Hydrothermal behavior of hollow ceramic bricks from Southern Brazil brickyard

Comportamento higrotérmico de tijolo cerâmico de olaria do sul do Brasil

Abstract

The presence of moisture in buildings can lead to pathological manifestations, and the behavior of materials when exposed to various conditions can be predicted through computational simulations. For this purpose, the hygrothermal characteristics of building elements are paramount. In Brazil, there is a gap in studies on the hygrothermal properties of materials, compromising simulations. This article discusses the possibilities of using European data in simulating moisture transport in ceramic brick walls in the southern region of Rio Grande do Sul, Brazil. The results were generated by comparing hygrothermal simulations with WUFI Pro 6.5 using the simulation program database with data collected from laboratory tests on ceramic bricks from a southern Brazilian brickyard. Tests for water vapor diffusion resistance, water absorption, and hygroscopic curves were conducted. Although both situations led to the growth of filamentous fungi, experimental data led to3% lower values compared to database results. Regarding surface condensation, a likely higher occurrence was observed when using laboratory test data.

Keywords: Hygrothermal performance; Hygrothermal simulations; Moisture.

Resumo

A presença de umidade nos edifícios pode gerar o aparecimento demanifestações patológicas. Pode-se prever o comportamento de materiais expostos a condições diversas através de simulações computacionais. Para isso, as características higrotérmicas dos elementos de construção são fundamentais. No Brasil, há uma lacuna nos estudos sobre as propriedades higrotérmicas dos materiais, comprometendo as simulações. Esse artigo discuteas possibilidades de utilização de dados europeus na simulação do transporte de umidade em paredes de tijolos cerâmicos na região Sul do Rio Grande do Sul. Os resultados foram gerados comparando-se simulações higrotérmicas com o software WUFI Pro 6.5 utilizando a base de dados do programa de simulação, com dados coletados em ensaios de laboratório para tijolo cerâmico de uma olaria do Sul do Brasil. Foram realizados ensaios de resistência à difusão de vapor de água, absorção de água e curvas higroscópicas. Embora ambas as situações conduziram ao crescimento de fungos filamentosos, os dados experimentais geraram resultados 3% inferiores à base de dados. Quanto à condensação superficial, observou-se provável maior ocorrência ao utilizar os dados dos ensaios.

Palavras-chave:  Desempenho higrotérmico; Simulações higrotérmicas; Umidade

Introduction

Moisture and temperature can significantly impact the performance and durability of building components. Hygrothermal performance refers to the transport of heat and moisture within the building, and understanding it is crucial for designing more efficient edifications. Hygrothermal simulation tools offer various benefits to buildings, such as supporting the choice between different designs, comprehending how moisture and heat transport phenomena occur, and preventing condensation and filamentous fungi growth (Santos, 2019). With these tools, conducting a precise analysis of hygrothermal performance in buildings is possible, considering the appropriate selection of material properties available in databases (Zanoni, 2015; Nascimento, 2016).

In Brazil, studies focusing on the hygrothermal properties of materials are recent, leading to a gap in the national database (Zanoni, 2015). Although hygrothermal building performance simulation is accurate, its reliability depends on input data and the numerical model. Thus, the lack of adequate input data, particularly regarding hygrothermal characteristics of construction materials, restricts the effectiveness of this tool. In this context, the experimental study of Brazilian materials is paramount (Belizario-Silva; Brito, 2024).

This gap is also evident in the Brazilian Building Performance Standard NBR 15575 (ABNT, 2021a), which establishes guidelines for thermal performance evaluation. However, the standard does not define parameters or methods for conducting simulations or on-site measurements to assess the hygrothermal behavior of building elements. In other words, it does not provide specific guidance on moisture in buildings (Zanonietal., 2020). It is necessary to assess whether the databases available in hygrothermal simulation software can be used under adverse conditions compared to their originating locations and whether hygrothermal properties influence the envelope behavior in response to climate conditions, in addition to the arising effects on the internal environment and the durability of the analyzed construction systems (Jorne, 2010).

Building performance simulations contribute to the quest for solutions to enhance their energy efficiency, providing a viable alternative to analyze how construction systems behave under different weather and environmental conditions (Kleber, 2018). In this context, the user should define appropriate material properties in the simulation software since problems related to Brazilian buildings' performance, for instance, may not be appropriately perceived if values from inappropriate sources (especially those from high-performance standards) were used (Hens, 2015).

