Influence of the Geometric Shape of the Courtyard of Traditional Wooden Folk Houses on the Lighting Performance of Their Central Room: A Case Study of the Traditional Folk Houses of the Tujia People in Western Hunan, China

Abstract

Although traditional Chinese wooden residential buildings have historically adapted to their respective regions, they face challenges in meeting modern living standards, particularly with regard to insufficient indoor natural lighting. This study focuses on three representative Tujia residences: the “L-shaped” dwellings, the “U-shaped” dwellings, and the courtyard residences, with the aim of improving their indoor lighting performance. Using Ecotect 2011 software for computer simulations, the study investigates the impact of altering the geometric shapes of courtyards in traditional wooden residential buildings on the lighting of the central room. The results indicate that, for the “L-shaped” dwellings, the geometric dimensions of the courtyard have little impact on the lighting of the central room. For the “U-shaped” dwellings, the optimal courtyard geometry is achieved with a well index (WI) of 1, balancing residential functionality, economic considerations, and indoor lighting performance. Regarding the courtyard residences, the best results are obtained by minimizing the building height while maximizing the well depth index to 1. Additionally, the study shows that a square layout of 90° ∗ 90° is most favorable for courtyards, effectively balancing lighting performance, functionality, and aesthetics. These findings provide valuable insights for the renovation of existing traditional residences and the design of new buildings, aiming to enhance overall indoor lighting effectiveness.

1. Introduction

As China’s population continues to grow and the process of urbanization rapidly advances, the demand for improved building standards in rural areas has become increasingly prominent [1,2,3,4]. However, while this development trend enhances living conditions, it also encroaches upon traditional rural landscapes, and the migration of urban populations has led to a significant decrease in rural populations [5,6,7,8]. These changes have prompted the Chinese government to actively implement a series of policies focused on rural revitalization. In this context, the necessity of studying Chinese rural settlements becomes particularly important [9,10,11,12].

As an important form of tangible cultural heritage, traditional dwellings possess significant value. The Xiangxi region is renowned for its rich historical and cultural heritage, with various ethnic groups’ traditional dwellings exhibiting distinctive architectural styles [13,14,15]. These dwellings differ from the conventional wooden structures of traditional Chinese architecture, forming a crucial part of cultural heritage. However, despite their historical and cultural significance, these ethnic traditional dwellings have been gradually neglected amid the decline of traditional villages, and their living environments have not been adequately addressed [16,17,18]. Indoor lighting is crucial for the livability of buildings, directly impacting residents’ quality of life. Insufficient natural light or abnormal light spectra indoors are associated with various health issues. The problem of inadequate natural lighting is particularly prominent in traditional dwellings in the Xiangxi region. Addressing this issue can not only improve living conditions but also align with the broader goals of rural revitalization. Therefore, this study conducts an in-depth analysis of the lighting performance of traditional Tujia dwellings in China, providing valuable insights for the renovation of existing traditional dwellings and the design of new buildings, aiming to enhance overall indoor lighting conditions.

2. Literature Review

Many scholars have conducted in-depth research on indoor lighting environments. Some scholars have focused on the establishment and optimization of lighting evaluation standards, aiming to create a scientific and rational assessment system. Silva and colleagues have proposed a new simple tool for assessing the energy efficiency of street lighting design. Three indicators were developed: one for assessing lighting performance and the other two for assessing energy performance. These indicators were quantified and combined through weighting and aggregation procedures to form a comprehensive score for street lighting design. The assessment tool was applied to a business park located in Viana do Castelo, Portugal, and the results were discussed [19]. Marc and colleagues investigated the optimization of industrial production area lighting by employing remote microcontroller commands for lighting sources. The primary achievement was lighting optimization aimed at achieving uniform light flux over the working surface with minimal energy consumption through individual or group commands of lighting sources, dependent on the measurement of lighting level [20]. Hao et al. analyzed the impact of LED lamp arrangement on the uniformity of illumination in indoor visible light communication (VLC) systems. They proposed a method based on the Multiple Input/Multiple Output (MIMO) system model, taking first-order reflection into consideration, to accurately analyze the arrangement of LED lamps for optimal performance. The study demonstrated that, under the optimal arrangement, the uniformity of illumination is improve [21]. Petrinska et al. introduced a lighting control system based on an evolutionary optimization algorithm. The operation of this system is optimized using a genetic algorithm, aiming to maximize the utilization of natural daylight and minimize the need for supplementary artificial lighting. Additionally, the lighting control system is designed to satisfy both energy efficiency and user satisfaction considerations [22]. Wang et al. proposed a method for intelligent illuminance control in a dimmable LED lighting system. By utilizing a quantified human perception model to optimize the distribution of illuminance in indoor environments, it is possible to enhance energy efficiency while ensuring comfort. The research findings reveal that despite the dimmable nature of LED lights, achieving both comfort and energy efficiency in large-scale lighting systems remains challenging [23]. Scholars such as Li proposed a light source layout optimization strategy based on an improved artificial bee colony algorithm. By analyzing the indoor space lighting model, they derived expressions for light source output and illuminance on the target plane. To enhance the algorithm’s search capability in specific areas, the study combined the artificial bee colony algorithm and proposed an improved version suitable for indoor lighting optimization [24]. Stankovic et al. analyzed and compared the lighting design criteria in the three major international green building certification systems, LEED, BREEAM, and CASBEE, and proposed guidelines for applying these standards to Serbian building practice [25].

