再生混凝土细观层次的数字图像模型分析

针对再生混凝土已有细观骨料模型算法复杂、建模理想化和处理技术手段传统等问题,基于真实骨料图像,结合数字图像处理和边界矢量化技术,通过ANSYS软件的参数化语言编程,建立了再生混凝土数字图像细观模型。应用数字图像细观模型模拟了单轴受压立方体试块的应变云图,分析了宏观力学响应和再生粗骨料对再生混凝土抗压强度的影响。研究结果表明:大多数再生混凝土裂纹从大骨料边界产生、发展和形成。再生粗骨料掺量(质量分数)在50%内的再生混凝土,不同骨料模型模拟的抗压强度值不同。本文提出的数字图像细观模型模拟结果均符合试验现象和力学规律,证明了建模方法的合理性和有效性。

历史建筑智能识别可行性研究--运用正射影像和数字图像检测技术的江南水乡古镇实验

随着数字技术的快速发展,利用数据信息对历史建筑进行判定已成为可能。文章以数字影像为切入点,建构了一种基于历史建筑数字影像特征,借助智能检测模型,实现在复杂环境中识别历史建筑的方法。该方法通过无人机采集的正射影像,采用两阶段物体检测算法和深度神经网络模型,以具体实景为对象,经过反复实验获得了对江南水乡古镇进行历史建筑智能识别的初步模型。同时通过案例,进一步分析了该方法的适用性和下一步优化升级的方向。该项研究将有力地辅助专家和技术人员进行现场判定工作,包括对历史建筑资源的先期预调查、历史建筑保护状况的持续监测,以及为相关的评估工作提供依据。

基于3种细观层次再生混凝土骨料模型的对比分析

运用ANSYS有限元软件的参数化设计语言,建立了再生混凝土随机圆形和随机多边形细观骨料模型,应用数字图像处理技术建立了再生混凝土数字图像骨料模型.运用3种模型模拟了再生混凝土的宏观力学响应、单轴受压立方体试块强度和应变变化过程,将模拟结果和实验结果进行对比分析.从模型建立过程和数值模拟结果等,总结对比3种模型,推荐随机多边形骨料模型.结果表明,随机多边形骨料模型符合真实的骨料分布特征,数值模拟结果符合实验结果和力学规律.

A Case Study of Using External DEM in InSAR DEM Generation

Synthetic aperture radar interferometry (InSAR) has been used as an innovative technique for digital elevation model (DEM) and topographic map generation. In this paper, external DEMs are used for InSAR DEM generation to reduce the errors in data processing. The DEMs generated from repeat-pass InSAR are compared. For steep slopes and severe changes in topography, phase unwrapping quality can be improved by subtracting the phase calculated from an external DEM. It is affirmative that the absolute height accuracy of the InSAR DEM is improved by using external DEM. The data processing was undertaken without the use of ground control points and other manual operation.

Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data

At 5:39 am on June 24, 2017, a landslide occurred in the village of Xinmo in Maoxian County, Aba Tibet and Qiang Autonomous Prefecture(Sichuan Province, Southwest China). On June 25, aerial images were acquired from an unmanned aerial vehicle(UAV), and a digital elevation model(DEM) was processed. Landslide geometrical features were then analyzed. These are the front and rear edge elevation, accumulation area and horizontal sliding distance. Then, the volume and the spatial distribution of the thickness of the deposit were calculated from the difference between the DEM available before the landslide, and the UAV-derived DEM collected after the landslide. Also, the disaster was assessed using high-resolution satellite images acquired before the landslide. These include Quick Bird, Pleiades-1 and GF-2 images with spatial resolutions of 0.65 m, 0.70 m, and 0.80 m, respectively, and the aerial images acquired from the UAV after the landslide with a spatial resolution of 0.1 m. According to the analysis, the area of the landslide was 1.62 km2, and the volume of the landslide was 7.70 ± 1.46 million m3. The average thickness of the landslide accumulation was approximately 8 m. The landslide destroyed a total of 103 buildings. The area of destroyed farmlands was 2.53 ha, and the orchard area was reduced by 28.67 ha. A 2-km section of Songpinggou River was blocked and a 2.1-km section of township road No. 104 was buried. Constrained by the terrain conditions, densely populated and more economically developed areas in the upper reaches of the Minjiang River basin are mainly located in the bottom of the valleys. This is a dangerous area regarding landslide, debris flow and flash flood events Therefore, in mountainous, high-risk disaster areas, it is important to carefully select residential sites to avoid a large number of casualties.

