强震作用下铁路隧道横通道交叉结构抗震措施研究

依托四川茂县跃龙门铁路隧道工程,以主线单线隧道与横通道正交结构为研究对象,通过ABAQUS建立有限元分析模型。选取El-Centro地震波数据,通过应用扩展有限元理论,对横通道与主隧道交叉结构在最不利地震条件下的裂损进行研究,并提出减震层结合柔性接头的抗震措施。研究分析得到:减震层结合柔性接头的设置减小并抑制了交叉结构隧道在强震作用下的开裂范围。柔性接头的设置阻止了纵向裂缝的扩展,在交叉口处中部设置环向柔性接头能完全阻止交叉部位拱顶的裂缝生成;在初期支护和二次衬砌之间设置减震层,给予衬砌更大变形空间,使二次衬砌不易受初期支护变形受力影响而开裂。     

微囊藻CO2-浓缩机制基因型的动态变化及其对CO2的竞争效应

由于具有高效的CO₂-浓缩机制,蓝藻在低CO₂浓度条件下具有竞争优势。然而,随着大气中CO₂浓度急剧增加,蓝藻CO₂-浓缩机制如何响应的研究较少。因此,本文以常见水华蓝藻——微囊藻为研究对象,通过对滇池微囊藻水华动态及不同CO₂-浓缩机制基因型进行监测,探讨蓝藻CO₂-浓缩机制基因的微进化特征及其动态变化。同时,设置高(0.08%)、中(0.04%)、低(0.02%)CO₂浓度(V/V)进一步揭示微囊藻不同CO₂-浓缩机制基因微进化对CO₂的竞争效应。结果表明:滇池无机碳浓度在4个采样点存在空间差异性,均呈现先降低后升高的趋势,并以HCO₃^-为主要无机碳存在形式。调查期间,东大河、观音山、洛龙河和生态所4个采样点的微囊藻均以sbtA基因型占绝对优势,相对丰度远高于bicA基因型。在不同水华时期,bicA基因型和sbtA基因型呈现相反的变化趋势,即从...     

1988-2016年洞庭湖大型底栖动物群落变化及驱动因素分析

洞庭湖是我国第二大淡水湖泊,其水文条件对湖泊湿地生态系统健康的维系发挥着不可替代的作用.近年来,水环境恶化日益威胁湖区水生态系统健康.然而,有关底栖动物水生态健康评价的研究仍然停留在物种群落结构方面,缺乏底栖动物群落功能对水污染响应的研究,尤其在较长时间尺度上.因而,本研究分析了19882016年近30 a来洞庭湖的水质和底栖动物群落数据,探寻底栖动物群落功能对水环境恶化的响应规律.结果表明,洞庭湖水体总氮浓度是威胁底栖动物物种和功能群落变动的主要因素.此外,不断恶化的水环境驱动底栖动物物种和功能群落结构改变,表现为敏感水生昆虫的比例下降,寡毛类、小型软体动物比例的上升,并伴随着体长为1.00~1.99 cm、背扁型、侧扁型、不移动等功能性状类别比例的下降.同时,水环境恶化降低物种丰富度、功能丰富度和劳氏二次熵多样性.基于距离的冗余分析结果显示,水体氮营养盐、重金属离子和有机污染物共同驱动底栖动物物种群落结构的变异,而营养盐类与无/有机污染物决定着其功能群落结构的变异.鉴于洞庭湖水质不断恶化的状况,本研究建议采取一系列措施,包括合理管控湖区周边废水直排入湖、取缔湖区内的非法采砂以及调控枯水季洞庭湖水位等.生物监测和评价方面,建议将底栖动物物种和功能群落一并纳入评价体系,且优先选用物种丰富度、功能丰富度和劳氏二次熵指数评估换水周期较短的大型浅水湖泊水质变化对底栖动物物种和功能多样性的影响.     

Innovative Techniques for Measuring the Oil Content of Oil-Contaminated Porous Media

The oil content of oil-contaminated porous media is an important parameter for the assessment and remediation of oil pollution in soil and groundwater. However, an accurate measurement method is not available. In this study, we propose a new equation to calculate the oil content of water-bearing media based on traditional extraction–ultraviolet spectroscopy. Further, an improved experimental method was developed. The results indicate that the pure solid weight and oil content of oil-contaminated media can be accurately determined by introducing the oil drying loss coefficient (γ). The average relative errors of the improved method range from −0.14% to −0.96%. They are much smaller than errors of −4.49% to −10.97% of the original methods, indicating that the accuracy of measured oil content is enhanced. In addition, the accuracy of the new method does not depend on oil volatility and oil content.     