Many mathematical models have been developed to simulate the simultaneous transport of moisture and heat in building envelopes, some of which are integrated into simulation software such as DELPHIN, MOIST, and WUFI. The WUFI software, validated by the reference test of EN 15026 (DIN, 2007) and widely used in hygrothermal simulations, is recognized as one of the most reliable software tools available.

Therefore, this study used the WUFI Pro 6.5 software to assess hygrothermal conditions in building envelopes. Building performance simulations were based on the Künzel model (1995). The definition of hygrothermal properties of materials was required as input data, manually entered or retrieved from the program database. Simulations were run with actual climate conditions based on weather files. The outputs provided temperature and relative humidity profiles over the years, along with isopleth graphs, enabling risk analysis, like the occurrence of filamentous fungi (Künzel, 1995).

So, the present paper presents and discusses the different results obtained through hygrothermal simulation of hollow ceramic brick walls using database/default data and data collected from laboratory tests. Additionally, the risk of surface condensation occurrence and fungi formation inside the building was assessed through graphs. The objective was to examine the possibilities of using European data from the software database in simulating moisture transport in ceramic brick walls in the Southern region of Rio Grande do Sul (RS), Brazil. The hygrothermal properties of bricks from a brickyard in Pelotas, RS, were evaluated through laboratory tests, including water vapor diffusion resistance, water absorption, and isotherms. Thus, the study aims to contribute to understanding the influence of laboratory-measured hygrothermal properties of materials on moisture transfer.

Literature review

Moisture in buildings

Moisture can increase thermal discomfort and electricity consumption, further causing the degradation and deterioration of building elements (Mendes, 1997). Moreover, moisture can promote the growth of fungi, affecting building occupants' health (Zanoni, 2015). The study of moisture in buildings aims to verify the occurrence of condensation on the surface or internally, which is essential from the perspective of building element performance. Numerical simulation is a viable alternative for quantifying moisture, water vapor, and temperature transfer processes (Pinheiro, 2013). In Brazil, the most commonly used construction technique, ceramic brick masonry, presents a potential risk of moisture damage, especially in regions with high external vapor pressure, high rates of wind-driven rain, and densely populated areas (Morishita et al., 2016).

Hygrothermal properties

The hygrothermal properties of materials, such as water vapor resistance factor, liquid water absorption, and equilibrium moisture content (hygroscopic curves), are essential for understanding the heat and moisture transfer process within a computational simulation scenario (Zanoni, 2015). The water vapor diffusion resistance factor, μ, is used to evaluate vapor permeability. It represents the ratio between the air vapor permeability coefficient and the vapor permeability coefficient of the studied material. This factor indicates how many times the vapor diffusion resistance of the material is higher than that of a layer of air at rest, with equal thickness, and under the same environmental conditions (Freitas; Pinto, 1999). The coefficient of liquid water absorption, according to NBR 13281 (ABNT, 2021b), characterizes the capillarity of the material when in contact with liquid water. It refers to the ability of a material to absorb liquid water by suction over time. Lastly, equilibrium moisture content (adsorption and desorption) curves are graphical representations that demonstrate the relationship between moisture content in the materials and their exposure environment relative humidity (Salomão, 2016).

Mold Growth

Among the moisture-related problems caused by high water content in building materials is the growth of microorganisms, such as mold, which can lead to severe health and comfort consequences for building occupants (Chang et al., 2017). The development of fungi inside buildings is generally caused by a favorable combination of factors, including temperature, relative humidity, and nutrients (substrate). Oxygen, pH value, light exposure, and fungal spore attachment also contribute to fungal growth (Sedlbauer, 2001).

Sedlbauer (2001) states that relative humidity should be below 60% to prevent fungal proliferation. However, some species can grow at lower or higher relative humidity levels. In Pelotas (RS), the location focus of this study, the principal genera of filamentous fungi found include Penicillium, Paecilomyces, Cladosporium, Fusarium, and Trichoderma (Guerra, 2012). Sections “Isopleth model” and “Sedlbauer model” report models that predict mold growth in building materials.

Isopleth model

The isopleth model allows for determining spore germination time and mycelium growth rate by comparing building materials hygrothermal and mold growth conditions. This model presents curves that define favorable environments for fungal growth, considering temperature, relative humidity, and the exposure time for different fungal classes (Sedlbauer, 2001).

