Micromechanical analytical and inverse numerical modeling methods for determining the transverse elastic modulus of bamboo

Abstract Bamboo has recently become a key material in green engineering. However, measuring its transverse elastic modulus (ET) is difficult due to the inherent structural properties of bamboo culm. In this study, two micromechanical analytical models, the Chamis model and Reuss model, and a finite element (FE) inverse numerical method were used to calculate the elastic modulus perpendicular to the bamboo grain by using a specially designed strip-reinforced polymer specimen. A bamboo veneer microtensile test was used to verify these approaches. The effect of the specimen geometry on measurement accuracy was also determined. This novel approach was also used to determine the ET of two bamboo species. The Chamis model had the best performance because its assumptions regarding the fiber section geometry were consistent with the actual specimen; the Reuss model had the worst results. The result of the FE method was slightly distorted due to the high sensitivity of parameters. A parametric study revealed that the micromechanics and FE descriptions of the modulus of the resin–fiber combination differed. The fiber volume fraction affected the prediction accuracy, but not the width or spacing of the bamboo strips. The strain and stress distribution of composite repeating units were studied. The results of ET measurements for the two bamboo species were reasonable. In conclusion, a novel, verified, simple, and accurate method was developed for determining the ET of bamboo..

Medienart:

Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:57

Enthalten in:

Wood science and technology - 57(2022), 1 vom: 17. Dez., Seite 75-92

Sprache:

Englisch

Beteiligte Personen:

Chang, Chun-Wei [VerfasserIn]
Lin, Chi-Yen [VerfasserIn]
Kao, Hao-Wei [VerfasserIn]
Chang, Feng-Cheng [VerfasserIn]

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© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

doi:

10.1007/s00226-022-01445-3

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

OLC2134024259