EVALUATION OF THE Peltophorum vogelianum Benth. WOOD SPECIES FOR STRUCTURAL USE

ABSTRACT

Wood is a material used for various purposes since ancient times and is mainly used in civil and rural construction and industry. Due to the predatory exploitation of known trees, it is necessary to characterize new species for use in urban and rural structures as alternatives of species commonly used. This study aimed to determine the physical and mechanical properties of Guarucaia wood (Peltophorum vogelianum Benth.) based on the Brazilian standard ABNT NBR 7190 (1997) and estimate the strength and stiffness as a function of apparent density using the analysis of variance and also estimate stiffness as a function of its strength. The mechanical properties of P. vogelianum were considered compatible for structural use when compared with others used for the same purpose, being classified in the class C50 of dicotyledon species and evidencing the possibility of its use for structural purposes. According to the results of the poor quality in the fit of regression models in the statistical analysis, the strength and stiffness could not be estimated as a function of apparent density nor stiffness properties as a function of their respective strengths.

KEYWORDS
Peltophorum vogelianum; characterization; apparent density; regression models; analysis of variance (ANOVA)

INTRODUCTION

Wood is a natural and renewable material that has been used by humans for various purposes since ancient times, such as shelters, tools, and supplies. Currently, this abundant material in Brazil has been used in the construction, furniture, pulp and paper, sports equipment, and musical instrument industry (Zangiácomo et al., 2014; Beech et al., 2017; Christoforo et al., 2017a).

The use of this a versatile material implies knowing all its properties (anatomical, physical, mechanical, and chemical) so that its use can be performed efficiently, meeting the environmental demands by products and services provided by society (Dias & Lahr, 2004; Machado et al., 2014; Christoforo et al., 2017b; Aquino et al., 2018).

The high demand for wood by the various sectors of the industry led to selective and predatory extraction of species known to the construction market, thus leading to an increase in prices of these wood species. Thus, it is necessary to characterize and evaluate new wood species for structural use (Lahr et al., 2016a; Cavalheiro et al., 2016; Silva et al., 2018). The use of wood species Peltophorum vogelianum Benth. can be considered a good alternative, occurring in the Brazilian states of Bahia, Rio de Janeiro, Minas Gerais, Goiás, Mato Grosso do Sul, and Paraná (Lorenzi, 1998).

Timber structures in Brazil are designed using the Brazilian standard ABNT NBR 7190 (1997), which establishes requirements for the design, classification, and characterization of wood, defining the tests for determining wood physical and mechanical properties. However, these tests require the use of expensive equipment, available only at research centers.

Apparent density, defined as the ratio between the mass and apparent volume, with samples at the standard moisture of 12%, is a physical property of easy experimental determination that can be correlated with strength and stiffness properties by mathematical methods, allowing their estimation (Almeida et al., 2014; Dadzie & Amoah, 2015; Almeida et al., 2016; Christoforo et al., 2016). The possibility of estimating the strength and stiffness properties as a function of apparent density is an alternative to reduce costs and time.

The appendix B of the Brazilian standard ABNT NBR 7190 (1997) presents standard tests for determining stiffness properties (compressive and tensile strength parallel to fibers, compressive and tensile strength perpendicular to fibers, and static bending) of the wood, requiring testing machines, strain gauges, or dial indicators to measure deformations, unlike the strength properties, which are obtained from the relationship between the maximum stresses and geometric properties of the cross-sections of samples.

Considering the importance of stiffness properties in the sizing of wood structures, such as bridges, sheds, and timber residences (Ruelle et al., 2011; Machado et al., 2014; Dadzie & Amoah, 2015; Komariah et al., 2015), it is important to evaluate the possibility of estimating the stiffness properties as a function of the respective strength properties.

No studies can be found in the literature on the physical, mechanical, or anatomical characterization of the species P. vogelianum Benth., which reinforces the unprecedentedness of the present research. In order to contribute to the use of new wood species for structural purposes, this research aimed to characterize the wood species P. vogelianum Benth., as well as evaluate the possibility of estimating strength and stiffness properties as a function of apparent density and stiffness properties as a function of their strength properties.