In WUFI Pro, the risk of fungal growth is assessed through the isopleth model using LIM curves (Lowest Isopleth for Mold) on the internal surfaces of building elements based on temperature and relative humidity (FIBP, 2018). LIM curves establish the minimum temperature and relative humidity conditions for fungal development according to substrate categories (0, I, and II). Points above LIM curves indicate that the combination of temperature and relative humidity on the internal surface is favorable for fungal growth (Sedlbauer, 2001).

Sedlbauer model

The bio-hygrothermal model from Sedlbauer (2001) predicts fungal formation by calculating the critical moisture content required for spore germination. The WUFI Bio, an extension of the WUFI program, applies this model to assess fungal growth. Output data from simulations with the WUFI Bio include mold growth rate and mold index.

The mold growth rate is zero when the spore moisture content is below the critical moisture content. Furthermore, the model considers mold growth acceptable below 50 mm/year, unacceptable above 200 mm/year, and requires further investigation when between 50 and 200 mm/year (Santos, 2019).

On the other hand, the mold index encompasses different levels of fungal growth, according to the VTT model by Viitanen et al. (2009). The mold index ranges from 0 to 6, where 0 represents inactive spores with no fungal growth, and 6 indicates pronounced growth, covering almost 100% of the surface (Sales, 2016). Based on this index, the results can be categorized as (FIBP, 2018):

1. acceptable;

2. additional criteria or investigations are necessary to assess acceptability;

3. unacceptable; and

4. evaluation impossible.

Method

This study is divided into three distinct stages (as shown in Figure 1):

1. research of available standards;

2. laboratory tests; and

3. building performance simulations.

Step 1: research of available standards

The ISO (International Organization for Standardization) supports the standardization of Brazilian production techniques through ABNT (Brazilian Association of Technical Standards), promoting national technological development, standardizing production processes, documents, and other technical procedures, such as NBR 13281-1 (ABNT, 2021b). Based on the criteria of matching and qualifying building products, registrations, and procedures, ISO standards were chosen in this research to carry out the laboratory tests corresponding to the hygrothermal variables, as follows: ISO 12572 (ISO, 2016) - Hygrothermal performance of construction materials and product - Determination of water vapor transmission properties, BS EN ISO 15148 (BSI, 2002) - Determination of the coefficient of water absorption by partial immersion, and BS ISO 24353 (BSI, 2008) - Determination of moisture adsorption/desorption properties in response to moisture variation.

Step 2: laboratory testing

Experimental tests were conducted to obtain the hygrothermal data for water vapor diffusion resistance, according to ISO 12572 (ISO, 2016); water absorption, according to BS EN ISO 15148 (BSI, 2002); and adsorption and desorption isotherms, according to BS ISO 24353 (BSI, 2008). The tests were carried out at the Laboratory of Materials and Built Environment Technology (LAMTAC - NORIE) at UFRGS for a hollow ceramic brick with dimensions of 9 cm x 9 cm x 14 cm from a brickyard in the region of Pelotas, Southern Brazil, which is certified for commercial use. The use of hollow ceramic brick is present in 82% of buildings in Brazil, according to the Continuous National Household Sample Survey (PNAD Continua), as it is considered a quality and traditional material, thereby justifying its selection as the research object (Morishita, 2020; IBGE, 2023).

Figure 1
Infographic of the method

Water vapor diffusion resistance

The water vapor diffusion resistance test, conducted based on ISO 12572 (ISO, 2016), followed a methodology similar to Salomão (2016). Figure 2 illustrates the preparation of ceramic brick specimens and the execution of the test.

As shown in Figure 2(a), glass containers measuring 10 cm x 10 cm x 15 cm were used as cup holders for the three tested specimens, keeping the original width of the material. Double-sided tape (in green) was used to ensure a distance of 2 cm between the specimens and the calcium chloride (CaCl₂) desiccant. In Figure 2(b), a 2 cm layer of granulated CaCl₂ was placed within the containers, overlaid by the 2 cm layer of air and the brick. Figure 2(c) shows that the glass container was sealed at the edges to ensure vapor passage only through the faces of the brick. The specimens were placed in a climate-controlled chamber with a saturated magnesium nitrate (Mg(NO₃)₂) solution, which determined a relative humidity of 85%, corresponding to the average in Pelotas-RS, as depicted in Figure 2(d). The specimens were weighed daily at the same time until mass stabilization, totaling 120 days as per ISO 12572 (ISO, 2016). The test was conducted inside a climate chamber with a relative humidity (RH) of 60 ± 5% and a controlled temperature of 23 ± 2°C, as seen in Figure 2(e).

