Evaluation of the characteristic values of mechanical properties in five tropical wood species using different statistical methods

ABSTRACT Brazilian Code NBR 7190:2022 for timber structures design adopts a simplified approach for determining characteristic values from small samples, based on the Centered Estimator Method assuming data normality. However, there is a gap in literature regarding its accuracy compared to the widely used approach in interna-tional codes, which defines the characteristic value as the 5th percentile of a fitted statistical distribution. This study evaluated strength and stiffness properties in tension and compression parallel to grain of five Brazilian tropical species, comparing the characteristic values obtained by NBR 7190-3:2022 with those derived from the 5th percentile of normal, lognormal, two-parameter Weibull, three-parameter Weibull, Gamma, and Logistic distributions. Results indicated that the normal distribution was adequate in most cases, while three-parameter Weibull distribution demonstrated greater flexibility in fitting, in capturing skewness in strength/stiffness distributions but also resulted in less conservative characteristic values. Additionally, it was observed that NBR 7190-3:2022 method led to characteristic values of mechanical properties, on average, 7% to 29% higher than those obtained from the 5th percentile of the analyzed statistical distributions. These results suggest the need to revise the Centered Estimator Method in NBR 7190-3:2022, to improve estimating characteristic value reliability.

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Publication Details

Journal
Matéria (Rio de Janeiro)
Published
2025-01-01
DOI
https://doi.org/10.1590/1517-7076-rmat-2025-0309
Primary Topic
Forest ecology and management
Type
article
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article

Evaluation of the characteristic values of mechanical properties in five tropical wood species using different statistical methods

Francisco Antônio Rocco Lahr, Clara Gaspar Fossi de Souza, José Ricardo Gabriel Kuniyoshi, André Luís Christoforo
Matéria (Rio de Janeiro)
Forest ecology and management
article

Evaluation of the characteristic values of mechanical properties in five tropical wood species using different statistical methods

Francisco Antônio Rocco Lahr, Clara Gaspar Fossi de Souza, José Ricardo Gabriel Kuniyoshi, André Luís Christoforo
article en

Abstract

ABSTRACT Brazilian Code NBR 7190:2022 for timber structures design adopts a simplified approach for determining characteristic values from small samples, based on the Centered Estimator Method assuming data normality. However, there is a gap in literature regarding its accuracy compared to the widely used approach in interna-tional codes, which defines the characteristic value as the 5th percentile of a fitted statistical distribution. This study evaluated strength and stiffness properties in tension and compression parallel to grain of five Brazilian tropical species, comparing the characteristic values obtained by NBR 7190-3:2022 with those derived from the 5th percentile of normal, lognormal, two-parameter Weibull, three-parameter Weibull, Gamma, and Logistic distributions. Results indicated that the normal distribution was adequate in most cases, while three-parameter Weibull distribution demonstrated greater flexibility in fitting, in capturing skewness in strength/stiffness distributions but also resulted in less conservative characteristic values. Additionally, it was observed that NBR 7190-3:2022 method led to characteristic values of mechanical properties, on average, 7% to 29% higher than those obtained from the 5th percentile of the analyzed statistical distributions. These results suggest the need to revise the Centered Estimator Method in NBR 7190-3:2022, to improve estimating characteristic value reliability.

Matéria (Rio de Janeiro)Vol. 30
Universidade Federal de São Carlos (BR), Universidade de São Paulo (BR), Universidade Brasil (BR)
Openalex Percentile: Top 73%
Forest ecology and management
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Evaluation of the characteristic values of mechanical properties in five tropical wood species using different statistical methods — Francisco Antônio Rocco Lahr, Clara Gaspar Fossi de Souza, et al. · Matéria (Rio de Janeiro) (2025) | TGRS Research Map | TGRS