Model to Improve Classrooms’ Visual Comfort Using Waste-Based Shading and Its Validation in Mediterranean Schools

Abstract

European non-residential buildings constructed before building energy codes consume more energy and resources than new buildings. Existing educational buildings comprise 17% of this outdated stock. These buildings can be retrofitted to create a conducive learning environment that can improve students’ comfort. The refurbishment of facades is a common solution to improve the energy performance of schools when the aim is to improve the daylighting comfort. This study develops a methodology to optimize facade renovation solutions including (1) preparation, (2) simulations of the simplified model using local shading, and (3) modeling a realistic optimized facade design. This study evaluates visual comfort by considering multiple-dimensional metrics such as useful daylight illuminance (UDI), annual sunlight exposure (ASE), illuminance uniformity, and the daylighting factor. The three parameters of the louvres on which this study focuses are the distance from the new facade to the exterior wall, the blade degrees, and slat spacing. The methodology was first applied to improve the facade proposal with reused roof tiles from the project Waste-based Intelligent Solar-control-devices for Envelope Refurbishment (WiSeR). The results illustrate that implementing these solutions efficiently improves the indoor visual comfort in the classroom while avoiding overheating issues. For a constant-gaps surface, a shading distribution with alternated gaps gives better results for the aforementioned light metrics. Specifically, the most suitable values are a 7 cm distance from the new shading system to the existing wall, slat degrees at 0, and louvre spacing at 21 cm.

1. Introduction

Human progress and development have led to environmental challenges such as air pollution, the warming of the planet, acidification of the oceans, and the urban heat island effect, among others [1]. In this context, the European Union faces three great challenges: (i) to lower greenhouse gas emissions [2]; (ii) to diminish the final energy consumption reached in the residential transport and energy industry sectors [3,4]; (iii) and to reduce the percentage of building and construction waste out of the total landfilled solid waste, which is almost half in many countries [5]. Therefore, in 2020, the circular economy action plan by the European commission was set to reduce pressure on natural resources and ensure less waste [6].

The construction industry is responsible for a high percentage, between 30 and 40% [7], of these environmental issues: over 40% of global energy use and 30% of global greenhouse gas emissions [8]. Within the European Union, almost 30% of buildings are over 50 years old, and 70% run at a lower energy efficiency [9]. Non-residential building stock that was constructed before the introduction of building energy codes and has a low building performance consumes more energy and resources than new buildings. Innovation in indoor thermal comfort is still lacking in such buildings [10].

Previous studies show that renovating the building envelope significantly enhances energy performance [11], reduces CO₂ emissions [12], and decreases energy consumption [13]. While the most effective approach combines envelope and heating system renovation [14], the high cost of heating upgrades makes facade refurbishment the preferred option. Facade improvements also lower dependency on heating and cooling, adapting to Spain’s diverse climates. Studies have highlighted the cost-effectiveness and sustainability of these upgrades, even exploring low-cost shading solutions for schools [15].

Educational buildings account for 17% of the aforementioned existing obsolete stock and require considerable costs for maintenance every year [16]. In Spain, the construction of schools underwent a boom period after direct state intervention in 1920 [17,18]. More than 41,000 schools are in use, constructed since the 1960s, and need urgent renovation regarding visual and thermal comfort to adapt to the new building codes [19]. Former studies within the research group have considered the cost of different solutions [20], as well as other sustainability requirements such as the environmental [21] and social requirements [22]. Some studies have even explored the possibility of developing low-cost solutions for the refurbishment of school shading systems [23]. Beyond these studies and energy implications [24], among others, the renovation of a building involves adapting it to the needs for which the building is intended. The educational building stock in Spain is obsolete not only in terms of energy consumption but also because it suffers from a lack of consideration for optimal orientations of natural light inputs, solar protection, glare and visual connection [25]. In this context, the refurbishment of schools could incorporate innovative solutions which contribute to the circular economy while achieving the new standards’ minimums of visual performance.

This is especially relevant in schools [24] because students spend more than 30% of their time inside schools. Also, based on technical literature, children are distinct from adults in metabolic rate and they have limited adaptive behavior [26]. The retrofitting of existing educational buildings could help to create a conducive educational environment that improves learning performance. Indoor thermal comfort and the infiltration rate enhance students’ attention and memory [27]. Furthermore, children are more sensitive to indoor environment than adolescents [28]. Thus, it is essential to consider both students’ and teaching teams’ adaptations to spaces for educational activities. In addition, logically, children’s visual perception has a huge influence on their comfort and health [29]. In the past 30 years, indoor environmental quality has been researched continuously worldwide. Studies have examined quality with and without windows [30], window size [31], the distribution of seats [32], the color temperature of classroom lighting [33], natural elements [34,35], types of lighting [36], visual preferences of children [37], and a structural model for visual comfort [38]. The openings of educational buildings depend on multiple factors [39], such as global environmental requirements, pedagogical movements, and specific standards for the educational building phase [40].