After the water vapor diffusion resistance tests ended, the mass change rate was calculated according to Equation 1.

$∆m_{12}=\frac{m_2-m_1}{t_2-t_1}$ Eq. 1

Where:

∆m ₁₂ is the mass change per time for a single determination (kg/s);

m₁ is the mass of specimen and cup assembly in time t₁ (kg);

m₂ is the mass of specimen and cup assembly in time t₂ (kg); and

t₁ and t₂ are the weighing times (s).

Next, the water vapor permeance (W) was determined with Equation 2, where ∆p is calculated from the air temperature and relative humidity measurements during the test.

$W=\frac{G}{A\mathit{.}∆p}$ Eq. 2

Where:

W is thewater vapor permeance concerning partial vapor pressure (kg/(m².s.Pa));

G is the water vapor flow rate through specimen (mean of five successive determinations of ∆m₁₂ for each specimen) (kg/s);

A is the area of specimen (m²); and

∆p is the barometric pressure (Pa).

Figure 2
Water vapor diffusion resistance test

Subsequently, the water vapor permeability (δ) was calculated using Equation 3. Finally, the water vapor resistance factor (μ), was determined according to Equation 4.

$\mathrm{\delta }=\mathrm{W\; x\; d}$ Eq. 3

$\mathrm{\mu }=\mathrm{}\frac{\mathrm{\delta }\mathrm{air}}{\mathrm{\delta }}$ Eq. 4

Where:

δ is the water vapor permeability (kg/(m.s.Pa));

W is thewater vapor permeance concerning partial vapor pressure(kg/(m.s.Pa));

d is the mean thickness of specimen (m);

µ is the water vapor resistance factor [-]; and

δair is the water vapor permeability of air (kg/(m.s.Pa)).

Water absorption

Figure 3 shows the preparation for the water absorption test, following BS EN ISO 15148 (BSI, 2002). The test involves the specimens' partial immersion in water without a temperature gradient to determine the short-term liquid water absorption coefficient. Six specimens were prepared, leading to 300 cm² of area in partial contact with water, as shown in Figure 3(a), 3(b), and 3(c). Figure 3(d) shows that the lateral sides of the specimens were sealed, leaving the top free to ensure the contact of only the lower face with water.

Figure 4 demonstrates the execution of the water absorption test according to BS EN ISO 15148 (BSI, 2002). In Figure 4(a), a container is shown containing a grid that prevents complete submersion of the specimens in water, maintaining a controlled water layer with a height of 3 mm to 5 mm, regarding the specimens' thickness. The specimens were positioned over the grid, ensuring that contact with water was limited to their lower faces, as illustrated in Figure 4(b). During the experiment, the weights of the specimens were monitored at intervals of two hours and fifty minutes. Over this period, water began to emerge on the upper surfaces, as illustrated in Figure 4(c). Upon reaching 8 hours of testing, the specimens were completely wet, marking the end of the procedure, as indicated by BS EN ISO 15148 (BSI, 2002).

Figure 3
Water absorption test - preparation of specimens

Figure 4
Water absorption test - execution

After the weighing, the difference between masses at each weighing time and the initial mass per area were calculated according to Equation 5.

$∆m_t=(m_t-m_i)/A$ Eq. 5

Where:

∆m _t is themass gain per surface area after time t (kg/m²);

m_t is the mass of the specimen after time t (kg);

m_i is the initial mass of the specimen (kg); and

A is the surface area (m²).

With the calculation results, a graph was plotted, resulting in the standard type A, with water on the surface. Thus, the water absorption coefficient A _w was calculated with Equation 6.

$A_w=\frac{{∆m}_{\mathit{tf}}-{∆m}_0}{\sqrt{\mathit{tf}}}$ Eq. 6

Where:

∆_w is thewater absorption coefficient (kg/(m².s^0.5));

∆m _tf is the value of mass on the straight line at time t_f (kg/m²);

∆m ₀ is the initial value of mass (kg/m²); and

/is the square root of the duration of the test (s^0.5).

