Volume 13 (2022)
Volume 12 (2021)
Volume 11 (2020)
Volume 10 (2019)
Volume 9 (2018)
Volume 8 (2017)
Volume 7 (2016)
Volume 6 (2015)
Volume 5 (2014)
Volume 4 (2013)
Volume 3 (2012)
Volume 2 (2011)
Volume 1 (2010)
Evaluating the microscale failure response of various weathering grade sandstone based on microscale observation and microstructural modelling subjected to wet and dry cycles

Kausar Sultan shah; Mohd Hazizan bin Mohd Hashim; Hafeez Ur Rehman; Kamar shah bin Ariffin

Articles in Press, Accepted Manuscript, Available Online from 08 June 2022

http://dx.doi.org/10.22044/jme.2022.11699.2160

Abstract
  The significance of rock failure can be found from the fact that microfracture genesis and coalescence in the rock mass results in macroscale fractures. Rock may fail due to an increase in the local stress, natural fractures, weathering inducing micro-crack genesis, coalescence, and propagation. Therefore, ...  Read More

Application of Stochastic Simulation in Assessing Effect of Particle Morphology on Fracture Characteristics of Sandstone

K. Sultan shah; M. H. bin Mohd Hashim; H. Rehman; K. S. bin Ariffin

Volume 12, Issue 4 , October 2021, , Pages 969-986

http://dx.doi.org/10.22044/jme.2021.11418.2124

Abstract
  Indirect tensile testing is used in order to investigate the effect of particle morphology (shape and size) on the various weathering grade sandstone fracture characteristics. Several fracture characteristics are discussed in depth in this work including the fracture length (FL), fracture deviation area ...  Read More

Analysis and Forecast of Mining Accidents in Pakistan

K. Sultan Shah; I. Mithal Jiskani; N. Muhammad Shahani; H. Ur Rehman; N. Muhammad Khan; S. Hussain

Volume 11, Issue 4 , October 2020, , Pages 967-976

http://dx.doi.org/10.22044/jme.2020.10082.1945

Abstract
  In the mining sector, the barrier to obtain an efficient safety management system is the unavailability of future information regarding the accidents. This paper aims to use the auto-regressive integrated moving average (ARIMA) model, for the first time, to evaluate the underlying causes that affect ...  Read More