Regarding the above, the use of waste-based shading systems to reshape building waste into novel envelopes is a sustainable strategy for incorporating a circular economy in the construction sector [41]. Recycled building materials are beneficial for promoting the circular economy and a sustainable solution [23]. Recent evidence suggests that the industrial by-product gypsum could be recycled and reused in construction and building materials [42]. In addition, prefabricated panels with recycled PET materials could be seen as sustainable materials for construction [43]. Some researchers evaluated the feasibility of recycling waste slurry into building materials [5]. Another study indicates that recycled aggregate materials could replace natural aggregate, depending on the conditions, purpose, and engineering project [44]. Moreover, general construction and demolition waste (CDW) can be applied in the construction industry [45].

In this sense, the main research question of this paper is whether new shadings within the circular economy can create comfortable environments focusing on optimizing the visual aspects of learning. This research paper is framed within the project Waste-based Intelligent Solar-control-devices for Envelope Refurbishment (WiSeR, Abbreviations section presents the list of abbreviations used in this text) [46]. Thus, the objective of this research paper is to develop advanced shading devices built using recycled materials [15]. This research paper focuses on the daylighting behavior of the new shading devices; other parts of the project will focus on other crucial issues such as the devices’ energy and carbon emissions performance. The paper describes a novel method for optimizing the indoor visual comfort of shading devices in the refurbishment of school buildings. This method is validated by applying it to patterns of WiSeR shading solutions on a selected free-running school building facade. These solutions based on the circular economy concept could present serious technical and feasibility disadvantages. The present paper exclusively focuses on the daylight performance of these solutions. Therefore, this study relies on former projects regarding issues such as its durability, maintenance, and thermal and weather performance [47]. Furthermore, this study considers the aesthetic concerns [48], initial costs and technical expertise [15], and certification and regulation [49] of architectural solutions within the circular economy.

The sections of the paper are as follows. Section 2 explains the materials and methods, Section 3 presents and discusses the results, and Section 4 draws conclusions.

2. Methodology

This project presents a methodology with three phases as depicted in Figure 1.

The first phase starts with choosing the weather data, assessing parameters, and preparing the model. The second phase optimizes the model following a simplified approach and the third phase optimizes the model using a more realistic method. This research method moves from simplified to more complex and realistic, to achieve the research objectives.

2.1. First Phase: Preparation

The preparation phase has two main steps: (S1.1) the selection of weather data and evaluation parameters and (S1.2) the preparation of the model. The assessment parameters include the evaluation parameters for indoor visual comfort and daylight metrics. This study mainly follows UNE-EN 12464-1 [50], which establishes light and lighting at workplaces, serving as the standard for evaluating indoor visual comfort in the target classrooms. Furthermore, the information gathered from the CIBSE Lighting Guide (LG10-2014) [51] are used, given that it is the complementary standard related to daylighting factor in UNE-EN 12464-1 [50]. The model is prepared by defining the target building and then studying its energy performance. To achieve this, the tool DesignBuilder v8.9 [52] is used to obtain a general overview of the energy performance of the building, including temperature, solar gains, and daylight.

2.2. Second Phase: Simplification of the Optimization Model

The second phase applies louvres as local shading devices to explore and define the values of the parameters of louvres in indoor energy performance. This phase has the following steps: (S2.1) analysis of the parameters of the chosen shading alternative, (S2.2) analysis of the distance between the louvres and the facade, (S2.3) study of the angle of the blades, and (S2.4) study of the slat spacing. To conclude, this phase compares the simulation results of distinct values of the same type of parameter, while other parameters remain unchanged.

In Step S2.1, the basic parameters of the selected shading alternative are obtained, including the number of tiles, slat spacing, angle, length, and the distance from the new facade to the exterior wall. This step ensures that the simplified model parameters align with the actual model parameters.

In Step S.2.2, the distance from the facade to the louvres is analyzed and determined. This experiment, focusing on the distance between the louvres and the exterior wall, aims to assess how this spacing influences indoor daylighting and thermal performance in the selected classroom. As mentioned earlier, indoor illuminance levels are evaluated using data from the CIBSE Lighting Guide (LG10-2014), which serves as the reference standard for the daylighting factor. According to this guide, a daylighting factor below 2 indicates insufficient indoor lighting, while a factor above 5 suggests that artificial lighting is unnecessary but may lead to glare and overheating [51].

In Step S2.3, the blade angles are studied and determined through modeling and simulations at various louvre angles: 0°, 30°, 45°, and 60°, with selected slat spacing values. These angle values are chosen from the default range available for blinds, spanning from 0° to 60°.