Building Extraction from DSM Acquired by Airborne 3D Image

Segmentation and edge regulation are studied deeply to extract buildings fromDSM data produced in this paper. Building segmentation is the first step to extract buildings, anda new segmentation method-adaptive iterative segmentation considering rati-o mean square-is proposedto extract the contour of buildings effectively. A sub-image (such as 50X50 pixels) of the image isprocessed in sequence, the average gray level and its ratio mean square are calculated first, thenthreshold of the sub-image is selected by using iterative threshold segmentation. The current pixelis segmented according to the threshold, the average gray level and the ratio mean square of thesub-image. The edge points of the building are grouped according to the azimuth of neighbor points,and then the optimal azimuth of the points that belong to the same group can be calculated by usingline interpolation.

Development of a mass model in estimating weight-wise particle size distribution using digital image processing

Particle size distribution of coarse aggregates through mechanical sieving gives results in terms of cumu- lative mass percent. But digital image processing generated size distribution of particles, while being fast and accurate, is often expressed in terms of area function or number of particles. In this paper, a mass model is developed which converts the image obtained size distribution to mass-wise distribution, mak- ing it readily comparable to mechanical sieving data. The concept of weight/particle ratio is introduced for mass reconstruction from 2D images of particle aggregates. Using this mass model, the effects of several particle shape parameters （such as major axis, minor axis, and equivalent diameter） on sieve-size of the particles is studied. It is shown that the sieve-size of a particle strongly depend upon the shape param- eters, 91% of its variation being explained by major axis, minor axis, bounding box length and equivalent diameter. Furthermore, minor axis gives an overall accurate estimate of particle sieve-size, error in mean size （D-50） being just 0.4%. However, sieve-size of smaller particles （〈20 ram） strongly depends upon the length of the smaller arm of the bounding box enclosing them and sieve-sizes of larger particles （〉20 mm） are highly correlated to their equivalent diameters. Multiple linear regression analysis has been used to generate overall mass-wise particle size distribution, considering the influences of all these shape parameters on particle sieve-size. Multiple linear regression generated overall mass-wise particle size distribution shows a strong correlation with sieve generated data. The adjusted R-square value of the regression analysis is found to be 99 percent （w.r,t cumulative frequency）. The method proposed in this paper provides a time-efficient way of producing accurate （up to 99%） mass-wise PSD using digital image processing and it can be used effectively to renlace the mechanical sieving.

Acquisition of Directional Parameters in Aerial Images Based on DEM Data

This paper develops a method which can be used to assist aerial navigation by determining the spatial position and posture of the aerial photographic plane. After the method, aerial images match known DEM to capture the spatial position and posture. Some aerial images and terrain data are used to testify our method. Compared with those of analytic and stereo mappers, the results by our method are correspondent to real measurements well.

A Novel Method for Multi-image Matching Synthesizing Image and Object-space Information

A novel method for multi-image matching by synthesizing image and object-space information is proposed. Firstly, four levels of image pyramids are generated according to the rule that the next pyramid level is generated from the previous level using the average gray values of the 3 by 3 pixels, and the first level of pyramid image is generated from the original image. The initial horizontal parallaxes between the reference image and each searching image are calculated at the highest level of the image pyramid. Secondly, corresponding image points are searched in each stereo image pair from the third level of image pyramid, and the matching results in all stereo pairs are integrated in the object space, by which the mismatched image points can be eliminated and more accurate spatial information can be obtained for the subsequent pyramid image matching. The matching method based on correlation coefficient with geometric constraints and global relaxation matching is introduced in the process of image matching. Finally, the feasibility of the method proposed in this paper is verified by the experiments using a set of digital frame aerial images with big overlap. Compared with the traditional image matching method with two images, the accuracy of the digital surface model (DSM) generated using the proposed method shows that the multiimage matching method can eliminate the mismatched points effectively and can improve the matching success rate significantly.

