Visual representation and characterization of three-dimensional hydrofracturing cracks within heterogeneous rock through 3D printing and transparent models

The heterogeneity of unconventional reservoir rock tremendously affects its hydrofracturing behavior. A visual representation and accurate characterization of the three-dimensional （3D） growth and distribution of hydrofracturing cracks within heterogeneous rocks is of particular use to the design and implementation of hydrofracturing stimulation of unconventional reservoirs. However, because of the difficulties involved in visually representing and quantitatively characterizing a 3D hydrofracturing crack-network, this issue remains a challenge. In this paper, a novel method is proposed for physically visualizing and quantitatively characterizing the 3D hydrofracturing crack-network distributed through a heterogeneous structure based on a natural glutenite sample. This method incorporates X-ray microfocus computed tomography （μCT）, 3D printing models and hydrofracturing triaxial tests to represent visually the heterogeneous structure, and the 3D crack growth and distribution within a transparent rock model during hydrofracturing. The coupled effects of material heterogeneity and confining geostress on the 3D crack initiation and propagation were analyzed. The results indicate that the breakdown pressure of a heterogeneous rock model is significantly affected by material heterogeneity and confining geostress. The measured breakdown pressures of heterogeneous models are apparently different from those predicted by traditional theories. This study helps to elucidate the quantitative visualization and characterization of the mechanism and influencing factors that determine the hydrofracturing crack initiation and propagation in heterogeneous reservoir rocks.

Rock characterization while drilling and application of roof bolter drilling data for evaluation of ground conditions

Despite recent advances in mine health and safety, roof collapse and instabilities are still the leading causes of injury and fatality in underground mining operations. Improving safety and optimum design of ground support requires good and reliable ground characterization. While many geophysical methods have been developed for ground characterizations, their accuracy is insufficient for customized ground support design of underground workings. The actual measurements on the samples of the roof and wall strata from the exploration boring are reliable but the related holes are far apart, thus unsuitable for design purposes. The best source of information could be the geological back mapping of the roof and walls, but this is disruptive to mining operations, and provided information is only from rock surface.Interpretation of the data obtained from roof bolt drilling can offer a good and reliable source of information that can be used for ground characterization and ground support design and evaluations. This paper offers a brief review of the mine roof characterization methods, followed by introduction and discussion of the roof characterization methods by instrumented roof bolters. A brief overview of the results of the preliminary study and initial testing on an instrumented drill and summary of the suggested improvements are also discussed.

A Vision-Based Fingertip-Writing Character Recognition System

This paper presents a vision-based fingertip-writing character recognition system. The overall system is implemented through a CMOS image camera on a FPGA chip. A blue cover is mounted on the top of a finger to simplify fingertip detection and to enhance recognition accuracy. For each character stroke, 8 sample points (including start and end points) are recorded. 7 tangent angles between consecutive sampled points are also recorded as features. In addition, 3 features angles are extracted: angles of the triangle consisting of the start point, end point and average point of all (8 total) sampled points. According to these key feature angles, a simple template matching K-nearest-neighbor classifier is applied to distinguish each character stroke. Experimental result showed that the system can successfully recognize fingertip-writing character strokes of digits and small lower case letter alphabets with an accuracy of almost 100%. Overall, the proposed finger-tip-writing recognition system provides an easy-to-use and accurate visual character input method.

ADAPTIVE RECONSTRUCTION TECHNIQUE FOR THE LOST INFORMATION OF THE RECTANGULAR IMAGE AREA

The adaptive reconstruction for the lost information of the rectangular image area is very important for the robust transmission and restoration of the image. In this paper, a new reconstruction method based on the Discrete Cosine Transform (DCT) domain has been put forward. According to the low pass character of the human visual system and the energy distribution of the DCT coefficients on the rectangular boundary, the DCT coefficients of the rectangular image area are adaptively selected and recovered. After the Inverse Discrete Cosine Transform (IDCT), the lost information of the rectangular image area can be reconstructed. The experiments have demonstrated that the subjective and objective qualities of the reconstructed images are enhanced greatly than before.

In-situ imaging of strain-induced enhancement of hydrogen evolution activity on the extruded MoO_(2)sheets

Strain engineering is a useful strategy for modifying the catalytic activity of electrocatalysts.However,in-situ visual characterization of the strain effect on the catalytic activity at nanoscale remains a huge challenge.Herein,we performed in-situ electrochemical scanning tunneling microscopy(EC-STM)imaging measurements at the local strained regions of extruded singlecrystal molybdenum dioxide(MoO_(2))sheets with combination of current noise analysis(n-EC-STM).The intensity-enhanced noise was observed at the local strained region compared to the unstrained regions in the same frame,which reveals the positive effect of compressive strain on the hydrogen evolution reaction(HER)activity of MoO_(2)provided that the intensity of noise is positively correlated with catalytic HER Faradic current.Therefore,we clearly“see”the strain-induced enhancement of HER activity of MoO_(2)at nanoscale by means of noise visualization.This work extends the visual characterization of strain engineering in electrocatalysis and related fields.