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Estimation model of mechanical properties from the compressive strength values

Authors :
Anderson Renato Vobornik Wolenski
João Paulo Boff Almeida
André Luís Christoforo
Francisco Antonio Rocco Lahr
Rodrigo Guerra Peixoto
Source :
Maderas: Ciencia y Tecnología, Vol 22, Iss 4 (2020)
Publication Year :
2020
Publisher :
Universidad del Bío-Bío, 2020.

Abstract

To ensure the safety of wooden structures, estimation of wood strength is based on the characteristic strength values. The Brazilian standard (NBR, in Portuguese Norma Brasileira Regulamentadora) 7190 proposes equations to estimate the strength properties with a simplified procedure, which allows obtaining the characteristic values through relations that correlate different mechanical properties. Using these equations, the values of tensile (ft0,k) and shear (fv0,k) strength can be calculated in a simplified way from the compressive strength (fc0,k) values. In the present work, 36 tropical hardwood species were evaluated for tensile, shear and compressive strength in the direction parallel to the grain, with a total of 1296 experimental measurements, and the precision of the relations defined by the Brazilian standard was assessed using the analysis of variance (ANOVA) method. Two-parameter regression models, based on linear, exponential, logarithmic and geometric functions, were used as an alternative proposal for the estimation of the strength properties. The statistical analysis validated the proposed relations, with the linear (ft0,k) and geometric (fv0,k) regression models being the models of best fit, with the coefficients of determination (R2) equal to 63,02 % and 70,15 %, respectively. In addition, new simplified equations were suggested. The least squares method was used to determine the optimal coefficient (α) for validation of the Brazilian standard equations. The obtained coefficients validated the tensile strength relationship (ft0,k = fc0,k / 0,77), but failed to validate the shear strength relationship (fv0,k = 0,12∙ fc0,k). In the latter case, the obtained values were significantly higher (up to 91 % higher) when compared to those estimated by the Standard

Details

Language :
English, Spanish; Castilian
ISSN :
07173644 and 0718221X
Volume :
22
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Maderas: Ciencia y Tecnología
Publication Type :
Academic Journal
Accession number :
edsdoj.6fcfb9df17a4870bd48e3d32a65a57f
Document Type :
article