Research

Sahar's research focuses on assessing mud rush hazards in underground cave mines. She applies machine learning and statistical methods to mine datasets to better understand mud rush susceptibility (likelihood of occurrence) and severity (volume and runout distance), aiming to enhance mud rush hazard management practices.

2019 - present : PhD Candidate, Geological Engineering, The University of British Columbia, Canada   

2022 -  present:  Mining Geotechnical Specialist, WSP Canada 

2017-2019 : Geotechnical Consultant, Farnofan Ltd, Iran 

2014-2017:  MSc, Geotechnical Engineering,  Sharif University of Technology, Iran 

2009-2014:  BSc, Civil Engineering, Sharif University of Technology, Iran  
 

  • Ghadirianniari, S., McDougall, S., Eberhardt, E., Varian, J., Llewelyn, K., Campbell, R., & Moss, A. (2024). Statistical analysis of the impact of ore draw strategies on wet inrush hazard susceptibility in a panel cave mine. International Journal of Rock Mechanics and Mining Sciences, 174, 105632.
  • Ghadirianniari, S., McDougall, S., Eberhardt, E., Varian, J., Llewelyn, K., Campbell, R., & Moss, A. (2024). Wet inrush susceptibility assessment at the Deep Ore Zone mine using a random forest machine learning model. Mining Technology.
  • Ghadirianniari, S., McDougall, S., Eberhardt, E., Llewelyn, K., Campbell, R., & Moss, A. (2022). Impact of draw strategy on wet muck spill hazard severity at the Deep Ore Zone mine. In Caving 2022: Fifth International Conference on Block and Sublevel Caving (pp. 597-610). Australian Centre for Geomechanics.
  • Varian, J., McDougall, S., Ghadirianniari, S., Llewelyn, K., Campbell, R., Eberhardt, E., & Moss, A. (2022). Development of a wet muck spill susceptibility tool for short-term prediction through a logistic regression approach. In Caving 2022: Proceedings of the Fifth International Conference on Block and Sublevel Caving (pp. 1459-1470). Australian Centre for Geomechanics.