BSTC Straube Driving Rain-final

Driving Rain Data for Canadian Building Design John F Straube and C.J. Schumacher

University of Waterloo, Waterloo, Ont., Canada

ABSTRACT This paper presents a methodology for calculating driving rain loads as a function of climate and building geometry. The wind speed and direction data from CWEC weather files are used in combination with rainfall normals to predict the annual driving rain for sixteen directions in twenty-two major Canadian cities. This data is plotted and tabulated. Modification factors are presented to convert these raw driving rain data to actual driving rain loads on vertical building surfaces.

INTRODUCTION Moisture is the most common cause of building enclosure performance problems. In Canada, air leakage condensation, one of the major sources of wetting, has received a great deal of attention in the past. However, the amount of water deposited on the above-grade building enclosure by driving rain is generally larger than any other source, including condensation, in almost all cases. In the past, rain control usually meant preventing rain from penetrating to the interior of the building or wetting interior finishes. Today, more rain penetration problems are due to rain absorption into materials, staining, and penetration into wall cavities where mould, rot, and corrosion can be sustained.

Canadian research has improved our understanding of rain penetration, and a common set of control strategies have been developed for practice [CMHC 2000, Straube & Burnett 1999] Despite the importance of driving rain to building performance, there is still a lack of quantitative data of the magnitude, duration, and frequency of rain deposition on buildings.

Driving rain, both in the free wind and deposition on a test house, have been measured for several years at the Building Engineering Group's (BEG) full-scale natural exposure and test facility, the Beghut. Measurements have also recently been undertaken on other buildings in the field. The predictive capacity developed from these field measurements is presently being applied to a range of Canadian climates with funding from the CMHC ERP grant program and NSERC.

CALCULATING DRIVING RAIN Driving rain is defined as the quantity of rain that passes through a vertical plane in the atmosphere. The amount of driving rain in unobstructed wind flow can be calculated with reasonable accuracy. Raindrops fall to the ground at their terminal velocity and are blown sideways at the speed of the wind (Figure 1). The speed at which raindrops fall is a function of the size of the drop. Essentially, as the drop size increases the rain drop terminal speed increases at a decreasing rate. The wind carries the drops along horizontally due to drag. The combination of gravity and wind forces determines the trajectory of the drop, and simple geometry can then be used to assess the amount of rain passing through a vertical plane. Complicating this assessment is the fact that there is a range of raindrop sizes in any rainstorm. Research by various meteorologists can be used to correlate the distribution of drop sizes in a rainstorm with the intensity of the rainfall.

Based on a similar analysis, Lacy [1965] proposed a simple equation relating wind speed and rainfall intensity to driving rain :

rv = 0.208 · V· rh (1)

where, rv is the rate of rain passing through a vertical plane (l/m2/h),

V is the average wind velocity (m/s), and

rh is the average rainfall rate on a horizontal plane such as the ground (mm/m2/h).

This equation was based on a mix of field measurements and calculations. Subsequent theoretical work and a considerable amount of field measurement has allowed us to extend and generalize Equation 1 to

rv = DRF · V(h) · rh (2)

where V(h) is the wind speed at the height of interest (m/s),

10th Canadian Conference on Building Science and TechnologyOttawa, May 2005 149

The proportionality constant in Equation (2), is the ratio of rain on a vertical plane (driving rain) to rain on a horizontal plane (falling rain) and has been defined [Straube & Burnett 1997] as the driving rain factor (DRF). Field studies at the University of Waterloo [Straube & Burnett 1997], in Germany [Kuenzel 1994] and computer models [Choi 1994] have found that the value for the DRF ranges between 0.20 to 0.25 for average conditions. This is the reason that the simple Lacy equation was so successful. However, DRF does vary considerably for different rainfall intensities and rain storm types. For example, it can range from more than 0.5 for drizzle to as little as 0.15 for intense cloudbursts.

