Under this rule, claims about residential insulation must be based on specific ASTM procedures. Of these, ASTM C177, Standard Test Method for Steady-state Heat Flux Measurements and Thermal Transmission Properties by Means of the Guarded-hot-plate Apparatus, and ASTM C518, Standard Test Method for Steady-state Thermal Transmission Properties by Means of the Heat Flow Meter Apparatus, are by far the most commonly used, as they can be quickly completed with small easy-to-handle samples—typically between 305 x 305 mm (12 x 12 in.) and 609 x 609 mm (24 x 24 in.). These test methods use an apparatus that places an air-impermeable hot and cold plate in direct contact with the test sample (Figure 1). Further, the rule requires R-value tests be conducted at a mean temperature of 24 C (75 F) and a temperature differential of 27.8 C (50 F). For reasons of technical ease, this means insulation is usually tested with the cold side at about 10 C (50 F), and the warm side at around 38 C (100 F).
In other words, the label R-value typically only provides a metric of a material’s thermal performance under one standard test condition. Clearly, the parameters of this one test do not represent any typical combination of real indoor and outdoor temperature conditions, much less the full range of conditions insulation might experience in building applications.
BSL’s research into temperature-dependant R-values started out by reproducing the work of Mark Graham of the National Roofing Contractors Association (NRCA). The testing has since been extended to consider various insulation materials using a wider range of realistic temperature conditions.
Using ASTM C518 procedures, materials were tested at a range of hot and cold temperatures. Initial tests were done at the same setpoints used by Graham. These mean temperatures of –4, 4, 24, and 43 C (25, 40, 75, and 110 F), were per ASTM C1058, Standard Practice for Selecting Temperatures for Evaluating and Reporting Thermal Properties of Thermal Insulation (shown as the “Standard” R-value tests in Figure 2).
For later tests, BSL researchers selected temperatures to reflect more realistic in-service conditions, from cold, winter air temperatures through to hot, solar-heated surface temperatures (see BSL “Service Temperature” tests in Figure 2).
As expected (based on the physics of heat transfer), most of the tested insulating materials exhibited nearly linear temperature dependency over the range of temperatures buildings normally see. Results are given in Figure 3 for fibreglass batt, stonewool batt, high-density expanded polystyrene (EPS), XPS, and closed-cell sprayed polyurethane foam (SPF).
Figure 4 shows results for nominal RSI-3.52 (R-20) XPS tested at two, four, six, and 44 months after purchase to investigate the effect of aging. For all these tests, the line’s slope shows a consistent pattern where the material is more thermally resistant at colder mean temperatures and less thermally resistant at warmer mean temperatures.
As most materials follow a consistent pattern, their temperature dependency can be predicted and accommodated. Most of the time, a layer of the insulation can be measured (i.e. get R-value or conductance) at several mean temperatures and then material properties can be easily predicted (i.e. R-value/in. or conductivity). This process works with standard and in-service temperatures—it should work with almost any temperature difference.
However, it is possible for materials to have an unusual pattern of temperature dependence. Graham demonstrated that polyiso insulation products (available at the time of testing) displayed a markedly non-linear pattern over numerous samples from different manufacturers. More specifically, the measured R-value was significantly lower than the label R-value for tests conducted at both warm and cold temperatures.
In BSL testing, polyiso was tested more extensively to better understand this unusual pattern of temperature dependency. Figure 5 shows the measured R-value of three different polyisocyanurate products, tested in 100-mm (4-in.) thick samples—two layers of 50-mm (2-in.) thick product—at BSL’s ‘service temperatures.’
It should be noted the results in Figure 5 are only applicable to the specific thickness and temperatures tested—in this case, 100 mm (4 in.) at an indoor temperature of 22 C (72 F) and outdoor temperatures between –18 and 62 C (0 and 144 F).
Researchers at BSL have since developed a draft test method to fully quantify the R-value for materials having unusual temperature dependence. The method produces a temperature-dependent R-value curve independent of thickness. Figure 6 presents an example of such a curve for several different materials. Using this approach, the temperature-dependent R-value can be quantified once, over a range of temperatures, for a given insulation product. The results can then be extended to predict the R-value of the product at any thickness and temperature.
Understanding design implications of temperature dependency
In and of itself, temperature dependency is not a reason to avoid a particular type of insulation. Polyisocyanurate insulation has been used as an example in this discussion because it exhibits an unusual relationship between R-value and temperature, and because it is commonly used in commercial roof and residential wall assemblies. Like all insulation materials, polyiso has pros and cons.
It should also be remembered all materials exhibit some temperature dependence. When temperature-dependant thermal performance is not taken into account, three problems can result:
- increased energy consumption;
- poor occupant comfort; and
- reduced building durability.
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