DWG三维模型自动转换为X三维模型的方法研究

DWG三维模型作为一种成熟的三维模型格式已广泛应用于各领域,但在实际工作中,往往需要将其放置到多种三维设计平台中,而许多平台并不直接支持该格式,这限制了DWG格式三维模型的重复利用。本文首先分析了DWG三维模型格式,而后利用DWG.SDK二次开发包,实现了将DWG三维模型转换为X三维模型的方法并通过实例对该方法进行了验证,该方法拓宽了DWG三维模型的应用范围。     

The fate of waste in Hawaii: Technology assessment and solid waste planning in Hawaii, 1968–78

In this article I consider the initial period of solid waste management planning in the US state of Hawaii. The State encountered a number of economic and ecological controversies during its solid waste management planning, a process that was prompted by the US Environmental Protection Agency. Some issues, like project financing, were common across the US, while others, such as the potential of waste materials to reduce reliance on imported food and materials, were more unique to Hawaii. The controversies from this initial planning period were never quite fully resolved; as they lingered, they were interpreted differently across the Islands. Based on a close reading of government, advocacy group, waste industry and news media documents, I examine the controversies over solid waste management of the time and consider how the ‘dual nature’ of waste in Hawaii—simultaneously an ecological threat and (potential) economic input—shaped the adoption of solid waste management systems there. This article adds to an expanding literature examining infrastructure in environmental and technology histories.     

中国能源生态效率的空间格局与空间效应

能源生态效率兼顾能源利用中的生态效益与经济效益,是对能源—环境—经济3E系统效率的度量。基于考虑非期望产出的SBM模型对中国1997-2012年省际能源生态效率进行测度,从空间格局规模、格局强度与格局纹理三个方面分析能源生态效率的空间分布特征和演变规律,运用空间计量模型验证中国省际能源生态效率的空间溢出效应及其影响因素。研究表明:1中国能源生态效率整体偏低,低效率省份约占40%,广东、海南、福建位于能源生态效率值的最前沿,宁夏、甘肃、青海、新疆为主要的低能效地区。全国能源生态效率总体上呈U型演变格局,局部地区主要有增长型、波动型、突变型和平稳型等4种演变类型;2中国能源生态效率在省际尺度上表现出显著的全局与局部空间集聚特征,高高集聚区主要分布在东部沿海和南部沿海地区,低低集聚区主要分布在西北地区和黄河中游地区。空间格局的变化主要发生在高低集聚区与低高集聚区,其中又以京津冀地区的集聚类型演变最为显著;3中国能源生态效率存在着明显的空间效应,某一地区的能源生态效率对相邻地区的空间溢出程度均强于相邻地区的误差冲击对该地区的影响程度;在影响能源生态效率空间效应的诸多因素中,产业结构的影响最大。     

陕西省能源供给与经济及生态环境协调性分析

作为我国能源供应的战略基地和大西北生态脆弱区,陕西省经济增长和生态环境协调能力关乎国家能源和生态安全,探究陕西省能源供给与经济及生态环境发展(3E)的协调性及关联性具有重要的理论和现实意义。以能源供给为切入点对陕西省3E现状进行定性分析,推断能源供给对陕西省经济增长的结构性支撑作用。选取25个指标构建3E指标体系,运用层次分析、模糊综合评价等方法对各子系统发展水平及各子系统之间协调性进行定量分析。结果表明:(1)陕西省能源供给、经济增长与生态环境间具有较高的协调性;(2)陕西省能源供给、经济增长和生态环境协调关系波动大;(3)能源供给、经济增长和生态环境协调度对能源供给变化具有较高的敏感性。     

石灰土中秸秆还田降解率及其对土壤肥力的影响

石灰土具有高的有机碳的积累,但营养成分的供给速率偏低,导致土壤贫瘠。本文通过室内模拟实验,研究相同来源玉米秸秆在岩溶土与非岩溶土中的降解情况,对秸秆降解率、土壤理化性质、土壤肥力等进行动态检测,结果表明：（1）总体上岩溶土秸秆降解速率比非岩溶土快。秸秆降解速度最快主要集中在最初60天,之后呈缓慢上升趋势,到98天基本达到平衡。非岩溶土降解峰值出现时间为第42天,岩溶土为第28天,峰值出现时间前者比后者滞后14天。总降解时间持续160天,岩溶土降解率为77%,非岩溶土为75%。（2）秸秆降解期间,土壤pH值前期有下降的趋势,后期慢慢回升,这与秸秆降解过程中不同时期降解产物变化规律相吻合。秸秆还田可以提高土壤肥力,其中速效氮和速效钾含量增加非常明显。（3）与岩溶土相比,全量检测结果显示各肥力指标在非岩溶土含量低,但升幅百分比高;有效态检测结果显示非岩溶土速效磷和速效钾含量高。说明秸秆还田一些营养元素有效态在非岩溶土中更易于释放,而岩溶土由于其土壤质地的特殊性,许多养分被土壤粘土矿物牢固结合,营养元素供给速率慢,但因此也易于养分全量的累积。     