FIGURE 1: DRIVING RAIN

Comparisons of field measurements with theoretical analysis [Straube 1998] has shown that the value for the Driving Rain Factor (DRF=1/Vt) can be calculated quite precisely from rainfall and wind speed data using:

Vt(Ø) = -.166033 + 4.91844•Ø - .888016•Ø2 + .054888•Ø3 ! 9.20 (3)

where Vt(Ø) is the raindrop terminal velocity (in m/s) for a raindrop diameter (mm) Ø

The following relation has been found to represent the distribution of raindrop sizes as a function of rainfall intensity:

F(Ø) = 1- exp{-( Ø1.30· rh0.232

)2.245} (4)

where F(Ø) is used to calculate the median drop diameter from the rainfall intensity at everyhourly interval.

The experimental work references has shown that the quantity of driving rain in an unobstructed wind flow can be calculated with an accuracy of better than 10% using Equations 2 through 4 [Straube 1998].

The cosine of the angle between the plane of interest and the direction of the wind can be used do account for wind direction on a plane oriented in a specific direction.

Finally, wind speed can be converted to stagnation pressure (assuming a temperature of 15 C) using

Pstag = 0.6 V2(5)

Previous Driving Rain Data Formats

To assess the influence of climate on driving rain exposure, designers have in the past resorted to Boyd's driving rain map of Canada [Boyd 1963] or Grimm’s map of the United Stated [Grimm 1982]. These maps plot the annual Driving Rain Index (DRI). The DRI is the product of the annual average wind speed and total annual rainfall, that is:

rv = V· rh (6)

where V and rh are annual averages.

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Although useful as broad and relative climate measures, the DRI does not represent the actual quantity of rain deposition. However, as can be seen by comparison with Equation 2, the DRI could be converted to an actual quantity by use of the proper DRF based on hourly values.

For lack of better information, these DRI plots assume that both the wind speed during rain and wind direction during rain are the same as those during average conditions. While measurements have shown that the distribution of wind speed during rain is almost the same as (typically 10 to 20% higher) that during all hours the wind direction during rainfall is often quite different (factors of 2 to 5) than during non-rainy hours [Surrey et al 1995]. Both of these conclusions are climate dependent.

A further limitation of the application of DRI plots to building design is that they do not reflect the impact of orientation and exposure. It is clear to practitioners that different localities have different building faces with significantly higher rain deposition and that a bungalow is exposed differently than a high rise building on a hilltop.

Hence, there is a need for more accurate plots of driving rain that reflect the different climates of Canada, account for the actual distribution of wind speed and rain fall intensity, and account for wind direction during rain.

DRIVING RAIN DATA

We have begun a project to develop new more useful and more accurate driving rain maps and data for Canada. Using Equations 2 to 4, hourly weather data of wind speed and rainfall rate can be processed and driving rain data generated. To be useful to designers, wind direction should be taken into account and this is easily done if hourly average wind speed during rain is available.

There are several choices of weather data. Hourly data containing the three required elements are available for at least 20 years at many different locations throughout Canada. Canadian Weather files for Energy Calculation(CWEC) data files are also widely available and represent a typical year on the basis of temperature and solar radiation. We have chosen to use CWEC files for our initial driving analysis to simplify the problems of choosing an average rain year. We plan to also generate data using multi-year weather files for a number of locations.

One of the challenges of using CWEC files is that they do not provide direct quantities of falling rain intensity. Instead, the files include categories of rainfall type and intensity, located in column 76 of the .CW2 files. These categories represent a range of rainfall quantity. However, summing the average of each range over a year does not necessarily result in the correct total rainfall for a site based on climate normals. Hence, we have applied weightings to each category as shown in Table 1 and normalized the results using the 30 year normal monthly rainfall quantities published by Environment Canada.

