Life of insulating units
Forty-five years ago, accelerated testing to determine the probable life of sealing arrangements in insulating glass units was a mere dream. The Canadian Building Digest published an article whose author insisted that “It is necessary to rely on such evidence of quality and ‘probable’ satisfactory performance as it can be obtained.”
Today, much has changed in accelerated lab testing of IGUs. We now know that several variables play a part in determining IGU durability, including:
• The moisture resistance of the materials used to affect the seal between any moisture barrier and the edge of glass
• The amount of desiccant used and its moisture absorption capacity in relation to the volume and humidity in the IGU
• The length of the moisture vapor transmission path through each material in the edge-seal design
• The width of this path between the moisture barrier and the edge of the glass.
Based on quantifying these variables, a theoretical desiccant depletion model can be created, and a probable life expectancy can be calculated. We can then determine how altering the materials or designs can affect IGU life expectancy. This calculation is called the Moisture Resistance Index. The higher the MRI, the longer the IGU’s life expectancy.
The MRI equation
By anticipating the life expectancy through the MRI equation, manufacturers can determine the materials most effective in the long term and can then improve their products.
To calculate the MRI consider a few terms:
• Primary sealant: The sealant with the lower permeability in a dual-seal system
• Secondary sealant: The sealant with the higher permeability in a dual-seal system
• Float: The dimension of the gap between non-permeable barriers in the edge seal, typically glass on one side and metal spacer on the other.
To figure the MRI, first determine the permeance coefficient, Mc. The permeance coefficient represents the rate that moisture can penetrate the barriers. With two or more barriers, such as that in a dual-sealed IGU, use the following formula to figure the combined permeance coefficient:
Mc = 1
lp / µp+ ls /µs
l equals the length of the flow path or secondary sealant length in meters
µ equals the average permeability, nanograms per second, square meter for one meter thickness and one Pascal pressure difference: ng / (s n m n Pa)
In the next step, the float, f, is factored into the permeance equation so that the flow is calculated across a unit length, say, 1 meter, of the actual seal.
The equation to determine combined permeance in a unit having a given float, Mcf, is:
Mcf = 1
lp / (µp n fp) + ls / (µs n fs)
The terms l/(µ n f) above are the reciprocal of the permeances of the individual elements, or resistance to vapor flow, and can be added to find the composite resistance, as follows:
Mcf = 1 = 1
Rcf Rp + Rs
This equation can then be used to express the resistance to vapor flow, the inverse of the equation above:
Rc = R1 +R2
Finally, MRI can be calculated as follows:
MRI = lp /(µp n fp) + ls /(µs n fs)
Applying the MRI formula
For the purpose of this paper, three hypothetical sealants with different permeabilities are used as a demonstration for figuring the theoretical life expectancy of an IGU. The following examples have permeabilities that differ by orders of magnitude:
The primary sealant (µp= 0.02 ng/ snmnPa) can be interpreted as a having a very low-permeability rate.
(µ1=2.0 ng/snmnPa & µ2=20.0 ng/ snmnPa) reflect the permeability range of secondary or structural sealants.
The dimensions used in the table at right are taken from an Insulating Glass Manufacturers Association survey and also from real-world examples. They are combined here to give the best and worst scenarios based on the differing constructions.
Since the life expectancy directly relates to the flow of water vapor through the IG seal system, the MRI can be used as a predictor of the relative life expectancy of the unit.
To demonstrate how this index works, the table below shows life-expectancy results using the foregoing data and the equations detailed earlier.
The MRI data presented in the table above provide a relative comparison of the design effects of moisture vapor path length, sealant permeability and float.
Case 1 incorporates a very short primary seal path length with a large float dimension that may be typical of under-compressing the primary seal in real life manufacturing conditions. This combination produces the lowest MRI, or the shortest IG life expectancy, in our examples at approximately one-sixth that of the next best example.
Case 2 doubles the primary seal path length while decreasing the float dimension by a factor of three, resulting in six
Case 3 more than doubles the primary seal path length over Case 2 while increasing the float dimension by a factor of two to further improve MRI by 21 percent. All of these examples are dimensions found in real world examples of IG construction. The related cost variables associated with the changes are very small while the impact on IG longevity is quite significant.
Modeling unit design
The MRI model shown here is a simple approach to es
For example, if an IG spacer design that experiences natural age death in 10-to-15 years and has a theoretical MRI of 350 is compared to an alternate design with an MRI of 700, the alternate could increase longevity into the 20-to-30-year range. This same logic could also apply to premature failures resulting from minor flaws in fabrication or adverse service conditions. Units designed to last longer—designed to have a higher MRI—should have decreased moisture flow and, therefore, should perform longer under rea-world conditions.
Increase MRI, increase service life
Of course there are many variables that can shorten the service life of an IGU and it is difficult to model or even test the impact of these. A complex model that accomplishes this is in the works at TNO TPD supported by the U.S. Department of Energy. TNO TPD is part of the Netherlands Organization for Applied Scientific Research TNO, the largest independent research institute in the
Statistically, the rate of premature failure on most systems remains extremely low. The ideal approach is to op
MRI is a useful tool in designing and op