Finally, Step S2.4 addresses the determination of slat spacing. Initially, various values of slat spacing are selected, resulting in a differing number of slats for each specified spacing. It is observed that wider spacing between the louvre blades necessitates a reduced number of blades, which is also applicable to the tile system. Subsequently, simulations are conducted for each corresponding scenario.

2.3. Third Phase: More Realistic Optimization

The primary objective of the third phase is to further optimize the design plan established in the preceding phase. This phase comprises three distinct steps. The first step involves determining the appropriate visual field, which serves as a foundation for subsequent design considerations. Given that the target users of the classroom are students aged 10 to 12 y.o. and their teachers, it is essential to investigate the average height of these two demographic groups. Furthermore, it is imperative to examine the height and width of the visual fields corresponding to the tile system for both groups in two positions: standing and sitting. The data gathered will facilitate the calculation of an average value that is representative of the general population. Based on this result, the authors will design a specialized version of the tile-system facade. In the second step, a selected classroom within the school is subjected to analysis. This process closely resembles that of the first step; however, a key distinction lies in the fact that the classroom analyses are grounded in real-world conditions. Specifically, the focus is on understanding how teachers and students engage in activities within the classroom and how different areas of the room are utilized. Upon completion of this analysis, two design patterns are proposed for the classroom. Finally, the last component involves simulating each design pattern and conducting a comparative analysis of the results.

Step S3.1 focuses on determining the appropriate visual field for the external view. As previously mentioned, this component primarily emphasizes indoor human activities. The rationale behind this focus is that the design of a classroom facade must take into account indoor illuminance and ensure a comfortable environment for reading and studying. Additionally, it is essential to consider the perspectives from which teachers and students observe the outside through windows, influenced by the spaces they occupy. To facilitate this investigation, the authors conducted a study on the average heights and visual fields of the users. This step also establishes the necessary visual dimensions. According to the Spanish standard UNE-EN 17037:2020+A1 [53], regarding daylight in buildings, the evaluation of the external view’s width is contingent upon the most distant point within the interior space and the width of the exterior facade situated between two interior walls.

Step S3.2 aims to optimize the facade following the actual conditions observed within the selected classroom. The primary objective of this segment is to enhance the facade design by integrating insights gained from the preceding visual field analysis. This optimization process is divided into three sub-steps: (1) an examination of classroom usage and occupancy patterns, (2) the formulation of conclusions regarding the visual field based on real-world conditions, and (3) the design of a revised tile system facade tailored to the classroom environment.

Finally, Step S3.3 encompasses the construction of full-scale models and the execution of simulations for each design pattern derived from the preceding steps. This phase aims to develop design models based on the refined design patterns associated with the selected shading alternatives. Subsequently, simulations regarding daylighting will be conducted using DesignBuilder v8.9 [52]. The resulting data will serve as comparative statistics, facilitating a comparison with that of the classroom lacking any local shading.

3. Results and Discussion

This section presents and discusses the results of the nine steps of the methodology previously presented in Figure 1, from S1.1 to S3.3.

3.1. First Step of the Preparation (S1.1)

In this step, climate data were collected using Spanish Weather for Energy Calculation (SWEC) files [54], to ensure the accuracy of the original data. This study chose the newer TMYx data with values from 2007 to 2021 [55]. This choice was made because this database provides a comprehensive representation of general weather conditions during the specified period and even indicates trends for future weather patterns. Utilizing this database to evaluate building performance allows the authors to obtain a holistic overview for assessing the impact of the newly designed facades on the existing building.

The adopted UNE-EN 12464-1 [50] standard specifies various requirements of lighting related to different types of educational premises. The standard for educational buildings was chosen as the reference criteria because the target building is a primary school. The illuminance that should be maintained in classrooms of general school buildings is 500 lux. However, the illuminance that should be maintained in classrooms of young children is 300 lux. Consequently, the authors define the acceptable range of maintained illuminance as being between 300 lux and 500 lux. Another metric referenced in the document is the Unified Glare Rating (UGR), which pertains to artificial lighting and is thus excluded from this study. Moreover, the adopted CIBSE Lighting Guide (LG10-2014) [51] stipulates that a daylighting factor below 2 indicates insufficient indoor lighting. If the daylighting factor exceeds 5, it indicates that artificial lighting is unnecessary; however, it may also lead to issues such as glare and overheating.

