Research on the Indoor Thermal Environment of Industrial Architectural Heritage Based on Human Thermal Comfort—A Case Study in Hefei (China) During Winter

Abstract

With the development of China’s social economy and urbanization, there is a significant stock of urban industrial architectural heritage. Considering the increasing demand for urban land and the renewal of idle sites, the reuse of industrial architectural heritage has become an important measure for urban development, while preserving the city’s industrial memory and the authenticity of architectural heritage. This paper conducts a reuse study on the industrial architectural heritage in Hefei based on human thermal comfort. The motor factory welding workshop and the diesel engine factory cylinder casting workshop in Hefei are selected as research objects. By measuring the physical parameters of the indoor thermal environment and the thermal comfort of human bodies before and after the renovation of these two workshops and by conducting data statistics and regression analyses on the measured data and questionnaire data, an actual mean thermal sensation MTS model of human thermal comfort in the indoor space of the industrial architectural heritage before and after reuse is established. This paper compares the neutral temperature, comfortable temperature range, and duration of thermal comfort at different times for the research objects; analyzes the reasons for the differences in the results; and draws conclusions from the comparative analysis, providing a theoretical basis for the practice of comfortable environment transformation of industrial architectural heritage.

1. Introduction

1.1. Overview

In the 1980s, some major cities in China entered a stage of industrial structure optimization and upgrading, with certain industrial factories beginning to relocate from the city center, resulting in a large number of industrial architectural remnants. As people’s recognition of industrial architectural heritage and their identification with industrial culture has strengthened [1,2], the renewal and optimization of heritage spaces have received increasing attention and are considered an important part of the urbanization process [3]. The revitalization and renewal of industrial architectural heritage play crucial roles in optimizing the allocation of urban architectural spaces [4] and upgrading the industrial and economic structure [5,6].

The indoor and outdoor spatial environments of buildings, represented by physical environmental parameters such as temperature, humidity, and wind speed, comprehensively affect the comfort level of the occupants [7,8,9]. The reuse of industrial architectural heritage differs from the renovation of other types of buildings, as the initial design purpose of industrial buildings was for industrial production, with different target users and activity types compared to public and residential buildings [10]. Therefore, the indoor thermal environment of many renovated factory buildings is not suitable for new users under their new functions. Some renovated industrial buildings adopt architectural air conditioning systems to create a suitable space environment for users, but this form of using air conditioning systems to separate the indoor environment from the outdoor space is different from passive renovation methods and natural ventilation in the indoor thermal environment [11]. The complete use of mechanical air conditioning systems may not meet the indoor thermal comfort requirements of the renovated heritage buildings [12], leading to more energy consumption and possibly posing health risks to users of the renovated spaces [13,14]. Human thermal comfort, as the most direct experience of building occupants [15], is an important indicator for evaluating the quality of the building’s thermal environment. It involves the subjective evaluation of the comfort level of the indoor thermal environment by the building’s occupants and the thermal physical parameters of the indoor space [16,17,18,19], thereby judging the comfort level of the indoor space. How to improve the quality of the building space environment after the reuse of industrial architectural heritage from the perspective of human thermal comfort has become an urgent issue to address [20].

1.2. Literature Review

The study of human thermal sensation or human thermal comfort within building interiors dates back to the 1920s in the field of architectural science. The late 1960s saw a rapid development of thermal comfort research, accompanied by the study of building energy efficiency. With the development of social economy and an improvement in the average level of knowledge, people have come to realize that maintaining a good thermal environment indoors, with comfortable interior spaces, is of great significance in terms of improving building energy efficiency and ensuring the health of building occupants.

