The assessment of the mechanical and physical properties of in situ timber

Bather, Mike; Ridley-Ellis, Dan

Abstract

The refurbishment of existing buildings is a more sustainable option than demolition and reconstruction, leading to significant reductions in CO2 emissions and many other benefits. Policy across Europe is leaning more towards retaining and upgrading buildings rather than replacement and this is already a significant contributor to health and wellbeing. Since many buildings contain structural timber, there is a need for its structural appraisal.
Current methods of structural appraisal are largely (i) inappropriate, as they utilise visual grading codes of practice intended for use on large batches of new timber and not for use on individual pieces of timber, (ii) inaccurate, as the visual grading parameters used are only weakly correlated with timber’s mechanical and physical properties, and (iii) imprecise, as they utilise strength classification, which groups all timber into a small number of classes with associated characteristic properties. Therefore, better methods are needed.
This paper presents a very brief overview of a recently completed PhD study on a practical structural engineering approach to develop models that combine visual observations, non-destructive and semi-destructive techniques to estimate characteristic values of modulus of elasticity (MoE), bending strength (MoR) and density, in a manner consistent with the Eurocodes and in a way that accounts for the variability of in situ timber. In the creation of the models, quantile regression and bootstrapping are used in novel ways.

Citation

Bather, M., & Ridley-Ellis, D. (2022, September). The assessment of the mechanical and physical properties of in situ timber. Paper presented at Northern European Network for Wood Science and Engineering (WSE) 2022, Goettingen, Germany

• Presentation Conference Type: Conference Paper (unpublished)
• Conference Name: Northern European Network for Wood Science and Engineering (WSE) 2022
• Start Date: Sep 21, 2022
• End Date: Sep 22, 2022
• Deposit Date: Jun 27, 2023
• Keywords: NDT, SDT, characteristic values, Eurocodes, quantile regression, bootstrapping
• Publisher URL: https://www.uni-goettingen.de/de/wse+2022/652657.html