Due to the complexity of real-time daytime illuminance on the working plane, which fluctuates with seasonal variations and weather conditions, it is challenging to assess daylight illuminance using a singular metric. Consequently, this study introduces a multi-dimensional approach to evaluate the illuminance levels on the working plane without reliance on artificial lighting. It uses different parameters in each of the two aforementioned phases (see Figure 1). The second phase, which is the simplification of the optimization model, primarily studies the illuminance, daylighting factor, and illuminance uniformity considering the time-consuming factor. The third phase involves comparing the daylight illuminance levels on the working plane of the target classroom before and after the integration of the new facade design patterns. This analysis focuses on four key daylight metrics: useful daylight illuminance (UDI), annual sunlight exposure (ASE), illuminance uniformity, and the daylighting factor. Notably, UDI provides a general overview of the illuminance level of the target classrooms during the entire year [56], while the ASE describes the percentage of space that receives too much direct sunlight for 250 occupied hours per year to contribute to avoiding glare. Additionally, the daylighting factor functions as a supplementary parameter that reveals the direct distribution of daylight illuminance across the working plane.

3.2. Second Step of the Preparation (S1.2)

This project chose Bellvitge School as the target building because it is the real reference building for the cluster BCN.C2 [57]. Hence, it is the closest to the cluster centroid and was validated by checking the results against the annual energy consumption. By choosing this school, the results can be upscaled to the entire BCN.C2 cluster. Step S1.2, which involves the preparation of the model, conducts a year-long simulation using DesignBuilder v8.9 software to identify potential issues and evaluate design alternatives that may effectively address these challenges. According to previous studies [58], the school employs a central heating system utilizing water radiators, powered by natural gas, to maintain warmth during the winter months. However, there is no cooling system or mechanical ventilation available for the summer season. Domestic hot water is supplied to the kitchen, changing rooms, and throughout the entire third floor. Additionally, the window aperture operates at a 45-degree angle through a sliding mechanism, and natural ventilation is scheduled from 10 PM to 11 PM.

Table A1. Monthly environmental energy simulation results of temperature and solar gains.

Magnitude	Monthly
	January	February	March	April	May	Jun	July	August	September	October	November	December
Operative Temperature (°C)	15.84	17.08	17.98	18.78	21.03	24.83	27.64	26.54	25.61	23.89	19.96	16.44
Glazing (KWh)	−683.96	−619.44	−678.62	−273.85	−215.96	−135.96	−83.03	−82.27	−299.18	−612.28	−630.87	−515.66
Computer + Equip (KWh)	17.22	17.40	20.26	14.42	19.25	13.86	8.64	8.64	14.93	19.75	18.46	15.07
Internal Natural Vent. (KWh)	−30.01	−24.65	−13.62	5.66	14.44	14.89	18.33	12.85	5.34	−7.37	−24.22	−21.93
Walls (KWh)	−137.69	−149.69	−185.07	−103.63	−104.51	−64.06	−17.80	−16.78	−76.13	−136.25	−142.45	−111.85
Floors(int) (KWh)	−87.81	−88.74	−74.46	−28.90	−26.72	−17.12	−24.21	−24.08	−22.64	−58.36	−85.89	−57.27
Roofs (KWh)	−119.29	−112.04	−111.39	−27.95	−36.67	−0.83	28.75	10.28	−13.26	−64.13	−102.18	−72.37
Artificial Lighting (KWh)	3.35	1.49	0.76	0.00	0.00	0.00	0.00	0.00	0.00	0.43	5.03	3.00
Solar Gains (KWh)	583.76	563.17	613.06	259.45	279.09	176.62	45.52	54.02	288.56	586.49	546.29	411.77

in Appendix A shows the monthly temperature and heat gains of Bellvitge School to date.

This project focuses on the classroom of Bellvitge School with the worst performance, according to the teaching team. This classroom is on the third floor facing south. Figure 2 shows the classroom location (Figure 2a), the interior view (Figure 2b), and the floor plan (Figure 2c).

Table 1. Evaluation of daylight metrics on the working plane of the studied classroom.

UDI100–2000 lux Area Percentage		ASE Area	Average Illuminance (lux)	Daylighting Factor (max)	Daylighting Factor (min)	Illuminance Uniformity (min/max)
50% Wt	80% Wt
57%	7%	31.58%	484	14.48	1.351	0.093

Legend: Wt means working time, which is from 9.00 to 16.30 in the Bellvitge School [59].

depicts the current lighting performance of the studied classroom.

Figure 3 and Figure 4, which illustrate the distribution of useful daylight illuminance (UDI) hours and the daylighting factor, respectively, demonstrate a generally similar trend. Researchers noticed that the area surrounding the glazing on the playground side receives significant direct sunlight, resulting in high daylighting factors that correspond to fewer UDI hours annually. Moreover, the optimal UDI hours are concentrated in the middle area of the working plane. In sum, while the classroom achieves adequate illuminance on the working plane, challenges such as glare, excessive solar gains, and overheating remain. These factors have been integrated into the development of simulation models aimed at providing user-centered solutions.