Other scholars have explored methods to improve indoor lighting through technological means, striving to enhance the lighting efficiency of buildings. Lee et al. studied the development of a dimming lighting control system using general illumination and location-awareness technology. By integrating general illumination and dimming technology, combined with location-based lighting control technology, the system can optimize indoor illuminance distribution, thereby reducing energy consumption and improving lighting efficiency [26]. Taleb and colleagues selected a real office building in Dubai as a case study. They used Integrated Environmental Solutions (IES) simulation software and validated it by calibrating the actual measurements of air temperature and illuminance against the predicted readings. The simulation assessed the performance of various strategies, including krypton-filled and xenon-filled double glazing, reflective coating glazing, photovoltaic glazing, and white-coated glazing [27]. Albatayneh et al. studied the impact of advancements in LED lighting technology on the optimum window-to-wall ratio of residential buildings in Jordan. The study results showed that, due to the high energy efficiency of light-emitting diode (LED) luminaires, power consumption for lighting purposes can be reduced even when the lighting system is operating at full power. LED lighting technology can significantly save energy [28]. Chen et al. studied methods for improving the energy efficiency of indoor lighting systems based on computer vision technology, utilizing real-time video streams to achieve intelligent control of the lighting system, thereby enhancing energy efficiency [29]. Katunský et al. assessed the indoor environmental quality of industrial halls by analyzing the physical parameters of indoor lighting in large industrial halls during the winter and summer periods through in situ measurements and computational methods [30]. Chew et al. explored the development and future direction of smart lighting systems. The study results indicate that smart lighting systems, as an evolution of traditional lighting control, are important due to the introduction of autonomous operation and data-driven control methods [31].

Additionally, some researchers have studied the lighting characteristics of different types of buildings in detail, providing theoretical support and practical guidance for lighting design across various building types. These studies collectively advance the field of indoor lighting, laying a solid foundation for improving building environments and enhancing the quality of living. Gassar et al. pointed out that optimizing building performance at the early design stage is an effective approach to achieving sustainable design goals. The study covers various types of buildings, including office buildings, residential buildings, schools, and hospitals [32]. Boyce et al. explored the history and evolution of indoor lighting standards. The paper covers building types such as office buildings, schools, hospitals, and residential buildings [33]. Heschong et al. conducted a study on the impact of daylighting on human performance in schools. The results showed a statistically significant relationship between daylighting and student performance [34]. Krüger et al. analyzed the daylighting conditions in classrooms of a public school in Curitiba, Brazil. The results indicated significant differences in daylighting levels depending on the building’s orientation [35]. Li et al. studied the daylighting performance and energy-saving effects in office buildings in Hong Kong. They found that the daylighting performance in the perimeter areas was significant [36]. Sahar Diab et al. analyzed the indoor daylight quality in the pediatric ward of Jordan University Hospital. They proposed improvements to enhance visual comfort within the patient rooms [37]. Lam et al. used computer simulations to evaluate the daylighting and solar heat in a commercial office building in Hong Kong. They proposed a simple assessment tool suitable for the design stage [38]. Pellegrino et al. conducted a parametric study in Turin, Italy, to evaluate the impact of daylighting on total energy consumption in offices with different architectural features. The results showed that optimizing daylighting can significantly reduce energy consumption [39]. Husini et al. studied the impact of daylight fluctuations and illuminance levels on visual comfort in office buildings. They proposed design optimization recommendations [40].

Previous scholarly efforts have delved into the indoor light environments of traditional homes. For instance, Mariem et al. studied the “dig pit houses” and found that when the WI (well index) = 0.5, the size of the interior courtyard leads to better interior lighting performance, and that increasing the number of wall surfaces on the courtyard surface tends to produce a significant improvement in room lighting [41]. Gao et al. explored key design parameters of patio space in Huizhou Traditional Dwellings, guiding renovations and new designs while maintaining spatial character [42]. Sui et al. systematically evaluated the daylighting performance of Skywell Dwellings in Xingxian Village [43]. Nocera and colleagues explored the daylight performance of classrooms in a historical school building located in Siracusa, Sicily, Italy. The study used Radiance software for simulations, employing Climate-Based Daylight Modelling (CBDM) to assess and improve visual comfort in classrooms. They proposed several technological solutions to enhance daylight quality while respecting the cultural value of the building [44]. Anubrata Mondal and colleagues introduced a method to implement interior lighting design using modern and energy-efficient lamps in Jorasanko Thakurbari, a cultural heritage building with over 200 years of history located in Kolkata. The study emphasized the importance of maintaining internal and external architectural lighting characteristics while preserving cultural heritage. The design plans were simulated and optimized using DIALux-Lighting software [45]. Balocco and colleagues introduced a natural light design method for historical buildings, specifically applied to the Palagio di Parte Guelfa library in Florence. The design utilized solar radiation control and advanced daylight systems, including two light shelves, a skylight, and two light pipes, to improve lighting without altering the building’s structure [46].