Adsorption and desorption isotherms

Figure 5 depicts the preparation for the adsorption and desorption isotherm tests according to BS ISO 24353 (BSI, 2008). The adsorption determination starts from dried specimens, involving water vapor migration from the air into the material. On the other hand, the desorption isotherm starts with saturated specimens, involving the evaporation of moisture from the material.

In Figure 5(a), specimens were cut according to the recommended dimensions of the standard. In Figures 5(b) and 5(c), two specimens were wrapped in aluminum foil, exposing only one surface. They were then preconditioned in a chamber with a controlled relative humidity of 60% and a temperature of 23 °C. During the test, specimens were alternately exposed in chambers with controlled relative humidity of 75% and 50%, as shown in Figure 5(d). The relative humidity was controlled with a datalogger. The test was conducted over four cycles, each lasting 24 hours.

The cyclic value of the moisture adsorption content was calculated with Equation 7, regarding an average of the specimens.

${\mathit{Pa},}_{\mathit{ac}}=\frac{m_{a4}-m_{d3}}{A}$ Eq. 7

Where:

Pa,_ac is the moisture adsorption content at the time of completion of the moisture adsorption process of the 4^th adsorption/desorption cycle (kg/m²);

m_a4 is the mass of the specimen at the time of completion of the moisture adsorption process of the 4^th absorption/desorption cycle (kg);

m_d3 is the mass of the specimen at the time of completion of the moisture desorption process of the 3^rd adsorption/desorption cycle (kg); and

A is thesurface area of adsorption/desorption (m²).

The cyclic value of the moisture desorption content was calculated with Equation 8, and the average value of the specimens was also used.

${\mathit{Pa},}_{\mathit{dc}}=\frac{m_{a4}-m_{d4}}{A}$ Eq. 8

Where:

Pa,_dc is the moisture desorption content at the time of completion of the moisture desorption process of the 4^th adsorption/desorption cycle (kg/m²);

m_a4 is the mass of the specimen at the time of completion of the moisture adsorption process of the 4^th absorption/desorption cycle (kg);

m_d4 is the mass of the specimen at the time of completion of the moisture desorption process of the 4^th adsorption/desorption cycle (kg); and

A is the surface area of adsorption/desorption (m²).

Step 3: computer simulation

Two programs, EnergyPlus 9.0 and WUFI Pro 6.5, were used for building performance simulation. The simulation models were set according to the initial draft of the ABNT standard “ABNT Computational Simulation of the Hygrothermal Behavior of Walls - Procedure” (ABNT, 2023), from the Working Group on Moisture of the ABNT Energy Efficiency Commission.

The weather file used for Pelotas, bioclimatic zone 2, according to standard NBR 15220-3 (ABNT, 2005), was the TRY weather file developed by Leitzke et al. (2018). Pelotas has a humid subtropical climate characterized by high humidity and hot summers, as illustrated by Figure 6.

In the simulations, the EnergyPlus 9.0 program was first used to create a file for internal hygrothermal conditions. A building was modeled in the SketchUp Make 2017 program using the Euclid plugin version 9.3. The simulated building had 36.15 m², with dimensions of 6.0 m x 5.9 m, and was divided into four thermal zones. This building included an integrated living room and kitchen, two bedrooms, and a bathroom, based on the SINAT, National System of Technical Evaluations of Innovative Products and Conventional Systems, Guideline No. 001 (SINAT, 2017) and depicted in Figures 7 and 8.

The entire building was modeled to consider heat and moisture exchanges between spaces, and only the living/kitchen area, which had the worst solar orientation, was used to generate the output file with internal temperature and relative humidity data for the input of internal hygrothermal conditions to the WUFI Pro 6.5 program.

Figure 5
Adsorption and desorption isotherms

Figure 6
Climate of Pelotas/RS, Brazil

Figure 7
Floor plan

Figure 8
Section plan

In the simulation with EnergyPlus, the Conduction Transfer Function (CTF) algorithm was used due to the high computational time taken by the Combined Heat and Moisture Transfer (HAMT) algorithm, which performs simultaneous heat and moisture transfer calculations. Therefore, only the thermal properties of the materials were considered.

