Binks Institute for Sustainability: Development of a rapid characterisation method for the engineering response of trees for hazard assessment and use in nature-based solutions

Climate Change is resulting in increasingly extreme weather events which can have significant impacts on transport infrastructure:

Heavy rainfall in upland areas can generate destructive debris flows (rapid movements of fluidised soil) cutting off critical transport corridors, with the most well-known example in Scotland being the A83 Rest and Be Thankful. Tree planting has been proposed as a nature-based solution that can reduce triggering of flows (through root stabilisation of soil) and reduce the impact of flows (acting as natural/bioengineered baffles).  

Extreme winds can result in windthrow of trees adjacent to overhead lines of rail infrastructure, causing loss of service and potentially fires; overhead lines will become significantly more prevalent as rail continues to electrify (Net-zero).  

Both these examples require the quantification of the push-over resistance of trees for engineering design/hazard assessment. This is difficult to do due to the natural variability of biological systems and the difficulty of conducting destructive tests on live trees.  

 The supervisory team have recently supervised an SRPe-funded UoD PhD project (student: Andrea Marsiglia) which has conducted preliminary tests of a low-cost dynamic monitoring system which can be used to record the response of trees under ambient wind vibrations to characterise the tree response implicitly including the biological variability. During this project, some initial field testing was conducted at the UoD Botanic Gardens. There remain a number of challenges before the method can be widely applied in practice, chiefly relating to the models for converting the low magnitude dynamic vibration response to the expected large displacement rapid monotonic response expected when subject to debris flows or extreme wind gusts (design case), and a need for further validation beyond the initial pilot scale of work to date.  

This project will utilise a new efficient modelling approach developed in a recent UoD PhD project for modelling slow tree-pulling tests (thesis of Dr Xingyu Zhang) and adapt this for dynamic and fast monotonic loading by incorporating velocity dependent elements to capture rate effects. The new model will be validated through physical model tests conducted on the UoD centrifuge facility, simulating dynamic vibrational and rapid monotonic loading using the centrifuge’s ground motion simulator in conjunction with an award-winning procedure developed by the principal supervisor. Once validated, the model will be used to generate a suitably large statistical dataset to fully explore and understand the mapping between ambient measurements and design conditions.  

Once validated, the method will then be applied to the field dataset collected in the recent work at UoD Botanic Gardens. This dataset will be significantly extended through further dynamic measurements at the Botanic Gardens (proposed project collaborator Kevin Frediani), using expertise from the James Hutton in field instrumentation and plant science (proposed collaborator Dr David Boldrin). 

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