Moreover, numerous researchers have conducted in-depth studies on how geometric factors of houses affect indoor lighting. M. Omrani et al. pointed out that, by adjusting the length, width, and height of the courtyard, the natural lighting level of underground pit dwellings can be effectively improved, thereby enhancing the quality of the living environment [41]. Ruijing Gao et al. explored the improvement of indoor lighting quality by optimizing the courtyard design of Huizhou traditional dwellings. The study results showed that lowering the window edge height can improve the lighting effect near the window, and increasing the window width and courtyard width can enhance the overall lighting quality of the room [42]. Meng Zhen et al. explored the optimization of natural lighting in residential buildings by changing the length, width, and height of houses through simulation analysis. The study used DIALux software to analyze important factors affecting natural lighting in the residential area of Xi’an, such as latitude, date, window position, building aspect ratio, building height, and window area [47]. Ehsan Sorooshnia et al. conducted a study from the perspective of different orientations, exploring the improvement of indoor lighting effects in Sydney dwellings by optimizing window configurations while balancing energy savings and visual comfort. The study employed the NSGA-II multi-objective optimization method, testing windows with different orientations, and performed simulation analyses on visual and thermal comfort, energy usage, and outdoor views [48]. Michael, et al. proposed and evaluated an integrated adaptive system consisting of individual movable modules for the improvement of indoor environmental conditions. The system was assessed through natural lighting analysis simulations using Ecotect and Desktop Radiance. The analysis indicated that, under appropriate geometrical configurations, the system could significantly improve the uniformity and comfort of indoor lighting while simultaneously reducing issues of glare [49]. These studies indicate that the geometric dimensions of a house (L, W, H) have a significant impact on lighting effects in architectural design. Optimizing these factors can greatly improve indoor lighting conditions, thereby enhancing living comfort and visual experience.

Existing studies primarily scrutinize urban modern buildings [50,51,52,53,54] and limited attention has been given to the daylighting performance of traditional wood-frame dwellings’ interiors. Moreover, contemporary research on traditional houses focuses predominantly on external windows [55] and internal patios [42], while relatively little research has been conducted on the effects of traditional wood-framed residential courtyards on interior light performance. However, the external environment has an impact on the internal lighting of a building [56]. Consequently, this paper introduces a novel perspective by investigating the influence of the geometry and angle of external courtyards on the interior lighting of traditional wooden houses among the Tujia people in western Hunan. The study reveals that these spontaneously constructed houses, lacking guidance from current standards and neglecting indoor lighting considerations, fail to meet visual experience and mental health needs. Consequently, a scientific analysis of the current lighting situation in traditional houses is essential, accompanied by region-specific optimization strategies.

3. Method

3.1. Study Area and Object

The Tujia people, one of the major ethnic minorities in southwestern China, have historically inhabited the Xiangxi region, where they are the most widely distributed and populous minority. They are mainly concentrated in the northern part of the Wuling Mountains, between the Qingjiang and You rivers. The value of traditional village dwellings primarily lies in the authenticity of their architectural forms and materials [57]. Tujia traditional architecture predominantly uses wood as the primary material, characterized by robust and durable structures, stilted buildings, moonbeams, and exquisite decorations. These features exhibit significant architectural heritage value. The preservation of these traditional elements has rendered them an important tangible cultural heritage, with high research value. Located in Fenghuang County, Xiangxi, Hunan Province, Naqiu Village is a notable traditional Tujia village that retains many traditional Tujia dwellings, offering substantial research value. This village is situated 44 km southeast of Yongshun County and is currently managed by the Naqiu Village Committee of Gaoping Township. It is a natural village located approximately 12 km from the township government seat, with geographic coordinates of 109°54′53.3″ E longitude and 28°48′27.2″ N latitude. The village covers an area of about 11,000 square meters. The entire village consists of 46 households, with a total population of approximately 290 people, of which more than 100 are permanent residents. All residents are Tujia ethnic people, predominantly with the surname Xiang. The permanent residents primarily engage in farming, mainly cultivating rice, corn, and tobacco, and raising livestock.

The residential buildings in the village are highly distinctive and represent the typical traditional architectural style of the Tujia ethnic group, possessing significant research value. The residences mainly consist of two parts: the main house and the stilted building (diaojiaolou), along with some auxiliary functional rooms. Based on their layout, the residences can be classified into four types: “I-shaped”, “L-shaped”, “U-shaped” dwellings, and courtyard residences (Figure 1). The “I-shaped” layout refers to a design where the stilted building is constructed at one end of the main house, running parallel to it, often due to topographical constraints. The “L-shaped” layout refers to the stilted building being arranged at a right angle to the main house, which is the most typical form of Tujia dwellings in Xiangxi. The “U-shaped” layout features stilted buildings on both sides of the main house, forming a “dustpan mouth” structure, also known as “one main, two wings” or “three-in-one water”. This design makes the courtyard space in front of the main hall the center of the residence. In this configuration, courtyard walls often appear, accompanied by an eight-character facing gate as the courtyard entrance. Courtyard residences involve setting up a facing gate at the opening of the U-shaped structure, forming an inner courtyard. This layout can further develop into a “two-entry courtyard” or “two entries with one embracing hall”, and even more complex courtyard forms.

