Short courses

Course 1:

GEOTECHNICAL SYSTEMS THAT EVOLVE WITH ECOLOGICAL PROCESSES COURSE

Overview

Geotechnical systems, are required to perform safely throughout their service life, which can span from decades for levees to in-perpetuity for TSFs. The conventional design practice by geotechnical engineers for these systems utilises the as-built material properties to predict its performance throughout the required service life. The implicit assumption in this design methodology is that the soil properties are stable through time. This is counter to long-term field observation of these systems, particularly where ecological processes such as plant, animal, biological and geochemical activity is present. This course presents an integrated perspective and new approach to this issue; considering ecological, geotechnical and mining demands and constraints.

Course presenters

Professor Andy Fourie

School of Civil, Environmental and Mining Engineering,The University of Western Australia, Australia

Professor Mark Tibbett

School of Agriculture, Policy and Development, University of Reading, UK

Programme*

07:30   Registration

08:30   Session 1

  • Introducing concepts and purpose
  • Geotechnical principles and good practice for soils and post-mining landscapes
  • An introduction to the biology of the soil (part 1)

10:30   Morning break

11:00   Session 2

  • An introduction to the biology of the soil (part 2)
  • Differing perspectives: ecology versus engineering

12:30   Lunch

13:30   Session 3

  • How biology colonises and changes soil
  • Soil property and parameter change through time
  • Participant discussion

15:00   Afternoon   break

15:30   Session 4

  • Managing an evolving engineered land system: towards an integrated geo-ecological approach
  • Closing discussion

17:00   Wrap-up

** The preliminary programme is subject to change.


Course 2:

Advangeo®: Artificial neural networks for analyzing and predicting geological and geotechnical process – background, software and application examples

Overview

Geological and geotechnical processes such as soil liquefaction, slope instabilities, soil erosion and mineral deposit formation are results of complex interactions in geological systems controlled by multiple parameters. The analysis and prediction of these processes faces serious problems because of complex and often unclear cause – effect relationships preventing the application of mathematical rules and relationships for process description. In this environment, self-learning methods of artificial intelligence show exclusive strengths for establishing respective models usable for process prediction. The course introduces the attendee into the background of artificial neural network data analysis, and its application for analyzing and predicting instability processes in mining waste, slope instabilities and prediction of mineral occurrences for more sustainable natural resource management. Together with the presenter, the attendees create real models and apply them for prediction purposes.

Course presenters

Dr. Mandy Schipek, MSc Geoecology, PhD Hydrogeology

Beak Consultants GmbH, Freiberg: Project Manager Hydrogeology & Geohazards 

 

Peggy Hielscher, MSc Geology

Beak Consultants GmbH, Freiberg: Project Manager Machine Learning

 

Programme*

07:30   Registration

08:30   Session 1

  • What are artificial neural networks (ANN)?
  • Application of ANN in a spatial and geological environment
  • Application examples
  • Advangeo® software

10:30   Morning break

11:00   Session 2: Waste pile stability analysis

  • How to build a real mining waste pile stability model?
  • Data base and data preparation
  • Model setup
  • Model application for instability predictive mapping

12:30   Lunch

13:30   Session 3: Slope instability analysis for infrastructure risk assessment

  • How to build the model?
  • Data base and data preparation
  • Model setup
  • Model application for slope instability predictive mapping

15:00   Afternoon   break

15:30   Session 4: Mineral predictive mapping for more resource sustainability

  • How to build the model?
  • Data base and data preparation
  • Model setup
  • Model application for slope instability predictive mapping

17:00   Wrap-up

  • Closing discussion
  • Conclusions

** The preliminary programme is subject to change.