Checking for non-preferred file/folder path names (may take a long time depending on the number of files/folders) ...
This resource contains some files/folders that have non-preferred characters in their name. Show non-conforming files/folders.
This resource contains content types with files that need to be updated to match with metadata changes. Show content type files that need updating.
Authors: |
|
|
---|---|---|
Owners: |
|
This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) for information on this resource. |
Type: | Resource | |
Storage: | The size of this resource is 0 bytes | |
Created: | Apr 01, 2018 at 7:12 p.m. | |
Last updated: | Apr 09, 2018 at 6:06 p.m. | |
Citation: | See how to cite this resource |
Sharing Status: | Public |
---|---|
Views: | 1986 |
Downloads: | 58 |
+1 Votes: | Be the first one to this. |
Comments: | 1 comment |
Abstract
The structural integrity of deep, large underground facilities such as tunnels, mines, pumped storage facilities, and physics laboratories requires the ability to predict rock mass stability under loading to ensure the safety of human occupants and the longevity of the underground space. Deformation occurs over time scales that range from milliseconds to decades and spatial scales that range from millimeters to facility scale. Beginning with design, prediction is typically based on finite element models using available or estimated properties. As with most geotechnical problems, much of the difficulty of prediction lies in the inability to sufficiently characterize the rock properties, especially discontinuities. As a consequence, semi-quantitative measures, such as Rock Mass Rating (RMR) or the Hoek-Brown Geological Structure Index (GSI) [1], are used to characterize the rock mass together with empirical charts for design criteria such as rock bolt spacing for ground control. During and following construction, validating model predictions is necessary to assess their performance. Parameter adjustment, or even the physics incorporated within the model, can be made using back analysis. This monitoring should be a continuous or periodic process over the life of the facility. For civil structures, the post-construction era will be measured in decades. With the inherent uncertainties and high stresses associated with the deep underground environment, the potential for rock failure must always be borne in mind. Mitigating the risk is prudent, but formal cost-benefit analysis may be precluded by the uncertainties. Keeping abreast of the condition of the facility through Structural Health Monitoring (SHM) is gaining acceptance for underground construction [2]. One reason for the growth in research in monitoring is that maturing technologies, like fiber-optic sensors and associated instrumentation, can collect data that were not previously achievable. They are robust and geometrically flexible, possess long-term stability, are cost effective, and extend coverage in spatial extent with improved resolution or provide data at a higher sampling rate. In addition to fiber-optic technology, a host of new technologies with potential for underground geotechnical applications exist, including LIDAR, wireless “smart dust”, piezoelectric sensors, and high resolution electrical and seismic imaging [3; 4; 5; 6; 7]. The subject of this paper is mainly to describe preliminary experiments, future needs, and instrumentation and monitoring plans of the authors' research activities in the 2400-meter Deep Underground Science and Engineering Laboratory (DUSEL) in the Black Hills of South Dakota, USA, where fiber-optic sensors and water-level tiltmeter arrays have been installed.
Raw project data is available by contacting ctemps@unr.edu
Subject Keywords
Content
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
Comments
CTEMPs OSU-UNR 6 years, 7 months ago
Raw project data is available by contacting ctemps@unr.edu
ReplyNew Comment