Based on the aforementioned discussion, this study investigates three typical Tujia dwellings in Naqqiu Village, Xiangxi Prefecture, Hunan Province, China: L-shaped dwellings, U-shaped dwellings, and courtyard residences. The reason for choosing these three types of dwellings over I-shaped dwellings is as follows: I-shaped dwellings have no courtyards and better lighting conditions. In contrast, L-shaped dwellings, U-shaped dwellings, and courtyard residences are surrounded by other buildings, forming a courtyard that obstructs the central dwelling, thus affecting its lighting. Therefore, their indoor lighting conditions may be relatively poor, making the study of their indoor lighting particularly significant. Moreover, the widespread existence of timber-framed dwellings in China, coupled with the Tujia people being a widely distributed and populous minority in the country, makes the study of Tujia timber-framed dwellings not only highly representative but also significant for understanding the architectural heritage and residential environment changes within China’s multi-ethnic culture. Consequently, this study selected typical Tujia L-shaped dwellings, U-shaped dwellings, and courtyard residences and used Ecotect-RADIANCE software for simulation. The research explores the impact of changing the geometric shapes and angles of traditional residential courtyards on the lighting of the central room. Figure 2 shows photos of the central rooms of the selected dwellings.

3.2. Research Factors

The length (L), width (W), and height (H) of a house significantly affect lighting because these geometric dimensions directly determine the way light propagates and distributes within the building. The length (L) of a house impacts the depth to which natural light penetrates the interior; longer houses may result in insufficient lighting in deeper areas. The width (W) of a house mainly affects the area and angle at which light enters the house. A wider house can improve lighting by increasing the window area and optimizing window placement. However, if the width is too large without enough windows, the central areas may suffer from inadequate lighting. The height (H) of a house influences the vertical propagation of light. Higher ceilings allow light to penetrate deeper into the interior, thus improving lighting. However, if a house is too high without appropriately positioned and sized windows, the light may not be effectively utilized. Therefore, this study investigates the impact of changes in courtyard geometric dimensions and angles on house lighting. We tested a range of courtyard widths (W: 3 m to 11 m) and heights (H: 2.4 m to 8 m), assessing their effects on the lighting performance of the main hall in traditional wooden houses of the Tujia ethnic group in western Hunan. Additionally, this study explores the impact of altering the courtyard plan angle on natural lighting in the central room.

3.3. Research Methodology

In this study, we selected the Daylight Factor (DF) to evaluate the indoor daylight performance of traditional dwellings in the Xiangxi region of China for the following reasons. First, Chinese residential daylight standards (GB 50033-2013 and GB 55016-2021) [58,59] explicitly require the use of DF and illuminance metrics, providing a solid basis for our choice. The Daylight Factor is a crucial parameter for assessing the adequacy of natural lighting indoors. DF represents the ratio of the illuminance at a specific point on the indoor horizontal surface to the illuminance on an unobstructed outdoor horizontal surface at the same time, typically expressed as a percentage. The formula for calculating DF is:

(1)$DF={\displaystyle \frac{E_{inside}}{E_{outside}}}\times 100\mathrm{\%}$

where $E_{inside}$ denotes the illuminance at a specific point indoors, and $E_{outside}$ denotes the illuminance under unobstructed outdoor conditions. $DF$ reflects the efficiency and quality of natural daylight in building design, which is significant for energy conservation and enhancing indoor comfort. Previous studies employing these metrics have demonstrated their relevance and effectiveness in evaluating daylight performance [60,61,62]. Selecting DF as the metric to evaluate the indoor daylight performance of traditional dwellings aligns with national standards and accurately reflects the performance of building designs in terms of natural lighting.

This study specifically adopts the computer modeling and simulation approach, a well-established method validated by numerous studies and daylighting software evaluations [63,64]. The chosen simulation tool for this research is Ecotect Radiance 2011 software, a lighting simulation software developed by Ward at the Lawrence Berkeley National Lab, Berkeley, CA, USA. Additionally, Ecotect serves as an environmental analysis software platform. Ecotect functions as both an accurate modeling and export tool, facilitating the input of environmental geometry for RADIANCE calculations. Results can be seamlessly exported to the Ecotect interface, allowing for visualization on an analysis grid. Many scholars have used Ecotect to study the effects of indoor daylighting in buildings [49,65,66,67].

To streamline the methodology, this study simplifies the courtyard plan by considering it as a rectangle. The courtyard is then reduced to a rectangular model for ease of evaluation. Defining a square courtyard involves assessing two key dimensions: the width (W) and height (H), illustrated in Figure 3. The Well Index (WI), a critical parameter in this study, is determined based on Aizelwood’s formula (1995):

WI = H/W (square plan yard)

WI = H(W + L)/2WL (rectangular plan yard)

Using Ecotect, the DF distribution of the central room is modeled and evaluated. The first simulation explores the impact of varying the courtyard width (W), while the second simulation focuses on the effect of varying the courtyard height (H). Both simulations maintain a constant grid size for the central room, and all models are uniformly oriented to face south.

Properties such as the window-to-wall ratio and transmittance of a building’s exterior windows can affect interior lighting effects [68]. Consequently, in all simulations, the central room of the reference model maintains uniform geometric properties, featuring an identical window-to-wall ratio of 0.3 and consistent window placement. To eliminate the influence of window cleanliness, all windows are modeled as openings without glass. Additionally, to disregard the surfaces’ reflectance parameter, uniform values for reflectance, emissivity, and thickness are applied to all surfaces. DF results are displayed on the analysis grid at a height of 750 mm above the ground. Seven longitudinal axes (a–g) are labeled to facilitate the comparison of simulation results for various yard dimensions. The average DF in the central room is assessed for different width and height values of the courtyard. The first simulation explores the variation of width (W) dimensions while keeping length (L) and height (H) constant at 5 m each. Width (W) is manipulated within the range of 3 m to 11 m, resulting in a Well Index (WI) range from 1.3 to 0.7.

3.4. Research Framework

This study first selected typical traditional dwellings in Naqiu Village as research subjects, including L-shaped, U-shaped, and courtyard-type houses. These dwellings are representative as they have been inhabited for a long time and their architectural forms conform to the traditional Tujia dwellings. According to the Architectural Lighting Design Standard (GB 50033-2013), detailed measurements of the illuminance of these dwellings were conducted to evaluate their indoor lighting effects and to verify the accuracy of software simulations. The study adopted a grid method with uniformly distributed measurement points at a working surface height of 0.75 m. The measurement was conducted from 10 a.m. to 2 p.m. During this period, the solar altitude is relatively high and the sun is near the center of the sky hemisphere, minimizing short-term indoor illuminance fluctuations, thereby ensuring the accuracy and reliability of the measurements. This region falls into lighting climate zone V, with a K value of 1.20. Figure 4 shows the schematic diagram of the measurement points. Subsequently, the Ecotect-RADIANCE software was used to model and simulate the lighting of the three traditional dwellings, and the collected data was thoroughly analyzed. In all simulations, the lighting grid was consistently placed 750 mm above the floor, with data collected at the grid nodes. To ensure consistency, the timing of the illuminance simulation and measurement was synchronized. To analyze the differences between the simulated and measured values, two statistical error analysis indicators were used: Mean Bias Error relative (MBErel) and Root Mean Square Error relative (RMSErel). Errors are considered typical and acceptable when the calculation results are within 20%. The calculation formulas for these indices are as follows:

(2)$RMS{E}_{rel}={\displaystyle \frac{1}{{\dot{E}}_{mea}}}\sqrt{{\displaystyle \frac{{\sum }_{i=1}^n {\left(E_{simulation,i}-E_{mea,i}\right)}^2}{n}}}$

(3)$MB{E}_{rel}={\displaystyle \frac{1}{n}}\sum _{i=1}^n {\displaystyle \frac{E_{simulation,i}-E_{mea,i}}{E_{mea}}}$

Afterward, the Ecotect-RADIANCE software was used to simulate the L-shaped, U-shaped, and courtyard-type dwellings, varying the height, width, and angle of the courtyards to detect the lighting performance of their main halls and collect data at the grid nodes. In this study, the daylight factor (DF) was the primary indicator for evaluating daylight performance. To replicate authentic traditional wooden structures, some materials were selected from the Ecotect library to create the models. The light reflectance value is crucial for accuracy, sourced from the Engineering Toolbox website, and input into the Ecotect Material Settings tool (see Table 1). According to the 2013 regulations of the Ministry of Housing and Urban-Rural Development of the People’s Republic of China, the daylight factor (DF) is the primary indicator for evaluating daylight performance, with a DF between 2% and 5% indicating good daylight conditions. The purpose of the simulation was to derive the DF values and their distribution in the central room of each model. A grid 750 mm above the ground was used as the analysis platform. The selected grid size balanced model dimensions and simulation efficiency. DF calculations were performed every 50 cm along the grid axis, providing sufficient lighting information for the central room while ensuring smooth software operation. For ease of longitudinal comparison, the grid’s longitudinal axis was divided into seven reference lines (a–g), spaced 1 m apart. Figure 5 shows the grid locations and reference lines (indicated by dashed lines) in the selected case studies.

The focus of this study is to understand the impact of courtyard dimensions (especially width, height, and angle changes) on the daylight factor of residential buildings. By processing and carefully analyzing the data, we aim to elucidate how the geometric shape of the courtyard affects indoor lighting performance. The final structure of the research framework is summarized in Figure 6, outlining our comprehensive research methodology.

4. Results and Discussion

4.1. Analysis of Model Validation Results

Figure 6 presents a scatter plot comparing the measured illuminance values with the simulated illuminance values for three types of residential buildings. For L-shaped residences, the relative root mean square error (RMSErel) is 17.44%, and the relative mean bias error (MBErel) is 6.65%, with an average measured illuminance of 210.27 lux (Figure 7). For U-shaped residences, the RMSErel is 11.04% and the MBErel is −7.78%, with an average measured illuminance of 294.33 lux (Figure 8). For courtyard-style residences, the RMSErel is 11.25% and the MBErel is 11.44%, with an average measured illuminance of 194.6 lux (Figure 9). Given that the error values are below the critical threshold of 20%, there is a high degree of consistency between the Ecotect simulated values and the measured data, validating the accuracy of the simulation method. Additionally, the illuminance levels for all types of residences do not meet the 300-lux standard set by the Architectural Lighting Design Standard (GB 50033-2013), indicating insufficient indoor lighting for traditional local residences.

4.2. The Impact of the Geometric Dimensions of L-Shaped Residential Courtyards on Indoor Lighting

By modeling the different dimensions of the courtyard enclosed by L-shaped residential buildings, we examined the impact of varying heights, widths, and courtyard angles. The height range was set between 2.4 m and 8 m, the width between 3 m and 11 m, and the courtyard angle between 60° and 120°. Simulation results, whether viewed through heat maps (Figure 10) or line graphs (Figure 11), indicate that the average daylight factor (DF) does not change significantly with variations in height, width, and angle, exhibiting an overall stable trend. This stability is likely to be due to the L-shaped residence having only one side auxiliary structure, which does not significantly obstruct indoor lighting.

4.3. The Impact of Courtyard Geometric Dimensions on Indoor Lighting in U-Shaped and Courtyard-Style Dwellins

U-shaped dwellings and courtyard residences have enclosed courtyards, whose geometric dimensions significantly affect indoor lighting. These courtyards are the primary focus of this study. Figure 12 illustrates the change in average DF concerning different widths (W). Notably, the average DF for U-shaped dwellings declines with increasing W while, for courtyard residences, it ascends with widening W. In U-shaped dwellings, the average DF experiences a rapid decrease from 3 m to 5 m (WI range 1.3–1), with a reduction rate of 7%. Subsequently, it gradually diminishes, reaching a minimum of 4.3% at W = 11 m. Conversely, the average DF of courtyard residences accelerates as W expands from 3 m to 5 m (WI range 1.3–1), with a growth rate of 20%, slowing down after reaching 3.4%, and finally peaking at 4.1% with W = 11 m. Examining the DF distribution in the grid (Figure 13), widening the courtyard increases DF values nearer the entrance but does not significantly improve spaces farther away, which largely remain below 0.5%.

A comparison of average DF along various vertical axes (Figure 14) reveals that, in U-shaped dwellings, most vertical axes maintain a desirable DF range of 2% to 5%. However, within the W range of 3–5 m, several vertical axes exceed 5% and, in the 5–7 m range, a few axes breach the 5% threshold. Courtyard residences consistently maintain optimal average DF (2–5%) in the parlor space. It is noteworthy that the average DF curve for the vertical reference line in U-shaped dwellings becomes smoother with increasing W, indicating better illumination uniformity. In contrast, the average DF curve for the vertical reference line in courtyard residences becomes less smooth, signifying a decrease in illumination uniformity as W increases.

In the second simulation, the focus shifts to altering the height dimension (H), with L and W fixed at 5 m, and H ranging from 2.4 m to 8 m, resulting in WI indices ranging from 2.1 to 0.6 (Figure 15). The outcomes reveal a consistent decrease in average DF with increasing H for both U-shaped and courtyard residences. For U-shaped dwellings, when H rises from 2.4 m to 3.2 m (WI of 1.6), the average DF remains relatively stable. However, from 3.2 m to 4.8 m (WI of 1.0), the average DF declines more rapidly, with a reduction rate of 10%. Subsequently, the reduction rate slows to 3%, reaching a minimum of 3.8% at H = 8 m. Conversely, courtyard residences are notably affected by H. Throughout the H range of 2.4 m to 8 m, the average DF consistently drops, with an average reduction rate of 13%, reaching a trough of 1.9% at H = 8 m. Examining the DF distribution across various height values (Figure 16) reveals that even in the most favorable height case (H = 2.4 m), the DF distribution is non-uniform, with over half the room area having a DF below 0.5%.

Comparing average DF along different vertical axes (Figure 17) underscores that higher H values result in poorer average DF. In U-shaped dwellings, from H = 2.4 m to 4 m, most vertical axes exceed 5% while, for other H values, they generally fall within the optimal range of 2–5%. Courtyard residences exhibit average DF exceeding 5% for H = 2.4–3.2 m, but some vertical axes fall below 2% at H = 8 m.

4.4. Effect of Courtyard Angle on the Light Performance of the Central Room

This segment of the study delves into the influence of internal courtyard angles on the natural lighting performance of the central room in traditional wood-framed dwellings. The investigation is tailored to identify the most optimal courtyard angle by manipulating left-side and right-side angle values and observing their combined effects on interior lighting. Through a comprehensive examination of Xiangxi Tujia dwellings, six distinctive U-shaped and courtyard models were selected (Figure 18). The internal angles were set as follows: 60° ∗ 60°, 60° ∗ 90°, 60° ∗ 120°, 90° ∗ 90°, 90° ∗ 120°, and 120° ∗ 120°. It was ensured that each courtyard had equal area and height, allowing for a study of the impact of different courtyard angles on indoor lighting. The reference models, U-shaped dwelling, and courtyard residence were maintained, with a consistent grid sensor placement in the central room. The dimensions of the room, measuring 7.25 m in length and 3 m in width, remained unchanged. The courtyard height (H) was fixed at 5 m, and the area of all courtyard shapes equaled 50 m².

Simulation results (Figure 19) highlight the significant impact of courtyard angles on the daylighting performance of indoor parlors in residential houses. Whether in U-shaped dwellings or courtyard residences, increasing the angle between the left and right sides of the courtyard from 60° ∗ 60° to 120° ∗ 120° notably enhances the indoor parlor’s daylighting performance. The average DF for U-shaped dwellings increased from 2.9% to 6.1% and, for courtyard residences, it increased from 2.4% to 5.0%. It is noteworthy that when transitioning from a courtyard angle of 60° ∗ 60° to 60° ∗ 90°, both U-shaped dwellings and courtyard residences exhibit a faster increase in average DF compared to the shift from 60° ∗ 90° to 120° ∗ 120°. The growth rates during this angular interval are nearly identical for both dwelling types. However, in the progression from 60° ∗ 90° to 120° ∗ 120°, the average indoor DF of U-shaped dwellings increases relatively more quickly.

These findings underscore a strong correlation between the courtyard’s plane angle in traditional wooden dwellings and indoor lighting levels. A larger angle corresponds to a higher average indoor DF. Notably, when the courtyard angle is 90° ∗ 90°, the indoor hall’s lighting effect surpasses that of a 60° ∗ 120° courtyard angle in both U-shaped dwellings and courtyard residences. The DF distribution graph (Figure 20) indicates better uniformity when the left and right angles of the courtyard are equal. However, more than half of the room areas still register DF values below 0.5%.

Similar to the previous study, this section utilizes seven longitudinal reference lines (labeled a, b, c, d, e, f, g) on the analysis grid to assess how changes in courtyard angles impact the lighting in the longitudinal space of the interior room. When comparing the mean DF distribution on the longitudinal reference lines for various yard angles (Figure 21), the d reference line, positioned at the center, consistently exhibits the most favorable lighting effect, mirroring observations from the earlier part of the study. In the U-shaped dwelling, when courtyard angles are 60° ∗ 60° and 60° ∗ 90°, virtually all average DFs on the longitudinal reference lines fall within the optimal range of 2–5%. However, with a courtyard angle of 60° ∗ 90° or greater, the average DF for most of its central room surpasses 5%. For courtyard residences, when the courtyard angle ranges from 60° ∗ 60° to 90° ∗ 90°, the average DF on nearly all longitudinal reference lines stays within the optimal range of 2–5%. Once the courtyard angle reaches 90° ∗ 90° or higher, the average DF for the central room is mostly above 5%.

5. Conclusions

The simulation study draws key insights regarding the impact of traditional Chinese wood-frame residential courtyard geometry on indoor daylight performance:

• (1). The Impact of Courtyard Geometry on Daylighting in L-Shaped Dwellings

For the L-shaped dwellings, the courtyards are not fully enclosed and present a semi-open layout. As a result, the geometric dimensions of these courtyards have a minimal impact on the internal lighting. This is likely to be due to the lack of significant obstruction from the auxiliary structures, which allows natural light to penetrate more freely into the interior spaces. Consequently, variations in the height, width, and angle of the courtyards do not significantly alter the daylight factor (DF) within these dwellings. This finding aligns with the simulation results, which show stable DF values despite changes in the courtyard dimensions, highlighting the limited influence of semi-open courtyards on indoor lighting performance.

• (2). Width (W) Influence:

Width (W) significantly affects the Daylight Factor (DF) and its distribution within both U-shaped and courtyard residences. In U-shaped dwellings, the average DF decreases with increasing W due to the greater obstruction of natural light by the expanded courtyard boundaries. This reduction in DF becomes less pronounced after the width reaches 4.7% (WI = 1), indicating a threshold beyond which further increases in width have a diminishing impact on lighting performance. This suggests that, while larger courtyards initially hinder light penetration, the effect stabilizes once a certain width is surpassed. In contrast, courtyard residences exhibit an increase in average DF with growing W, as wider courtyards allow more natural light to enter the interior spaces. This growth rate also slows after reaching 3.4% (WI = 1.0), highlighting an optimal range for courtyard dimensions that balances enhanced daylighting with structural and economic considerations. Therefore, the optimal width for courtyards, achieving a balance between economic feasibility and functional effectiveness, is when the WI is 1.

• (3). Height (H) Impact:

Courtyard height (H) significantly affects the average Daylight Factor (DF) and its distribution in the central room. In U-shaped dwellings, the average DF decreases with rising H, but the rate of decline slows after reaching 4.4% (WI = 1.0), indicating that, beyond this point, the negative impact of increased height on daylight penetration diminishes. Courtyard residences are more affected by H, showing a steady decrease in average DF as H increases, suggesting that taller courtyards significantly obstruct natural light. The optimal H for U-shaped dwellings is when WI equals 1, balancing economic considerations and functional effectiveness. For courtyard residences, minimizing courtyard height is feasible and advisable as it enhances daylighting without compromising the functionality of the space.