3.3. Study of the Parameters of the Alternative “Roof to Facade” (S.2.1)

Before using the local shading installed in DesignBuilder v8.9 to determine the proper parameters for the following optimization, it is crucial to investigate the original metrics of the chosen shading alternative. This is the “Roof to Facade” proposal, because it was the most sustainable waste-based alternative for the case study [15]. According to the design [48], the distance from the facade to the alternative is 5 cm, the angles of the tiles are 0 degrees with concave faces down to the ground, and the slat spacing between two tiles is 21 cm. In addition to these metrics, the width of the tiles is 5 cm.

3.4. Distance from the Louvres to the Exterior Wall (S.2.2)

According to the practical operability and cost calculations [39], three values were selected: 5 cm, 7 cm, and 10 cm, as illustrated in Figure 5.

Under the conditions of keeping other parameters unchanged and similar to the original design (“Roof to Facade”), the authors simulated the daylighting and thermal performance of the classroom with blinds at these three distances. Subsequently, all the results were compared with those of the simulation of the classroom without louvres. Notably, the distance for the original design of “Roof to Facade” is 5 cm. Moreover, 7 cm is the limit for using the previous hanging material, and 10 cm means switching to a longer hanging material, which might increase the cost calculations [48].

Furthermore, Figure 6 presents the simulation outcomes of Step 2.2 (see Figure 1) conducted by DesignBuilder v8.9, detailing the indoor daylight factor, solar gains through windows, and operative temperature within the classroom, both before and after the incorporation of blinds. In particular, the figure highlights how these parameters vary according to the different distances maintained between the facade and the blinds. In addition, Figure 6 reveals that these blinds could dramatically decrease the maximum indoor daylighting factor and control the average indoor factor in a reasonable range. Compared to the maximum indoor daylight factor of 14.482 observed in the classroom without louvres, the implementation of louvres at various distances to the exterior wall significantly reduced this maximum value. Specifically, the maximum daylight factor decreased to 4.265 with 5 cm from louvres to facade, 4.454 with 7 cm from louvres to facade, and 4.315 with 10 cm from louvres to facade. Furthermore, the data indicated that the average indoor daylight factor for the classroom with blinds installed remained within acceptable limits across all three louvre distances. The classroom with blinds installed at 10 cm had the highest average daylighting factor of 2.110, compared to 2.067 at 5 cm and 2.081 at 7 cm. The findings further indicate that the use of louvres notably reduced solar gains through exterior windows, as well as indoor operative temperatures, in comparison to the scenario without any form of local shading. The mean score for reduced solar gains was 23.71 kW. Nevertheless, the variations in results for classrooms equipped with louvres at different distances from the exterior wall were negligible. As illustrated in Figure 6, only a slight difference was observed between the scenario without blinds and the scenario with louvres.

Based on the simulation results from the first experiment (see

Table 2. Daylighting factor results related to distance from the louvres to the exterior wall.

Daylighting Data	Distance from the Louvres to the Exterior Wall
	No Blinds	5 cm	7 cm	10 cm
Average daylighting factor	4.838	2.067	2.081	2.110
Maximum daylighting factor	14.482	4.265	4.454	4.315
Illuminance uniformity (min/max)	0.093	0.177	0.148	0.185

Legend: Underlined values do not meet standards (CIBSE).

), this project concludes that the addition of blinds at varying distances from the exterior wall can influence indoor illuminance, operative temperature, and solar gains through the windows. In this instance, the effects on the operative temperature and solar gains show minimal variation across the three proposed configurations. Consequently, it is appropriate to compare the daylight illuminance, daylighting factor, and uniformity to determine the optimal value according to specific needs. The simulation results indicated that the classroom with louvres positioned 10 cm from the exterior wall achieved a higher average daylight illuminance level compared to the configurations at 5 cm and 7 cm, particularly in terms of the daylighting factor and illuminance uniformity. Although the 10 cm-spaced louvres demonstrated a slightly superior performance in the average daylighting factor, the difference between the 10 cm and 7 cm configurations was minimal. Therefore, a 7 cm distance from the new facade to the exterior wall was selected.

Figure 7 and Figure 8 show the illuminance of the classroom with the shading devices separated 7 cm from the facade plane. This distribution is similar to the cases of separating shading by 5 and 10 cm [39]. Therefore, the illuminance study did not alter the performance of the three distances and 7 cm was chosen for the following steps.

3.5. Angle of Blades (S2.3)

A statistical analysis of the data indicated that variations in the angle of the blinds significantly affect indoor illumination and solar gains from exterior windows, while the impact on the indoor operative temperature is less pronounced. It is notable that the results demonstrate that the blinds’ effectiveness in reducing solar radiation increases according to the angle of the blades. A key finding of this experiment was that louvres positioned at 0 degrees exhibit the best energy performance in terms of the daylighting factor. These louvres not only provide an acceptable average daylighting level but also maintain the maximum daylighting factor below 5, effectively mitigating glare issues within the classroom. In contrast, simulation results for classrooms equipped with louvres at other blade angles (15°, 30°, 45°, and 60°) indicate that, while they succeeded in reducing solar gains, they are unable to meet the average indoor illuminance standards.

