Improved rockfall modelling for the design of mitigation measures
The main objective of this master thesis is to evaluate current practices and modelling tools for designing rockfall protection barriers.
Several different modelling tools are currently used for designing rockfall mitigation measures, e.g. RocFall, Rockyfor3D and RAMMS Rockfall. Research comparing rockfall runout models to hazard zoning has provided professionals with improved mitigation measures and design tools with rockfall models. A focus on parameter sensitivity will improve design criteria, reduce uncertainties, and improve the basis for rockfall mitigation planning and design. The results will bridge the gap between NVE’s guidelines for hazard zoning and NVE's 'Physical Mitigation Handbook'.
The thesis will address modelling tools used to design rockfall mitigation methods. Modelling tools vary significantly in their outcomes, and the experience is that different modelling tools will, or could, produce varying results, and consequently different mitigation measure dimensions (e.g. catchment dam height or energy level for rockfall barriers). Therefore, knowledge of how the modelling software and the input parameters affect important design parameters, such as rockfall bounce height and energy level, is needed to design proper mitigation and avoid overly conservative/costly measures.
The work should focus on relevant case studies from previous rockfall projects, including cases where rockfalls were registered directly towards or near the mitigation measure. Back-calculations of these rockfalls using the various available models will produce data on the important parameters, such as bounce height, velocity and energy, to be followed by an evaluation of the various models.
If time permits, a framework for the design of mitigation measures based on the modelling may be included. However, the thesis details will be designed in collaboration with the candidate and be somewhat based on her/his background.
The student will select case sites in cooperation with NGI, which will be cases with adequate data. The thesis project will also partly be based on recent research carried out in 2020 and three MSc theses at the University of Oslo, to be completed in June 2021. The thesis project will build on one MSc thesis at the University of Oslo within the same topic, to be completed in June 2023.