MATERIAL AND METHODS

Wood samples from P. vogelianum extracted from western Pará State were properly stocked, resulting in samples with moisture content close to 12%, which is the equilibrium humidity defined by the Brazilian standard ABNT NBR 7190. The specimens were approximately 15 years old until harvesting.

Tests were performed at the Laboratory of Wood and Wood Structures (LaMEM), Department of Structural Engineering (SET), São Carlos Engineering School (EESC), University of São Paulo (USP).

Physical and mechanical properties were obtained according to prescriptions of the Brazilian standard ABNT NBR 7190 (1997), as set out in Appendix B. The evaluated properties and the number of experimental determinations per property are shown in Table 1. Three physical and 12 mechanical properties were evaluated, resulting in obtaining 180 experimental values. P. vogelianum wood was classified in the appropriate strength class (ABNT, 1997), according to the characteristic value of the compressive strength parallel to fibers (f_c0,k).

TABLE 1
Physical and mechanical properties evaluated for the species Peltophorum vogelianum.

Property	Abbreviation	ND
Apparent density	ρ12	12
Total radial shrinkage	TRS	12
Total tangential shrinkage	TTS	12
Compressive strength parallel to fibers	fc0	12
Compressive strength perpendicular to fibers	fc90	12
Tensile strength parallel to fibers	ft0	12
Tensile strength perpendicular to fibers	ft90	12
Shear strength parallel to fibers	fv0	12
Strength to cracking	fs0	12
Conventional strength in static bending test	fm	12
Hardness parallel to fibers	fH0	12
Hardness perpendicular to fibers	fH90	12
Longitudinal modulus of elasticity in the compressive parallel to fibers	Ec0	12
Modulus of elasticity in the compressive perpendicular to fibers	Ec90	12
Longitudinal modulus of elasticity in the tensile parallel to fibers	Et0	12
Conventional modulus of elasticity in the static bending test	Em	12
Toughness	W	12

• ND – number of determinations.

The classification of P. vogelianum wood in the strength classes for the dicotyledon group was performed using [eq. (1)], where f_k is the characteristic strength value and n is the number of specimens. The strength results from Equation 1 should be placed in ascending order (f₁≤f₂≤…≤f_n), not considering the highest value if the number of specimens is odd, and not taking f_k values lower than f₁ and nor at 0.70 of the mean value.

(1) $$f_{c0,k}=\left(2\cdot \frac{f_1+f_2+f_3+\dots +f_{\left(n/2\right)-1}}{\left(n/2\right)-1}-f_{n/2}\right)\cdot 1,10$$

Regression models (Equations 2 to 5) based on analysis of variance (ANOVA) were used to estimate strength and stiffness properties as a function of wood apparent density and also stiffness as a function of strength, with Y being the estimated property (dependent variable), X the independent variable, and a and b the parameters adjusted by the least-squares method.

(2) $$Y=a+b\cdot X{}_{\left[\text{Lin}-\text{linear}\right]}$$

(3) $$Y=a\cdot e^{b\cdot X}{}_{\left[\text{Exp}-\text{exponential}\right]}$$

(4) $$Y=a+b\cdot Ln(X){}_{\left[\text{Log}-\text{logarithmic}\right]}$$

(5) $$Y=a\cdot X^b{}_{\left[\text{Geo}-\text{geometric}\right]}$$

The ANOVA of regression models at 5% significance level (α) showed that the null hypothesis formulated consisted of non-representativeness of tested models (H₀: β = 0) and representativeness as an alternative hypothesis. P-value higher than the significance level implies the acceptance of H₀ (the model is not representative, i.e., variations in the independent variable cannot explain variations in the estimated properties), refuting it otherwise (the tested model is representative). The coefficient of determination (R²) was used to evaluate the quality of the obtained adjustments, allowing selecting the best accuracy for each evaluated relationship. Fifty-five density regression models were used as an estimator of 16 other variables (including the physical properties TRS and TTS), and 16 other models for strength properties as stiffness estimators, which resulted in 72 equations in all.

RESULTS AND DISCUSSION

Table 2 shows the mean values (X_m), coefficients of variation (CV), maximum values (Max), minimum values (Min), and the mean confidence interval (CI, 95% confidence) of physical and mechanical properties of Guarucaia wood, already shown in Table 1.

TABLE 2
Results obtained from the physical and mechanical properties of Guarucaia wood.

