Acoustic test methods such as longitudinal vibration have been developed to predict the elastic properties of wood. However, attention has not been shifted to using this method to predict other mechanical properties, especially on Nigeria's preferred, and lesser-used wood species. Thus, we further investigate relationships among mechanical and acoustic properties of selected hardwood species with a view of predicting the mechanical properties of wood from acoustic parameters. Clear wood samples (324) of 20 by 20 by 20 mm3 were collected axially from Albizia adianthifolia, Gmelina arborea, Delonix regia, and Boscia anguistifolia trees, and conditioned before testing. The longitudinal vibration method was adopted to test for the dynamic (acoustic) parameters and properties (fundamental frequency, damping factor, dynamic modulus of elasticity, sound velocity, specific elastic modulus, radiation coefficient, acoustic conversion efficiency, acoustic impedance) while the universal testing machine was used to test for the mechanical properties (static modulus of elasticity, modulus of rupture, maximum compression strength parallel to grain). The damping factor, dynamic modulus of elasticity, and acoustic impedance were the best acoustic parameters that significantly correlated with the static modulus of elasticity (−0.57, 0.81, 0.76), modulus of rupture −0.64, 0.82, 0.85) and maximum compression strength parallel to grain (−0.52, 0.78, 0.84), respectively. There was a significant difference in the mechanical properties with respect to species, thus A. adianthifolia and G. arborea were mechanically better than D. regia and B. anguistifolia for construction or structural purposes. This study revealed that additional new acoustic measures are suitable for inferring mechanical wood properties.
Acoustic properties of wood are associated with the wood structure's response to vibration generally induced by surface impact or excitation (Shirmohammadi et al. 2020). The general acoustic properties of interest are dynamic modulus of elasticity (dMOE), sound velocity (V), damping ratio (tan δ), specific dynamic elastic modulus (Es), and acoustic coefficient (K) (Spycheret al. 2008, Sproßmann et al. 2017). Authors such as Obataya et al. (2000) and Olaoye et al. (2019) have found the longitudinal vibration acoustic method suitable for predicting static elastic modulus of wood.
Wood is one of the oldest, most versatile, and most lightweight renewable resources that has been accepted and conditioned for structural and construction applications on its stiffness properties (Green 2001, Smith and Snow 2008, Ramage et al. 2017). The strength properties of wood considered for construction purposes may be generally assessed through visual grading; however, it is scientifically determined through assessing the mechanical properties. Mechanical properties are characterized by the response of a material to externally applied forces (Murugan 2020). Furthermore, it was highlighted that static modulus of elasticity (sMOE), bending strength, and parallel compression strength are the most sought-after mechanical properties for assessing the strength of wood. (Vernay 2000, Messaoudene et al. 2008).
Mechanical methods such as resistance drilling, screw withdrawal, hardness test (Nowak et al. 2021), and the use of a universal testing machine (UTM) have been adopted for measuring the strength properties of wood. Notwithstanding, the common method of determining the mechanical properties of wood is through the use of the UTM. This method is considered expensive, demanding high maintenance cost; it is time-consuming—about 10 minutes per sample—and also damages the wood samples, thus rendering an undesirable effect. Consequently, there has been a continuous and concerted effort to search for cheaper, faster, safer, and non-destructive means of determining the mechanical properties of wood.
In light of the above, scholars have endeavored to engage acoustic techniques such as the longitudinal vibration method to evaluate some mechanical properties of wood. Leite et al. (2012), Olaoye (2019), and Olaoye and Okon-Akan (2020) estimated the sMOE of selected wood species from the dMOE, while Chauhan and Sethy (2016) estimated the modulus of elasticity (MOE) and modulus of rupture (MOR) from dMOE using three different vibration acoustic methods. They all found a suitable relationship among properties measured. However, the suitability of the longitudinal vibration acoustic method where two or more species are combined has yet to be adequately demonstrated.
Although the relationship between sMOE and dMOE of wood has been established, there is little or no investigation into the suitability of other acoustic parameters such as V, tan δ, and Es as predictors for other static mechanical properties. It is thus appropriate to suspect additional significant relationships. Additionally, the application of the longitudinal vibration acoustic method on Nigeria's preferred and lesser-used wood species has not gained prominence. Therefore, investigation into the relationship among these properties is needed to reveal and broaden knowledge of other acoustic parameters useful for predicting more mechanical properties, especially on selected wood species in Nigeria. Hence, this study aimed at determining the relationship among the mechanical and acoustic properties of selected hardwood species with the view of predicting the mechanical properties using the longitudinal vibration acoustic method.
