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Research article - Peer-reviewed, 2020

Prediction of mechanical performance of acetylated MDF at different humid conditions

Ahmed, Sheikh Ali; Adamopoulos, Stergios; Li, Junqiu; Kovacikova, Janka

Abstract

Change of relative humidity (RH) in surrounding environment can greatly affect the physical and mechanical properties of wood-based panels. Commercially produced acetylated medium density fiberboard (MDF), Medite Tricoya®, was used in this study to predict strength and stiffness under varying humid conditions by separating samples in parallel (//) and perpendicular (⊥) to the sanding directions. Thickness swelling, static moduli of elasticity (MOEstat) and rupture (MORstat), and internal bond (IB) strength were measured at three different humid conditions, i.e., dry (35% RH), standard (65% RH) and wet (85% RH). Internal bond (IB) strength was also measured after accelerated aging test. A resonance method was used to determine dynamic modulus of elasticity (MOEdyn) at the aforementioned humid conditions. Linear regression and finite element (FE) analyses were used to predict the MDF’s static bending behavior. Results showed that dimensional stability, MOEstat, MORstat and IB strength decreased significantly with an increase in RH. No reduction of IB strength was observed after 426 h of accelerated aging test. A multiple regression model was established using MOEdyn and RH values to predict MOEstat and MORstat. In both directions (// and ⊥), highly significant relationships were observed. The predicted and the measured values of MOEstat and MORstat were satisfactorily related to each other, which indicated that the developed model can be effectively used for evaluating the strength and stiffness of Medite Tricoya® MDF samples at any humid condition. Percent errors of two different simulation techniques (standard and extended FE method) showed highly efficient way of simulating the MDF structures with low fidelity.

Keywords

acetylation; wood fiber; strength; stiffness; internal bonding strength; thickness swelling; regression; finite element analysis

Published in

Applied Sciences
2020, volume: 10, number: 23, article number: 8712

Authors' information

Ahmed, Sheikh Ali
Linnaeus University
Swedish University of Agricultural Sciences, Department of Forest Biomaterials and Technology
Li, Junqiu
Linnaeus University
Kovacikova, Janka
Linnaeus University

Sustainable Development Goals

SDG12 Ensure sustainable consumption and production patterns

UKÄ Subject classification

Composite Science and Engineering
Wood Science

Publication Identifiers

DOI: https://doi.org/10.3390/app10238712

URI (permanent link to this page)

https://res.slu.se/id/publ/109099