Leaks in translucent structures are highly undesirable, as they can damage interior finishes, cause excessive moisture in the structural layers of exterior walls, and other detrimental effects. Currently, in many countries, regulatory requirements for the watertightness of translucent structures are standardized tests that are not contingent upon specific climatic conditions. This article proposes a calculation method for determining the water permeability of translucent structures, particularly wind pressure and precipitation intensity. Subsequently, water permeability tests were conducted on window-type translucent structures to validate the newly developed method’s efficacy under the climatic conditions of Krasnodar, Russia. Laboratory tests employed a total of nine design load combinations, each lasting 10 minutes. As a result of the study, the trans-lucent structure, previously certified as Class R6 according to GOST 33792-2021, exhibited leakage under a pressure differential of 285-420 Pa and a precipitation intensity of 0.38–0.88 l/m2/min. This observation underscores the significance of considering real-world conditions during laboratory testing for the reliability of building structures. Nevertheless, it is crucial to acknowledge that this method for determining the water permeability of translucent structures is applicable to any region worldwide, provided that long-term meteorological observations of horizontal precipitation and wind speed are available.
1.Introduction
The raindrops penetration through translucent structures is an undesirable phenomenon that can damage the interior decoration, cause excessive moisture in the structural layers of the outer walls, and negatively affect the health of residents’ buildings [1–6]. In most countries worldwide, there are no methods for determining the required water permeability of translucent facade structures for a specific construction site. The compliance of translucent facade structures with project requirements in terms of water permeability is confirmed through tests conducted according to standard methods that do not model all possible wind and rain combinations for a particular construction region.
Translucent facade structures of buildings often occur during operation during rains accompanied by wind. Rain caused by wind occurs when raindrops are deflected by wind [6–7]. The horizontal component of the vertical rain is formed under conditions where the wind directed along the horizontal umbrella with its pressure changes the vertical trajectory of the drops to an inclined one (for a significant portion of the vertical drops) or horizontal immediately. Drops that enter the structure are parts of inclined or horizontal components from the initial (vertical) drops, directed only along the holes and defects in the form of cracks. In this case, due to the pressure drop between the external pressure and the pressure in the chamber, the droplets enter through the holes [8–11].
Currently, there are three main groups of methods for assessing the amount of rainfall that falls on a vertical enclosure during rain with wind:
Direct empirical methods based on the processing of multi-year-old specialized meteorological observations of rain parameters in a specific climatic region [12–13]. This method of determining rainfall parameters is the most accurate, but its practical application is currently limited due to the requirement for expensive meteorological equipment that continuously records readings in automatic mode. Semi-empirical methods, which adapt standard meteorological observations to solve problems of determining rainfall intensity on vertical facade surfaces, have long been the most common in practice and are incorporated into regulatory documents [14–17]. Numerical methods based on CFD modelling, which describe wind flow using the Navier–Stokes equation [18–20], have limited practical application due to their labor-intensive calculations.
The method for assessing the water permissibility of translucent structures planned in this work differs from others [14–17] in that it considers all possible design situations characteristic of a specific construction region. Calculated values for rainfall and pressure intensity before testing structures are combined to identify the worst operating condition. The developed methodology for assessing the water permeability of translucent structures also takes into account the duration of wind pressure and its abrupt changes.
The purpose of this study is to develop theoretical foundations and methods for determining the permeability of translucent facade structures under the combined action of wind loads and atmospheric precipitation. To achieve this goal, the following tasks will be solved:
Scientific justification of calculated combinations of wind loads and atmospheric precipitation to determine the water resistance limit of translucent facade structures. Experimental studies of the mechanism of water permeability of translucent facade structures of window types under the influence of rain and wind.
