导管架平台拆除过程稳定性及影响因素分析

现有服役海洋平台正逐步走向老龄化,海洋平台拆除成为海洋工程新的经济增长点。针对达到服役年限的导管架平台,基于数值分析方法模拟拆除过程,开展平台在不同拆除阶段和环境载荷等参数下的稳定性及影响规律研究。基于钢结构整体稳定性理论,以导管架平台拆除过程中顶点位移为参考,定义导管架平台拆除作业稳定性指标,提出拆除作业阶段划分方法,通过分析导管架平台在不同影响因素作用下拆除过程稳定性响应,给出拆除作业建议。选取我国南海某4裙12腿进行实例分析,结果表明:主桩腿对导管架平台起决定性承载作用,拆除部分主桩腿后需要引入外部支撑力,以保证拆除作业安全进行;拆除构件越多,来浪方向和环境载荷大小对平台影响越加显著。研究结果可为导管架平台拆除作业提供参考。     

遗传算法优化的BP神经网络卫星钟差预报

针对BP (Back Propagation)神经网络模型预测卫星钟差中权值和阈值的最优化问题, 提出了基于遗传算法优化的BP神经网络卫星钟差短期预报模型, 给出了遗传算法优化BP神经网络的基本思想、具体方法和实施步骤. 为验证该优化模型的有效性和可行性, 利用北斗卫星导航系统(BeiDou navigation satellite system, BDS)卫星钟差数据进行钟差预报精度分析, 并将其与灰色模型(GM(1,1))和BP神经网络模型预报的结果比较分析. 结果表明: 该模型在短期钟差预报中具有较好的精度, 优于GM(1,1)模型和BP神经网络模型.     

Terrestrial heat flow and lithospheric thermal structure in the Chagan Depression of the Yingen-Ejinaqi Basin,north central China

The Chagan Depression in the Yingen-Ejinaqi Basin, located at the intersection of the Paleo-Asian Ocean and the Tethys Ocean domains is an important region to gain insights on terrestrial heat flow, lithospheric thermal structure and deep geodynamic processes. Here, we compute terrestrial heat flow values in the Chagan Depression using a large set of system steady-state temperature data from four representative wells and rock thermal conductivity. We also estimate the “thermal” lithospheric thickness, mantle heat flow, ratio of mantle heat flow to surface heat flow and Moho temperature to evaluate the regional tectonic framework and deep dynamics. The results show that the heat flow in the Chagan Depression ranges from 66.5 to 69.8 mW/m², with an average value of 68.3 ± 1.2 mW/m². The Chagan Depression is characterized by a thin “thermal” lithosphere, high mantle heat flow, and high Moho temperature, corresponding to the lithospheric thermal structure of “cold mantle and hot crust” type. We correlate the formation of the Yingen-Ejinaqi Basin to the Early Cretaceous and Cenozoic subduction of the western Pacific Plate and the Cenozoic multiple extrusions. Our results provide new insights into the thermal structure and dynamics of the lithospheric evolution in central China.     

中国铁路客运流联结的城市时间可达性

基于中国铁路客户服务中心提供的客运流数据,采集全国地级以上行政单元（未含港澳台数据）间铁路客运运行的最短历时,基于GIS网络分析和空间分析等方法,选取时间可达性和一日交流圈2个指标对城市可达性进行测度和分析。研究发现： ① 城市时间可达性水平划分为7个级别,在空间上呈现中心-外围式圈层结构,中心区域沿铁路干线和高速铁路线轴向扩展,廊道效应明显,东部、中部地区的城市时间可达性优于西部地区。② 城市之间的时间可达性小于2.0 h的城市对在空间上构成了由京广、京沪、京哈、京福、杭深、青太、徐兰、沪汉蓉、沪昆、广昆等高速铁路连接的“五纵五横”带状分布格局。时间可达性小于10.0 h的城市对覆盖了“胡焕庸线”东南部的大部分区域,城市带转为城市网络。③ 直辖市、省会/首府城市一日交流圈以31个城市为中心,按照时间可达性由小到大呈现轴向扩展,廊道效应明显。基于城市一日交流圈划分了19个城市群和拉萨城市圈,为城市群的划分提供方法借鉴。     