Table 3. Daylighting metrics in June with specific angles of blades.

Daylighting Data	Angle of Blades
	No Blinds	0°	15°	30°	45°	60°
Average daylighting factor	4.838	2.081	1.399	0.955	0.683	0.462
Maximum daylighting factor	14.482	4.454	2.809	1.973	1.374	1.081
Uniformity (min/max)	0.093	0.148	0.217	0.195	0.206	0.172

Legend: Underlined values do not meet the standards (CIBSE).

and

Table 4. Temperature and heat gains in June with specific angles of blades.

Temperature and Heat Gains	Angle of Blades
	No Blinds	0°	15°	30°	45°	60°
Operative temperature (°C)	24.83	24.76	24.74	24.73	24.74	24.71
Solar gains (kWh)	176.62	152.49	142.52	134.59	128.71	124.75

present the building performance metrics concerning temperature, heat gain, and indoor illuminance for classrooms with louvres installed at various blade angles. To sum up, taking into account indoor illuminance and solar gains, louvres positioned at 0 degrees represent an effective solution for achieving adequate indoor illuminance while minimizing glare and overheating issues. These results are aligned with related former studies [60].

3.6. Slat Spacing (S2.4)

In light of the existing window dimensions, three specific values of slat spacing were chosen, each corresponding to a different number of slats: nine slats at 15 cm, eight slats at 17 cm, and seven slats at 21 cm. The results of this experiment (see

Table 5. Temperature and heat gains in June with specific slat spacing.

Temperature and Heat Gains	Slat Spacing of Louvres
	No Blinds	15 cm	17 cm	21 cm
Operative temperature (°C)	24.83	24.76	24.76	24.76
Solar gains (kWh)	176.62	148.18	149.94	152.49

) demonstrated the relationship between the slat spacing of the louvres and indoor energy performance.

Table 5 and

Table 6. Daylighting factor in June with specific slat spacing.

Daylighting Data	Slat Spacing
	No Blinds	15 cm	17 cm	21 cm
Average daylighting factor	4.838	1.440	1.688	2.081
Maximum daylighting factor	14.482	2.653	3.171	4.454
Illuminance uniformity (min/max)	0.093	0.192	0.175	0.148

Legend: Underlined values do not meet standards (CIBSE).

demonstrate that louvres with slat spacing of 15 cm, 17 cm, and 21 cm significantly impact indoor operative temperature, solar gains, and indoor illuminance when compared to the classroom without louvres. Nevertheless, blinds with varying slat spacing produced different effects on the indoor thermal environment parameters. Indoor illumination was the most affected parameter, followed by solar gains, with operative temperature experiencing the least impact.

The experiment reveals that a slat spacing of 21 cm meets the standard requirements for indoor illuminance, achieving an average daylighting factor of 2.08. Additionally, the maximum daylighting factor for louvres with this spacing reached 4.45. The data consistently indicate a trend wherein increasing slat spacing correlated with higher solar gains from exterior windows. Statistical test results suggest that louvres with a slat spacing of 21 cm effectively provide satisfactory indoor thermal performance and illuminance simultaneously.

3.7. Determining the Visual Dimensions (S3.1)

A prior study on the heights of Spanish schoolchildren found that the mean height of girls aged 10 to 12 is 147 cm, while that of boys in the same age range is 146 cm [61], as depicted in Figure 9. Moreover, male teachers have an average height of 176 cm, while female teachers have an average height of 162 cm [62]. Thus, four situations may occur depending on the type of use and user: sitting and standing positions for adults and children. As a result, a preliminary visual field is established, allowing users to maintain good visual contact with the exterior from a standard room.

In the selected classroom, the distance between the most remote point of the utilized area of the interior space and the facade is 5.65 m, and the width of the exterior facade between two interior walls is 9.40 m. As a result, the width view for each opening is roughly 2.20 m (see Figure 10). In addition, the total dimensions of the view openings must be at least 1.0 m by 1.25 m, equating to a minimum area of 1.25 square meters [53].

