| Citation: | Sheng He, Lanying Lin, Zaixing Wu, Zhangmin Chen. Application of Finite Element Analysis in Properties Test of Finger-jointed Lumber[J]. Journal of Bioresources and Bioproducts, 2020, 5(2): 124-133. doi: 10.1016/j.jobab.2020.04.006
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Finger-jointed lumber production has now become the most extensively used method for spliced lumbers jointing together endwise. The properties of finger-jointed lumber are affected by many different factors such as the end- pressure. The main mechanical properties to be tested for structural use finger-jointed lumber include the modulus of elasticity in static bending and the bending strength. The most commonly used method for testing these properties at present is the experimental test. In this study, we used finite element method to investigate the end-pressure range, the modulus of elasticity in static bending and the bending strength for Pinus sylvistriv var. finger-jointed lumber under three different fitness ratios (0 mm, 0.1 mm, 0.3 mm). With finite element analysis (FEA) modelling results compared with the experimental test results, it is possible to find the relationship between these two kinds of results and use the FEA to predict the properties of finger-jointed lumber. The FEA applied in the end pressure tests showed a narrower range compared with the modelling results. It indicated that the FEA could be used in the prediction of the end pressure for finger-jointed lumber. The modelling results for modulus of elasticity (MOE) test and bending strength (MOR) test showed about 20% discrepancies compared with the experimental results. Moreover, the MOE modelling results showed the same trend as experimental results under three different fitness levels while the MOR modelling results showed the different trend. It can be concluded that the FEA is a feasible way in analyzing the properties of finger-jointed lumber if the errors could be eliminated properly. Some modifications should be made in order to realize the prediction of the properties of finger-jointed lumber more accurately.
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