应急管理部多层级视频会议系统跨网段转发技术

介绍应急管理部视频会议系统接入地震系统的基本情况,结合地震应急视频会议系统应用现状,分析多层级跨网视频会议系统的架构特点,着重分析跨网段"背靠背"转发优化技术方案在视频会议系统融合中的实现与应用,以期为类似的应用场景提供参考。     

2017年九寨沟MS 7.0地震震源深度测定

为了更好地确定2017年8月8日九寨沟M_(S )7.0地震震源深度其发震机理,利用四川、甘肃和青海区域地震台网的观测波形数据,采用多种方法研究了此次地震的震源深度。首先,采用gCAP方法反演了九寨沟M_(S )7.0地震的震源机制解和矩心深度,结果显示,节面Ⅰ走向243°/倾角87°/滑动角-158°,节面Ⅱ走向151°/倾角68°/滑动角-3°,矩震级为M_(W )6.5,矩心深度为8 km;然后,采用ISOLA近震全波形方法反演了此次地震的震源机制解,反演结果与gCAP方法结果相差不大,矩心深度为7 km;最后,通过sPn震相与Pn震相之间的走时差测定此次地震初始破裂震源深度,结果显示深度约为12 km。研究表明,九寨沟M_(S )7.0地震的矩心深度为7—8 km,初始破裂深度约为12 km。     

面向地震巨灾保险的建筑特性快速提取方法

房屋建筑分类是抗震设计和地震风险分析的基础,是巨灾保险的纽带环节,也是结构易损性准确、完备分析的前驱保障,快速获取建筑特性参数非常关键。基于影像数据获取结构特性相比传统手段具有显著优势,然而其准确性具有一定挑战性,从影像数据得到实时的、较准确的结构特性成为地震保险数据获取技术的关注焦点。本文采用深度学习方法开展从影像数据中提取面向地震保险需求的建筑特性数据,构建基于深度学习方法的建筑高度识别模型和基于机器视觉的建筑高度识别方法,运用基于Xception神经网络深度学习和机器视觉的模型,对北京地区的建筑高度进行模型测试,该方法可为地震保险分析提供重要的基础数据支持。     

Numerical investigation on special modes with narrow amplification diagram in harbor oscillations

Ocean Dynamics - In the studies of harbor oscillations, some modes with extremely narrow amplification diagram are significantly common. An extended mild-slope equation and a fully nonlinear...     

Evaluation of multidecadal and longer-term temperature changes since 850 CE based on Northern Hemisphere proxy-based reconstructions and model simulations

The temperature variability over multidecadal and longer timescales(e.g., the cold epochs in the late 15 th, 17 th, and early 19 th centuries) is significant and dominant in the millennium-long, large-scale reconstructions and model simulations;however, their temporal patterns in the reconstructed and simulated temperature series are not well understood and require a detailed assessment and comparison. Here, we compare the reconstructed and simulated temperature series for the Northern Hemisphere(NH) at multidecadal and longer-term timescales(30 years) by evaluating their covariance, climate sensitivity and amplitude of temperature changes. We found that covariances between different reconstructions or between reconstructions and simulations are generally high for the whole period of 850–1999 CE, due to their similar long-term temporal patterns. However,covariances between different reconstructions or between reconstructions and simulations steadily decline as time series extends further back in time, becoming particularly small during Medieval times. This is related to the large uncetainties in the reconstructions caused by the decreased number of proxy records and sample duplication during the pre-instrumental periods.Reconstructions based solely on tree-ring data show higher skill than multiproxy reconstructions in capturing the amplitude of volcanic cooling simulated by models. Meanwhile, climate models have a shorter recovery(i.e., lag) in response to the cooling caused by volcanic eruptions and solar activity minima, implying the lack of some important feedback mechanisms between external forcing and internal climate processes in climate models. Amplitudes of temperature variations in the latest published tree-ring reconstructions are comparable to those of the multiproxy reconstructions. We found that the temperature difference between the Medieval Climate Anomaly(950–1250 CE) and the Little Ice Age(1450–1850 CE) is generally larger in proxybased reconstructions than in model simulations, but the reason is unclear.     

Pollen-based Holocene quantitative temperature reconstruction on the eastern Tibetan Plateau using a comprehensive method framework

Quantitative climate reconstruction on long timescales can provide important insights for understanding the climate variability and providing valuable data for simulations. Unfortunately, the credibility of some attempts was hampered by incomplete reconstruction procedures. We here establish a comprehensive framework resting on high-quality Chinese modern pollen database, including modern pollen data screening, calibration set selection, major climate factor analysis, appropriate model selection, strict statistical assessment of results and ecological interpretation. The application of this framework to three high-resolution pollen records from the eastern Tibetan Plateau allows accurate quantitative inferences of Holocene temperature changes, which is the major control of regional vegetation. The results show that the mean warmest month temperature(MTwa)during the early Holocene was ca. 10.4℃ and reached the highest value at 8.5–6 ka BP(ca. 11℃). The early and mid-Holocene(11–5 ka BP) warmth was followed by 1.2℃ temperature decrease, culminating in the coolest temperatures of the Holocene during the Neoglacial cooling. Superimposing on the general cooling trend, MTwareveals a significant 500-yr periodicity with varying intensities through time, showing that warm(cold) intervals are in phase with solar maxima(minima) periods. This spectral similarity indicates a possible connection of multi-century scale climate fluctuations with solar forcing.