Modeling of environmental influence in structural health assessment for reinforced concrete buildings

One branch of structural health monitoring (SHM) utilizes dynamic response measurements to assess the structural integrity of civil infrastructures. In particular,modal frequency is a widely adopted indicator for structural damage since its square is proportional to structural stiffness. However,it has been demonstrated in various SHM projects that this indicator is substantially affected by fluctuating environmental conditions. In order to provide reliable and consistent information on the health status of the monitored structures,it is necessary to develop a method to filter this interference. This study attempts to model and quantify the environmental influence on the modal frequencies of reinforced concrete buildings. Daily structural response measurements of a twenty-two story reinforced concrete building were collected and analyzed over a one-year period. The Bayesian spectral density approach was utilized to identify the modal frequencies of this building and it was clearly seen that the temperature and humidity fluctuation induced notable variations. A mathematical model was developed to quantify the environmental effects and model complexity was taken into consideration. Based on a Timoshenko beam model,the full model class was constructed and other reduced-order model class candidates were obtained. Then,the Bayesian modal class selection approach was employed to select the one with the most suitable complexity. The proposed model successfully characterizes the environmental influence on the modal frequencies. Furthermore,the estimated uncertainty of the model parameters allows for assessment of the reliability of the prediction. This study not only improves the understanding about the monitored structure,but also establishes a systematic approach for reliable health assessment of reinforced concrete buildings.     

Progress in the Development of Control Strategies for the SBR Process

The sequencing batch reactor (SBR) process has shown great success in the treatment of industrial wastewater from intermittent discharge factories and for the treatment of domestic wastewater from medium or small towns. As automation technology has developed, many studies have been conducted to determine the optimal conditions for the SBR process. This review outlines the progress and application of control strategies that have been developed for the SBR process and provides a summary and comparison of the advantages and disadvantages of various control strategies, especially fixed‐time control strategies and various real‐time control strategies. Moreover, an analysis and discussion of novel optimal control methods for biologic nutrient removal are provided. Although previous studies in this field have greatly enriched our understanding of SBR systems, it is clear that many unsolved problems remain. Therefore, a summary of unanswered questions regarding control strategies for the SBR process is provided and future research directions are suggested.     

Study of the train-induced vibration impact on a historic Bell Tower above two spatially overlapping metro lines

There is concern regarding the long-term vibration effects caused by metro trains on historic buildings. In this paper, the impact of metro train-induced vibrations on the Bell Tower in Xi’an above two spatially overlapping tunnels was studied.Metro Line 2 has been operational since 2011, and Line 6 is still under construction. To study and control the effect of micro vibrations on the Bell Tower, a metro train–track–tunnel–soil 3D dynamic FE model was developed. The vibration response generated by Line 2 was then predicted, and the influences of train speed on ground vibration were analysed. In addition, a detailed in situ measurement, which helped calibrate the numerical model and determine the dynamic behaviour of timber structures, was performed. Finally, the calibrated models and measured results were used to predict vibrations caused by road traffic and trains from two spatially overlapping metro lines. This was performed under different route schemes and train operation conditions.The results showed that installing steel spring floating slab tracks (FST) and decreasing train speeds had obvious effects on controlling the ground peak particle velocity (PPV). Simulated results from both the input impulse and output response generated by metro Line 2 matched well with actual measurements. If correct designs are employed, it is possible to resolve the vibration problem on historic buildings caused by metro trains.     

基于PS-InSAR和GIS的北京平原区建筑荷载对地面沉降的影响

北京平原区地面沉降问题日益突出,成因复杂,既包括人为地下水开采和城市建筑荷载作用,又包括自然土体固结和活动构造影响。地下水开采和建筑荷载是重要的驱动因素。如何提取区域尺度建筑载荷,评价其对地面沉降影响,是地面沉降灾害防治工作需要开展的重要环节。本文以简化后的容积率表征建筑载荷,首先利用PS-InSAR技术获取研究区地面沉降信息,然后使用GIS空间分析的方法提取出同等地下水开采影响下的不均匀沉降分布,其次采用阴影长度法提取了研究区建筑体高度,最终结合空间分析和回归分析方法研究建筑容积率与地面沉降之间的关系。主要研究结论：① 北京地区地面沉降比较严重,沉降速率大于30 mm/a的区域占比21.08%;② 地下水开采同等影响下的不均匀沉降区呈H形分布于平原区中部和北部;③ 阴影长度法能够较准确的评估出建筑容积率,可用于区域尺度静载荷的提取与分析;④ 在地质条件相似、水位变化相同的局部区域内,地面沉降速率与建筑容积率具有一定相关性,但相关系数较低。     

野山河码头隧道爆破设计

分析野三河码头隧道爆破施工要求,通过相应的经验公式计算,确定野山河码头隧道的爆破参数,以保证隧道爆破施工过程中所引起的振动速度不大于邻近建筑物的安全允许振速,并保证开挖过程中的效率。     

