Distribution and quantitative zonation of unloading cracks at a proposed large hydropower station dam Site Distribution and quantitative zonation of unloading cracks at a proposed large hydropower station dam Site

最小化 最大化

Vol14 No.10: 2106-2121

Title】Distribution and quantitative zonation of unloading cracks at a proposed large hydropower station dam Site

Author】ZHAO Wei-hua1*; FROST J. D.2; HUANG Run-qiu1; YAN Ming1; JIN Long-de2

Addresses】1 State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, Sichuan 610059, China; 2 School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA

Corresponding author】weihuageo@gmail.com

Citation】Zhao WH, Frost JD, Huang RQ, et  al. (2017) Distribution and quantitative zonation of unloading cracks at a proposed large hydropower station dam Site. Journal of Mountain Science 14 (10). https://doi.org/10.1007/s11629-017-4431-y

DOI】https://doi.org/10.1007/s11629-017-4431-y

Abstract】Rock mass unloading is an important rock engineering problem because unloading may impact the stability of a rock mass slope. Based on hydroelectric engineering principles, this study focuses on the classification of unloading zones to reflect the rock mass structure characteristics. Geological background and slope structure of the study region were considered to investigate the distribution and deformation of the unloading process. Quantitative indices were classified according to the formation mechanisms and the geological exhibition of unloading zones. The P-wave velocity (), the ratio of the wave velocity (, the ratio of the test P-wave velocity along the adit depth to the P-wave velocity of intact rock), the sum of joint openings every 2 meters (), and the density of open joints () were calculated as quantitative indices for the rock mass unloading zone. The characteristics of the unloading zone of rock mass slopes at the dam site were successfully determined. The method of combining qualitative data with quantitative indices was found to be effective for the classification of slope unloading zones.

Keywords】Slope Structure; Unloading Phenomena; Classify Unloading Zones; Quantitative Indexes