Property	Xm	CV (%)	Min	Max	CI
ρap (g/cm3)	0.92	8.00	0.73	0.98	0.87; 0.97
εr,2 (%)	4.13	18.00	3.45	6.12	3.67; 4.58
εr,3 (%)	8.09	11.00	7.23	9.89	7.54; 8.63
fc0 (MPa)	64.00	10.00	53.00	71.00	58.18; 65.81
ft0 (MPa)	75.00	18.00	54.00	103.00	66.10; 83.89
ft90 (MPa)	5.60	19.00	4.00	7.80	4.90; 6.29
fv0 (MPa)	20.00	18.00	16.00	26.00	17.45; 22.54
fs0 (MPa)	1.00	14.00	0.80	1.20	0.93; 1.06
fM (MPa)	95.00	16.00	76.00	124.00	85.47; 104.53
fH0 (MPa)	96.00	16.00	60.00	117.00	86.47; 105.53
fH90 (MPa)	77.00	24.00	33.00	94.00	65.56; 88.43
W (N·m)	12.70	39.00	6.00	19.30	9.59; 15.81
Ec0 (MPa)	16214	14.00	13196	19605	14789; 17639
Et0 (MPa)	14370	16.00	10765	18075	12931; 15809
EM (MPa)	15002	22.00	12328	24559	12868; 17136

Based on the characteristic value [56 MPa] of the compressive strength parallel to fibers (f_c0,k) of P. vogelianum wood (Equation 1), it was grouped into the strength class C50 of dicotyledons.

The f_c0 value [64 MPa] of Guarucaia wood was close to the value obtained in the study carried out by Dias & Lahr (2004) [62 MPa]. This species is in the same resistance class as Cupiúba [57 MPa] (Silva et al., 2018) and Eucalyptus urophylla [46 MPa] (Lahr et al., 2017), which are commonly used in structures (ABNT NBR 7190, 1997).

The value of compressive strength parallel to fibers (f_c0) of P. vogelianum wood [64 MPa] was higher when compared to other species, such Branquilho [48 MPa] (ABNT NBR 7190, 1997), Louro Preto [56 MPa] (ABNT NBR 7190, 1997), Cambará [34 MPa] (Lahr et al., 2016b), and Angelim Araroba [50 MPa] (ABNT NBR 7190, 1997). Branquilho, Louro Preto, and Angelim Araroba woods are indicated for structural use (ABNT NBR 7190, 1997), reinforcing the potential use of Guarucaia wood species for this purpose.

Considering the mean value obtained for apparent density [0.92 g/cm³], P. vogelianum wood can be classified as a heavy wood (Melo et al., 1990), in the same class as Pariri [0.92 g/cm³] (Almeida et al., 2015), Jatobá [1.08 g/cm³] (Lahr et al., 2016c), Minquartia guianensis, Lecythis poiteaui, Mezilaurus itauba, Manilkara huberi, Brosimum rubescens (Silveira et al., 2013), and Cupiúba [0.84 g/cm³] (Silva et al., 2018). P. vogelianum wood presented a higher density when compared to Cedrela odorata [0.41 g/cm³] (Fernandes et al., 2018), Liquidambar sp. [0.55 g/cm³] (Freitas et al., 2015), and Hovenia dulcis [0.51 g/cm³] (Leite et al., 2014).

The Brazilian standard ABNT NBR 7190 (1997) establishes the maximum value of the coefficient of variation as a criterion to consider an adequate characterization, being 18% for perpendicular and 28% for tangential strengths. All properties met the normative requirement, except toughness (W), which exceeded the limit (39%).

Table 3 shows the best adjustments obtained using regression models for apparent density in the estimation of the other properties, in which the models considered significant by ANOVA (5% significance) are underlined.

TABLE 3
Regression models based on apparent density as an estimator of other properties.