科尔沁湿草甸参考作物蒸散发模拟分析

为探明气候变化下干旱半干旱地区湿草甸参考作物蒸散发(ET₀)影响因子,使用FAO 56 P-M模型对科尔沁湿草甸ET₀进行模拟,利用涡度相关系统对模型的适用性进行评价,并通过通径分析及指标敏感性分析对ET₀的影响因子进行辨识。结果表明:(1)小时尺度模拟精度最高,日尺度次之,月尺度较差,小时尺度上晴、阴、雨3种天气条件下模拟效果不同,晴天最优,阴雨天较差。(2)ET₀年内变化呈单峰曲线状,生长季明显高于非生长季,集中在3—10月,占全年89.79%。生长季典型晴天ET₀逐小时分布特征遵循倒“U”单峰型变化规律。(3)通径分析结果显示,对ET₀的通径系数以及对回归方程估测可靠程度E的总贡献均表现为VPD(饱和水汽压差) > T_min(最低气温) > R_n(冠层表面净辐射)>u₂(2 m高度风速),即VPD为影响ET₀最重要的因子;指标敏感性分析中,在去除VPD后引起的E变化最大,说明ET₀对VPD的变化最为敏感,其次为u₂、T_min和R_n。     

“一带一路”建设背景下重庆与东盟国家贸易格局演变和影响因素分析

“贸易畅通”是“一带一路”建设的重要内容,重庆作为中国西部地区内陆开放高地,贸易发展优势明显。运用贸易强度指数和HM指数,分析2001—2017年重庆与东盟国家贸易格局和贸易依赖程度,并分析影响重庆与东盟国家贸易格局的影响因素。结果表明：①重庆与东盟国家贸易联系紧密,增长速度快,贸易总额在“一带一路”沿线六大区域中始终保持领先地位;②马来西亚和泰国成为重庆与东盟国家中最重要的贸易伙伴,越南、新加坡、菲律宾和印度尼西亚紧随其后,而与缅甸、柬埔寨、老挝和文莱的贸易总额较少;③在进口方面,形成以马来西亚、泰国和越南为首的多元进口格局,泰国和越南进口伙伴地位上升。在出口方面,形成以马来西亚为首的多元出口新格局,越南出口地位下降;④在市场相互依赖程度方面,重庆出口对东盟国家特别是马来西亚和新加坡贸易市场的重要性程度上升,而对东盟国家市场依赖程度较小;⑤产业结构、贸易通道、文化交流和政策等是影响重庆与东盟国家贸易格局的重要影响因素。     

“一带一路”沿线国家石油资源流动类型演变

综合运用石油自给率、流动比率等方法,以“一带一路”沿线国家为研究对象,对1995—2014年各国石油资源流动类型时空演变进行研究。结果表明：1）1995—2014年石油净补给型国家数量较为稳定,无产型或低产型国家的石油贸易倾向变化相对较小;基本自给型国家数量占比最大,1995年占比1/2,其余四个年份占比稳定在1/3;净支出型国家数量显著增加,至2014年其中有5个国家保持不变,表明这些国家的石油产量具有较大的优势。2）1995年和2014年汇地国家均为39个国家,其中有34个国家一直保持汇地职能,空间分布上呈东多西少,南多北少,东西分化以西亚、中亚、东欧为界;有14个国家一直保持源地职能,其空间分布格局与汇地相应,西多东少,南多北少,主要分布于西亚、东欧及中亚;交流地数量较少,呈分散分布,且分布地不稳定。3）从数量变化来看,研究期内汇地略有增加,源地略有减少,交流地略有增加;“一带一路”源地总出口量与汇地总进口量的比呈逐年降低趋势。     