The optimized facade is designed to enhance indoor visual comfort while providing an appropriate visual field for both teachers and students. This analysis aims to establish a visual field that allows individuals of varying ages in a typical classroom to achieve a clear view through the gap area in four specific scenarios (see Figure 11). Figure 11 illustrates the depth of the gap area within the recycled tile system facade under various conditions, with measurements recorded as 390 mm for standing students, 400 mm for seated students, 420 mm for standing teachers, and 300 mm for seated teachers. In addition, Figure 12 provides a consolidated summary of these gap depths across the four scenarios, namely seated students, standing students, seated teachers, and standing teachers. As presented in Figure 12, the total vertical span of the window area measures 1310 mm, where the base point at 0 mm represents the lowest boundary of the window area, while the top point at 1310 mm indicates its highest position along the vertical axis. To satisfy all the situations, 420 mm was selected for the depth of the gap area of the recycled tile system facade for the following design. To facilitate the design process, the recycled tile system was considered to be a huge grid with rectangles of 210 mm × 510 mm, as presented in Figure A1 in Appendix B.

3.8. Results of Design Patterns for the Selected Classroom (S3.2)

This step focuses on optimizing the facade by incorporating the results from the previous visual field analyses into the design of the selected classroom type. The following subsections present the results from the aforementioned three sub-steps.

3.8.1. Space and Occupancy (SS3.2.1) and Visual Field (SS3.2.2)

In the school, a typical traditional classroom is divided into spaces for two main uses: one for sending a message (mostly used by a teacher) and the other for receiving it (mostly used by students). In general, the three windows align with the three sections of the interior spaces (see Figure 13a). Consequently, the primary objective is to analyze three subsections for each zone (see Figure 13b–d) in order to identify the optimal gap width for the new facade (see Figure 14).

3.8.2. Design Proposal for the Classroom (SS3.2.3)

Considering a classroom’s frequent usage, two types of tile-system facades have been developed and modeled based on the analysis detailed below (see Figure 15 and Figure A2 in Appendix C). One design features a continuous gap, while the other employs a staggered-gap system. An important consideration is that the total surface area of the gaps is 3.21 square meters, with a width of 2.60 m for each opening. Both measurements comply with the requirements of the Spanish standard UNE-EN 17037:2020+A1, which specifies a minimum area of 1.25 square meters and a width of 2.20 m, respectively [53].

3.9. Simulation Results of the Optimized Project for the Selected Classroom (S3.3)

Table 7. Indoor energy performance of both designs and the classroom without shading.

	Indoor Energy Performance
	Operative Temperature June (°C)	Operative Temperature January (°C)	Solar Gains June (kWh)	Solar Gains January (kWh)	Average Daylighting Factor	Maximum Daylighting Factor	Illuminance Uniformity (min/max)
Design 1	24.74	14.36	156.95	378.65	2.392	5.744	0.146
Design 2	24.74	14.42	157.31	394.18	2.384	4.775	0.156
No shading	24.83	15.13	170.38	570.90	5.032	14.630	0.096

Legend: Underlined values do not meet standards.

presents the simulation results for the indoor energy performance of the selected classroom, incorporating designs 1 and 2, which are based on an analysis of the visual comfort field related to user characteristics and behaviors. Regarding the operative temperature in June and January, the difference between the two designs is less than 1 °C. However, the variation in solar gains from exterior windows is more pronounced. For instance, tile-system design 2 efficiently reduces solar gains from 170.38 kWh to 157.31 kWh in June, while design 1 lowers solar gains from 170.38 kWh to 156.95 kWh. In January, solar gains for the classroom with design 2 decreased from 570.90 kWh to 394.18 kWh, whereas design 1 decreased to 378.65 kWh. This indicates that design 2 is more advantageous for winter heating. In addition, both designs maintain the average daylighting factor within an acceptable range. However, design 1 includes some values exceeding 5, which may lead to overheating issues in summer. In contrast, the results show that design 2 performs well in terms of the daylighting factor, with its maximum value controlled at 4.775.

As expected, the illuminance uniformity was greater in design 2 than in design 1, which had better evenness.

As presented in the state scatter graphs (see Figure 16 and Figure 17), the majority of the illuminance values for design 1 are concentrated between 150 lux and 300 lux, while those for design 2 are concentrated between 150 lux and 250 lux. In addition, the highest illuminance value is centered on the area close to the outside window in both designs of facade patterns. Moreover, the simulations illustrate that the distribution of illuminance in the working plane is closely connected to the design gap of the plan. In the plots for design 1, the maximum illuminance decreased gradually from the teacher’s area to the student’s area. Regarding the illuminance, both designs have a similar performance, although design 1 has a slightly wider area of over 500 lux. This difference could imply glare issues or additional energy savings, considering CIBSE [51]. However, it would satisfy Spanish standards [53].

The percentage of useful daylight illuminance area results (see

Table 8. Results of UDI, ASE, and average illuminance.

	UDI Area Percentage		ASE Area	Average Illuminance (lux)
	50% Wt	80% Wt
Design 1	97%	33%	7.80%	239
Design 2	97%	33%	9.44%	238
No shading	51%	4%	32.85%	503

Legend: Wt means working time.