EP	Model	P-value	a	b	R2 (%)
TRS	Exponential	0.8048	4.74	−0.16	0.64
TTS	Geometric	0.2377	8.37	0.43	13.62
fc0	Linear	0.3054	39.03	25.56	10.45
ft0	Geometric	0.7099	75.41	0.24	1.44
ft90	Linear	0.5751	3.25	2.56	3.25
fv0	Exponential	0.1917	8.45	0.94	16.39
fs0	Exponential	0.0016	0.24	1.56	64.88
fM	Logarithmic	0.8314	96.57	11.64	0.48
fH0	Logarithmic	0.2758	101.45	59.25	11.73
fH90	Logarithmic	0.1996	84.82	81.95	15.86
W	Exponential	0.0090	0.30	4.01	51.01
Ec0	Geometric	0.3962	16721.39	0.42	7.29
Et0	Geometric	0.1533	15306.90	0.81	19.27
EM	Linear	0.9588	14982.02	−0.02	0.03

• EP – estimated property.

Apparent density was considered significant only in the estimation of strength to cracking (f_s0) [R² = 64.88%] and toughness (W) [R² = 51.01%], being the exponential model the best fit for both properties. Figure 1 shows the two regression models considered significant.

FIGURE 1
Density models as cracking (a) and toughness (b) estimators.

The significant adjustments in Table 3 show that the coefficients of determination are below 70% and hence with low precision (Christoforo et al., 2017a). The poor quality of the adjustment of regression models in the statistical analysis of properties indicates the impossibility of using the apparent density as their estimator in the present study. This impossibility (low precision) to estimate most properties may be due to the anatomical characteristics of the wood itself, which requires further studies to evaluate if there is an effective relationship. Related studies have shown the existence of a good correlation between apparent density and other properties due to the use of more than one wood species and mean values instead of sample values. The use of the mean value reduces the intrinsic variability of wood, but this approach could not be used here, as it is only one species. It is important to point out that Almeida et al. (2014) evaluated the use of apparent density with toughness estimator and found good quality regression models in the adjustment [R² > 70%]. It can be explained by the use of species with different densities and strength classes. Silva et al. (2018) also found a significant relationship between apparent density and toughness, with good fit quality [R² = 75.82%].

In addition, some authors have found significant relationships between apparent density and compressive strength, such as for woods of Calycophyllum multiflorum [R² = 52.59%] (Christoforo et al., 2017a), Vatairea sp. [R² = 63.57%] (Lahr et al., 2016a), and Castelo [R² = 52.84%] (Almeida et al., 2016), different from that found for Guarucaia in the present study.

Table 4 shows the best adjustments obtained in the estimation of stiffness properties as a function of their strength property.

TABLE 4
Regression models to estimate stiffness properties as a function of strength properties.

EP	Model	P-value	a	b	Equation	R2 (%)
Ec0	Linear	0.8051	18076	−30	$E_{\mathit{c}\mathit{0}}\mathit{=}a+b\mathit{·}{f}_{\mathit{c}\mathit{0}}$	0.64
Et0	Geometric	0.1946	2862	0.37	$E_{\mathit{t}\mathit{0}}\mathit{=}a\mathit{·}{f_{\mathit{t}\mathit{0}}}^{\mathit{b}}$	16.19
EM	Geometric	0.8040	9498	0.10	$E_{\mathit{M}}\mathit{=}a\mathit{·}{f_{\mathit{m}}}^{\mathit{b}}$	0.65

• EP – estimated property.

Table 4 shows that the models were not significant, revealing the impossibility of estimating stiffness properties as a function of the respective strength property.

CONCLUSIONS

The characterization of P. vogelianum wood was adequate for structural use according to the Brazilian standard ABNT NBR 7190 (1997).

Considering the criteria established in the Brazilian standard and due to the characteristic compressive strength value, P. vogelianum wood is classified into the C50 strength class, being compatible with other species of structural use. It evidences the possibility of using Guarucaia wood for structural use.

According to the values of coefficients of determination obtained in the adjustments, regression models did not show good precision in the estimation of the properties, revealing the impossibility of using the apparent density as an estimator of other properties and strength properties as an estimator of stiffness properties. More comprehensive results require the use of a variety of species.

ACKNOWLEDGMENTS

To the Coordination for the Improvement of Higher Education Personnel (CAPES) and the National Council for Scientific and Technological Development (CNPq) for all the support provided during the development of this research.

REFERENCES

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Publication Dates

• Publication in this collection
  09 Dec 2019
• Date of issue
  Nov-Dec 2019

History

• Received
  25 Aug 2018
• Accepted
  02 Oct 2019