The exploration of theories on human thermal comfort within building interiors began in the first half of the 17th century. Among them, Yaglou, Houghton, Barker, and others studied environmental factors such as relative humidity, air temperature, and wind speed that influence the thermal environment, exploring the comprehensive impact of various environmental factors on human thermal comfort. Through the combination of physical parameter measurements on site and surveys of the occupants’ subjective experiences, they ultimately arrived at the effective temperature (ET) [21]. The American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) conducted the first experiments on human comfort in the early 20th century at the Pittsburgh Artificial Environment Laboratory, drawing comfort lines based on the subjective perceptions of the subjects. In the 1930s, Bedford and other researchers proposed a seven-level evaluation scale corresponding to thermal comfort sensation in 1936 [22]. Pierce of Yale University, through related research on human thermal comfort, arrived at conclusions distinct from the effective temperature. Professor Gagge, based on research of effective temperature, added other physical parameters related to indoor thermal environments, such as indoor air velocity and the metabolic rate of the occupants, to explore the standard effective temperature (SET) [23]. In the 1960s and 1970s, scholars worldwide reached a new peak in experimental research on human thermal comfort, with researchers from Western countries such as the United States and the United Kingdom, as well as from Hong Kong, China, conducting a large number of studies on building indoor human thermal comfort and achieving significant research results. In the 1970s, the ASHRAE research institution conducted research and exploration based on the local thermal environment and a target population in the United States, proposing the famous ASHRAE 55-1974 standard in 1974 [24]. In the 1980s, the International Organization for Standardization (ISO) formulated the ISO 7730 standard [25]. In 1988, Richard e Dear and other scholars proposed an adaptive model and related theories through research on different climatic regions and environments [26]. A series of theoretical research achievements on human thermal comfort have become important references for evaluating and controlling thermal environments worldwide.

Professor Xu Wenhua and others were among the earliest to conduct research on thermal environments in China. Their work, “Thermal Environment”, systematically summarized the theoretical achievements related to thermal comfort and thermal sensation [27]. Tian Yuanyuan and others conducted exploratory research on the thermal sensation, humidity sensation, and wind sensation of subjects [28]. Li Zhengrong and others systematically studied the advantages and disadvantages of indoor ventilation systems in buildings through thermal comfort simulations and proposed optimization strategies for building ventilation renovations [29,30,31,32]. Zhang Yufeng and others explored human thermal comfort in campus buildings and summarized a temperature range suitable for natural ventilation in school buildings in hot and humid regions [33,34,35,36]. Stanimirovic, M. and other scholars have attempted to achieve thermal comfort goals in rural areas using natural materials [37]. Ke Yao and other scholars studied the thermal comfort of residential buildings in hot summer and cold winter regions and provided references for the design, creation, and evaluation of home environments in these regions [38,39,40]. Xiao Min and others researched the thermal comfort of sports facilities and proposed optimization schemes for the construction of protective structures, indoor ventilation, and cooling [41,42]. Sun Zhen and others studied the influence of split-type air conditioning on thermal comfort and provided theoretical bases for the design and energy-saving regulation of indoor thermal environments in buildings [43,44].

In summary, the focus of the reuse of industrial architectural heritage at present is mainly on the preservation of industrial heritage memory and the insertion of new functions. The research on thermal comfort is largely concentrated on newly constructed buildings such as public buildings and residential buildings, and transformation efforts are also mostly within these building categories. There is a lack of exploration of renovation strategies for industrial architectural heritage based on human thermal comfort research, and there is still no appropriate technical system or systematic research methods in this aspect. The theoretical research in this area is relatively scarce. This article will conduct research and argumentation in this direction. Taking the typical old industrial city of Hefei as an example, with the industrial architectural heritage in the Hefei area as the research object, through means such as field investigation and simulation analysis, the physical parameter status and thermal comfort level of the indoor space of typical industrial architectural heritage in Hefei, such as the welding workshop of Hefei Motor Factory and the cylinder casting workshop of Hefei Iron and Steel Plant, was measured on site in winter. The measured and surveyed data were then subjected to a linear regression analysis to establish a human thermal comfort evaluation model for the indoor space of the industrial architectural heritage samples. This provides a theoretical reference for the future renovation design of indoor spaces in industrial architectural heritage. This approach to transformation design starting from the thermal comfort needs of the space users after reuse also aligns more with the pursuit of humans for health, safety, and comfort, providing new ideas and methods for the reuse of industrial architectural heritage.