The selected wood species considered in this study were Albizia adianthifolia, Gmelina arborea, Delonix regia, and Boscia anguistifolia. Albizia adianthifolia is a tall tree (about 36 m) with a few large, widely spreading branches. It is widespread in tropical Africa and southern Africa, and is commonly called “ayinre bona bona” in Yoruba, southwestern Nigeria (Lock and Keay 1991). Also, G. arborea is a widely cultivated and distributed exotic wood species in Nigeria. It has found prominence in uses for acoustic application and musical instruments such as the talking drum (Aiyeloja et al. 2015). It produces high-quality wood, which is harvested for the manufacture of furniture, musical instruments, plywood, and matches (Beentje et al. 2003, Orwa et al. 2009). Delonix regia belongs to the family Fabaceae, and is a medium-sized tree found in tropical countries (Shewale et al. 2012). Its wood has been explored for making cutlery, industrial and domestic woodware, musical instruments, tool handles, and toys (Patro 2016). Boscia angustifolia is a shrub or small tree about 6 m high that belongs to the family Capparaceae and it is commonly found across Africa (Burkill 1985).
Materials and Methods
Sample collection and preparation
Three trees (diameter at breast height of 25 ± 2 cm) of each species, A. adianthifolia, G. arborea, D. regia, and B. anguistifolia (making a total of 12 trees), were felled. Gmelina arborea and B. anguistifolia were felled from Gambari Forest Reserve, Oyo State, Nigeria, while A. adianthifolia and D. regia were felled from farmland. The trees were partitioned axially (top, middle, and base) using a chainsaw, and further converted to wood samples of 20 by 20 by 20 mm3 (radial by tangential by longitudinal; British standards [BS] 373 1957) using the circular machine. Twenty-seven clear wood samples were collected from each tree for the acoustic and mechanical properties test, thus making a total of 324 wood samples (i.e., 27 wood samples with 3 replicates of each tree species and 4 tree species) considered for this study. All wood samples were oven-dried at 103°C ± 2°C for 24 hours and conditioned at 80% relative humidity and 30°C for 1 month before testing, to reach equilibrium moisture content.
Gambari Forest Reserve, formally known as Ibadan District Native Authority Forest Reserve, lies between latitudes 7°25′N and 7°55′N and longitudes 3°53′E and 3°9′E. It is situated between River Ona on the west and the main motor road from Ibadan to Ijebu-Ode on the east. The site map is shown in Figure 1. The forest reserve has a typical humid climate with two distinct seasons a year. The two seasons are the rainy season, which runs from April until October, and the dry season, which falls between November and March. The annual rainfall is 1,257 mm. The relative humidity ranges between 84.5% (June till September) and 78.8% (December till January). The mean annual temperature ranges from 21.0°C to 31.3°C (Shomade 2000).
The longitudinal vibration test
Equations 3 through 9 were used to calculate other selected acoustic parameters.
Static bending test
The experiment was set up in a completely randomized design and data obtained were subjected to analysis of variance, Pearson correlation (r), and regression analysis at α0.05.
Yij = μ + Ti + Eij
Yij = individual observation
μ = mean
Ti = treatment effect (tree species)
Eij = error term
The mean mechanical and acoustic properties of the hardwood species are reported in Table 1. The sMOE was highest (9.58 GPa) for G. arborea wood while A. adianthifolia wood had the highest MOR (106.31 N mm−2) and MCS// (52.61 N mm−2). For the acoustic properties measured, G. arborea wood had the highest values for FF (1073 Hz), dMOE (11.30 GPa), V (4528.54 m s−1), Es (20.55 GPa), K (8.27), ACE (4013.83 m4 kg−1 s−1), Z (2,492.05 × 103 kg m−2 s−1), but lowest value for tanδ (0.002).
Table 2 shows the correlation analysis among the mechanical and acoustic properties. The least coefficient of correlation (r = 0.15) was obtained with MCS// and ACE while r was highest (0.85) with MOR and Z. All the correlations among these properties were significant, except for sMOE with ACE (0.18), and MCS// with ACE (0.15). Also, Figures 4 through 14 revealed the best selected significant relationship among the mechanical and acoustic properties measured. Each figure shows the exponential and linear relationships of selected properties, for effective comparison. The gray and black trend lines represent the exponential and linear relationships respectively. The highest coefficient of correlation of determination (R2) obtained was with MOR and Z (0.73; linear relationship) while the least R2 was with MCS// and tanδ (0.27; exponential and linear relationship). Meanwhile, Figures 15 through 25 show the graphical relationships among these properties for the different wood species.
