Risk Level Control by Geotechnical Monitoring on Different Tunnel Projects Stages

EasyChair Preprint 2914

Abstract

Natural and man-made impacts are registered in the “underground structure - enclosing environment” system at all stages of its existence. Hazardous processes may differ significantly at different intervals of an extended underground structure and at different times. This requires a dynamic approach to assessing, forecasting and reducing probability of emergency situations, as well as minimizing losses in different areas of the object. Therefore, it is reasonably to evaluate the influence of negative factors on extended underground structures from the standpoint of risk management. Geotechnical risks make the most significant contribution to the level of uncertainty in making design and constructive decisions due to their nonlinear variability both in terms of area and depth, and in time. For the purposes of geotechnical risk control in time can be successfully applied tools of digital geomechanics, mathematical modeling, deep learning methods based on neural networks, algorithms for evaluating the technical condition of underground structures based on BIM technology. The initial information is a field study of the stress-strain state of structures and enclosing environment as a part of the system of multi-disciplinary geotechnical monitoring which provides the development of possible accidents scenarios with the manifestation of each risk-criterion indicator hazardous for the tunnel.

Keyphrases: BIM technology, Field study of the stress-strain state, Geotechnical risks, automated process control system, geotechnical monitoring, geotechnical monitoring system, risk management, risk rating, severo muisky tunnel, stress-strain state, tunnel construction, underground structure

@booklet{EasyChair:2914,
  author    = {Vladimir Maslak and Mikhail Lebedev and Kirill Romanevich},
  title     = {Risk Level Control by Geotechnical Monitoring on Different Tunnel Projects Stages},
  howpublished = {EasyChair Preprint 2914},
  year      = {EasyChair, 2020}}