COEFFICIENT OF SEISMIC PREDICTION USING SCALED DISTANCE METHOD FOR DYNAMIC LOADS IN SLOPE STABILITY ANALYSIS

  • Ifa Aulia Chusna UPN "Veteran" Yogyakarta
  • Bagus wiyono UPN "Veteran" Yogyakarta
  • Wawong Dwi Ratminah UPN "Veteran" Yogyakarta
  • Toto Sudarto Geotechnical, Hydrology, and Infrastructure Section, PT Suprabari Mapanindo Mineral, Indonesia
  • R. Dikky Surya Ramadhan Geotechnical, Hydrology, and Infrastructure Section, PT Suprabari Mapanindo Mineral, Indonesia

Abstract

Blasting is a well-known method for breakage the overburden in coal mining activities. The blasting vibration is widely considered to be the paramount modeling parameter because it affects slope instability. Increasing the distance from the blasting center to the face of the slope can intensify the vibration on the slope as a dynamic load in the horizontal direction. This paper is presented in order to calculate the prediction of the coefficient of seismic as the input modeling for assessing the dynamic safety factor based on the magnitude of the vibration received by the toe of the slope. The Peak Particle Velocity (PPV) and Peak Ground Acceleration (PGA) would be predicted through the scaled distance method, furthermore, the PGA prediction value would be calculated to determine the distribution data. PPV and PGA prediction based on the field measurement have a high relation with the R2 indicator about 0.9923 and 0.8202, respectively. The PPV prediction from field measurement have a better accuracy than the Holmberg-Persson Modified. The Kh average as a dynamic load in slope stability analysis was 0.031 from the Gamma Distribution.

Keywords: Coefficeint of Seismic, Blasting Vibration, Overburden Blasting, Scaled Distance

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Published
2023-04-17
How to Cite
[1]
I. A. Chusna, B. wiyono, W. D. Ratminah, T. Sudarto, and R. D. S. Ramadhan, “COEFFICIENT OF SEISMIC PREDICTION USING SCALED DISTANCE METHOD FOR DYNAMIC LOADS IN SLOPE STABILITY ANALYSIS”, Journal Technology of Civil, Electrical, Mechanical, Geology, Mining, and Urban Design, vol. 8, no. 1, pp. 63-72, Apr. 2023.