2. Methods

2.1. The Geographical Conditions and Climate Characteristics of Hefei

Hefei is located in the central part of Anhui Province, within the temperate zone, situated between the Yangtze and Huaihe Rivers. The city experiences a distinct four-season climate, with cold winters, hot summers, and mild spring and autumn. It belongs to a transition climate type from warm temperate to subtropical, with a humid subtropical monsoon climate. The average annual temperature ranges from 15 to 16 °C, with an annual rainfall of approximately 1000 mm and daylight hours exceeding 2100. The frost-free period lasts about 230 days. The annual temperature varies between −1 °C and 32 °C, with the hot season lasting 3.6 months and the cold season 3.1 months, from the end of November to early March, with an average daily high temperature below 11 °C. The monthly rainfall shows seasonal variation, with July being the wettest month, with the highest cumulative rainfall of 200 mm on 2 July, and January being the driest month, with the lowest cumulative rainfall of 24 mm on 27 December. The wind speed varies seasonally with minimal changes, with a period of higher wind lasting about 3.8 months, from 31 January to 27 May, with an average wind speed exceeding 12.8 km/h. The period of relative calm lasts 8.2 months throughout the year. Hefei City experiences a stuffy period lasting 4.4 months, from 15 May to 28 September, during which at least 25% of the time is characterized by discomfort, oppression, or unease; from the end of October to early April, most of the time is comfortable due to dry conditions [45].

2.2. Target Buildings

This article selects the existing main factory building of Hefei Electric Motor Factory and the reconstructed factory building of Hefei Diesel Engine Factory (now known as the Hechai 1972 Cultural and Creative Park) as the objects of actual measurement, analyzing their indoor thermal environment. Such traditional industrial architectural heritage sites are characterized by their complete scale, large extensive land area, convenient transportation within the factory area, and locations ranging from the city center to different suburban areas. Consequently, the comprehensive optimization design for the integrated reuse of such industrial architectural heritage, aimed at achieving low energy consumption, innovation, and high user satisfaction, holds significant practical implications.

For the comparative study on the indoor thermal environment of industrial architectural heritage factory buildings before and after renovation, this research selects the welding workshop factory building as the field measurement subject for the indoor thermal environment of the industrial architectural heritage space before reuse (Figure 1) and after reuse (Figure 2). The building features a roof truss structure, with a horizontal length of approximately 18 m, a depth of about 120 m, and a ridge height of around 14 m. For the reference industrial architectural heritage factory building after renovation, the original diesel engine cylinder casting workshop factory building, now known as the Hechai 1972 Contemporary Art Museum A Hall, was chosen as the field measurement subject for the indoor thermal environment of the industrial architectural heritage space after reuse. The building structure is a “ribbed doubly curved arch” large span structure, with a horizontal length of 91.2 m, a depth of 36.9 m, and a ridge height of 12.3 m (Figure 3) [46].

Hefei Electric Motor Factory and Hefei Diesel Engine Factory have the same architectural type, with both initially constructed around the same year. They are made of similar building materials and have comparable sizes, consisting of multiple large-span structures. Their straight-line distance is about 10 km apart, so the external environment and climate are similar. By using these two factories as the subjects of measurement, this study can effectively assess the characteristics of the indoor thermal environment of industrial architectural heritage buildings before and after reuse, which offers a certain level of reliability (

Table 1. Comparison of characteristics of measured objects.

		Electric Motor Factory Workshop (Welding Shop)	Diesel Engine Factory Workshop (Cylinder Casting Shop)	Contact Features
Year of Establishment		1956	1954	Similar Construction Time
Building Material	Wall	Red brick	Red brick	Same construction materials
	Roof	Concrete, tile	Concrete, tile
	Floor	Concrete	Concrete
Building Structure		Roof truss structure	Ribbed doubly curved arch structure	Both are representative structures of industrial factory buildings
Original Function		Welding workshop in the electric motor factory	Cylinder casting workshop in the diesel engine factory	Both are industrial production operation workshops
Building Scale		Floor area of approximately 2160 m2, ridge height of about 14 m	Floor area of approximately 3365 m2, ridge height of about 12.3 m	Similar scale
Current State		Idle	Converted into a contemporary art center	State comparison
Location		555 East Changjiang Road	310 Jinzhai South Road	Similar external environment

).

