Dynamic Thermal Performance and Energy Benefits of Using Massive Walls in Residential Buildings

Low R-value Massive Walls - Negative Impact of Thermal Mass

Dynamic Thermal Performance of Simple Multilayer Wall Assemblies

Simple multilayer walls without thermal bridges are accurately described by one-dimensional models. Because DOE-2 can simulate these wall without compromising the accuracy, dynamic hot box tests were not performed on them except for one example. A wall constructed with a foam core and two equally thick concrete layers on both sides was tested in the hot box. Experimental results collected from this test were used to calibrate the computer model for simple multilayer walls. The same material data was used for all wall configurations analyzed in this section. See Table 3.

Four series of massive walls are depicted on Figures 2, 3, 4, and 5. These 19 walls are grouped according to R-value;

Figure 2: R - 3.03 m ² K/W [17.2 hft²F/Btu],
Figure 3: R - 2.29 m²K/W [13.0 hft²F/Btu],
Figure 4: R - 1.58 m²K/W [9.0 hft²F/Btu], and
Figure 5: R - 0.88 m²K/W [5.0 hft²F/Btu].

There are four wall material configurations within these groups:

Based on equations (1) and (2), DBMS values were calculated for all 19 wall material configurations and presented in Tables 4 - 7

Table 3. Thermal properties of material for multilayer walls.

Table 4. DBMS values for RSI - 3.03 (R-17.2) walls.

Table 5. DBMS values for RSI - 2.29 (R-13.0) walls.

Table 6. DBMS values for RSI - 1.58 (R-9.0) walls.

Table 7. DBMS values for RSI - 0.88 (R-5.0) walls.

* DBMS values lower than 1.0 indicate that for the house containing massive walls of low steady-state R-value, space heating and cooling loads may be higher than for the house containing light weight walls of the same R-value.

Data presented in Tables 4 - 7, show that the most effective wall assemblies are walls with thermal mass (concrete) being in good contact with the interior of the building (walls 1, 2, 3 in Table 4 and 5, also walls 1 and 3 in Tables 6 and 7). Walls where the insulation material is concentrated on the interior side of the wall have the smallest DBMS values (wall 4 in Table 4 and 5, also wall 3 in Tables 6 and 7). Other wall configurations with the concrete wall core and insulation placed on both sides of the wall have higher DBMS values (walls 5, 6 in Table 4 and 5, also wall 4 in Table 6).

The most favorable climate for application of the massive wall systems is in Phoenix. The worst location for these systems is Minneapolis. As shown in Table 7, for Minneapolis and Miami, in buildings containing low R-value walls with the insulation material concentrated on the interior side of the wall, total building loads can be higher than in the case of the light weight walls of the same steady state R-value (DBMS lower than 1).

Different proportions in wall mass or insulation distribution (walls 1 vs. 2 and 5 vs. 6) effect significant differences in DBMS values in the same climates. This indicates that the DBMS value is sensitive to the changes in wall exterior and interior layers. Data presented in Tables 4 - 7 cannot be used to predict dynamic thermal performance of walls with significantly different exterior or interior layers (for example walls with brick or siding exterior finish).

For the four common wall material configurations, detailed relations between steady-state R-values and dynamic R-value equivalents are depicted in Figures - 6, 7, 8 and 9. They can be used for estimation of the approximate dynamic benefit for walls of similar configurations. For walls with more complicated configurations these values have to be estimated individually.

Complex Two- and Three-dimensional Wall Assemblies - One-dimensional Simplifications are not Accurate

Complex walls cannot be analyzed using simple one-dimensional tools. The methodology applied for dynamic thermal performance evaluations of complex massive wall systems needs to be able to thermally analyze complicated geometries and material configurations. In this section, the ICF (Insulating Concrete Form) wall is used as an example. Two- or three-dimensional heat transfer similar to that in this example can be observed in most masonry units and some of the ICF forms. Some experimental and theoretical results for the ICF wall system are presented herein.

As shown in Figure 10, the example ICF wall has a complex three-dimensional internal structure. The basic component of this wall is the 0.23 m. (9.25-in.) thick EPS foam wall form. The thickness of the exterior and interior form walls (made of foam) varies from 3.8 to 8.8 cm. (1.5 - 3.5-in.). These foam components of the form are connected with the metal mesh going across the wall. There is a three-dimensional network of vertical and horizontal channels (about 15.75 cm. or 6.25-in. in diameter) inside the ICF wall form. These channels have to be filled with concrete during the construction of the wall. The exterior surface of the wall is finished with a 13-mm(½-in.) thick layer of stucco and on the interior surface 13- mm(½-in.) thick gypsum boards are installed. Reinforced high-density concrete is poured into the internal channels formed by ICF units.