The building had ceramic brick walls with plaster on all sides, ceramic tile flooring, wooden doors, a ceramic tile roof, and a concrete slab. The hygrothermal characteristics of ceramic bricks were based on the experimental results and a similar material from the WUFI Pro database; the plaster characterization followed the software database, as presented in Table 1. The thermal characteristics of the materials were based on the Brazilian Standard NBR 15220 (ABNT, 2005), according to Table 2.

The spaces were considered naturally ventilated, and the occupancy conditions, lighting systems, equipment, and window opening patterns followed the criteria outlined in the initial draft of the ABNT standard for building moisture (ABNT, 2023). For occupancy, two people per bedroom, four in the living room/kitchen, and one in the bathroom were considered, as shown in Table 3. Lighting was set at 5 W/m² in all areas. The metabolic rate generated by the occupants was 130 W/person in the living room/kitchen, 81 W/person in the bedrooms, and 130 W/person in the bathroom. The moisture generated by people was set at 285 W for the kitchen and 285 W for the bathroom. Occupancy or activation times are also shown in Table 3.

The window opening pattern for occupancy followed the occupied times in Table 3 for each area and was configured in the AirFlowNetwork item. Automatic window opening control was based on temperature, enabling window opening when the indoor air temperature (Tinternal) was equal to or higher than the thermostat temperature (Tthermostat), which was set at 19 ºC (Tinternal ≥ Tthermostat) and when the indoor air temperature was higher than the external temperature (Tinternal ≥ Texternal). The thermostat for window opening was set at 19 ºC according to NBR 15575 (ABNT, 2021a). Doors were set to remain open, except for the bathroom door and the entrance door of the dwelling. Windows were open during occupancy periods, except for the bathroom window, which remained open at all times, even during unoccupied periods.

The ground temperature was configured in the "Ground Domain" section of EnergyPlus 9, following Eli et al. (2019), which used a finite difference heat transfer model to calculate soil temperatures.

The hourly internal temperature and relative humidity data of the living/kitchen space were used to create the file for input of the indoor environment in the WUFI Pro 6.5 program.

Following, WUFI Pro 6.5 was used for hygrothermal simulations, which were carried out for 3 years. Only the last year was considered to analyze the results regarding the conditioning period for the dynamic stabilization of relative humidity in the construction. The first year was disregarded as it entails pre-defined initial humidity and temperature (Schmidt, 2019).

Table 1
Thermal and hygrothermal characteristics of ceramic brick and plaster

Characteristics of ceramic brick and plaster
Properties	PA Test	PA WUFI	Plaster
Absorptance	0.4	0.4	0.2
Density (kg/m³)	1138	1138	1990
Porosity (m³/m³)	0.6	0.6	0.25
Specific heat (J/kg.K)	920	920	1000
Thermal conductivity (W/m.K)	0.9	0.9	1.15
Water vapor diffusion resistance factor	3.66	38.86	45.89
Typical Building Humidity Value (kg/m³)	100	100	200.01
Water absorption (kg/m².s)	0.01915	0.11	0.085
Saturation moisture content (kg/m³)	94.21	190	200
Reference moisture content (kg/m³)	20.46	18	24.65

Table 2
Thermal characteristics of the materials

Characteristics of the materials
Properties	Ceramic floor	Ceramic roof tile	Concrete slab	Wood Door
Thermal conductivity (W/m.K)	0.9	0.9	1.75	0.15
Density (kg/m³)	1300	1600	2200	450
Specific heat (J/kg.K)	920	920	1000	2300
Absorptance	0.4	0.4	0.7	0.2

Table 3
Internal conditions

In WUFI Pro 6.5, a comparative simulation was carried out between the ceramic brick using hygrothermal data collected in the tests, labeled as PA Tests, and a ceramic brick with hygrothermal data from the database of WUFI Pro 6.5 program, labeled as PA WUFI. The thermal properties of the two bricks are identical, consistent with the simulation conducted in the previous EnergyPlus program, selected according to the Brazilian Standard NBR 15220 (ABNT, 2005), as shown in Table 1.

A fine mesh was considered, and positions on the walls external and internal faces were monitored. The file resulting from the EnergyPlus 9.0 program was used for the internal climate. The same TRY weather file for the external climate was used for Pelotas (Leitzke et al., 2018) as in the EnergyPlus simulation.