2.Methods[1]
A new approach to determining the parameters for laboratory testing of translucent enclosure structures for water permeability is proposed. This method relies on using climate data on vertical precipitation intensity and wind speed during rain, the relationship between horizontal precipitation intensity and wind pressure is determined. Based on known relationships [21], the rainfall intensity and required water flow rate during testing are determined:
,
(1)
where Vz is the wind speed at height z (m/s), rh the amount of horizontal precipitation (mm/min), RAF is the rain transmittance coefficient; DRF is the precipitation coefficient of rain.
The coefficient DRF is determined by Equation (2) according to the relationship defined in [22]:
,
(2)
where D50 is the average diameter of a raindrop (mm).
The average drop diameter can be determined according to [23]:
(3)
The wind pressure could be determined using a well-known Bernoulli’s law of conservation of kinetic energy (4) [24]:
,
4)
where ρ is the air density (kg/m3), V10 is the wind speed, m/s, at a height of 10 m above the ground surface.
The intensity of the horizontal component of precipitation can be determined by multiplying the vertical precipitation values by cos 45º, and subsequently converting them to millimeters per minute (mm/min).
To convert hourly values of horizontal precipitation intensity to 10-minute values, the Linsley formula (5) [25] can be used.
,
5)
where i(t) is the unknown short-term precipitation intensity (mm/min), t is the given interval (s), ih is the hourly precipitation intensity (mm/h).
The following load combinations should be considered:
C1: light rain with light wind; C2: moderate rain with medium wind; C3: heavy rain with strong wind; C4: light rain with medium wind; C5: moderate rain with strong wind; C6: heavy rain with light wind; C7: light rain with strong wind; C8: moderate rain with light wind; C9: heavy rain with medium wind; t = 10 minutes for any of the specified load combinations.
As the intensities of horizontal precipitation components have been accounted for, it is not necessary to tilt the nozzles at a 45-degree angle to simulate the oblique effect of raindrops. To ensure that the entire surface of the structure is adequately covered with water, it is recommended to install at least three rows of nozzles.
2.1.Application of the Proposed Assessment Methodology for Krasnodar City (Russia)
Based on the data from The Federal State Budgetary Institution “Voeikov Main Geophysical Observatory” (FGBI “MGO”) (Table 1), meteorological data for the 50th observation period (1964–2024) were analyzed for several Russian cities, including Krasnodar.
Table 1. Initial meteorological data for Krasnodar city (fragment).
Date
The beginning
The Ending
Duration (min)
Rain amount (mm)
Wind speed max (m/s)
Rain intensity (mm/min)
1977.02.06:4-00
1977.02.06:18.00
1977.02.06:20.10
130
6.2
3
0.05
1977.02.28:16-00
1977.02.28: 0.00
1977.02.28: 3.00
180
10.1
7
0.06
1977.03.07:16-00
1977.03.07:20.50
1977.03.07:21.00
10
5.8
8
0.58
1977.03.19:4-00
1977.03.19:15.20
1977.03.19:17.10
110
9.6
6
0.09
1977.03.24:19-00
1977.03.24:22.40
1977.03.24:23.00
20
7.2
3
0.36
1977.03.25:4-00
1977.03.25:15.30
1977.03.25:17.10
100
11.2
7
0.11
1977.04.07:16-00
1977.04.07: 4.20
1977.04.07: 6.00
100
7.6
3
0.08
1977.04.13:16-00
1977.04.13: 3.00
1977.04.13: 3.50
50
14.8
3
0.3
1977.04.18:4-00
1977.04.18:18.00
1977.04.18:21.00
180
15.7
0
0.09
1977.05.25:16-00
1977.05.25: 2.50
1977.05.25: 3.00
10
11.7
10
1.17
1977.06.07:4-00
1977.06.07:18.00
1977.06.07:21.00
180
5.3
0
0.03
1977.06.16:19-00
1977.06.16:12.18
1977.06.16:12.42
24
10.3
3
0.43
1977.06.24:16-00
1977.06.24:17.10
1977.06.24:17.18
8
31.2
3
3.9
1977.07.02:16-00
1977.07.02: 9.08
1977.07.02: 9.10
2
31.4
3
15.7
1977.07.04:16-00
1977.07.04:10.05
1977.07.04:10.30
25
5.6
9
0.22
Figure 1. Meteorological data for the 50th observation period, spanning from 1964 to 2024, for Krasnodar city (Russia).