2.3. Measured Equipment and Time

The field measurement was conducted using the following equipment: the AZ-8778 Thermal Index Instrument Hygrometer (AZ Instrument Corporation Co., Ltd., Taichung City, Taiwan (China)) (black body temperature), the UT300S Infrared Thermometer (Uni-Trend Technology (China) Co., Ltd., Dongguan, China) (ground temperature and wall temperature), the ST-8817 Hygrometer (Dongguan Wanchuang Electronics Co., Ltd., Dongguan, China) (air temperature and relative humidity), and the AR-866A Thermal Wind Speed Gauge (Dongguan Wanchuang Electronics Co., Ltd., Dongguan, China) (wind speed). The tests were carried out at a height of 1.5 m, targeting the key areas of the facility under study. Data were recorded every 30 min. The basic parameters and measurement accuracy of the instruments are detailed in

Table 2. The basic parameters and measuring accuracy of the measuring instrument.

Device Name	Measurement Parameter	Measurement Range	Measurement Accuracy
AZ-8778 Thermal Index Instrument Hygrometer	Black Body Temperature	0~80 °C	±1 °C (indoor) ±1.5 °C (outdoor)
UT300S Infrared Thermometer	Ground Temperature	−32~400 °C	±2 °C or 2% (the ambient temperature is 23 ± 2 °C)
	Wall Temperature
ST-8817 Hygrometer	Air Temperature	−20~60 °C	±1 °C
	Relative Humidity	0.0~99.9% RH	±3.0 RH
AR-866A Thermal Wind Speed Gauge	Wind Speed	0~30 m/s	±1%

Actual measurement time: 11 December to 11 January, from 8:00 a.m. to 12:00 p.m. and from 1:00 p.m. to 6:00 p.m.

.

2.4. Layout of Measurement Points

Due to the large area and relatively open and spacious indoor space of the test object’s factory, in order to accurately achieve the objectives of this research topic, the test points were evenly distributed in representative locations within the indoor space (Figure 4 and Figure 5), ensuring the comprehensiveness of the test point setup. And, according to the operation requirements of the testing equipment, the measurement points should be maintained at reasonable spacing and approximately 1.5 m from the ground.

2.5. Participants

The field questionnaire survey objects in the Hefei Motor Factory and the Hefei Diesel Engine Factory were 23 factory visitors, including 15 males and 8 females. The ages of the participants ranged from 24 to 27 years old, and they sequentially participated in the actual measurement work in the workshops of the two factories.

To accurately analyze the impact of the indoor environment on the thermal comfort of personnel, the survey objects were required to stay in the room stably for more than 30 min before filling out the questionnaire, and in terms of activity level, they were asked to stand still during the measurement period. And, before the actual measurement, it was required that the participants avoid consuming alcohol and caffeine drinks the day before the experiment to ensure a good night’s sleep. During the measurement, in summer, the clothing worn by the participants was light, short-sleeved shirts, shorts, and sports shoes, while in winter, they wore moderately warm sweaters, long pants, and sports shoes.

The information from the questionnaire mainly included personal basic information: gender, age, height, weight, clothing thermal resistance, and the type of activity at the time of measurement. The survey objects were asked to score the thermal sensation of the factory space on a seven-level scale (hot, warm, slightly warm, moderate, slightly cool, cool, and cold) (Appendix A).

2.6. Measurement Process

For the two measurement locations in the Hefei Motor Factory and the Hefei Diesel Engine Factory, the research team chose one workshop in a factory area for on-site measurement each day, conducting the measurements sequentially. Each site was operated by a team of 6 people, alternating between tests. To ensure that both test objects could obtain relatively accurate data, the number of tests for both was the same, and each test was conducted at a time close to the other.

