Advanced Numerical and Experimental Methods for Timber Structures

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Wood Science and Forest Products".

Deadline for manuscript submissions: 31 January 2026 | Viewed by 62

Special Issue Editors


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Guest Editor
Faculty of Civil and Geodetic Engineering, University of Ljubljana, Ljubljana, Slovenia
Interests: timber structures; moisture; wood; mechanics

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Guest Editor
Department of Civil Building-Architecture and Environmental Engineering, University of L’Aquila, L'Aquila, Italy
Interests: timber engineering; composite structures
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Wood Science, Univerza v Ljubljani, Ljubljana, Slovenia
Interests: wood physics; non-destructive characterization; acoustics of wood; wood drying; hydrothermal treatment

Special Issue Information

Dear Colleagues,

This Special Issue invites high-quality research on advanced numerical modeling and experimental methods to improve the design and analysis of timber structures. The anisotropic and heterogeneous nature of wood, along with the complexity of modern engineered wood products like cross-laminated timber, hybrid timber beams, and their connections, presents challenges in accurately predicting structural behavior under varying loads and environmental conditions.

We welcome contributions on advanced numerical methods, including multi-scale finite element modeling (linear and nonlinear), multi-physics simulations, and probabilistic or stochastic approaches. Studies incorporating machine learning or data-driven optimization to address moisture transport, time- and moisture-dependent phenomena (e.g., creep and mechanosorption), and fracture mechanics are also welcomed.

We equally encourage experimental investigations that provide critical insights into moisture transport, creep, fracture mechanics, damage evolution, and time-dependent effects. Studies involving short- and long-term testing at small and full scales are welcome, especially those using methods such as digital image correlation (DIC), dynamic vapor sorption (DVS), computed tomography (CT), and long-term structural health monitoring (SHM).

This Special Issue aims to bridge material science, structural engineering, and digital innovation to support the safe, efficient, and sustainable application of timber in tall and complex structures. We look forward to receiving contributions that advance the state of the art in numerical and experimental methods for the design and analysis of timber structures.

Dr. Sabina Huč
Dr. Martina Sciomenta
Dr. Straže Aleš
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • connections
  • experimental methods
  • finite element modeling
  • fracture mechanics
  • machine learning
  • moisture transport
  • timber structures
  • time- and moisture-dependent creep

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Published Papers (1 paper)

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Research

15 pages, 3671 KiB  
Article
Initial Insights into Spruce Wood Fatigue Behaviour Using Dynamic Mechanical Properties in Low-Cycle Fatigue
by Gregor Gaberšček Tuta, Gorazd Fajdiga and Aleš Straže
Forests 2025, 16(8), 1324; https://doi.org/10.3390/f16081324 - 14 Aug 2025
Abstract
Damaged material invariably exhibits a lower resonance frequency than undamaged material due to its reduced stiffness. Under fatigue loading, damage accumulates until failure, so changes in resonance frequency can be utilised as a variable to predict fatigue life. Conventional fatigue life prediction methods [...] Read more.
Damaged material invariably exhibits a lower resonance frequency than undamaged material due to its reduced stiffness. Under fatigue loading, damage accumulates until failure, so changes in resonance frequency can be utilised as a variable to predict fatigue life. Conventional fatigue life prediction methods have a low success rate, prompting the exploration of alternative approaches. We have presented a novel method for predicting the fatigue life of spruce wood based on changes in resonance frequency during fatigue, using a representative specimen (i.e., one out of five specimens tested, with four used for static strength reference). We conducted a low-cycle fatigue test and monitored the resonance frequency alongside the dynamic and static modulus of elasticity. All three types of data were employed to predict fatigue life using between 40% and 100% of the measurement data. Of the two fatigue life prediction methods investigated, the Weibull cycle density distribution using resonance frequency measurements proved most appropriate. The error decreases monotonically with the amount of resonance frequency measurement data used for fatigue life prediction, reaching its lowest value of 1% when the full resonance frequency dataset is used. The proposed fatigue life prediction method should be further validated with a larger sample size, as fatigue is inherently a statistical phenomenon. Full article
(This article belongs to the Special Issue Advanced Numerical and Experimental Methods for Timber Structures)
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