Estimating the Service Life of Timber Structures Concerning Risk and Influence of Fungal Decay—A Review of Existing Theory and Modelling Approaches

Wood is a renewable resource and a promising construction material for the growing bio-based economy. Efficiently utilising wood in the built environment requires a comprehensive understanding of the dynamics regarding its usability. Durability is an essential property to consider, as various types...

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Bibliographic Details
Main Authors: Philip Bester van Niekerk, Christian Brischke, Jonas Niklewski
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Forests
Subjects:
Online Access:https://www.mdpi.com/1999-4907/12/5/588
Description
Summary:Wood is a renewable resource and a promising construction material for the growing bio-based economy. Efficiently utilising wood in the built environment requires a comprehensive understanding of the dynamics regarding its usability. Durability is an essential property to consider, as various types of exposure create conditions for the deterioration of wood through biotic and abiotic agents. Biodegradable materials introduce increased complexity to construction and design processes, as material decomposition during a structure’s lifetime presents a physical risk to human health and safety and costs related to repairs and maintenance. Construction professionals are thus tasked with utilising wooden elements to accentuate the material’s beneficial properties while reducing the risk of in-service decomposition. In this paper, only the cause and effect of fungal induced decay on the service life of wooden buildings and other wood-based construction assets are reviewed. The service life of wood components can thus be extended if suitable growing conditions are controlled. Multiple existing modelling approaches are described throughout the text, with special attention given to the two most comprehensive ones; TimberLife and the WoodExter. In choosing an appropriate model for a specific application, the authors recommend evaluating the model’s regional specificity, complexity, practicality, longevity and adaptability.
ISSN:1999-4907