Dataset Information

Characteristics of hydraulic fracture surface based on 3D scanning technology.

ABSTRACT: The surface characteristics of fractured specimens are important in hydraulic fracturing laboratory experiments. In this paper, we present a three-dimensional (3D) scanning device assembled to study these surface characteristics. Cube-shaped rock specimens were produced in the laboratory and subjected to triaxial loading until the specimen split in two in a hydraulic fracturing experiment. Each fractured specimen was placed on a rotating platform and scanned to produce 3D superficial coordinates of the surface of the fractured specimen. The scanned data were processed to produce high-precision digital images of the fractured model, a surface contour map and accurate values of the superficial area and specimen volume. The images produced by processing the 3D scanner data provided detailed information on the morphology of the fractured surface and mechanism of fracture propagation. High-precision 3D mapping of the fractured surfaces is essential for quantitative analysis of fractured specimens. The 3D scanning technology presented here is an important tool for the study of fracture characteristics in hydraulic fracturing experiments.

SUBMITTER: Zhang F

PROVIDER: S-EPMC6030275 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Characteristics of hydraulic fracture surface based on 3D scanning technology.

Zhang Fan F Ma Geng G Tao Yunqi Y Liu Xiao X Liu Yixin Y Li Rui R

Royal Society open science 20180620 6

The surface characteristics of fractured specimens are important in hydraulic fracturing laboratory experiments. In this paper, we present a three-dimensional (3D) scanning device assembled to study these surface characteristics. Cube-shaped rock specimens were produced in the laboratory and subjected to triaxial loading until the specimen split in two in a hydraulic fracturing experiment. Each fractured specimen was placed on a rotating platform and scanned to produce 3D superficial coordinates ...[more]

PMID: 30110461

Similar Datasets

Project description:This study aimed at illustrating how direct measurements, mobile laser scanning and hydraulic modelling can be combined to quantify environmental drivers, improve vegetation models and increase our understanding of vegetation patterns in a sub-arctic river valley. Our results indicate that the resultant vegetation models successfully predict riparian vegetation patterns (Rho = 0.8 for total species richness, AUC = 0.97 for distribution) and highlight differences between eight functional species groups (Rho 0.46-0.84; AUC 0.79-0.93; functional group-specific effects). In our study setting, replacing the laser scanning-based and hydraulic modelling-based variables with a proxy variable elevation did not significantly weaken the models. However, using directly measured and modelled variables allows relating species patterns to e.g. stream power or the length of the flood-free period. Substituting these biologically relevant variables with proxies mask important processes and may reduce the transferability of the results into other sites. At the local scale, the amount of litter is a highly important driver of total species richness, distribution and abundance patterns (relative influences 49, 72 and 83%, respectively) and across all functional groups (13-57%; excluding lichen species richness) in the sub-arctic river valley. Moreover, soil organic matter and soil water content shape vegetation patterns (on average 16 and 7%, respectively). Fluvial disturbance is a key limiting factor only for lichen, bryophyte and dwarf shrub species in this environment (on average 37, 6 and 10%, respectively). Fluvial disturbance intensity is the most important component of disturbance for most functional groups while the length of the disturbance-free period is more relevant for lichens. We conclude that striving for as accurate quantifications of environmental drivers as possible may reveal important processes and functional group differences and help anticipate future changes in vegetation. Mobile laser scanning, high-resolution digital elevation models and hydraulic modelling offer useful methodology for improving correlative vegetation models.

Dataset Information

Characteristics of hydraulic fracture surface based on 3D scanning technology.

Publications

Characteristics of hydraulic fracture surface based on 3D scanning technology.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets