Scanning Old Wood Like New: CT Technology Predicts Timber Strength Better Than Visual Inspection
Researchers have shown that CT scanning can reliably assess the structural strength of reclaimed timber beams—outperforming traditional eye-based grading. The finding matters because it could unlock billions in salvaged wood for construction while reducing waste, lowering building costs, and supporting the emerging mass-timber industry.
Originaltitel: Comparative Evaluation of Non-destructive and CT-derived Indicators for Stiffness Assessment of Reclaimed Norway Spruce Timber
This preprint presents a multimodal evaluation framework for reclaimed structural timber, combining X-ray computed tomography (CT), visual grading, dynamic excitation, four-point bending tests, and two classes of computational models (continuum-mechanics models and finite element analyses). Using 56 full-length reclaimed beams, the study compares the spatial sensitivity and predictive performance of established non-destructive techniques and CT-derived stiffness and density fields. The results demonstrate how voxel-resolved CT information can quantify stiffness- and defect-related variability and how these indicators relate to global and local mechanical performance. The analyses include:• Full-resolution CT-derived density and fibre-orientation fields• Longitudinal and transversal dynamic excitation measurements• Destructive and non-destructive mechanical bending tests• Visual grading according to INSTA 142, UNI 11119, and NS 3691-3• CT-based continuum-mechanics stiffness models• CT-informed finite element models with orthotropic material fields• Correlation, regression, and indicator-comparison analyses at beam and zone scales All underlying CT volumes, derived stiffness fields, CM and FE model outputs, profile-level results, and statistical analysis plots are openly available in the associated dataset: Dataset:Huber, J.A.J. et al. (2025). Multimodal Reclaimed Timber Dataset: X-ray CT Volumes, Visual Grading, Dynamic Tests, Mechanical Tests, and Finite Element and Continuum Model Results. Zenodo. DOI: https://doi.org/10.5281/zenodo.17682666 This preprint should be cited together with the dataset when reusing data, analysis workflows, or modelling approaches.