For the "sd" value configuration, no coating on the walls was considered, seeking to account for the most critical situations. The wind was disregarded for the simulations. The solar orientation considered was South. Driving rain was configured with the Standard 160 (ANSI; ASHRAE, 2009), which, according to Zanoni et al. (2018), is the most rigorous calculation model. For the "Rain Exposure Factor (FE)", a building with an average rain exposure category was considered, and for the "Rain Deposition Factor (FD)", a wall under a low-slope roof was considered.

Results and discussions

As a result, hygrothermal variables and simulations in WUFI Pro 6.5 are presented, demonstrating comparative differences through graphs and indicating where surface condensation and the growth of filamentous fungi have occurred. Furthermore, the impact of differences between national and international data on building performance simulation results was assessed.

Risk of surface condensation

Figures 9 and 10 illustrate the risk of surface condensation for the two analyzed brick characteristics (PA Tests and PA WUFI). The graphs depict the temperature behavior on the internal surface of the simulated facades (in red), the dew point temperature (in purple), and the relative humidity (in blue) throughout the simulation period.

As it can be observed in Figures 9 and 10, the internal surface temperature remained below the dew point. Moreover, the final relative humidity was above 80% for a significant portion of time, indicating that the systems pose a risk for surface condensation (Schmidt, 2019).

Figure 9
Temperature, Relative Humidity, and Dew Point on the Internal Surface for the simulations using experimental data (PA Tests)

Comparing the wall simulated with data from the WUFI Pro 6.5 database (PA WUFI) with the wall simulated using experimental results (PA Tests), a similarity in the behavior was observed during the simulation period. Both systems had relative humidity levels exceeding 90%, especially in the months with lower temperatures, which could represent a critical point in the construction system. Generally, both walls posed a risk of vapor condensation with critical points where relative humidity values were close to 100% on the internal surface. Concerning dew points, the dew temperature of the PA Tests wall reached 30.87 °C, closer to the material surface temperature of 32.83 °C, with a difference of 1.96 °C, but at no point during the simulation did the dew point temperature exceed the surface temperature. In the PA WUFI wall, the dew point temperature reached 29.69 °C, and the surface temperature was 32.07 °C, with a difference of 2.38 °C. Similar to the PA Tests wall, at no point did the dew point temperature exceed the surface temperature.

The wall simulated with experimental data (PA Tests) showed a higher variation in relative humidity, along with higher temperatures in the summer and lower temperatures in the winter.

Indeed, the PA Tests wall exhibited a peak maximum temperature of 33.51 °C, higher than that found in the PA WUFI wall, which was 32.78 °C. The minimum temperature of the PA Tests wall was 10.76 °C, which was also higher than that of the PA WUFI wall, which was 8.47 °C, resulting in a difference of 2.29 °C. Relative humidity values showed a 0.61% difference, with the highest value in the PA Tests wall (96.78%) and the lowest in the PA WUFI wall (96.17%). It is important to emphasize that the ceramic brick from the database had a vapor resistance coefficient and water absorption coefficient 10 times higher than the experimental values. These differences may influence depending on the chosen construction system.

Figures 11 and 12 present the data for temperature, relative humidity, and dew point temperature on the internal surface of the simulated walls, focusing on the winter period. In both systems, the most critical relative humidity, with higher values, effectively occurred predominantly during the winter, coinciding with months of lower air temperatures and, thus, creating more favorable conditions for fungal growth.

Figure 10
Temperature, Relative Humidity, and Dew Point on the Internal Surface for the simulations using the PA WUFI

Figure 11
Temperature, Relative Humidity, and Dew Point on the Internal Surface for the simulations using the tested data (PA Tests) in the winter period

Figure 12
Temperature, Relative Humidity, and Dew Point on the Internal Surface for the simulations using the PA WUFI in the winter period

Probability of mold Growth

Figure 13 presents the risk of fungal formation for the PA WUFI construction system. The points represent the hygrothermal conditions on the external and internal surfaces of the wall at specific moments. The color indication shows the times when each point occurred during the simulation, with yellow corresponding to the beginning of the hygrothermal calculation, followed by various shades of green, and finally, black points representing the end of the calculation (Schmidt, 2019). The boundary curves (LIM B I and LIM B II) represent acceptable limits for different types of construction material.