Each actual measurement session was divided into rounds of 40 min, with a 20 min interval between each round. Each round was further divided into four stages:

(1)

The first stage was for preparation, which lasted for 10 min.

(2)

The second stage involved standing still, lasting for 10 min. During this stage, the survey was filled out by the participants every 5 min.

(3)

The third stage was a slow walk, which also lasted for 10 min, and the survey was filled out by the participants every 5 min as well.

(4)

The final stage was standing still again, identical to the second stage.

Before the first round began, the participants had to enter the room 30 min in advance to stabilize their indoor condition, ensuring that the participants’ state upon entering the room was stable (Figure 6).

2.7. Calculation Method

The evaluation of the same building’s thermal environment through different evaluation indicators often yields different results (

Table 3. Current primary thermal comfort evaluation indicators.

Evaluation Indicator	Description	Scope of Application
Predicted Mean Vote/Predicted Percentage of Dissatisfied	It is a relatively comprehensive and accurate method of evaluating thermal comfort, which can better reflect the thermal comfort perceptions of the human body under different environmental conditions. It is easy to understand, but its calculation is rather complex, requiring data from multiple parameters, and errors may also occur in some cases.	Applicable to the evaluation of thermal comfort in various building environments, outdoor environments, sports facilities, and more.
ET (Effective Temperature)	It takes into account factors such as temperature, humidity, radiation, and wind speed, with a wide range of applicability. However, the drawback is that the calculation is complex, and there may be some discrepancies when estimating the impact of indoor relative humidity on the occupants.	It can only be applied to indoor building environments and situations where the activity intensity of the occupants is low.
ET* (New Effective Temperature)	Building on the effective temperature (ET), it incorporates air quality for a more comprehensive evaluation of human thermal comfort, with a more complex calculation than ET.	Generally, it is only suitable for spaces with light indoor clothing, low activity intensity, and low indoor wind speed.
SET (Standard Effective Temperature)	It is a comprehensive evaluation indicator based on human metabolic heat production and heat balance, but it does not reflect the influence of factors such as radiation and wind speed.	Applicable to indoor environments.
ATC (Adaptive Thermal Comfort)	It evaluates human adaptability to heat by reflecting the thermal comfort perceptions of the human body under different environmental conditions. However, it requires considering the influence of multiple factors on the human body, and the calculation is complex, making it difficult to implement and understand.	Applicable to the design, renovation, and operational management of buildings, as well as the evaluation of thermal comfort in various work environments, residential settings, and more.
Heat Stress Index	It considers various meteorological factors, work intensity, and individual characteristics to help prevent and control the risk of heat stress, but it does not reflect the overall performance of human thermal comfort.	Commonly used in environments such as workplaces and outdoor activities.
TOP (Environmental Operating Temperature)	It considers the comprehensive impact of environmental factors such as air temperature, mean radiant temperature, and air velocity on the human sense of heat, but it does not take into account the influence of clothing thermal resistance and metabolic rate on the human body.	The scope of application is relatively broad.
Fanger’s Comfort Equation	It comprehensively considers multiple environmental factors such as temperature, relative humidity, air speed, and radiant temperature to use the PMV (predicted mean vote) value to evaluate the thermal comfort perceptions of the human body. It is relatively comprehensive and accurate and can also better reflect the thermal comfort perceptions of the human body under different environmental conditions. However, the calculation is complex and requires data from multiple parameters, and errors may also occur in some cases.	Applicable to the evaluation of thermal comfort in various building environments, outdoor environments, sports facilities, and more.
DR Experiment Method	It directly measures physiological indicators of the human body to more accurately evaluate the adaptability and comfort of the human body to the thermal environment. However, this method requires a high level of technical support and equipment, and it involves monitoring the subjects for a relatively long period of time.	Directly measuring physiological indicators of the human body can more accurately evaluate the adaptability and comfort of the human body to the thermal environment. It is not very suitable for large-scale application scenarios.