TABLE 1: RAIN CATEGORIES FROM CWEC FILES

CWEC Data Flag (CWEC Rain Category) Rainfall Rate Weights

0 (None) 0

1 (Light Rain), 4 (Light Rain Showers), 7 (Light Freezing Rain) 2

2 (Moderate Rain), 5 (Moderate Rain Showers), 8 (Moderate Freezing Rain) 4

3 (Heavy Rain), 6 (Heavy Rain Showers) 8

The rainfall intensity for each hour calculated in this manner was then used to calculate the median drop diameter (using Equation 4), the terminal velocity of the median droplet (Equation 3) and the amount of driving rain (Equation 2). All values are based on open terrain near airports and a height of 10 m above grade.

The total annual driving rain, for each of 16 directions was calculated for 22 Canadian cities. Using Equations 2 through 4, the rain on a plane facing one of these 16 directions (cosine corrected for directions within +/- 90 degrees of the plane of interest) is plotted for 6 cities in Figure 2 through Figure 4. Hence, a DRF for each hour was calculated using Equation 3 depending on the intensity of rainfall (Equation 4).

Table 2 summarizes the rainfall (rain on a horizontal plane), the total driving rain (generated by summing each of the 16 directions without cosine correction), the average driving rain, and the quantity of driving rain on the


worst orientation. The summary statistics of total driving rain and the peak driving rain direction and quantity, have also been plotted on a map of Canada in Figure 5.

Vancouver, BC - Driving Rain 90° Incident, mm/yr

0

200

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600

800N

NNE

NE

ENE

E

ESE

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SSE

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Edmonton, AB - Driving Rain 90° Incident, mm/yr

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800N

NNE

NE

ENE

E

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SE

SSE

S

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FIGURE 2: VANCOUVER & EDMONTON DRIVING RAIN PLOTS

Toronto, ON - Driving Rain 90° Incident, mm/yr

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800N

NNE

NE

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Montreal, QC - Driving Rain 90° Incident, mm/yr

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800N

NNE

NE

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SE

SSE

S

SSW

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WSW

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WNW

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FIGURE 3: TORONTO & MONTREAL DRIVING RAIN PLOTS


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Halifax, NS - Driving Rain 90° Incident, mm/yr

0

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800N

NNE

NE

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St. John's, NF - Driving Rain 90° Incident, mm/yr

