System Reliability Analysis of an Offshore Jacket Platform

This study investigates strategies for solving the system reliability of large three-dimensional jacket structures.These structural systems normally fail as a result of a series of different components failures.The failure characteristics are investigated under various environmental conditions and direction combinations.Theβ-unzipping technique is adopted to determine critical failure components,and the entire system is simplified as a series-parallel system to approximately evaluate the structural system reliability.However,this approach needs excessive computational effort for searching failure components and failure paths.Based on a trained artificial neural network(ANN),which can be used to approximate the implicit limit-state function of a complicated structure,a new alternative procedure is proposed to improve the efficiency of the system reliability analysis method.The failure probability is calculated through Monte Carlo simulation(MCS)with Latin hypercube sampling(LHS).The features and applicability of the above procedure are discussed and compared using an example jacket platform located in Chengdao Oilfield,Bohai Sea,China.This study provides a reference for the evaluation of the system reliability of jacket structures.     

Creating adaptive social-ecological fit: The role of regional actors in the governance of Sea-level rise adaptation in San Francisco bay

Sea level rise is one of the most pressing climate adaptation issues around the world. Often, coastal communities are interdependent in their exposure to sea level rise – if one builds a seawall, it will push water to another – and would benefit from a coordinated adaptive response. The literature on social-ecological systems (SES) calls for actors placed at higher levels of governance (e.g. regional government in a metropolitan area) to improve coordination between local managers by serving as brokers. However, we lack empirical insight on how higher-level actors might improve coordination in practice, and theoretical development on the implications of their intermediation. To address these gaps, we study the case of adaptation to sea level rise in the San Francisco Bay Area. We build a social-ecological network of social actors and shoreline segments using original survey data and simulated scenarios of tidal and traffic interdependencies between shoreline segments. We perform a frequency analysis of network motifs that operationalize social-ecological ‘fit’ in the context of the Bay Area. We find that regional actors and non-governmental organizations increase social-ecological fit by providing intermediation between actors who work on different shoreline segments, whether interdependent or not. This shows that these actors provide adaptive social-ecological fit, future-proofing the Bay Area to current and future climate adaptation challenges.     

地面气温观测系统设计与实验研究

为提高大气温度测量的准确度,本文设计了一种新型地面气温观测系统并推导了相应的辐射误差修正方程。首先,利用计算流体动力学（CFD）方法对该测温系统进行结构优化设计以及辐射误差量化计算。然后,利用BP神经网络算法拟合可针对多变量变化的辐射误差修正方程。最后,以076B型强制通风测温仪器的测量值作为温度基准,验证该测温系统的测温精度。实验结果表明,该新型地面气温观测系统的测量值与基准温度的均方根误差（RMSE）和绝对误差（MAE）分别为0.031 ℃和0.041 ℃。     

狭长区域GNSS控制网数据处理方法研究

针对狭长区域GNSS控制网边长差异较大的问题,本文通过划分子网来降低数据处理的难度,从基线处理和网平差两个方面,分析了系统误差来源,研究了基准处理中卫星轨道误差、对流层误差以及网平差中位置、尺度、方位和时间演变基准误差的改正方法,形成了一套高精度数据处理方案。基于该方法,对三峡库区GPS滑坡监测网的实测数据进行了分析与处理,获得了高精度的处理结果,本研究对狭长区域GNSS控制网的建立具有借鉴意义和指导作用。     

浅谈高分辨率卫星影像数据在城市污水行业的应用

随着遥感技术的发展和卫星影像分辨率的不断提高,高分辨率卫星影像广泛应用于各个行业。本文介绍了对卫星影像进行DOM(数字正射影像)制作、河涌排放口定位、污水等级监督分类及变化监测等在城市污水行业中的应用。     

基于排水管网GIS系统开展修补测提高数据现势性

排水管网属于地下隐蔽设施,具有变化慢、变化隐蔽两大特点,因此其空间数据主体相对稳定,而改造节点、更新数据困难。本文通过排水管网GIS系统收集管网管理一线工作人员存在的数据问题,针对这些问题进行修补测及成果确认,从而快速修复管线,完善排水管网数据库,提高数据现势性。     

城市交通网络分形维数的不确定性估计、控制与分析

长度-半径维数模型作为描述城市交通网络复杂不确定性现象的一种分形分维方法,其自身存在的不确定性往往被忽视,且相关研究更是鲜见报道。故针对该模型在分形维数测算全过程中存在的不确定性问题,本文率先开展了系统剖析、定量估计和质量控制研究。首先对数据源、矢量化处理、测算中心、尺度选择、以及分维数模型估计等一系列环节进行了不确定性估计与分析,其中首次给出了分形维数在一定置信水平下的不确定性度量区间,并依据误差传播理论对误差的传递和累积进行了描述;然后着重提出了基于LMed S(Least Median of Squares)的质量控制方法。最后通过对拉萨市的算例实验表明:道路的矢量化过程、测算中心和测算尺度的选择都会导致分维的不确定性;并在对数据质量进行控制的基础上,通过置信区间对长度-半径维数模型的不确定性进行了在一定概率水平下的首次度量;同时结合区域现状对研究结果给出了合乎实际的解释。本文在描述表征不确定性问题的分形几何和分形维数的基础上,系统地揭示了其自身不确定性的本质,不仅进一步丰富了分形分维理论,为控制其质量奠定理论基础,而且可为城市交通网络分形维数的地学应用提供可靠的科学依据。     

大连市沿海丘陵地区地铁精密控制网关键技术研究

介绍了大连市沿海丘陵地区地铁施工控制网布设、观测中关键技术的研究及解决方案,其中利用GPS静态观测与传统精密导线测量相结合组成混合网平差、将精密导线点纳入二等水准网,实现平高复用等技术,可给同类工程实施提供参考。     

基于物联网和GIS的供水管网巡检系统的设计与实现

为了提高供水管网巡检效率,基于GIS和物联网技术设计实现了供水管网巡检系统。该系统能够有效地解决地理信息分析问题,也为管网改造、爆管抢修等业务提供支持,并为管网设备管理提供了科学化、制度化的保障。     

A Comparative Study of Various Supervised Learning Approaches to Selective Omission in a Road Network

Selective omission is necessary for road network generalisation. This study investigates the use of supervised learning approaches for selective omission in a road network. To be specific, at first, the properties to measure the importance of a road in the network are viewed as input attributes, and the decision of such a road is retained or not at a specific scale is viewed as an output class; then, a number of samples with known input and output are used to train a classifier; finally, this classifier can be used to determine whether other roads to be retained or not. In this study, a total of nine supervised learning approaches, i.e., ID3, C4·5, CRT, Random Tree, support vector machine (SVM), naive Bayes (NB), K-nearest neighbour (KNN), multilayer perception (MP) and binary logistic regression (BLR), are applied to three road networks for selective omission. The performances of these approaches are evaluated by both quantitative assessment and visual inception. Results show that: (1) in most cases, these approaches are effective and their classification accuracy is between 70% and 90%; (2) most of these approaches have similar performances, and they do not have any statistically significant difference; (3) but sometimes, ID3 and BLR performs significantly better than NB and SVM; NB and KNN perform significantly worse than MP, SVM and BLR.