). The operative temperature is a synthetic temperature parameter that takes into account the influence of various environmental factors such as air temperature, average radiant temperature, and wind speed. It is a more comprehensive indicator than other single parameters, thereby offering higher accuracy. Professor Humphreys conducted a study comparing the ASHRAE database with the SCATS database and analyzed the correlation between the mentioned environmental indicators and the thermal sensation voting values [47]. The results indicated that the operative temperature is more effective than other thermal environment evaluation indicators. It can establish a good linear relationship with human thermal sensation, which is why it has a wider range of applications in research [48].

The research object of this topic is the indoor space of individual industrial heritage buildings in the Hefei region. Typically, when studying thermal comfort in newly constructed indoor spaces, researchers would choose to predict the predicted mean vote (PMV) and other thermal sensation indicators. However, in this study of the reuse patterns of industrial heritage building spaces, not all are using heating and air conditioning methods to regulate the indoor thermal environment. Therefore, taking into account the climatic conditions of the Hefei region and the characteristics of the indoor spaces of industrial heritage buildings, the author has chosen to study the operative temperature.

(1)

Mean Radiant Temperature (Tmrt)

The mean radiant temperature (Tmrt) refers to the average temperature that the inner surfaces of the surrounding environment exert through radiation on the human body. In everyday life, the temperature of the inner surfaces of the environment is usually uneven, making it difficult to determine their thermal effect on humans. Therefore, it is defined as the temperature at which, assuming the human body is a black body and placed in a space with uniformly distributed black inner surfaces, the heat loss would be equal to the heat loss in a real environment with uneven inner surface temperatures. The calculation method for the mean radiant temperature can be obtained through the measurement of air temperature, globe temperature, wind speed, and other parameters, as shown in Equation (1).

$$Tmrt={[{(Tg+273)}^4+{\displaystyle \frac{(1.1\times {10}^8\times v^{0.6})}{\epsilon D^{0.4}}}\times (Tg-Ta)]}^{0.25}-273$$

(1)

where $Tmrt$ is mean radiant temperature, °C; $Tg$ is globe temperature, °C; $Ta$ is mean air temperature, °C; $v$ is air velocity, m/s; $\epsilon$ is black sphere reflectivity ($\epsilon$ = 0.95); and D is black sphere diameter, m (D = 0.04).

(2)

Operating temperature ($\mathrm{T}\mathrm{o}\mathrm{p}$)

The operating temperature is derived from the heat exchange formula between humans and the environment, specifically through the combined effect of the air temperature in the environment and the average radiant temperature. The calculation formula is as shown in Equation (2).

$$Top={\displaystyle \frac{h_r{T}_{mrt}+h_c{T}_a}{h_r+h_c}}$$

(2)

where $Top$ is operating temperature, °C; $\mathrm{T}\mathrm{a}$ is mean air temperature, °C; $Tmrt$ is mean radiant temperature, °C; h_r is radiant heat transfer coefficient, W/m²·°C; and h_c is convective heat transfer coefficient, W/m²·°C;

According to the “Indoor Thermal Environment Conditions” (GBT 5701-2008) [49], the operational temperature can be calculated with higher precision by categorizing and calculating based on different indoor air flow rates. The following formula can be used to calculate the operational temperature, as shown in Equation (3).

$$Top=A\times Ta+\left(1-A\right)\times Tmrt$$

(3)

where $Top$ is operating temperature, °C; $\mathrm{T}\mathrm{a}$ is mean air temperature, °C; and $Tmrt$ is mean radiant temperature, °C;

Constant A is related to the indoor wind speed of the building and is provided with specific values in ISO Standard 7726-2002 [50], as detailed in

Table 4. The air velocity corresponds to value A.