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800N

NNE

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FIGURE 4: HALIFAX & ST. JOHN’S DRIVING RAIN PLOTS

TABLE 2: ANNUAL DRIVING RAIN DATA DERIVED FROM CWEC FILES

Driving Rain (kg/m²) Avg Windspeed (m/s) City / Province

Horiz. Rainfall (kg/m²) Total Max Avg

Orient’n for Max All Hours During

Rain

Calgary AB 321 340 174 87 NW 4.4 5.9

Edmonton AB 366 428 264 118 NW 3.6 5.3

Prince George BC 419 302 200 94 SSW 2.4 3.2

Vancouver BC 1155 1084 764 337 E 3.3 4.4

Victoria BC 842 712 433 220 SSE 3 3.9

Churchill MB 264 369 161 101 ENE 5.9 6.8

Winnipeg MB 416 417 188 126 ESE 4.8 5.4

Fredericton NB 886 729 325 223 SSW 3.6 4

Saint John NB 1148 1593 786 479 SE 5.1 6.9

St. John's NF 1191 1913 1245 590 SSW 6.7 7.6

Halifax NS 1239 1283 656 384 SE 4.2 5.3

Sydney NS 1213 1893 1196 587 SSE 6 7.7

Yellowknife NT 165 201 93 58 ENE 4.3 5.3

North Bay ON 775 671 340 207 SSW 3.7 4.4

Ottawa ON 732 655 253 197 E 4.1 4.6

Toronto ON 685 646 308 194 ESE 4.2 4.8

Charlottetown PE 880 1044 487 318 SSE 5 6.2

Montreal QC 760 664 290 200 SSW 3.8 4.5

Quebec QC 924 765 438 240 ENE 3.8 4.4

Regina SK 304 400 137 113 ENE 5.6 6.5

Saskatoon SK 265 298 119 86 ESE 4.7 5.4

Whitehorse YT 163 99 53 29 SSE 3.3 3


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Although the result of analysis of CWEC files, not real weather data, these plots already show some important information. St. John’s, Halifax and Vancouver are, not surprisingly, the two large cities with the most driving rain. The total driving rain in Halifax is higher than Vancouver (1283 versus 1084 mm per year). The peak driving rain direction is of more importance for most building designers since it imposes the highest load. Driving rain from the worst direction is higher in Vancouver than Halifax (764 versus 656). The driving rain in other major population centers, such as Toronto and Edmonton are much less, and quite different than either of Vancouver or Halifax. The driving rain on the worst orientation in St John’s, Newfoundland and Sydney Nova Scotia are much higher, at around 1200 kg/m2/yr than either Vancouver or Halifax. It can also be seen from the figure that orientation has a very significant effect: the ratio of the amount of rain on the worst direction is between 5 and 10 times that on the most exposed direction.

Coincidence of wind speed and rainfall

The importance of wind speed to the intensity of driving-rain deposition has already been noted. High wind speeds also may generate high stagnation pressures that can drive rain into the cracks and openings of some types of enclosures. Small flaws in face-sealed claddings for example, will leak significantly more when exposed to pressure differences [Lacasse et al 2003]. Brickwork does not leak significantly more under pressures of 50 Pa than 0 Pa [Straube and Burnett 2000]. In most cases the increase in air pressure with wind speed is unimportant relative to the size of the increase in rain deposition with wind speed [Lacasse et al 2003]. Hence, although practitioners often observe an increase in rain-penetration control problems in high exposure conditions the evidence suggests that these problems are usually due not to an increase in air pressure difference but to an increase in rain deposition.

Table 2 summarizes the wind speed during all hours and the wind speed during rainfall. It is clear that the average wind speed is often slightly higher during rain, generally by about 10 to 20%. Most locations in North America have similar average wind speeds (i.e., 3 to 5 m/s at 10 m above grade), but it is clear that a location such as St John’s Newfoundland will have much higher imposed wind pressure during rain (V= 7.6 m/s, Pstag = 35 Pa) than Prince George (V = 3.2 m/s, Pstag = 6 Pa).

Figure 6 plots the results of a more detailed study of 25 years (1965-1990) of hourly wind and rain data for Seattle-Tacoma Airport, Washington. It can be seen that wind speed is slightly higher during rainfall (4.65 m/s), but the wind speed is, on average, relatively low (an average of 3.9 m/s). The plots shows that the hourly average stagnation pressures acting on a wall assembly during more than 99% of all rain events are lower than 20 Pa.

Hence, based on the data, it can be concluded that for the vast majority of the time during rain, the wind pressure acting on building enclosures during rain deposition is likely to be small (under 20 Pa). Even in Sydney NS, the average stagnation pressure is less than 40 Pa (although this pressure occurs fairly often in this location). Gust pressures can be twice these average pressures, but they tend to act for small fractions of time. The pressures used in testing (commonly 137 Pa or more) are too high to be considered realistic or indicative of the conditions leading to rain control failures commonly discovered in the field. Such test pressures may be useful for diagnostics and quality control however. Locations in climates affected by hurricanes may very well be different as they receive high rainfall rates coincidentally with high wind speeds. This is the subject of on-going research.

DRIVING RAIN ON BUILDINGS

The driving rain data presented above is a meteorological measure of climate. Building designers are more concerned with the amount of rain that is deposited onto the face of a building. The values given in the plots of directional driving rain can be modified to provide estimates of the quantity of driving rain deposition on a building. The first step is to assess the influence of building shape and aerodynamics, and the second is to correct for wind exposure.