东北地区水稻扩张的海拔优势区间分析

及时掌握水稻的时空分布信息,对调整和优化农业生产结构至关重要。论文利用综合考虑植被物候和地表水变化的水稻自动制图方法,结合海拔、地表水体因素开展2001—2017年东北地区水稻分布的时空演变研究。通过889个地面调研点位对水稻分类结果验证,总体精度达90.66%,Kappa系数为0.8128。研究表明:① 21世纪初,东北地区水稻种植面积呈先略减后持续增加的趋势,2017年水稻种植面积达2001年的2.13倍。其中,水稻扩张面积的60%分布在三江平原,30%分布在松嫩平原,下辽河平原仅占不足5%。水稻扩张的海拔优势区间在200 m范围内,随着海拔的上升水稻扩张与地表水关系越来越密切。② 三江平原内,水稻扩张幅度在海拔30~70 m范围内逐渐增加,使优势区间从相对高度70 m缩减至40 m内,也使得分布优势逐渐趋向于距地表水体较远的区域。而松嫩平原和下辽河平原水稻种植分布的海拔优势区间始终分别保持在相对高度100 m、40 m内。③ 三江平原水稻的集中分布和急剧扩张,使水稻分布优势逐渐趋向于距地表水体远的区域,这将对地下水带来更大的压力;而松嫩平原水稻分布受地表水体影响较大,分布优势随着距地表水体距离的增加而减小。研究可为农业部门评估水资源承载力、保障农业可持续发展提供数据支撑及理论参考。     

Winter cover crops in Dutch maize fields: Variability in quality and its drivers assessed from multi-temporal Sentinel-2 imagery

Planting a cover crop between the main cropping seasons is an agricultural management measure with multiple potential benefits for sustainable food production. In the maize production system of the Netherlands, an effective establishment of a winter cover crop is important for reducing nitrogen leaching to groundwater. Cover crop establishment after maize cultivation is obliged by law for sandy soils and consequently implemented on nearly all maize fields, but the winter-time vegetative ground cover varies significantly between fields. The objectives of this study are to assess the variability in winter vegetative cover and evaluate to what extent this variability can be explained by the timing of cover crop establishment and weather conditions in two growing seasons (2017–2018). We used Sentinel-2 satellite imagery to construct NDVI time series for fields known to be cultivated with maize within the province of Overijssel. We fitted piecewise logistic functions to the time series in order to estimate cover crop sowing date and retrieve the fitted NDVI value for 1 December (NDVI_Dec). We used NDVI_Dec to represent the quality of cover crop establishment at the start of the winter season. The Sentinel-2 estimated sowing dates compared reasonably with ground reference data for eight fields (RMSE = 6.6 days). The two analysed years differed considerably, with 2018 being much drier and warmer during summer. This drought resulted in an earlier estimated cover crop sowing date (on average 19 days) and an NDVI_Dec value that was 0.2 higher than in 2017. Combining both years and all fields, we found that Sentinel-2 retrieved sowing dates could explain 55% of the NDVI_Dec variability. This corresponded to a positive relationship (R² = 0.50) between NDVI_Dec and the cumulative growing degree days (GDD) between sowing date and 1 December until reaching 400 GDD. Based on cumulative GDD derived from two weather stations within Overijssel, we found that on average for the past three decades a sowing date of 19 September (± 7 days) allowed to attain these 400 GDD; this provides support for the current legislation that states that from 2019 onwards a cover crop should be sown before 1 October. To meet this deadline, while simultaneously ascertaining a harvest-ready main crop, in practice implies that undersowing of the cover crop during spring will gain importance. Our results show that Sentinel-2 NDVI time series can assess the effectiveness and timing of cover crop growth for small agricultural fields, and as such has potential to inform regulatory frameworks as well as farmers with actionable information that may help to reduce nitrogen leaching.