Air Velocity m/s	$<0.2$	$0.2~0.6$	$0.6~1.0$
A	0.5	0.6	0.7

. When the metabolic rate is between 1.0 and 1.3 met, the wind speed is less than 0.2 m/s, and the area is not directly exposed to sunlight, the calculation of the operational temperature can be taken as the average of the average radiant temperature and the air temperature, which also has a high degree of accuracy. See Equation (4) for the calculation method.

$$Top={\displaystyle \frac{Ta+Tmrt}{2}}$$

(4)

3. Results and Discussion

3.1. Winter Objective Data Comparison Analysis

The statistical data on the thermal environmental physical parameters of the indoor space of industrial architectural heritage buildings during the winter is shown in

Table 5. Statistics of physical parameters of indoor thermal environment of industrial building heritage in winter.

Physical Parameter	Test Location	Average	Deviation	Minimum	Maximum
Air Temperature /°C	Welding Shop (Before Reuse)	14.65	1.16	9.62	17.85
	Welding Shop (After Reuse)	20.12	0.89	19.07	22.54
	Cylinder Casting Shop (After Reuse)	18.08	0.99	16.50	19.62
Relative Humidity /%	Welding Shop (Before Reuse)	49.81	2.33	39.67	66.64
	Welding Shop (After Reuse)	59.74	1.45	51.01	69.77
	Cylinder Casting Shop (After Reuse)	57.39	2.04	47.90	68.24
Bulb Temperature /°C	Welding Shop (Before Reuse)	15.91	3.24	10.30	17.96
	Welding Shop (After Reuse)	22.47	1.21	19.40	23.80
	Cylinder Casting Shop (After Reuse)	18.42	0.51	15.27	20.95
Air Velocity /m/s	Welding Shop (Before Reuse)	0.12	0.09	0.00	1.40
	Welding Shop (After Reuse)	0.10	0.15	0.00	0.40
	Cylinder Casting Shop (After Reuse)	0.10	0.07	0.00	0.49
Mean Radiant temperature /°C	Welding Shop (Before Reuse)	14.98	0.66	9.41	18.02
	Welding Shop (After Reuse)	21.56	0.78	19.78	22.84
	Cylinder Casting Shop (After Reuse)	18.77	1.24	15.06	21.74
Operating Temperature /°C	Welding Shop (Before Reuse)	15.22	0.51	9.67	18.54
	Welding Shop (After Reuse)	20.79	1.54	19.12	22.78
	Cylinder Casting Shop (After Reuse)	18.28	0.39	15.74	20.51

, and a comparative bar chart can be seen in Figure 7.

From Table 5 and Figure 7, it can be observed that the average air temperature in the indoor spaces of the Hefei industrial architectural heritage samples before and after reuse shows the following: the welding workshop before reuse had an average air temperature of 14.65 °C, while after reuse, it was 20.12 °C. The cylinder casting workshop after reuse had an average air temperature of 18.08 °C. The average air temperatures of the two reused indoor spaces were close to each other and both were higher than those of the before reuse industrial architectural heritage spaces. The average air humidity before reuse in the welding workshop was 49.81%, which increased to 59.74% after reuse, and to 57.39% in the cylinder casting workshop after reuse. The difference in average air humidity between the two reused welding and cylinder casting workshops was minimal, and the average air humidity in both indoor environments fluctuated between 50 and 70% throughout the day. The average air humidity of the two reused indoor space samples was significantly higher than that of the before reuse welding workshop, and the indoor air humidity of the before reuse samples fluctuated between 39 and 70% throughout the day. The average air velocity before reuse in the welding workshop was 0.12 m/s, and it was 0.10 m/s in both the welding and cylinder casting workshops after reuse. The average wind speeds and the maximum wind speeds in the three environments were similar, with the minimum wind speed at 0 m/s in all cases. The indoor air velocities in the renovated welding and cylinder casting workshops tended to stabilize.