0%

3%

6%

9%

12%

15%

0 1 2 3 4 5 6 7

Wind Speed (m/s)

RelativePro

bability(%

)

During Rain

All hours

Wind Pressure (Pa)2.4 5.4 9.6 15 22 290.6

FIGURE 6: RELATIVE PROBABILITY DISTRIBUTION OF RAINFALL, WIND SPEED, AND WIND PRESSURE FOR SEATTLE, WA FROM 25 YEARS OR HOURLY DATA

Building Shape and Aerodynamics

When wind encounters a building, streamlines and pressure gradients form around it. While it is clear that driving rain is re-directed by these streams of air (since the droplets are carried with the wind), accounting for this effect is difficult.

A simple and practical approach for estimating rain deposition on buildings is to divide driving rain deposition into the effects of the undisturbed wind (the free wind driving rain, a climate and site specific value) and the effect of the aerodynamics and geometry of the local building. A linear factor, the rain deposition factor (RDF), can be used to transforms the rate of driving rain in the free wind (i.e. outside of the region disturbed by a building) to the rate of rain deposition on a particular building [Straube 1998]. Therefore for a particular orientation and spot on the building face:

rvb = RDF· DRF· V(h)· cos ( ) · rh (7)

where rvb is the rain deposition rate on a vertical building surface(l/m2/h),

is the angle between the normal to the wall and the wind direction, DRF is the Driving Rain Factor, which accounts for interaction of the wind and rain in the

undisturbed wind, and

RDF is the Rain Deposition Factor, the ratio of rain in the free wind to rain deposition on abuilding, which accounts for the effect of building shape and size on rain deposition.

The RDF is a function of the building's shape, aerodynamics, the wind's angle of attack, raindrop diameter, and wind speed. In general, since most rain events are of low intensity and have a similar distribution of raindrop sizes, average values of RDF measured in the field over a range of driving rain events have shown somewhat


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consistent results [Straube 1998] and have shown to predict a special case on a 15 minute basis [Straube 1997]. It is interesting to note that recent computer modeling back by field measurements [Block and Carmeliet 2004] have provided strong evidence to support a single RDF factor independent of rainfall intensity. Again, this conclusion would need to be confirmed in hurricane regions because of their different pattern of rain and wind. The most important dependencies are with the building shape and aerodynamics, and hence these are investigated below.

Other than Straube [1997, 1998] and Schwarz [1973] the literature contains few references of simultaneous measurements of driving rain in the environment and the driving-rain deposition on a building. However, when results from the literature of field measurements [Schwarz 1973, Frank 1973, Sandin 1988, Flori 1992, Henriques 1992, Kuenzel 1994, Straube 1998, Blocken and Carmeliet 2000], wind tunnel tests [Inculet 1994], and computer modeling [Choi 1994, Karagiozis et al 1997, Blocken and Carmeliet 2000] are evaluated in terms of calculated RDF there is a reasonable agreement of results. Until the results of further research are available, the RDF values given in Figure 7 (compiled from the references listed) are recommended. An RDF of 1.0 appears to be appropriate near the upper corners of blunt-edged, rectangular buildings. Over small areas with unusual or complex geometries (notches in the elevation of a building), much higher RDF values may be more realistic. An RDF of much less than one is likely over most areas of most buildings.

FIGURE 7: RAIN DEPOSITION FACTOR (RDF)

Peaked roofs and overhangs redirect airflow up and over the building at a distance further from the facade (Figure 8) and can thereby have a significant effect on rain deposition (regardless of the building size)[Inculet 1994]. For example, adding a 1.5 m wide canopy to a multi-storey building will result in a lower RDF value and can, in theory, be an effective and economical means of improving rain control. Similarly, a peaked roof not


only leaks less than a low-slope roof, it may also reduce the amount of driving rain on walls by deflecting the wind [Straube 1998].

