斜拉桥支架法施工的自适应安全监测技术

介绍自适应控制的基本原理及其运用现状。根据斜拉桥的实际情况选用自适应控制形式,在主要部位埋设传感器和相关的测试仪器,明确监测时间并在实施中严格执行。依据实测结果对标高、应力、容重等参数按实际情况进行修正,得出施工过程中的受力状态,从而调整施工。算出主梁各节点理论施工预拱度变化曲线等数据并与实测值进行比较,反复修正。自适应法达到了仿真计算与实际施工过程保持一致的最佳施工控制效果。绥芬河斜拉桥的施工证明,自适应法是一种很适合斜拉桥支架施工安全监测的技术,值得推广应用。     

Long‐Term Dynamics of a Fragmented Rainforest Mammal Assemblage

Abstract: Habitat fragmentation is a severe threat to tropical biotas, but its long‐term effects are poorly understood. We evaluated longer‐term changes in the abundance of larger (>1 kg) mammals in fragmented and intact rainforest and in riparian “corridors” in tropical Queensland, with data from 190 spotlighting surveys conducted in 1986–1987 and 2006–2007. In 1986–1987 when most fragments were already 20–50 years old, mammal assemblages differed markedly between fragmented and intact forest. Most vulnerable were lemuroid ringtail possums (Hemibelideus lemuroides), followed by Lumholtz's tree‐kangaroos (Dendrolagus lumholtzi) and Herbert River ringtail possums (Pseudocheirus herbertensis). Further changes were evident 20 years later. Mammal species richness fell significantly in fragments, and the abundances of 4 species, coppery brushtail possums (Trichosurus vulpecula johnstoni), green ringtail possums (Pseudochirops archeri), red‐legged pademelons (Thylogale stigmatica), and tree‐kangaroos, declined significantly. The most surprising finding was that the lemuroid ringtail, a strict rainforest specialist, apparently recolonized one fragment, despite a 99.98% decrease in abundance in fragments and corridors. A combination of factors, including long‐term fragmentation effects, shifts in the surrounding matrix vegetation, and recurring cyclone disturbances, appear to underlie these dynamic changes in mammal assemblages.     

论可持续发展视野中的农村社会支持

本文阐述了如何可持续发展观来指导农村社会支持，并提出在农村社会支持活动中，引进社会保险、社会服务、生态保护和心理培育等新的机制，运用综合性评价指标体系对各种农村社会支持项目及其结果进行经济效益、社会效益和心理效益三个方面的分析。     

基于FTA-SVM的车辆发动机故障识别方法

发动机结构日益复杂,其故障具有多样性和频发性的特点,收集大量故障样本存在很多实施障碍。为了提高车辆发动机的故障识别的效率和准确性,提出了一种新的结合故障树(FTA)和支持向量机(SVM)各自特点,从故障模式分析到故障类型识别的FTA-SVM故障识别方法。首先利用故障树在复杂系统故障模式分析中的优势,找出系统的故障模式,建立故障树模型,通过对故障树模型中各故障事件的分析,采集与故障事件状态相关的数据,建立数据与故障树底事件的映射模型,最后利用支持向量机在小样本数据处理中的优势,进行故障类型的识别。以发动机的失火故障为例建立了发动机失火故障树模型及故障数据与故障模式映射模型,验证了FTA-SVM方法的有效性和适用性。     

基于MDE和分形优化SVM的周期来压预测

为了解决周期来压的预测问题,首先对已知支架周期来压荷载曲线使用多重差异进化算法(MDE)进行拟合,将每重拟合形成的单一正弦曲线与上次差余曲线(Ei)再作差余曲线(Ei+1)。将这些Ei图通过分形几何的盒子法计算维度和相关系数(r)。将每条Ei的维度、r和支架相对距离(L)作为输入值,对应的Ei的周期Ti、缩放系数Si和纵移系数Di作为目标值,使用支持向量机(SVM)进行训练。通过对维度和r规律的研究得到拟设置支架处荷载各Ei的维度和r,带入训练后的SVM模拟得到Ei的Ti、Si和Di,进而得到Ei的表达式。将上述Ei求和即为所求拟设置支架处的周期来压荷载。实例分析说明,该种方法预测结果可以大体反映支架周期来压的基本形式和变化规律。     

Implementing SDG 15: Can large‐scale public programs help deliver biodiversity conservation,restoration and management,while assisting human development?

