The effect of temperature on insulation performance

by Katie Daniel | May 28, 2015 11:46 am

[1]

by Christopher Schumacher, M.A.Sc.
On the surface, R-value is a simple thing. In fact, it has become the standard metric of thermal performance precisely because it is easy to explain and understand. Most insulation materials have ‘label R-values’ stamped on their faces (or at least displayed in large print on the packaging), but these values do not tell the whole story of how insulation performs in service. Some complicating factors—such as thermal bridging—have become fairly well-known. However, in order to meet current needs for energy-efficient, durable, comfortable, and cost-effective buildings, it is critical to continuously improve the industry’s understanding and handling of insulated assemblies.

R-value is a measure of thermal resistance for materials. In other words, it denotes how much heat is prevented from flowing through a layer of material at a given thickness. In North America, R-value is most commonly given in imperial units, where one R = 1 (sf·F·hr)/Btu, and a 50-mm (2-in.) thick layer of insulation might be R-10. In Canada, RSI units are also used; one RSI = 1 (m²·K)/W and RSI = R / 5.678, meaning the 50-mm thick layer of insulation would be RSI-1.76. Regardless of the units used, the effectiveness of thermal resistance depends on a number of factors.

For example, temperature-dependent R-value is a phenomenon relatively unknown outside of the world of researchers and academics. Temperature dependency refers to changes in the R-value of insulation over a range of temperatures. For example, a 25-mm (1-in.) thick board of extruded polystyrene insulation (XPS) might have a label R-value of RSI-0.88 (R-5), but its actual performance may be closer to RSI-0.97 (R-5.5) under cold-climate winter conditions, or as low as RSI-0.72 (R-4.1) under hot-climate summer conditions. The label R-value is not incorrect; it refers to performance under a specific set of standard test conditions and does not necessarily reflect how a material performs on a building.

Temperature dependency matters because the insulation in real-world buildings often experiences temperatures differing significantly from standard test conditions. In fact, the standard test condition temperatures are almost never seen in a typical building. Research has characterized how R-values change with temperature by measuring materials at different mean temperatures and using various temperature ranges.

This article describes an ongoing research project at Building Science Laboratories (BSL) that has included a variety of insulation materials over several years. In most cases, the insulation performed a little better than expected when the mean temperature was lower (simulating cold outdoor conditions), and a little worse when it was higher (simulating warm outdoor conditions). Further, the relationship between R-value and temperature is nearly linear. Where this pattern occurs, R-values are predictable and temperature can be easily accounted for. However, some unusual patterns have also been found. Polyisocyanurate (polyiso) insulation provides a useful example of how unusual temperature dependency patterns can be identified and then accounted for in modelling and design.

Determining R-values
Before getting into the details of BSL’s research, it is important to understand the origins of the R-value and how it is typically measured. The R-value was proposed by Everett Shuman in the 1940s as an easy-to-compare, repeatable measure of insulation performance. Prior to that, thermal performance was expressed in terms of conductance or the ability for materials to conduct heat. Materials provide better performance when they have lower thermal conductance. Industry decision-makers felt consumers would be confused by the concept ‘smaller is better.’ When thermal performance is expressed in terms of R-value or thermal resistance, higher numbers represent better performance.

The R-value went on to become the de facto metric across North America, familiar to both consumers and professionals. It has helped many designers and consumers make more energy-efficient choices, but its importance in influencing purchase decisions has also led to some unscrupulous marketing claims. In the aftermath of the 1970s oil crisis in the United States, fraudulent R-value claims became so widespread the United States Congress passed a consumer-protection law in response, the “Federal R-Value Rule” (16 Code of Federal Regulations [CFR] Part 460, “Trade Regulation Rule Concerning the Labeling and Advertising of Home Insulation”).

The specified slider does not exist.

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.

Thermal performance
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.

Approach
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).

Results
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.

A useful example can be found with a large warehouse or light industrial building in a climate with hot summers. If the lighting and equipment loads are moderate, ventilation requirements are minimal, and there are few windows, then much of the cooling load will be associated with gains through the roof assembly. When the roof insulation is exposed to higher temperatures (as would be typical under a solar-heated roof surface), it delivers lower thermal performance (i.e. more heat gain) than expected based on the label R-value. This is true for all types of insulation material.

At the exterior surface the R-value might be reduced by 20 per cent. However, over the thickness of the roof insulation the average reduction in R-value might only be 10 per cent since the exterior layers protect the inner layers by keeping them closer to the indoor temperature.

The corresponding increase in heat flow would result in an approximate 10 per cent increase in energy consumption related to the roof assembly. Whether or not this has a significant impact on building operating costs will depend on the specific climate, the building construction and operation, and various other interrelated factors (e.g. thermal mass and equipment efficiency).