FIGURE 8: INFLUENCE OF OVERHANGS ON WIND AROUND BUILDINGS

Wind Exposure Corrections

It is clear from Equation 7 that rain deposition will increase directly with wind speed. Equation 7 is only accurate if the wind speed at the height of interest is applied and the terrain and site features are accounted for. This requires that the wind speed from weather data (typically collected at a height 10 m above grade in open terrain) be corrected. Wind speeds are also accelerated close to the ground on hilltops, and will be higher in exposed conditions (open country) than for buildings protected by other houses, by trees or by hills. Hence, building facades protected from high wind speeds are also protected from driving rain. The fact that wind speed increases rather rapidly with height means that the driving rain exposure of tall buildings is much higher than for low-rise buildings. Although there is only one study of rain deposition on tall buildings that measured rain deposition over the height of a building [Schwarz 1973], the results support the approach taken below. Other studies on tall buildings (van Mook 1999 , Lacy 1965] have been undertaken.

Using modified versions of the wind speed factors from the National Building Code of Canada [NBCC 1995] Figure 9 plots a wind exposure correction factor versus height and terrain. This factor can be used to adjust the amount of driving rain predicted by Equation 7. Exposed and sheltered locations are recommended based on the “speed up” function in the NBCC and the authors’ experience measuring driving rain.

EXAMPLE

As an example of using the data and methods described, consider two different walls in Toronto, one facing east and one west. Figure 3 shows a free wind driving rain quantity of 150 mm/yr for the west and 300 mm/yr for the east. If one considers a bungalow wall 2 m above grade, sheltered by closely spaced houses in a suburb, the 150 mm/yr would be modifying by a factor of 0.7 (from Figure 9) and a further reduction factor of 0.5 (from the note on sheltering). If the bungalow had a peaked roof with a 300 mm overhang, an RDF of 0.5 would capture the highest rain values. The result would be a driving rain total of 150*0.7*0.5*0.5= 26 mm per year, which is equivalent to 26 liters per m2 per year.

For an east facing wall on the top floor of a 50 m tall blunt edged (RDF=1.0) condominium in a suburban exposure, Figure 9 provides a correction factor of 1.5. Using and RDF of 1 for the top corners, the driving rain deposition would be predicted to be 300 * 1.5 * 1.0 * 1.0 = 450 mm per year or 450 l/m2/year – almost 20 times as much rain as the sheltered low-rise bungalow wall facing west.


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This example demonstrates the very significant influence of exposure and orientation in a climate. It should also be noted that the combination of high exposure and choice of building shape (high RDF) in a low driving rain climate (such as Edmonton) can result in much more rain deposition than a sheltered low rise building in a high driving rain climate (such as Vancouver).

0

10

20

30

40

50

0.5 0.8 1.0 1.3 1.5 1.8 2.0

Velocity Correction Factor

Heigh

tAbo

veGrade

[m]

City Center

Open Country

Suburban

Exposure:

Recommended multiplication factors to apply to above:Sheltered: 0.5 if buildings or obstruction of building height are within a distance equal totwice the building heightExposed: 1.3 if at the crest of hill or for that part of a building above an obstruction to flow

FIGURE 9: WIND SPEED CORRECTION FACTORS FOR DIFFERENT EXPOSURES AND HEIGHTS

CONCLUSIONS

Driving rain data, and the methodology for deriving them, have been presented for several locations in Canada. Simple modification factors have also been introduced to allow for the impact of wind exposure and building shape.


ACKNOWLEDGEMENTS

This research has been supported by grants from Canada Mortgage and Housing Corporation and the National Science and Engineering Research Council. This support is gratefully acknowledged.

REFERENCESBlocken, B., Carmeliet, J., 2000. “Driving Rain on Building Envelopes I: Numerical estimation and Full-scale

Experimental Verification”, J. of Thermal Envelope and Building Science Vol 24, No. 1, pp. 61-85. Blocken, B., Carmeliet, J. 2004. “A Simplified Approach for Quantifying Driving Rain on Buildings”, Proc. Of

Performance of Exterior Envelopes of Whole Buildings IX, Clearwater, Dec. Boyd, D.W., 1963. Driving-Rain Map of Canada, Division of Building Research, National Research Council, TN

