Biomechanics in the inference of the risk of falling trees

• Grant number: 23/03111-0
• Support Opportunities: Regular Research Grants
• Start date: August 01, 2023
• End date: October 31, 2025
• Field of knowledge: Agronomical Sciences - Forestry Resources and Forestry Engineering - Forestry
• Principal Investigator: Raquel Gonçalves
• Grantee: Raquel Gonçalves
• Host Institution: Faculdade de Engenharia Agrícola (FEAGRI). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated researchers: Mônica Ruy ; Rafael Gustavo Mansini Lorensani ; Stella Stopa Assis Palma ; William Martins Vicente

Abstract

Trees are complex beings, which associate biological and mechanical behaviors to maintain their phytosanitary and stability. In addition, in urban conditions, its stability is also associated with the conditions of the soil, the planting site and the surroundings, since paving and the presence of urban equipment can affect the proper development and fixation of the roots. The current climate crisis has provided increasingly frequent extreme events, which have led researchers and managers to seek new ways of inferring the risk of falling trees, which are important public assets in reducing temperatures and flooding in cities. Biomechanics is a study tool that views the tree not only as a biological being, but also as a structural one. A study carried out at PHd level, showed significant results when applying the finite element method (FEM) to simulate the behavior of trees and obtain displacements and stresses (normal and shear), with which resistance parameters of the wood of the species under study can be compared to infer the risk of rupture. The model, however, was only compared with a study carried out on a tree using a pulling test, which did not allow its validation, nor possible corrections of deviations to deepen and advance in the qualification of the results. Thus, this research aims to carry out field tests with different species to validate the proposed model as well as to use divergent results to deepen studies aimed at improving results. (AU)