• (4). Horizontal and Vertical Comparisons:

Changes in courtyard geometry have a greater impact on the average Daylight Factor (DF) of courtyard residences compared to U-shaped dwellings. Vertically, courtyard height (H) has a more pronounced effect on central room lighting than width (W). For courtyard residences, the average DF difference due to height variations is 3.3%, while for U-shaped dwellings it is 1.6%, indicating a significant influence of height on lighting conditions. Width variations result in a 1.7% average DF difference for courtyard residences and 1.0% for U-shaped dwellings, showing that, while width changes do affect lighting, their impact is less substantial than that of height changes.

• (5). Courtyard Plan Angle:

A higher courtyard plan angle corresponds to a higher average indoor Daylight Factor (DF), indicating that increasing the angle between the sides of the courtyard enhances natural light penetration and distribution within the interior spaces. Angles ranging from 60° to 120° show a significant increase in DF as the angle widens, allowing more light to enter and improving uniformity. However, for optimal functionality and aesthetics, a 90° ∗ 90° square layout remains the best choice. This configuration not only maximizes DF but also ensures an even light distribution, minimizing low illumination areas and creating a comfortable, visually pleasing environment. The 90° ∗ 90° angle also aligns with traditional architectural principles, preserving cultural and historical integrity while enhancing modern functionality, making it the preferred design for both U-shaped and courtyard residences.

• (6). Limitations and Future Work:

The study did not empirically measure the actual lighting performance of existing buildings, which is a limitation due to restricted conditions. Future research will include empirical validations. Additionally, the study did not fully consider environmental factors such as climate, seasonal changes, and surrounding landscape, which could also affect indoor lighting. These factors will be explored in future research. The results of the study are only for traditional Tujia wood-frame dwellings and may not be fully applicable to other structural types or ethnic groups. Future studies will include various structural types and ethnic groups to generalize the results. Moreover, the economic and practical feasibility of the proposed modifications, including implementation costs, potential structural changes, and impacts on cultural heritage preservation, were not discussed. Future research will address these aspects. Lastly, advancements in modern lighting technology and their integration with traditional architectural designs will be explored to enhance indoor lighting efficiency and effectiveness.

These findings offer valuable guidance for architects specializing in residential renovations, aiding in enhancing visual comfort, and reducing living and energy costs associated with artificial lighting.

Author Contributions

Y.H. designed and conducted the study, analyzed the data, prepared the figures, and wrote the manuscript. Z.L. supervised the work. J.W. and J.L. revised the manuscript. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures and Table

Figure 1. Types of Traditional Residences of the Tujia People in Western Hunan, China.

Figure 2. Photographs of the central rooms (in the photo on the right, there is a plaque inside the house with the inscription “Shou Bi Nan Shan”, which signifies the homeowner’s wish for longevity).

Figure 3. Dimensional identification of the U-shaped dwelling, the courtyard residence and the U-shaped dwelling.

Figure 4. Diagram of illuminance measurement points.

Figure 5. Analysis grid and longitudinal reference line.

Figure 6. Research framework and process.

Figure 7. Scatter plot of simulated and measured illuminance values for the L-shaped residential dwelling.

Figure 8. Scatter plot of simulated and measured illuminance values for the U-shaped residential dwelling.

Figure 9. Scatter plot of simulated and measured illuminance values for the courtyard residence.

Figure 10. (a) Heatmap of DF distribution as a function of H in the L-shaped residential dwelling; (b) Heatmap of DF distribution as a function of W in the L-shaped residential dwelling; (c) Heatmap of DF distribution as a function of angle in the L-shaped residential dwelling.

Figure 11. Variation of DF with different H, W, and angle in the L-shaped residential dwelling.

Figure 12. Variation of average DF for different W.

Figure 13. (a) Distribution of DF with W in U-shaped dwelling; (b) Distribution of DF with W in courtyard residence.

Figure 14. Distribution of DF on the longitudinal reference line for different W.

Figure 15. Variation of average DF at different H.

Figure 16. (a) Distribution of DF with H in U-shaped dwelling; (b) Distribution of DF with H in courtyard residence.

Figure 17. Distribution of DF on the longitudinal reference line over different H.

Figure 18. Types of courtyards at different angles.

Figure 19. Variation of average DF for different yard angles.

Figure 20. (a) Distribution of DF with courtyard angle in U-shaped dwelling. (b) Distribution of DF with the angle of the courtyard in courtyard residence.

Figure 21. Distribution of DF on the longitudinal reference line at different yard angles.

Table 1

Materials and reflection coefficients of each part of the study object.

Position	Material	Reflectance
Roof	Grey tile	8%
Interior floor	Lime	70%
Exterior floor	On ground	30%
Exterior wall	China Fir	20%
Interior wall	China Fir	20%
Window	China Fir	20%
Door	China Fir	20%

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