While Fig. 1 shows the graph of the relationship between rain intensity and wind speed for the period (1964-2024) taking into account all events, Table 1 shows a subset of the events shown in Fig. 1. Analyzing the data presented in Table 1, it becomes evident that precipitation events exhibit varying durations. Consequently, it is imperative to process the data such that all precipitation events have a duration of less than or equal to 10 minutes. However, the meteorological data highlighted in yellow does not necessitate processing, as these precipitation events also have a duration of less than or equal to 10 minutes.
Table 2 presents a simplified version of Table 1, incorporating the presented precipitation intensity values. The precipitation intensity values were averaged to 10-minute values, contingent upon the duration variation, as per Equation (5) [25].
Table 2. Processed values of horizontal precipitation and wind speed for Krasnodar city (fragment).
Duration (min)
Rain amount (mm)
Wind speed max (m/s)
Rain intensity mm/min
10
1.1
3
0.11
10
1.3
7
0.13
10
5.8
8
0.58
10
1.9
6
0.19
10
7.64
3
0.76
10
2.33
7
0.23
10
1.70
3
0.17
10
6.37
3
0.64
10
1.91
0
0.19
10
11.70
10
1.17
10
0.64
0
0.06
10
9.13
3
0.91
10
39.00
3
3.90
10
157.00
3
15.70
10
4.67
9
0.47
Next, it is imperative to exclude from the table of provided values (Table 2) rows where wind speed is zero. These speeds must be converted to pressure using the formula (4). Then, prior to plotting the relationship between typical horizontal precipitations and their corresponding wind pressures (Fig. 2), it is necessary to average the precipitation intensity values corresponding to the given wind pressure value.
Figure 2. Relationship between typical horizontal precipitations and their corresponding wind pressures.
From this point, we must graphically select the maxima from the set of points in Fig. 2. These points will be used to determine the most suitable function for the relationship between horizontal precipitation and wind pressure (Fig. 3). Subsequently, regression analysis will be employed to evaluate the appropriateness of the parameters under consideration. Furthermore, we will conduct a separate regression analysis of the distribution of each parameter (Fig. 4, 5), specifically the probability distribution of horizontal precipitation intensity and wind pressure with a return period of up to 100 years.
Figure 3. The correlation between typical horizontal precipitation and their corresponding wind pressures.
Figure 4. Probability of wind pressure distribution.
Figure 5. Probability distribution of horizontal precipitation intensity.
2.2.Watertightness Test
Watertightness tests are characterized by evaluating a component’s ability to prevent water ingress using a combination of water spray and pressure differentials. During this laboratory test, to accurately replicate real-world climatic conditions, it is imperative to incorporate wind gusts, which manifest as abrupt fluctuations in wind pressure within a three-second interval following the transition between two load configurations.
Test materials:
A. Single-leaf aluminum window (1900 × 1010 mm) (Fig. 6.a)) – design previously confirmed to class R6 (as per Table B.3 of GOST 33792-2021). B. Water spray nozzles with a flow rate of 1 l/min (Fig. 6.b)).
a) b)
Figure 6. a) General view of the test bench, b) Sprinkler device.
3.Results and Discussion
Table 3. Test parameters.
Return period
i (mm/min) or (l/m2/min)
Р (Pa)
–
P
2 years
0.50
0.88
186
5 years
0.80
0.38
285
15 years
0.93
0.14
371
30 years
0.97
0.08
399
50 years
0.98
0.05
411
100 years
0.99
0.03
420
When selecting test parameters from the Table 3, the minimum, average, and maximum wind pressure values are taken into account, along with their corresponding rainfall intensities.
