How microstructure impacts softwood stiffness? Hybrid multiscale homogenisation and AI-assisted sensitivity analyses

How microstructure impacts softwood stiffness? Hybrid multiscale homogenisation and AI-assisted sensitivity analyses | Research Square Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article How microstructure impacts softwood stiffness? Hybrid multiscale homogenisation and AI-assisted sensitivity analyses Arthur Thirion, Markus Königsberger, Sebastian Pech, Josef Füssl This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9223177/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Aug, 2026 Read the published version in Wood Science and Technology → Version 1 posted 11 You are reading this latest preprint version Abstract This study addresses the complex hierarchical nature of softwood by establishing quantitative links between its multiscale microstructure and macroscopic stiffness. A hybrid multiscale modelling framework is developed that combines analytical continuum micromechanics with a numerical finite-element unit-cell approach. The unit cell enables a more nuanced description of the cellular architecture, including cell misalignment, corner roundness, and cell wall heterogeneity.After the model has been successfully validated against independent experimental data, a neural network-based surrogate model is trained to map the 15 morphological microscale inputs to the macroscale engineering stiffness constants. This surrogate enables instantaneous predictions of material properties and a systematic assessment of sensitivities in the structure-property relationships. A Coefficient of Prognosis analysis provides quantitative measures of the relative contribution of each morphological input parameter to each engineering constant.The Coefficient of Prognosis analyses corroborate the dominant influence of density and microfibril orientation on the macroscopic stiffness moduli, while geometric cell features, such as lumen aspect ratio and radial cell wall alignment, emerge as critical second-order parameters for the transverse Young’s moduli and the rolling shear modulus. In contrast, the transverse Poisson’s ratios are predominantly controlled by cell geometry; density is only a secondary contributor. Furthermore, the importance of previously under-appreciated features, such as rays, in stiffening the radial direction is quantitatively established. These findings provide a better understanding of the structure-property relationships of softwood, offering a computationally efficient tool for future utilisation, development, and optimisation of wood products. continuum micromechanics Poisson's ratio shear modulus structure-property relationship unit cell wood cell geometry Young's modulus Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 25 Aug, 2026 Read the published version in Wood Science and Technology → Version 1 posted Editorial decision: Revision requested 11 May, 2026 Reviews received at journal 06 May, 2026 Reviews received at journal 04 May, 2026 Reviews received at journal 28 Apr, 2026 Reviewers agreed at journal 16 Apr, 2026 Reviewers agreed at journal 15 Apr, 2026 Reviewers agreed at journal 15 Apr, 2026 Reviewers invited by journal 14 Apr, 2026 Editor assigned by journal 14 Apr, 2026 Submission checks completed at journal 26 Mar, 2026 First submitted to journal 25 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information

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