矿山地下水位下降是导致房屋开裂的重要原因

在矿山地质灾害鉴定中,一般采用工程力学原理计算并确定矿山顶板的安全厚度、开采移动盆地的移动影响范围。而在有些地区出现的矿山地质灾害中,则必须结合矿山开采过程中水文地质条件的变化特征方能作出科学的鉴定。通过对部分矿山开采区红粘土地区房屋变形开裂形成机制的剖析,归纳了几种比较典型的矿山开采导致地下水位下降模式,说明矿山地下水位下降是导致房屋开裂的重要因素。     

数学形态学和模式识别在建筑物多边形化简中的应用

针对居民地图形化简的一个方面--建筑物多边形的化简,提出一种在与地图比例尺相关的动态栅格和矢量数据相结合的数据模型支持下,综合利用数学形态学和神经网络支持下的模式识别的化简方法.在Visual C 环境下实现基于此方法的系统并进行实验,实验结果说明此方法在保持街区的形态特征上效果明显.这种方法将制图综合知识融入图形化简操作之中,是自动制图综合智能化的一次新的尝试.     

基于机载激光扫描数据提取建筑物的研究现状

机载激光扫描系统是集成了GPS、惯性导航系统(INS)和扫描激光测距系统并利用飞机作为运行平台,来获取地面的三维位置,进而快速生成数字表面模型(DSM)。随着机载扫描激光测距系统的不断完善和发展,获取城市DSM数据也变得越来越快速,而且方便和经济可靠,地面激光点的密度也大大提高。目前国外激光扫描系统的激光点密度一般都达到了1～20点/m2,因此利用机载激光扫描系统获取的城市DSM提取建筑物也渐渐受到重视。利用激光扫描数据提取建筑物可以分为两大类,第一类是单纯以获取的机载激光测距数据来提取建筑物,第二类是融合激光测距数据和其他相关信息的建筑物提取,如融合航空影像、融合IKONOS高分辨率卫星影像来提取建筑物。本文对国际上利用机载激光扫描测距数据进行建筑物提取的最新研究进展进行了一些分析,同时也给出了应用我国研制的机载激光扫描数据提取建筑物的试验研究和初步结果。     

A Review of: “Applications of Spatial Data Structures: Computer Graphics,Image Processing,and GIS”. By H. SAMET. (Addison-Wesley Publishing Company,Inc, 1989.) [Pp. xv + 507; figures,tables, appendix,references, name and credit index,subject index.] Price US $49.95. ISBN 020150300 X (hardback).

The introduction of automated generalisation procedures in map production systems requires that generalisation systems are capable of processing large amounts of map data in acceptable time and that cartographic quality is similar to traditional map products. With respect to these requirements, we examine two complementary approaches that should improve generalisation systems currently in use by national topographic mapping agencies. Our focus is particularly on self‐evaluating systems, taking as an example those systems that build on the multi‐agent paradigm. The first approach aims to improve the cartographic quality by utilising cartographic expert knowledge relating to spatial context. More specifically, we introduce expert rules for the selection of generalisation operations based on a classification of buildings into five urban structure types, including inner city, urban, suburban, rural, and industrial and commercial areas. The second approach aims to utilise machine learning techniques to extract heuristics that allow us to reduce the search space and hence the time in which a good cartographical solution is reached. Both approaches are tested individually and in combination for the generalisation of buildings from map scale 1:5000 to the target map scale of 1:25 000. Our experiments show improvements in terms of efficiency and effectiveness. We provide evidence that both approaches complement each other and that a combination of expert and machine learnt rules give better results than the individual approaches. Both approaches are sufficiently general to be applicable to other forms of self‐evaluating, constraint‐based systems than multi‐agent systems, and to other feature classes than buildings. Problems have been identified resulting from difficulties to formalise cartographic quality by means of constraints for the control of the generalisation process.     

一种基于激光点云数据的房屋轮廓线提取方法

提出了一种基于激光点云数据提取房屋轮廓线的方法.首先在屋顶激光点云数据中搜索平面距离最远的两个激光点,选择其一为起始点,根据相邻边缘点连线的一侧不存在激光点的原则,检测屋顶所有的边缘点;然后对边缘点分组,利用最小二乘直线拟合方法分别拟合各条轮廓线并进行规则化;最后,选择轮廓线最外侧的激光点,对各条轮廓线进行平移外扩,并通过相邻轮廓线相交确定屋顶角点的坐标.实验结果表明,与通常采用的对屋顶激光点云构建不规则三角网(TIN)获取边缘点的方法相比,该算法运行效率明显提高,检测到的屋顶边缘点数量更多,获取的屋顶轮廓线精度更高.