Wood species intended for construction purposes must possess good mechanical traits, this thus implies that a good evaluation of mechanical properties is essential. Therefore, A. adianthifolia and G. arborea, which have the highest significant values of the mechanical properties sMOE, MOR, and MCS//, is the most suitable for construction purposes among the four species examined. Meanwhile, classification of the strength property of wood based on sMOE values according to Upton and Attah (2003) is thus; “very high” (19 GPa and more), “high” (14 to 19 GPa), “medium” (11 to 14 GPa), “low/medium” (9 to 11 GPa) and “low” (below 9 GPa). Consequently, A. adianthifolia and G. arborea wood had low/medium strength while D. regia and B. anguistifolia had low strength traits.
The mean sMOE value obtained in this study for G. arborea wood was slightly higher than those reported by Ataguba et al. (2015), who found sMOE values ranging between 7,900 and 8,000 N mm−2 for similar species. Meanwhile, the mean sMOE for B. anguistifolia obtained by Adebawo et al. (2019; 6,250 N mm−2) was a little higher than the mean sMOE obtained in this study while the MOR (46.44 N mm−2) and MCS// (24.20 N mm−2) were lower.
Interestingly, the sMOE values of the studied hardwood species were within the range of the following selected hardwood species in Nigeria: 7,090 N mm−2 for Celtis mildbraedii, 6,310 N mm−2 for Afzelia africana, 8,190 N mm−2 for Khaya ivorensis, 5,770 N mm−2 for Meliceae excelsa, and 3,930 N mm−2 for Triplochiton scleroxylon (Jamala 2013).
MCS// values are classified as very low (under 20 N mm−2), low (20 to 35 N mm−2), medium (35 to 55 N mm−2), high (55 to 85 N mm−2), and very high (over 85 N mm−2; Ojo 2020). Therefore, A. adianthifolia and G.arborea possess a medium MCS// while D. regia and B. anguistifolia is within the range of low MCS//.
The mechanical properties of wood can be influenced by its anatomical makeup (Kasal 2004). Therefore, with different anatomical makeup of wood species, properties such as fiber length, wood density, the orientation of microfibrils, and chemical composition may be responsible for the strength performance of wood species.
Relationship between sMOE and acoustic properties
A higher value of dMOE compared with the sMOE obtained for all the tested hardwood species supports findings of other researchers (Ilic 2001, Burdzik and Nkwera 2002, Targa et al. 2005, Leite et al. 2012, Chauhan and Sethy 2016). However, lower values of dMOE have also been found in some studies (Hodoušek et al. 2017, Olaoye 2019, Olaoye and Okon-Akan 2020). Variation in trends like this can be attributed to the type of acoustic method used, or sample dimensions, as opined by Hodoušek et al. (2017), especially sample length (Bucur and Archer 1984).
All the acoustic properties measured in this study had significant correlations with sMOE, except ACE, an indication that acoustic properties are a good predictor of sMOE. Thus, tanδ, dMOE, and Z are the acoustic properties that had the best suitable relationship with sMOE. Also, the results revealed that tanδ had a negative correlation with sMOE while dMOE and Z had a positive correlation with sMOE. This implies that the lower the tanδ, the higher the sMOE, while the more the dMOE and Z, the more the sMOE.
Similarly, a negative correlation (−0.59) was found between sMOE and tanδ, as well as a positive relationship (0.94) between sMOE and dMOE (Leite et al. 2012), thus supporting the findings in this study. The higher values of coefficient of determination (R2) imply that the exponential relationship for predicting sMOE from tanδ, dMOE, and Z was more suitable than its linear relationship (Figs. 3 through 5).
The R2 obtained in this study for sMOE and dMOE was lower than that of Leite et al. (2012; 0.85), Chauhan and Sethy (2016; 0.97), Baar et al. (2015; 0.83), Hodoušek et al. (2017; 0.81 to 0.87), but within range of Olaoye and Okon-Akan (2020; 0.65), Casado et al. (2010; 0.28 to 0.59), and Baar et al. (2015; 0.52). Figures 15 through 25 in this study confirms the opinion of Karlinasari et al. (2008),Ravenshorst et al. (2008), and Teles et al. (2011) that the strength of correlation between these properties can be dependent on species, or type of acoustic methods used, while Casado et al. (2010) also emphasized sample dimension as a cause of variation in strength correlation. Hence, the medium correlation obtained between sMOE and dMOE in this study may be due to different species used for this study or types of acoustic methods used in other studies.