Combination C1: Air pressure P = 0–186 Pa, water flow rate i = 0.03 l/m²/min, duration t = 10 min.
Observation: No leakage
Conclusion: The absence of leaks is likely attributable to the low wind pressure and low water flow rate.
Combination C2: Air pressure P = 186–285 Pa, water flow rate i = 0.38 l/m²/min, duration t = 10 min.
Observation: No leakage
Conclusion: Although the applied wind pressure and water flow rate are significant, they are insufficient to cause leakage for this window.
Combination C3: Air pressure P = 285–420 Pa, water flow rate i = 0.88 l/m²/min, duration t = 10 min.
Observation: Leaks in the lower left corner and under the hinges (upper right corner) starting from the 4th minute (Fig. 7).
Figure 7. Leak locations.
Conclusion: The tested window unit is not fully water-resistant under realistic conditions.
Combination C4: Air pressure P = 186–285 Pa, water flow rate i = 0.03 l/m²/min, duration t = 10 min.
Observation: No leakage
Conclusion: The absence of leakage is most likely attributed to the limited quantity of water, which hinders its uniform distribution across the surface of the tested unit.
Combination C5: Air pressure P = 285–420 Pa, water flow rate i = 0.38 l/m²/min, duration t = 10 min.
Observation: Leakage in the lower left corner and under the hinges (upper right corner) from the 4th minute (Fig. 7).
Conclusion: The tested window unit is not fully water-resistant under realistic conditions.
Combination C6: Air pressure P = 0–186 Pa, water flow rate i = 0.88 l/m²/min, duration t = 10 min.
Observation: No leakage
Conclusion: The tests unit appears to be resilient to this combination.
Combination C7: Air pressure P = 285–420 Pa, water flow rate i = 0.03 l/m²/min, duration t = 10 min.
Observation: No leakage
Conclusion: Despite the substantial wind pressure, there is no leakage due to the limited volume of water, which prevents its uniform distribution across the test unit’s surface.
Combination C8: Air pressure P = 0–186 Pa, water flow rate i = 0.38 l/m²/min, duration t = 10 min.
Observation: No leakage
Conclusion: The absence of leaks is primarily attributed to the relatively low wind pressure intensity.
Combination C9: Air pressure P = 186–285 Pa, water flow rate i = 0.88 l/m2/min, duration t = 10 min.
Observation: No leakage
Conclusion: The tests unit appears to be resilient to this combination.
This study overlaps with the work [27] where three different window designs were tested for water permeability under static and realistic dynamic air pressures. As a result of the above work, the windows failed at lower mean pressure conditions during the realistic fluctuating pressure testing (261 Pa) than during the static pressure tests (510 Pa).
On the other hand, this study and the work [28] share the same limitations in calibrating water flow during artificial rain simulation. Rain modeling in laboratory tests (rainfall simulators) still struggles to replicate natural rain. In practical settings, rain intensity fluctuates, whereas laboratory conditions typically result in constant water flow.
4.Conclusion
Consequently, given that the translucent enclosing structure, previously confirmed by Class R6 (as per Table B.3 of GOST 33792-2021, with a water resistance limit of approximately 450 Pa), leaks at a pressure differential of 285–420 Pa and an intensity of 0.38–0.88 l/m2/min, it is evident that considering realistic conditions during laboratory tests is crucial for the reliability of building structures. Thus, while standards remain essentially standardized quality control and administrative compliance tools, this methodology for evaluating the water tightness of facades, integrating real climatic conditions, makes it possible to adapt the performance of buildings to local risks, optimize their durability and ensure increased energy efficiency by avoiding oversizing or underperformance.
[1] Use of artificial intelligence: Apple Intelligence version iOS 18.4 was used to correct grammatical and stylistic errors. The authors confirm that the scientific content, data analysis, and conclusions were completed independently.