It was stated earlier most materials exhibit a decrease in R-value for hot temperatures, and an increase in R-value for cold temperatures. It seems obvious to ask whether any unexpected increase in energy consumption during warm weather is offset by unexpected reductions in consumption during cold periods. Again, the net performance will depend on specific climate, building construction, operation, and other issues. All the relevant factors (including insulation temperature dependence) can be accounted for using appropriate computer models (e.g. EnergyPlus and WUFI-Plus).

Even in those cases where the summer loss in performance is offset by the winter bonus, there may be other building performance considerations. Several design questions might be considered: will the brief reduction in R-value have a meaningful impact on the required HVAC system capacity? If not, does it result in interior surface temperatures that adversely affect thermal comfort?

Further, temperature dependence does not always result in better performance under colder temperatures. The tested polyiso insulation materials exhibited lower than expected R-values at higher and lower temperatures. For some time, polyiso board insulation has been the most commonly used low-slope roof insulation. In these applications, it is the only insulation in the assembly—as a result, the thermal performance is less than expected during both winter and summer conditions.

Polyisocyanurate is also increasingly being used as a continuous exterior insulation over insulated stud spaces in residential and commercial wall assemblies. In these applications, the thickness of a continuous insulation is typically specified to:

• minimize the impact of thermal bridging through the framing; and
• reduce the potential for air leakage condensation by controlling condensing plane temperatures.

The former is an energy consideration while the latter is a building durability concern.

For a practical illustration, a residential wall assembly with a 2×4 wood frame with RSI-2.29 (R-13) fibreglass batt insulation in the stud space and 19 mm (3⁄4 in.) of polyiso insulation on the exterior provides a nice example.

Assuming the polyisocyanurate insulation is rated as RSI 1.06/25 mm (R-6/in.), without accounting for temperature dependency, if the wall is subjected to conditions of 22 C (72 F) on the indoor side and –18 C (0 F) on the outdoor side, then the temperature at the condensing plane (i.e. the inside surface of the polyisocyanurate) is predicted to be –8.5 C (17 F), as illustrated in Figure 7.

In contrast, if it is assumed the polyiso exhibits a temperature dependence similar to that shown in Figure 6, then the predicted condensing plane temperature will be –12.1 C (10 F) as illustrated in Figure 8. In this case, the temperature dependence of the material is particularly significant because the entire thickness of the insulation is on the assembly’s cold side. That is to say none of the temperature-sensitive insulation is protected by itself or another material. To bring the condensing plane temperature back to the values originally expected, the thickness of the polyiso exterior insulation would need to be be increased to 38 mm (11⁄2 in.), as illustrated in Figure 9.

Specifying more insulation is also a good option when designing roof assemblies using polyisocyanurate. A good rule of thumb for both roofs and walls is to use NRCA’s recommendation to specify polyisocyanurate insulation by its desired thickness—not its label R-value. Ideally, the thickness would be specified on the basis of annual energy simulations and hygrothermal calculations using a measured temperature-dependant R-value like that illustrated in Figure 6. When material-specific, temperature-dependant R-values are unavailable, designers will have to make some assumptions. For polyisocyanurate roof insulation materials, NRCA recommends using an in-service R-value of 5 per inch thickness (i.e. RSI-0.88/25 mm) for heating-dominated climates and 5.6 per inch thickness  (i.e. RSI-0.99/25 mm) for cooling-dominated climates.

Another option is to use a hybrid insulation approach. Adding a layer of less-temperature-sensitive insulation outboard of the polyiso, protects the polyiso from extreme temperatures and gets the most value from both insulation layers. An example hybrid assembly is shown in Figure 10.

Conclusion
Temperature dependence can result in assemblies that do not function as expected or intended. In the case of those materials exhibiting strong temperature dependence, the consequences could be significant. Fortunately there are solutions, and as knowledge of this phenomena increases, more solutions will no doubt be developed.

The specified slider does not exist.

[2]Christopher Schumacher, M.A.Sc., is a principal with Building Science Consulting Inc. (BSCI), a consulting firm specializing in design facilitation, enclosure commissioning, forensic investigation, and training and communications. Its research division, Building Science Laboratories (BSL), provides a range of R&D services. Schumacher’s presentations on temperature-dependent R-values include the Westford Building Science Symposium in 2011 and the Rock-toberfest Rockwool Symposium in 2014. He has also written on this topic for buildingscience.com. He can be reached by e-mail at chris@buildingsciencelabs.com.

Source URL: https://www.constructioncanada.net/the-effect-of-temperature-on-insulation-performance/

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