Heating 7.2 was used for the dynamic three-dimensional heat transfer analysis of the ICF wall. The accuracy of Heating 7.2 was validated by examining its ability to predict the dynamic process measured during the dynamic hot box data for this massive wall. The steady-state R-value or the computer modeled ICF wall had to match the test generated R-value. Then, the computer program used temperatures and heat transfer coefficients recorded during the test with one hour time intervals. Values of heat flux on the surface of the wall generated by the program were compared with the values measured during the dynamic test. This task is described in detail by Kosny [7]. The general conclusion was that the computer program reproduced the test data very well. This exercise confirmed the ability of Heating 7.2 to reproduce the dynamic heat transfer process measured during the dynamic hot box test of the actual complex massive wall.

Response factors, heat capacity, and R-value were computed using the validated computer model of the ICF wall. They enabled calculation of the wall thermal structure factors and generation of the simplified one-dimensional equivalent wall configuration. This equivalent wall had a simple six layer structure and the same thermal response as the real wall [7]. Kossecka and Kosny [4,5,6] analyzed the case of a complex thermal bridge configuration. They showed that response factors, steady-state R-values, and thermal structure factors are the same for the complex wall and equivalent wall. One-dimensional approximate models of the complex structures based only on geometrical simplifications are much less accurate.

To illustrate this fact, a simple one-dimensional model was developed for the ICF wall. It was based on the total thickness of the ICF wall, 0.23 m. (9.25-in.) and the thickness of the exterior and interior foam forms which varies from 3.8 to 8.8 cm. (1.5 - 3.5-in.). The equal thickness for the exterior and interior foam forms was assumed as 5.08 cm. (2-in.). Due to the fact that computer programs like DOE-2 or BLAST can perform only one dimensional thermal analysis, it is likely that most DOE-2 or BLAST modelers would make similar simplifications. Comparisons of steady-state R-values and X response factors are presented in Figure 11. It is shown that for the simple one-dimensional model, the R-value is 38% higher that the R value calculated for the three-dimensional model of ICF wall. At the same time, R-values for the ICF wall and equivalent walls are equal. Also, the first five X response factors for this wall have significantly different values from the essentially equal X response factors calculated for the accurate three-dimensional model of ICF wall and the equivalent wall.

The equivalent wall technique is a relatively simple way to allow whole-building energy simulations (using DOE-2 or BLAST) for buildings containing complex assemblies. If the accurate equivalent wall could not be generated, the dynamic thermal performance evaluation will not be accurate because it is based on one-dimensional whole building simulations. It is possible to generate a series of response factors for the complex wall and modify DOE-2 source code to enable this type of wall data input. However, the equivalent wall technique represents all the thermal information about the wall by only five numbers (R, C, and three thermal structure factors). This is much simpler than the alternate use of a long series of response factors or Z-transfer function coefficients (for massive walls, 60 to sometimes 150 numbers multiplied by 3) which has to be accompanied with the troublesome modification of the program source code to enable this type of wall data input.

Low R-value Massive Walls - Negative Impact of Thermal Mass

As shown in Table 7, for buildings located in Minneapolis and Miami containing low R-value massive walls with the insulation material concentrated on the interior side of the wall, total building loads can be higher with thermal mass than with the equivalent lightweight wall of the same steady-state R-value (DBMS lower than 1). Extrapolating the data presented in Tables 4 - 7, it can be observed that massive walls with R-values below 0.53 to 0.7 m2K/W (3-4 hft2F/Btu), have negative impacts on building loads for all considered locations except Phoenix.

Two low R-value wall material configurations were simulated to analyze this interesting finding;
•    Solid 20.3 cm. (8-in.) thick wall made of high density concrete - 2240 kg/m³ (140 lb/ft ³).
•    Wall assembled with two-core 29.5 cm. (11-5/8-in.) thick concrete blocks made of high density concrete - 2240 kg/m ³ (140 lb/ft ³) insulated with 4.8 cm. (1-7/8-in.) foam inserts.

Due to the three-dimensional geometry of the wall assembled with two-core concrete blocks, the equivalent wall was generated for this wall. Steady-state R-values for these two walls are presented in Table 8.

Table 8. Steady-state R-values for solid 8-in. wall and two-core 29.5 cm. (11-5/8-in.) thick units insulated with 4.8 cm. (1-7/8-in.) foam inserts.

Based on results of computer modeling and equations (1) and (2), DBMS values were calculated for these two walls and are presented in Table 9. These results show that only in the special climate of Phoenix, did this traditional massive system used for foundations, have benefit above grade.

Table 9. DBMS values for low R-value walls.

* DBMS values lower than 1.0 indicate that for the house containing massive walls of low steady-state R-value, space heating and cooling loads may be higher than for the house containing light weight walls of the same R-value.

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© Oak Ridge National Labs and Polish Academy of Sciences
Updated August 9, 2001 by Diane McKnight