Pleiades卫星图像正射纠正方法

Pleiades卫星图像是一种应用时间尚短的新型遥感图像,目前还缺少对其专用的正射纠正处理方法。为此,以湖北省大冶—阳新地区的6景Pleiades图像为例,在Visual Studio 2008环境下,采用C#语言开发了针对Pleiades图像有理多项式系数(rational polynomial coefficients,RPC)文件格式的转换软件包,用于将Pleiades图像的RPC文件格式转换为IKONOS图像的RPC文件格式,并采用ERDAS9.2中的IKONOS图像的正射纠正模型对其进行纠正。该方法解决了对Pleiades图像进行正射纠正所需要解决的相关问题,开发的RPC文件转换程序可以用于批量的Pleiades卫星RPC文件格式转换,提高了转换效率和准确性,为大规模应用Pleiades图像奠定了基础。     

Study of dispersion of mass distribution of ultra-high energy cosmic rays using a surface array of muon and electromagnetic detectors

We consider a hypothetical observatory of ultra-high energy cosmic rays consisting of two surface detector arrays that measure independently electromagnetic and muon signals induced by air showers. Using the constant intensity cut method, sets of events ordered according to each of both signal sizes are compared giving the number of matched events. Based on its dependence on the zenith angle, a parameter sensitive to the dispersion of the distribution of the logarithmic mass of cosmic rays is introduced. The results obtained using two post-LHC models of hadronic interactions are very similar and indicate a weak dependence on details of these interactions.     

随机森林机器算法在江苏省小麦赤霉病病穗率预测中的应用

基于2002—2018年江苏省13个市的小麦赤霉病病穗率资料与生育期观测资料、相应时段内的逐日气象数据,应用随机森林机器学习算法,分生育期、分区域定量评估影响病穗率的主要气象因子特征变量和贡献率,按不同起报时间建立预测模型并进行验证。结果表明,各生育期重要特征变量贡献率的排序为:抽穗扬花期＞拔节期＞越冬期。抽穗扬花期湿度、连续≥3 d的雨日和日照对赤霉病起主导作用,拔节期日照、降雨量、湿度和雨日与越冬期气温和降雪对赤霉病均具有前期影响,甄别出的重要特征变量排序结果符合赤霉病菌发育、释放、侵染和流行规律;基于随机森林算法建立的病穗率预测模型的精度与重要特征变量个数、赤霉病发生区域、M_try参数设定、生育期有关;最早可在3月初进行预测,预测时效近3个月,起报时间越接近乳熟期,输入的重要特征变量越多,则病穗率预测准确率越高,病穗率模拟值与实测值的波动趋势完全一致,对赤霉病“中等”和“偏重”等级模拟效果好,表明随机森林算法在赤霉病预测中有较高的可靠性和业务应用潜力。      

GRAPES_GFS中三维参考大气的研究：参考态构造和实际预报试验

GRAPES_GFS（Global Regional Assimilation and PrEdiction System, Global Forecast System）采用基于等温大气构造的一维参考大气,前期的研究工作已在GRAPES_GFS的动力框架中引入了三维参考大气,并通过一系列理想试验检验了新方法的正确性以及计算精度。本部分研究工作,主要针对实际资料的预报试验,对比分析了不同三维参考态给定方法的优劣,并采用气候平均法,进行夏季两个月的四维变分循环预报试验。检验结果显示,使用三维参考大气后,模式的综合预报性能得到了提升,对流层高度场、温度场的预报偏差有所减小,长期积分过程中模式质量损失较为严重的问题也得到了明显的缓解。另外,通过动能谱的对比也可以看到使用三维参考大气后,模式在高层的能量耗散明显较小,能谱变化与观测更加吻合。      

Testing smarter control and feedback with users: Time,temperature and space in household heating preferences and practices in a Living Laboratory

Transitioning to more efficient and less carbon-intensive heating is a monumental policy challenge in the United Kingdom. However, very few households in the UK—and perhaps even elsewhere—have actual experience with state-of-the-art smart heating systems that may utilize enhanced control or feedback. Drawing from a unique sample of actual adopters of smart heating, this study closely examines the heating preferences, practices, and profiles of homes when they are given smarter heating systems. The study utilizes qualitative household data from the Energy System Catapult’s Living Laboratory of 100 smart homes in Birmingham (West Midlands), Bridgend (Wales), Manchester (Greater Manchester), and Newcastle (Northumberland). We examine the heating preferences and profiles of participants, with findings inductively organized around the themes of temperature, including tradeoffs between comfort, cost, and value; time, including the utility of heat scheduling; and space, including zonal heating controls. We also discuss patterns of learning, the emergence of environmental values, and issues of discomfort. We conclude by commenting on important distinctions between radiant and ambient heat, as well as between scheduled and on-demand heat. The main findings are 1) tradeoffs between comfort, value and cost occur when it comes to smart heating; 2) people want different numbers of warm hours in their homes at very different times; 3) households chose to heat different numbers of rooms; and 4) there are other non-monetary and non-functional aspects of smart heating that households value.