General Procedure
Dynamic Whole Building Energy Modeling of Residential Buildings
Evaluation of the dynamic thermal performance of massive wall systems combines experimental and theoretical analysis. For complex three-dimensional building envelope components, it is based on dynamic three-dimensional finite difference simulations, whole building energy computer modeling, dynamic guarded hot box tests, and sometimes, comparative field performance investigations [Kosny et.al. 1998a]. Dynamic hot box tests serve to calibrate detailed computer models. It is important to know, that all these costly and time-consuming steps are not necessary for all wall assemblies. For simple one-dimensional walls, only theoretical analysis can be performed without compromising accuracy.
Masonry or concrete walls having a mass greater than or equal to 146 kg/m2 (30 lb/ft2) and solid wood walls having a mass greater than or equal to 98 kg/m2 (20 lb/ft2) are defined by the Model Energy Code [MEC-1995, Christian 1991 ] as massive walls. They have heat capacities equal to or exceeding 266 J/m2K (6 Btu/ft2 0F). The same classification is used in this work.
Since 95 percent of U.S. residential buildings is constructed using light-weight building envelope technologies, energy performance of wood-framed walls is utilized as a base for performance comparisons in this work. A wide range of traditional wood-framed wall assemblies is considered, R-values from 0.4 to 6.9 Km2/ W (2.3 to 39.0 hft2 F/Btu). Energy performance data, generated by whole building energy simulations for residential buildings containing wood-framed walls, is compared against similar data generated for four basic types of massive walls. Each wall type consists of the same materials, concrete and insulating foam. Within the same type of walls, all sequences of materials are the same, however, individual material thicknesses change to match necessary R-values. Massive wall R-values range in this work from R - 0.88 m2K/W (5.0 hft2F/Btu) to R - 3.03 m2K/W (17.2 hft2F/Btu). Four basic material configurations are considered for massive walls:
- Exterior thermal insulation, interior mass (Intmass)
- Exterior mass, interior thermal insulation (Extmass)
- Exterior mass, core thermal insulation, interior mass, and (CIC)
- Exterior thermal insulation, core mass, interior thermal insulation (ICI).
The four types of massive walls above approximate most of the currently used multilayer massive wall configurations. For example, the first two wall configurations may represent any masonry block wall insulated with rigid foam sheathing. The last wall configuration may represent Insulated Concrete Forms (ICF) walls. Therefore, results presented in this work can be used for approximate energy calculations of most massive wall systems.
This procedure is similar to that used to create the thermal mass benefits tables in the Model Energy Code [MEC-1995]. The thermal mass benefit is a function of the climate. The R-value Equivalent for Massive Systems is obtained by comparing the energy performance of the massive wall with the light-weight wood-frame walls [Kosny et.al.1998, Kosny et. al. 1998a] and should be understood only as the R-value needed by a house with wood-framed walls to match the annual energy required by identical house containing massive walls.
The DOE-2.1E computer code is utilized to simulate single-family residences in representative U.S. climates. Heating and cooling energies calculated for residences with massive walls are compared to the heating and cooling energies for identical buildings simulated with lightweight wood-frame exterior walls. To find a relation between wall R-value and heating and cooling energies, a lightweight ranch-type building is simulated. Twelve different wood-frame walls with R-values from 0.4 to 6.9 Km2 / W (2.3 to 39.0 hft2F/Btu) are considered. This simulation is performed on ten U.S. climates using TMY2 weather files for a total of 120 simulations. The energy output data generated by these whole building simulations is used to estimate the R-value equivalents that would be needed in conventional wood-frame construction to produce the same energy demand as for the house with massive walls in each of the ten climates. The resulting values account for not only the steady state R-value but also the inherent thermal mass benefit.
To enable simple comparisons of dynamic energy performances of wall systems, ORNL’s BTC introduced in 1995 the Dynamic Benefit for Massive Systems model (DBMS) [Kosny at al 1998 ]. DBMS is a dimensionless multiplier of steady-state R-value. The product of DBMS and steady-state R-value is called “ Dynamic R-value Equivalent for Massive Systems.” It should be used only as an answer to the question: “What wall R-value should a house with wood frame walls have to obtain the same space heating and cooling energy consumption as a similar house containing massive walls?”
Comparative analysis of the space heating and cooling energies from two identical residences, one with massive walls and the other containing lightweight wood-frame exterior walls, was introduced in the Model Energy Code for development of thermal requirements for massive wall and was adopted by the authors. The DOE-2.1E computer code was utilized to simulate three single-family residences in ten representative U.S. climates. Two single-story ranch style houses of approximately 74 m2 (800 ft2) and 143 m2 (1540 ft2) floor area, were accompanied by a two story 279 m2 (3000 ft2) house. Over ten thousand whole building energy simulations were performed during this study. The heating and cooling energies generated from these building simulations served to estimate the R-value equivalents for massive walls. A list of cities and basic climate data are presented in Table 1.
Table 1. Ten U.S. climates used for DOE 2.1E computer modeling
| Cities: | HDD 18.3 C(65 deg F) | CDD 23.3 C(74 deg F) |
| Atlanta | 1705 (3070) | 9335 (16803) |
| Bakersfield | 1182 (2127) | 16641 (29954) |
| Boulder | 3037 (5466) | 4269 (7684) |
| Chicago | 3588 (6459) | 3670 (6606) |
| Fort Worth | 1344 (2420) | 20163 (36294) |
| Miami | 110 (198) | 21889 (39401) |
| Minneapolis | 4450 (8010 ) | 3781 (6806) |
| Phoenix | 802 (1444) | 30224 (54404) |
| Seattle | 2602 (4684) | 498 (897) |
| Sterling (Washington D.C.) | 2781 (5005) | 4286 (7715) |
The Sherman-Grimsrud Infiltration Method, which is an option in the DOE 2.1E whole-building simulation model [Sherman et al 1980], is used in all whole building simulations. An average total leakage area of 0.0005 expressed as a fraction of the floor area is assumed. This is the considered average for a single-zone wood-framed residential structure. This number cannot be converted directly to average air changes per hour because it is used in an equation driven by hourly wind speed and temperature difference between the inside and ambient which varies for the six climates analyzed for this study. However, for the ten climates this represents an air change per hour range which will not fall below an annual average of 0.35 ACH.
The total space heating and cooling energies for twelve lightweight wood-frame walls were calculated using DOE-2.1E simulations. The total space heating and cooling energies divided by floor area are presented on Figure 2. Regression analysis was performed to analyze the relation between the steady-state clear wall R-values of wood-stud walls and the total building annual energies for ten U.S. climates.
© Oak Ridge National Labs and Polish Academy of Sciences
Updated August 11, 2001 by Diane McKnight