污染物的排放进行严格控制。本文先对锅炉烟气脱硫除尘现状进行了分析,并在此基础上就电厂锅炉如何进行烟气脱硫与除尘提出了一些观点与认识,以供参考。     

中国南海高温高压井钻完井损失工时事件统计分析

为研究我国南海高温高压井钻完井、测试损失工时事件规律，对2009—2018年中国南海高温高压探井钻井日志进行分析，汇总501起海上高温高压井钻完井损失工时事件，并将其划分为复杂情况及事故停工、自然停工、修理停工3大类进行研究。结果表明:复杂情况及事故停工事件数与年份无明显关联，但与地质资料准确度关系密切，修理停工事件数随年份呈现震荡下降趋势；复杂情况及事故停工总损失工时最多，其中卡钻损失工时占比最高；修理停工总损失工时最少，其中钻井设备故障损失工时占比最高；灾难天气、洋流或地质活动是造成损失工时最多的原因，不安全行为是单起事件平均损失工时最多的原因，设备老化是修理停工最主要原因。研究结果可为后续高温高压井钻完井非生产时间成本估计模型提供数据基础。     

基于谐波沉降的管道力学分析*

为避免地面沉降引发的油气管道事故，研究沉降管道的力学特性，提出基于谐波沉降的管道力学评估方法。以中国石化某沉降管道为研究对象，通过现场测量的方法获得沉降区管道高程，利用傅里叶级数展开对不均匀沉降数据进行处理分析，获得管道谐波沉降的拟合函数。建立ANSYS有限元模型，采用土弹簧模型模拟非沉降区管道与土体相互作用关系，将谐波沉降作为位移载荷施加到沉降区管道，对含内压管道的沉降进行数值模拟，分析其应力、应变分布规律。结果表明:沉降与非沉降交界处管道应变及应力最大，基于应变的评估准则，管道运行状态为安全，为应急响应提供支撑。     

基于社会技术系统的复工企业疫情防控风险路径研究*

为对复工企业疫情防控中的风险致因因素进行分析，探寻复工企业疫情防控的风险路径，基于社会技术系统理论，建立宏观工效学模型，通过查阅并分析国家、地方政府、企业文件以及相关文献，从人员、技术、组织管理、内部环境及外部环境5个子系统出发，识别出16个复工企业疫情失控致因因素；运用社会网络分析（SNA）构建复工企业疫情防控关系网络，对各因素节点中心度进行计算，分析各节点在网络中的位置及影响程度；采用贝叶斯网络（BN）进行参数学习和推理学习，找出复工企业疫情失控的最大致因链。结果表明:复工企业疫情失控关系网络中，存在政府监督管理不力→防疫物资筹备不足→日常监管不到位，政府监督管理不力→ 防疫宣传、培训缺失→员工防疫知识欠缺，政府监督管理不力→防疫宣传、培训缺失→日常监管不到位3条最长风险路径。研究结果可帮助复工企业针对最长风险路径中的因素进行管理，从而有效地为复工企业防疫提供理论支持。     

Failure mode and effect analysis using regret theory and PROMETHEE under linguistic neutrosophic context

Failure mode and effect analysis (FMEA), which aims to identify and assess potential failure modes in a system, has been widely utilized in diverse areas for improving and enhancing the performance of systems due to it is a powerful and useful risk and reliability assessment instrument. However, the conventional FMEA approach has been suffered several criticisms for it has some shortcomings, such as unable to handle ambiguous and uncertain information, neglect the relative weights of risk criteria, and without considering the psychological behaviors of decision-makers. To ameliorate these limitations, this paper aims at establishing a hybrid risk ranking model of FMEA via combing linguistic neutrosophic numbers, regret theory, and PROMETHEE (Preference ranking organization method for enrichment evaluation) approach. In the presented model, linguistic neutrosophic numbers are adopted to capture decision-makers’ evaluation regarding the failure modes on each risk criterion. A modified PROMETHEE approach based on regret theory is presented to obtain the risk priority of failure modes considering the psychological behaviors of decision-makers. Moreover, a maximizing deviation model and TOPSIS (Technique for order preference similar to ideal solution) are separately applied to derive the weights of risk criteria and decision-makers. Finally, a numerical example relating to the supercritical water gasification system is employed to implement the presented method, and the effectiveness and feasibility of the proposed model are validated by the results derived from a sensitivity and comparison analysis.     

14个有价值的城市安全系统学理论基础问题

安全系统学是安全科学的核心基础理论,很适用于研究城市系统安全问题。本文从认识论和本体论出发阐述系统发生事故的本质原因,归纳了城市安全需要研究全生命周期与全球视野问题、微系统—中系统—宏系统耦合匹配问题、可持续—智慧—公共服务—多系统—生活生产安全—公共安全协同问题、输入与输入平衡关系、应急与涌现关系、信息与安全情报关系、安全管理与自组织关系、复杂城市与复杂科学关系,简述本质安全并非基础设施安全、风险管理需要精准安全、韧性并非物理性问题,认为使命—人—机—物—管—环—信—文的体系,以及工程—教育—管理—文化等对策应赋予新的安全内涵。上述内容是城市系统安全学的重要理论基础问题。     

北京垃圾分类工作现存问题与对策建议

《北京市生活垃圾管理条例》实施以来,北京垃圾分类工作取得“六升两降”八项成效。基于现阶段北京垃圾分类工作推进情况与存在的痛点、难点问题,提出通过购买第三方服务、借助科技手段与工具、多种渠道多种方式相结合、建立长效监督评价机制等方式,为顺利推进北京垃圾分类工作提供参考。     

Identifying socioeconomic and biophysical factors driving forest loss in protected areas

Protected areas (PAs) are a commonly used strategy to confront forest conversion and biodiversity loss. Although determining drivers of forest loss is central to conservation success, understanding of them is limited by conventional modeling assumptions. We used random forest regression to evaluate potential drivers of deforestation in PAs in Mexico, while accounting for nonlinear relationships and higher order interactions underlying deforestation processes. Socioeconomic drivers (e.g., road density, human population density) and underlying biophysical conditions (e.g., precipitation, distance to water, elevation, slope) were stronger predictors of forest loss than PA characteristics, such as age, type, and management effectiveness. Within PA characteristics, variables reflecting collaborative and equitable management and PA size were the strongest predictors of forest loss, albeit with less explanatory power than socioeconomic and biophysical variables. In contrast to previously used methods, which typically have been based on the assumption of linear relationships, we found that the associations between most predictors and forest loss are nonlinear. Our results can inform decisions on the allocation of PA resources by strengthening management in PAs with the highest risk of deforestation and help preemptively protect key biodiversity areas that may be vulnerable to deforestation in the future.