Among the Sustainable Development Goals (SDGs), the proposed SDG 15 promotes activities that, inter alia, “Protect, restore and promote sustainable use of terrestrial ecosystems”. An important potential contribution in achieving SDG 15 is through public programmes designed to jointly promote human development through poverty alleviation and improvement of human livelihoods and biodiversity conservation/management/restoration. An analysis of twenty public programmes with such joint objectives yielded twelve lessons learned. In addition to financial commitments, government and intergovernmental agency input for such public programmes includes ensuring political will and appropriate legal frameworks. Local communities and civil society provide input through traditional and indigenous ecological knowledge and stewardship. Appropriate shared inputs in development and the implementation of such public programmes, with communication between local community, broader civil society, the scientific community and governments will result in: better use and management of biodiversity; alleviation of poverty; security of livelihoods and better governance systems. The Ecosystem Approach of the Convention on Biological Diversity provides an ideal framework when planning and implementing new programmes. Application of the lessons learned to new public programmes will ensure that the answer to the question posed in the title is an emphatic “Yes”, and assist with the achievement of SDG 15.     

The role of situation awareness in accidents of large-scale technological systems

In the last two decades, several serious accidents at large-scale technological systems that have had grave consequences, such as that at Bhopal, have primarily been attributed to human error. However, further investigations have revealed that humans are not the primary cause of these accidents, but have inherited the problems and difficulties of working with complex systems created by engineers. The operators have to comprehend malfunctions in real time, respond quickly, and make rapid decisions to return operational units to normal conditions, but under these circumstances, the mental workload of operators rises sharply, and a mental workload that is too high increases the rate of error. Therefore, cognivitive human features such as situation awareness (SA)—one of the most important prerequisite for decision-making—should be considered and analyzed appropriately. This paper applys the SA Error Taxonomy methodology to analyze the role of SA in three different accidents: (1) A runaway chemical reaction at Institute, West Virginia killing two employees, injuring eight people, and requiring the evacuation of more than 40,000 residents adjacent to the facility, (2) The ignition of a vapor cloud at Bellwood, Illinois that killed one person, injured two employees, and caused significant business interruption, and (3) An explosion at Ontario, California injuring four workers and caused extensive damage to the facility. In addition, the paper presents certain requirements for cognitive operator support system development and operator training under abnormal situations to promote operators’ SA in the process industry.     

岩溶塌陷倾向性等级的KPCA-SVM预测模型

为了快速、有效地预测岩溶塌陷倾向性等级,在统计分析大量观测实例的基础上,选取岩性系数、岩体结构系数、地下水系数、覆盖层系数、地形地貌系数和环境条件系数作为特征指标。利用核主成分分析(KPCA)方法在高维空间提取岩溶塌陷影响因子的主成分,将获取的主成分作为支持向量机(SVM)的特征向量,建立基于KPCA的岩溶塌陷倾向性等级的SVM预测模型。将12组观测数据作为学习样本对模型进行训练。采用回代估计法进行回检,误判率为0。利用训练好的模型对2组待判样本进行预测。结果表明:经KPCA后指标个数减少,相关性降低,SVM运算的复杂度降低。用该模型所得预测结果的准确率为100%。     

水资源环境承载能力监测预警平台设计探讨

建立水资源环境承载力监测预警平台与机制,是实现我国环境管理战略由以环境污染控制为目标导向,向以环境质量改善为目标导向彻底转变的重要支撑手段。以水资源环境承载力领域的相关研究进展为基础,提出水资源环境承载力监控预警平台的设计框架,平台设计的逻辑结构、核心功能以及相对应的水资源环境承载力评估技术,并对该平台建设的困难、问题及未来的发展趋势进行了分析,以期为水资源环境承载能力监测预警机制建设提供有益的参考。     

战场环境下装备保障信息系统安全风险与防护

目的研究战场环境下装备保障信息系统的安全问题。方法从装备保障及装备保障信息系统的概念、分类和复杂战场环境下装备保障信息系统所面临的安全威胁入手,依照五分法把装备保障信息系统安全风险划分为5个等级,推导出风险评估模型,提出实施装备保障信息系统安全防护的技战术策略。结果战场环境下,为确保整个作战进程中装备保障活动安全、有效、稳定地进行,装备保障信息系统防护必须遵循统一协调、综合利用的积极防护原则,采用有效的风险控制措施加以应对。结论通过积极探索和发展装备保障信息安全与防护理论,找准战场环境信息防护中存在的薄弱环节,制定了装备保障信息安全防护策略,加强装备保障信息系统的安全管理工作,最终提高我军装备保障信息系统的防护能力。