长江中下游盛夏持续性高温干旱对短期降水影响的数值试验

应用IAP 2-L AGCM模式,并考虑了下垫面异常,模拟了长江中下游盛夏不同强度的持续性地表高温干旱对短期天气的影响。结果表明,这种持续性高温干旱对长江中下游及我国东南沿海短期降水有十分明显的影响,持续高温干旱的强度不同,其影响结果不同。持续性适度高温和严重干旱造成短期降水减少,高温干旱仍继续维持达1个月的正反馈过程。在此持续过程中,土壤湿度变化起主导作用,而土壤热力状况的影响相对较小。     

深水钻井隔水管紧急脱离后的反冲响应

深水钻井中,在恶劣海况或浮式平台定位失效等情况下,需紧急断开隔水管与水下防喷器的连接。隔水管突然脱离后会加速向上反冲,如果反冲作用控制不当,可能威胁钻井平台、隔水管体和水下井口的安全。介绍了国外隔水管紧急脱离与反冲响应的研究情况,分析了隔水管紧急脱离的原因与程序、脱离后的反冲过程、反冲控制方式和成功脱离标准、反冲响应的分析方法。建议:由于南海深水海况复杂,作业者需制定紧急脱离的预案和作业规程,并进行紧急脱离操作培训;由于隔水管紧急脱离后的反冲响应涉及多个非线性瞬态过程,研究者应该开展隔水管紧急脱离测试和反冲响应模拟计算,开发隔水管反冲响应分析软件。     

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经济空间场与ESDA结合的公共卫生事件应急策略制定

新型冠状病毒肺炎疫情引起了人们对国家公共卫生事件应对能力的广泛关注。基于波及效应梯度场提出了生产诱发梯度,进一步完善了经济空间场理论,并将其与探索性空间数据分析(exploratory spatial data analysis,ESDA)相结合,对医药制造业波及效应及空间布局进行了研究,制定了有效的公共卫生事件应急策略。经济空间场理论分析结果揭示了产业经济空间中医药制造业与各产业部门之间的波及效应,并由此得到了医药密切相关产业。同时,经济空间场理论与ESDA方法的结合能在区分中国大陆各省空间聚集类型的基础上,评估各省公共卫生事件的应对能力,从而为各省提出相应的应急策略和医药制造业发展建议。该方法综合考虑了产业波及效应和产业空间布局现状,不仅能够促进各省医药制造业的健康合理发展,也有助于增强各省突发公共卫生事件的应对能力。     

北斗卫星通信在应急自动气象站中的应用

为了能够在发生灾难事故时进行紧急通信,应急自动气象站采用了北斗卫星导航定位系统的简短通信技术。在北斗卫星通信方式设计过程中,采取压缩数据包长度、主动传输+失败应答通信模式、对通信终端采取休眠工作等方式,在保证数据传输质量的同时减少不必要的通信次数,降低系统功耗,延长工作时间。研究结果表明,采用本文的通信设计,可以实现:1)将数据包长度压缩60%,满足了北斗卫星短信包的长度要求。2)兼顾解决了数据完整性问题和通信资费问题,在正常工作状态下采用自动定时传输模式节约通信资费;在通信失败的情况下采用主从应答通信模式,通过向自动气象站发出数据补收命令,及时取得丢失的数据。3)有效地降低了系统的功耗,通信终端平均功耗下降了10%。     

洼地开采地下水的地质环境效应研究——以天津市黄港洼应急水源地为例

天津市是我国水资源缺乏、人均占有淡水资源最少的城市之一,也是我国地面沉降最为严重的地区之一。地面沉降现已成为天津市的主要地质灾害,并在一定程度上制约着天津城镇的可持续发展。天津市平原区洼地众多,这些洼地大部分是天津市的湿地分布区。在洼地内建设应急地下水水源地,既可以起到为城区供水,缓解城区的地面沉降,又可以改善洼地生态环境的作用。     

冰雪灾害条件下地质灾害应急抢险处置知识构成分析

知识库是冰雪灾害条件下地质灾害应急抢险决策支持系统的核心,知识库中的知识构成则是整个研究的基础。本文按照产生式规则法的知识表示方式,分别分析了冰雪灾害条件下地质灾害应急抢险处置知识的前提及结论部分的主要构成内容,并总结了应急抢险处置措施选择应该遵循的基本原则,另外还给出了根据知识构成抽取具体知识的范例,为冰雪灾害条件下地质灾害应急抢险知识库及决策支持系统的建立提供了基础性研究成果。     

Modeling and representation for earthquake emergency response knowledge: perspective for working with geo-ontology

Earthquake emergency response is one of the three earthquake disaster mitigation work systems in China, already achieving good results in some earthquake disaster mitigation situations. Earthquake emergency plans and emergency command systems are among the most important research and operations components of emergency response. These components commonly come with challenges, such as the pertinence of emergency commands and the operability of the countermeasures to be improved. The promise for solving this problem resides with applying knowledge that aids intelligence creation for decision-making. In this paper, we put forward a conceptual model of knowledge for earthquake disaster emergency response (EDER); compositions of EDER knowledge are introduced within architecture. A modeling method incorporating geo-ontology is used to build basic modeling primitives. Geo-ontology serves to represent geospatial characteristics of the EDER knowledge and addresses a need for semantic interoperability in the modeling process. A decision problem framework and a case study have been used as theoretical framework and an application test, respectively, to evaluate the EDER knowledge architecture and models. The EDER knowledge model provides a foundation for intelligent emergency response that helps solve knowledge problems to improve earthquake disaster response.     

Airborne near-real-time monitoring of assembly and parking areas in case of large-scale public events and natural disasters

A critical requirement for an effective and coordinated response by public entities tasked with management, security, and relief during large-scale public events or natural disasters is the availability of current situational information. However, today there is a lack of comprehensive operational systems allowing a near-real-time (NRT) collection, visualization, and provision of situational information for larger areas. In this study a methodological framework is proposed, which allows an NRT extraction and visualization of situational information based on aerial image acquisition. The framework combines digital image analysis using a generic supervised information extraction approach based on statistical modeling with a downstream web-based visualization component realized through an automatic update of web services. Even though being applicable for different scenarios, the workflow will be demonstrated for the specific use-case of a NRT monitoring of open spaces including assembly and parking areas. Compared to other approaches, image analysis results indicate a high robustness and a low demand for computational power sources (7 seconds per image). Due to a high degree of automation, the proposed workflow contributes to a NRT ‘end-to-end’ monitoring system, which was developed within the VABENE (German acronym for ‘traffic management under large-scale public events and disaster conditions’) project covering all parts from the acquisition of raw aerial imagery to the dissemination of information products to end-users.     

基于文本挖掘词频反文档频率方法的疾病症状权重挖掘研究

词频反文档频率是文档特征权值表示的常用方法,用以评估单词对于语料库中的其中一份文件的重要程度。通过合理映射病例库与语料库的词汇关系,对词频反文档频率模型进行改进,并将改进后的词频反文档频率模型应用到针灸处方疾病症状权重挖掘中,计算出疾病所对应的各种症状权重。实验统计了106种疾病,其中与临床诊疗经验相符合的有84种,准确率达79.2%,实验表明改进的模型能得到较好的疾病症状权重鉴别效果。