) reveals a substantial increase from 51% to 97% for both designs in comparison to the classroom without shading integration. It is clear that the use of shades enhances the visual conditions throughout the day, with a higher and uniform distribution of satisfactory time, corroborated by the state scatter graphs of useful daylight illuminance (UDI) hours presented in Figure 15 and Figure 16. In addition, the distribution of UDI hours of both designs, presented in Figure A3 and Figure A4 in Appendix D, is confirmed. Both designs can efficiently decrease the percentage of areas with unmet requirements in a decent range to below 10%. These designs show only a minimum of 1.64% regarding ASE, as depicted in Table 8.

To sum up, both designs improve the UDI hours similarly and reduce the ASE area for which requirements are not met to below 10%, within a decent range. However, design 2 performs slightly better, primarily concerning the daylighting factor, levels of solar gains, and distribution of illuminance. However, artificial lighting will be required according to Spanish standards [53].

3.10. General Discussion

This research project exclusively focuses on the daylight performance of the analyzed alternatives, which are waste-based and, therefore, could have important technical and feasibility weaknesses. Hence, as has been introduced in Section 1, this paper relies on former research papers regarding issues such as its durability and maintenance, among others [47].

The objectives and parameters used in this study are in line with those in [63,64], but there is a difference in the view analysis evaluation.

Section 3 shows that waste-based shading devices improve the daylight comfort of classrooms because they can efficiently decrease the average daylight factor of the working plane to within an acceptable range, while reducing glare and overheating problems. In addition, the study shows that the useful daylight illuminance area could also improve by up to 97% considering a 50% working time. This reinforces previous studies that analyzed other shading methods [65].

The difference between designs 1 and 2 is less than it would be if all the gaps in pattern 2 were at the lowest level. However, the distribution of the gaps follows the visual field of the occupant of each sector, including that of the teacher and the children.

The installation of this blinds-based shading system is likely to reduce solar gains in winter, which may lead to increased energy consumption for heating. According to previous related studies [15], this increase is relatively low. For example, for Bellvitge School it is approximately 1% or 1500 kWh/year. This issue could be addressed by incorporating movable shading solutions, as indicated in prior related research.

4. Conclusions

The application of the proposed methodology was successfully validated for the specific case study. Therefore, it is expected to be applicable to other cases, considering the characteristics of each classroom and school. The findings highlight the viability of designing waste-based facades by taking into account indoor illuminance and daylighting levels.

The results show that an optimized tile facade system can significantly enhance the indoor visual comfort of the selected classroom and mitigate overheating problems, effectively addressing the initial research question.

Based on the simplified model and the analyses of the three relative parameters of the louvres, the most appropriate parameters for the realistic model and simulation are a distance of 7 cm from the new facade to the exterior wall, blade angles set at 0 degrees, and a slat spacing of 21 cm. Specifically, the details are as follows:

• Louvres installed in classrooms at a distance of 5 to 10 cm from the exterior wall can effectively limit incident solar light while maintaining consistent parameters for the louvres (blade angle and slat spacing). Although variations in blade angles and slat spacing have a minimal effect on the operative temperature, these variations do impact the radiant temperature to some extent.
• For louvres with blade angles ranging from 0 to 60 degrees, the ability of the shading devices to block light and solar radiation increases non-linearly as the angle of the blades rises. At a distance of 7 cm from the wall and a vertical spacing of 21 cm, maintaining the blades at an angle of 0 degrees optimally satisfies the requirements for comfortable indoor illuminance while effectively preventing overheating and glare.
• Louvres with a slat spacing ranging from 16 cm to 21 cm have a minimal impact on the operative temperature when other parameters remain unchanged (distance from louvres to the exterior wall and blade angle). Increasing the number of blades beyond seven may result in inadequate indoor daylighting while keeping the other parameters consistent, as observed in the initial assessment of the shading device project. Therefore, a slat spacing of 21 cm is deemed suitable for the realistic model.

A comparison of the simulation results shows that both patterns offer similar improvements in the UDI hours and contribute to greater evenness of the distribution. Nevertheless, design 2, with staggered gaps, performs better in the daylighting factor, solar gains, and uniformity.

In consequence, future studies should include the validation of the relationship between the design of gaps in a shading system and indoor comfort, including the distribution of indoor illuminance, daylight factor, and ASE areas. Next steps also include incorporating the modeling and simulation of further optimized facade design materials and colors of the shading. Moreover, an investigation of the indoor ventilation and an improvement in it under different designs of roof-tile facades is also expected in the future. Both the aforementioned achievements and the future research steps aim to improve the indoor comfortable illuminance and provide a better visual field for the users. Furthermore, other parts of the project are integrating these conclusions, from studies focusing on daylighting behavior to others focusing on carbon emissions and energy consumption that also affect the classroom and school performance and comfort.