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Publication Number: FHWA-HRT-04-097
Date: August 2007
Measured Variability Of Southern Yellow Pine - Manual for LS-DYNA Wood Material Model 143
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1.11 TEMPERATURE EFFECTS
Typically, the moduli and strength of wood decrease as temperature increases. In addition, temperature interacts with moisture to influence the mechanical properties, as shown in figure 24.(16) This figure indicates that the temperature effects are more pronounced at high moisture content than at low moisture content. If the temperature change is not sustained, then the effect is reversible―the moduli and strengths will return to their original value at their original temperature. If the temperature change is sustained, then the effect is permanent, at least at elevated temperatures. This is because chemical changes occur in wood with prolonged exposure to elevated temperatures that degrade the wood properties and produce large reductions in strength. Repeated exposure to elevated temperatures also has a cumulative effect.
Guardrail posts may be exposed to extreme temperatures for prolonged periods of time. Guardrail posts in warm regions that are exposed to high temperatures for long periods of time will have different properties than those in cold regions of the country. In addition, bogie tests on guardrail posts indicate that energy absorption goes down when posts freeze. This was previously demonstrated in figure 4. Although these observations on guardrail posts suggest that mechanical properties are affected by temperature, no clear wood data are available for southern yellow pine or Douglas fir that document the effect. Thus, the data from Bodig and Jayne and the USDA Wood Handbook are used.(16,18)
Effect of temperature and moisture interaction on longitudinal modulus.
Here, three methods are suggested for modeling temperature effects. One method takes regional variations into account through the selection of a predefined temperature exposure parameter tabulated by region. This method would vary the moduli, strengths, and fracture energies as a function of the temperature exposure parameter. However, this approach is not practical at this time because neither the regional data nor the clear wood data are available to develop such a detailed model.
A second method specifies temperature effects by range. For example, three broad ranges could be modeled:
The user would specify a flag that indicates one of the three ranges. This method is simple to implement and easy to use, but does not give the user many choices.
A third method specifies the temperature directly. With this method, the room-temperature (20 °C) properties are scaled up or down according to the temperature specified. If no temperature is specified, the temperature defaults to room temperature (20 °C) and no scale factor is applied. This method is currently used for the default material properties.
The following factor (FM) is implemented to scale the clear wood moduli as a function of input temperature (T):
Coefficient a1 (°C-2) = −0.0000000377625
Coefficient a2 (°C-2) = −0.000001416
Coefficient a3 (°C-2) = −0.0000003125
Coefficient b1 (°C-1) = −0.000004817
Coefficient b2 (°C-1) = −0.000109895
Coefficient b3 (°C-1) = −0.000875
All six coefficients (a1, a2, a3, b1, b2, and b3) are obtained from fits to the data previously shown in figure 24(a) for six wood species. Equations 95 through 97 are plotted in figure 24(b). The data indicate that the stiffness of the wood increases when frozen and decreases when heated.
Equation 98 is based on the data shown in figure 25. Figure 25 indicates that temperature has a stronger effect on strength than it has on stiffness. For temperatures below 20 °C, the increase in strength is twice that modeled for the increase in moduli. For temperatures above 20 °C, the decrease in strength is twice that modeled for the decrease in moduli. These plots are reproduced from the USDA Wood Handbook and are a composite of the results obtained from several studies.(18)
Temperature effects are more pronounced for the strength parallel to the grain than for the modulus parallel to the grain.
Source: Forest Products Laboratory.(18)
The wood data shown in figure 25 may seem inconsistent with the bogie test data previously shown in figure 4. The bogie data indicate that it takes less impact force to break a frozen wood post than a room-temperature post. This may be because frozen posts are more brittle than room-temperature posts, so temperature may affect fracture energy.
The author is not aware of any fracture intensity or energy data for frozen pine or fir that demonstrate the effect of temperature, either parallel or perpendicular to the grain. Therefore, the perpendicular-to-the-grain energy is modeled independent of temperature (using the FPL quadratic equations). However, wood is expected to become more brittle as temperature decreases. Therefore, parallel to the grain, a reduction in fracture energy is modeled upon freezing and an increase in fracture energy is modeled upon heating.
The variation in fracture energy with temperature is based on correlations of dynamic bogie impact with frozen and room-temperature grade 1 posts. Good frozen grade 1 correlations are obtained with a parallel-to-perpendicular energy ratio of 5, which is very brittle behavior. To accommodate variation with temperature, the default parallel-to-the-grain energies are modeled with a linear variation with temperature (T) between frozen and room-temperature values:
Here, T is the temperature in degrees Celsius (°C) between 0 and 20 °C, and room temperature is 20 °C. For temperatures lower than 0 °C, the frozen fracture energies are the default values. For temperatures higher than 20 °C, the room-temperature fracture energies are the default values.
Topics: research, safety, infrastructure, structures, materials
Keywords: research, safety, infrastructure, structures, materials, wood, LS-DYNA, orthotropic, material model, damage, rate effects, guardrail
TRT Terms: guardrails, wood