398, Ottawa,. Choi, E.C.C. 1994. Determination of the wind-driven-rain intensity on building faces. Journal of Wind Engineering

and Industrial Aerodynamics, Vol 51, pp. 55-69. Flori, J-P. 1992. Influence des Conditions Climatiques sur le Mouillage et le sechalge d'une Facade Vertical. Cahiers du

CTSB 2606, September. Frank, W. 1973. Entwicklung von Regen and Wind auf Gebaeudefassaden, Verlag Ernst & Sohn, Berichte aus der

Bauforschung, Vol 86, pp. 17-40. Grimm, C.T., 1982. "A Driving Rain Index for Masonry Walls", Masonry: Materials, Properties, and Performance,

ASTM STP 778, J.G. Borchelt, Ed., American Society of Testing and Materials, pp. 171-177. Henriques, F.M.A. 1992. "Quantification of wind-driven rain - an experimental approach", Building Research and

Information, Vol. 20, No. 5, 1992, pp. 295-297. Inculet, D.R., Surry, D. 1994. Simulation of Wind-Driven Rain and Wetting Patterns on Buildings. Report BLWT-

SS30-1994, U. of West. Ontario, London, November. Karagiozis, A., Hadjisophocieous, G., and Cao, S., 1997. "Wind-Driven Rain Distributions on Two Buildings",

J. of Wind Engineering and Industrial Aerodynamics, Vol 67 and 68, pp. 559-572. Künzel, H.M., 1994. Regendaten für Berechnung des Feuchtetransports, Fraunhofer Institut für Bauphysik, Mitteilung

265. Lacy, R.E., 1965. Driving-Rain Maps and the Onslaught of Rain on Buildings. Building Research Station Current

Paper 54, HMSO Garston, U.K.. Lacasse, M. A., O’Connor, T.J., Nunes, S., Beaulieu, P. 2003. Experimental Assessment of Water Penetration and

Entry into Wood-Frame Wall Specimens - Final Report. MEWS Consortium, IRC/NRCC,Ottawa, February, 2003.

Rain Penetration Control Guide, 2000. CMHC Report, Ottawa. Sandin, K. 1988. “The Moisture Conditions in Aerated Lightweight Concrete Walls”. Proc. of Symposium and Day

of Building Physics, pp. 216-220. Lund University, Swedish Council for Building Research. Schwarz, B. 1973. Witterungsbeansphruchung von Hochhausfassaden. HLH Bd. 24, Nr. 12, pp. 376-384. Straube, J.F. 1998. Moisture Control and Enclosure Wall Systems. Ph.D. Thesis, Civil Engineering Department,

University of Waterloo, Waterloo, Canada. Straube, J.F. Burnett, E.F.P., 1999. "Rain Control and Design Strategies". J. of Thermal Insulation and Building

Envelopes, July, pp. 41-56. Straube, J.F., Burnett, E.F.P. 2000. "Pressure Moderation and Rain Control for Multi-Wythe Masonry Walls".

Proc of International Building Physics Conference , Eindhoven, September 18-21, pp. 179-186. Straube, J.F., Burnett, E.F.P. 1997,"Driving Rain and Masonry Veneer", Water Leakage Through Building Facades,

ASTM STP 1314, R.J. Kudder and J.L. Erdly, Eds., American Society for Testing and Materials, Philadelphia, pp. 73-87.

Surry, D., Skerlj, P.F., and Mikitiuk, M.J. 1995. An Exploratory Study of the Climatic Relationships between Rain and Wind. CMHC Research Report, Ottawa, February.

Users Guide -to National Building Code of Canada 1995 Structural Commentaries (Part 4) 1996. Canadian Commission on Building and Fire Codes, National Research council, Canada.

Van Mook, F.J., 1999. “Measurements and simulations of driving rain on the main building of the TUE” Proc. Of 5th Symposium on Building Physics I the Nordic Countries, Goteborg, Swede, August, pp. 377-384.


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