Research on Auto-Classification Method of Remote Sensing Images in Mountainous Areas——An Application in Southwest of China

In mountainous areas, it is the undulant terrain, various types of geomorphic and land use that make the remote sensing images great metamorphism. Moreover, due to the elevation, there are many areas covered with shadow, clouds and snow that make the images more inaccurate. As a result, it would be very difficult to carry out auto-classification of RS images in these areas. The study took Southwest China as the case study area and the TM images, SPOT images as the basic information sources assisted by the auxiliary data of DEM, NDVl, topographical maps and soil maps to preprocess the images. After preprocessing by topographic correction and wiping off clouds, snow and shadows, all the image data were stacked together to form the images to be classified. Then, the research used segmentation technology and hierarchical method to extract the main types of land use in the area automatically. The results indicated that the qualitative accuracies of all types of land use extracted in Southwest China were above 90 percent, and the quantitative accuracies was above 86 percent. The goal of reducing workloads had been realized.

Contributions of non-tectonic micro-fractures to hydraulic fracturing—A numerical investigation based on FSD model

Shale gas has been discovered in the Upper Triassic Yanchang Formation, Ordos Basin, China. Due to the weak tectonic activities in which the shale plays, core observations indicate abundant random non-tectonic micro- fractures in the producing shales. The non-tectonic micro-fractures are different from tectonic fractures and are characterized by being irregular, curved, discontinuous, and randomly distributed. The role of micro-fractures in hydraulic fracturing for shale gas development is currently poorly understood yet potentially critical. Two-dimensional computational modeling studies have been used in an initial attempt toward understanding how naturally random fractured reservoirs respond during hydraulic fracturing. The aim of the paper is to investigate the effect of random non-tectonic fractures on hydraulic fracturing. The numerical models with random non-tectonic micro-fractures are built by extracting the fractures of rock blocks after repeated heating and cooling, using a digital image process. Simulations were conducted as a function of:(1) the in-situ stress ratio;(2) internal friction angle of random fractures;(3) cohesion of random fractures;(4) operational variables such as injection rate; and(5) variable injection rate technology. A sensitivity study reveals a number of interesting observations resulting from these parameters on the shear stimulation in a natural fracture system. Three types of fracturing networks were observed from the studied simulations, and the results also show that variable injection rate technology is most promising for producing complex fracturing networks. This work strongly links the production technology and geomechanical evaluation. It can aid in the understanding and optimization of hydraulic fracturing simulations in naturally random fractured reservoirs.

Accuracy Improvement of ASTER Stereo Satellite Generated DEM Using Texture Filter

The grid DEM(digital elevation model) generation can be from any of a number of sources:for instance,analogue to digital conversion of contour maps followed by application of the TIN model,or direct elevation point modelling via digital photogrammetry applied to airborne images or satellite images.Currently,apart from the deployment of point-clouds from LiDAR data acquisition,the generally favoured approach refers to applications of digital photogrammetry.One of the most important steps in such deployment is the stereo matching process for conjugation point(pixel) establishment:very difficult in modelling any homogenous areas like water cover or forest canopied areas due to the lack of distinct spatial features.As a result,application of automated procedures is sure to generate erroneous elevation values.In this paper,we present and apply a method for improving the quality of stereo DEMs generated via utilization of an entropy texture filter.The filter was applied for extraction of homogenous areas before stereo matching so that a statistical texture filter could then be applied for removing anomalous evaluation values prior to interpolation and accuracy assessment via deployment of a spatial correlation technique.For exemplification,we used a stereo pair of ASTER 1B images.