Nevertheless, a significantly higher exponential relationship between sMOE and dMOE suggests that sMOE had a suitable exponential increment with an increasing dMOE, as against the linear relationship opined by several researchers (Leite et al. 2012; Baar et al. 2015; Chauhan and Sethy 2016; Olaoye and Okon-Akan 2020).
The significant exponential positive relationship between sMOE and Z also implies that sMOE will increase exponentially with increasing Z. As such, the information provided by this study confirms that tanδ, dMOE, and Z had a better exponential relationship that is useful for predicting sMOE.
Relationship between MOR and acoustic properties
As is evident in Table 2, all the acoustic properties had either a positive or negative significant relationship with MOR. However, tanδ, dMOE, K, and Z had the best significant coefficient of correlation with MOR. The r values are indications that tanδ, dMOE, K, and Z had degrees of linear association of 64%, 82%, 64%, and 85% respectively.
The r (0.54) obtained by Baar et al. (2015) for MOR and dMOE was lower, while Chauhan and Sethy (2016) found a higher r (0.88). Nonetheless, different r values for correlation between MOR and dMOE have been recorded for different wood species (r = 0.76, 0.52, 0.58, 0.62, 0.17) and with different acoustic methods (r = 0.54, 0.49, 0.27, 0.12, 0.22;Baar et al. 2015). Therefore, it can be opined that acoustic methods, wood species, and combination of different wood species contributed differently to the degree of association between MOR and dMOE, thus, supporting Karlinasari et al. (2008), Ravenshorst et al. (2008), and Teles et al. (2011). It can then be argued that r values can be altered where more than one species is jointly studied, as evident in Figures 15 through 25.
Furthermore, the linear relationships of MOR with dMOE and Z were stronger than their exponential relationships whereas MOR with tanδ had a stronger exponential relationship. Meanwhile, the relationship (exponential and linear) between MOR and K was neutral. These assertions were reached based on the values of R2 found for each relationship (Figs. 6 through 9). Inferentially, MOR can be best predicted by dMOE (linearly), Z (linearly), and tanδ (exponentially)
Relationship between MCS// and acoustic properties
Similarly, MCS// was significantly correlated with all acoustic properties measured except with ACE. Since tanδ, dMOE, K, and Z had the best degree of association with MCS//, then they can be considered as the most suitable acoustic predictors for MCS//.
It can be deduced from Figures 10 through 13 that a linear relationship is stronger than an exponential relationship where acoustic properties are utilized for predicting MCS// based on the proportion of variation explained. This study has therefore revealed dMOE and Z as the best acoustic properties having a good positive linear relationship needed to predict MCS// of wood.
The wood species performed differently in terms of their relationship with dynamic properties. Notwithstanding, the R2 values obtained with species combinations were higher than R2 for the independent species. This shows that species effect exists for longitudinal acoustic method on wood, as it does with acoustic testing on standing trees (Wang and Ross 2008), thus suggesting that the application of longitudinal vibration acoustic method for two or more wood species combination is better than for independent species. Due to the significant relationship found among the acoustic and mechanical properties, this study confirms the suitability of the longitudinal vibration acoustic method for predicting dMOE and other mechanical properties of wood, especially with Nigerian species.
This study successfully investigated the relationship between mechanical and acoustic properties of selected hardwood species useful for predicting mechanical properties of wood. Owing to some of the significant relationships recorded, it is concluded that the longitudinal vibration acoustic method is more suitable for use when considering species combinations, and suggests that it can be easily and cheaply used to predict the mechanical properties of wood species in Nigeria. It was found that A. adianthifolia and G. arborea were better because of their significantly higher values of MOE, MOR, and MCS//. As such, these species are more suitable for construction and mechanical purposes than D. regia or B. anguistifolia.
The authors are, respectively, Lecturer I, Federal College of Forestry (email@example.com [corresponding author]), Principal Research Fellow, Dept. of Forest Products Development and Utilization (firstname.lastname@example.org), and Principal Lecturer, Federal College of Forestry (email@example.com), Forestry Research Inst. of Nigeria, Ibadan, Nigeria. This paper was received for publication in July 2021. Article no. 21-00048.