The interior surface of the PA WUFI wall had the highest concentration of points ranging between 80% and 100% relative humidity. The system exhibited favorable conditions for fungal formation, especially during the intermediate and final periods of the simulation, when points were above the boundary curve (LIM B II), with relative humidity above 80% and internal temperature exceeding 20 °C.

Figure 14 presents the graphs related to the risk of fungal formation for the PA Tests wall. Both the external and internal surfaces displayed points with favorable conditions for filamentous fungal growth, particularly in the intermediate and final periods of the hygrothermal simulation, meaning points clustered above the boundary curve (LIM B II) with relative humidity above 80% and internal temperature exceeding 20 °C.

The point clouds related to the external surfaces of both systems showed relative humidity of up to 100%, indicating a favorable condition for fungal development, especially for the PA Tests wall.

Figure 13
Isopleths on the External and Internal Surfaces for the simulations using the PA WUFI

Figure 14
Isopleths on the External and Internal Surfaces for the simulations using experimental data (PA Tests)

Table 4
Mold Growth and Mold Index, WUFI Bio

Models	Mold Growth (mm/year)	Mold Index (MI)	WUFI Bio Review
PA Tests	399	4.565	Red: Not acceptable
PA WUFI	424	4.775	Red: Not acceptable

When assessed using the bio-hygrothermal model (WUFI Bio 4.0), both systems yielded unacceptable results for use, as shown in Table 4. Therefore, the surface of the innermost layer of the systems, in contact with the air, exhibited Mold Growth (mm) higher than 176 mm/year and Mold Index (MI) higher than 2, according to the WUFI Pro 6.5 manual (Schmidt, 2019). The assessment by the bio-hygrothermal model confirmed the significant fungal formation in both evaluated systems, also observed with the isopleths, Figure 13 and 14. Using international database values in this analysis led to a further increase in filamentous fungal growth.

Conclusions

This study evaluated the hygrothermal behavior of two masonry wall systems, considering different hygrothermal properties. One simulation scenario used data from the WUFI Pro 6.5 database, while the other incorporated values obtained through laboratory tests on a hollow ceramic brick. Building performance simulations were conducted using WUFI Pro 6.5 and EnergyPlus 9.0 software for Pelotas-RS, Brazil. The systems were assessed for the risk of vapor condensation and filamentous fungi formation on the internal surface of the facades.

From the test and simulation results, some differences were observed among the analyzed conditions. Regarding mold growth, there was a 3% difference when using the WUFI Pro 6.5 ceramic materials database (PA WUFI) compared to experimentally characterized ceramic material (PA Tests). However, both situations led to unacceptable mold growth results. Concerning the risk of surface condensation, a maximum difference of 2.29°C was observed between the simulated minimum temperature conditions, suggesting a more significant condensation potential when using experimental results.

An important limitation that may interfere with the simulation of the constructive performance of a homogeneous material is the presence of air layers inside the hollow ceramic brick model, as it can impact moisture transport. Experimental tests on the thermal properties of hollow bricks are suggested to further research the topic, as well as a study on the impact of internal climatic conditions on building performance simulation results. External climatic conditions in different areas of Brazil cannot be generalized; thus, simulations for other regions are suggested for data comparison. Additionally, experimental tests on the hygrothermal properties of materials from various Brazilian regions are recommended to create a national-level database.

This article reinforced that studies to characterize the hygrothermal properties of national building materials are paramount for understanding building performance and preventing moisture-related pathologies. In this sense, the knowledge gap filled by this research confirmed the relevance of hygrothermal studies for understanding moisture transport and showed that using European data can impact the results.

Acknowledgment

The authors acknowledge the financial support received from the Brazilian governmental agencies CAPES (“Fundação Coordenação de Aperfeiçoamento de Pessoal de Nível Superior”) and CNPq (“Conselho Nacional de Desenvolvimento Científico e Tecnológico”). The authors acknowledge the Laboratório de Materiais e Tecnologia do Ambiente Construído (LAMTAC/NORIE) from the Universidade Federal do Rio Grande do Sul (UFRGS).

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Edited by

• Editor:
  Enedir Ghisi

• Editora convidada:
  Kelen Dornelles

Publication Dates

• Publication in this collection
  07 Oct 2024
• Date of issue
  2024

History

• Received
  24 Jan 2024
• Accepted
  27 Apr 2024