The data results indicate that in the winter, the indoor spaces of the welding workshop in the industrial architectural heritage building had a wider range of fluctuations in average air temperature and relative humidity before reuse. After reuse, the average air temperature and relative humidity in the welding and cylinder casting workshops showed a trend towards similar fluctuations in the indoor environment. Therefore, relative humidity and air temperature are significant factors affecting human thermal comfort in the indoor spaces of industrial heritage buildings before and after reuse. This suggests that in the context of renovation and reuse, managing these environmental parameters is crucial for creating a comfortable indoor climate.

3.2. Comparative Analysis of Subjective Evaluation Results in Winter

(1)

Voting values for the perception of cold and heat

A frequency distribution of the voting values for the sensation of cold and heat experienced by the participants in the indoor space of the industrial heritage buildings before and after reuse is shown in Figure 8. By comparing the voting numbers in the three sample indoor spaces of the winter industrial heritage buildings, it is found that 83.42% of the voting values for the welding workshop before reuse fell between −1 and 1 (from slightly cool to slightly warm), whereas for both the welding workshop and the cylinder casting workshop after reuse, all the voting values (100%) were within the range of −1 to 1. This indicates that the three sample indoor spaces can provide a relatively good temperature environment in winter. However, the voting values for the sensation of cold and heat in the welding workshop before reuse were lower than those in the after-reused welding workshop and cylinder casting workshop, suggesting that there is still room for improvement in the indoor temperature environment of the former. Furthermore, 66.30% of the voting values for the welding workshop before reuse were chosen between −3 and −1 (cold to slightly cool), indicating that the welding workshop before reuse had instances of lower indoor temperatures during winter.

(2)

Expecting temperature voting value

A frequency distribution of the expected temperature voting values of the participants in the indoor spaces of the industrial heritage buildings before and after reuse during winter is shown in Figure 9. By comparing the voting values for temperature expectations in the three sample spaces during winter, it is found that, before reuse, more than half of the participants in the welding workshop desired an increase in temperature for this sample indoor space. In addition, the voting results on the sensation of cold and heat in the winter reuse welding workshop indicated that more than half of the participants experienced it as slightly cool to cold (between −1 and −3 on the scale, slightly cool to cold), suggesting that the indoor temperature in the welding workshop before reuse was low. The indoor air temperature is an important factor affecting the thermal comfort of people indoors during winter. After reuse, the voting values for the welding workshop and the cylinder casting workshop were relatively close, with more than 78% of the participants expecting the temperature to remain unchanged. This indicates that the indoor temperature environment in the welding workshop and the cylinder casting workshop after reuse was comfortable during winter.

(3)

Humidity sensory voting value

A frequency distribution of the voting values for humidity sensation of the participants in the indoor spaces of the industrial heritage buildings before and after reuse during winter is shown in Figure 10. Through the comparison of the humidity sensation voting values of the three samples, the voting values for humidity sensation in the welding workshop before reuse were between −1 and 1 (slightly humid to slightly dry), accounting for 93.08% of the votes. After reuse, the voting values for humidity sensation in the welding workshop were between −1 and 1, reaching 97.22% of the votes. For the cylinder casting workshop after reuse, the voting values for humidity sensation were between −1 and 1, with 96.97% of the votes. It can be concluded that over 90% of the voting values for humidity sensation in the three indoor spaces during winter were within the range of comfortable humidity sensation, which clearly indicates that the indoor spaces of these industrial heritage buildings, before and after reuse, can provide a relatively comfortable humidity environment for the users in winter.

(4)

Expected humidity voting value

A frequency distribution of the expected humidity voting values of the participants in the indoor spaces of the industrial heritage buildings before and after reuse during winter is shown in Figure 11. The comparison of the expected humidity voting values in the three different industrial heritage building samples’ indoor spaces indicates that during winter, in the welding workshop before reuse, about half of the participants believed that the indoor relative humidity level needed to be increased, suggesting a lower comfort level of humidity during the winter. In both the welding workshop after reuse and the cylinder casting workshop, more than 78% of the votes chose to keep the indoor relative humidity level unchanged, and in conjunction with the humidity sensation voting values, it is shown that the humidity environment in the welding workshop and cylinder casting workshop after reuse can largely meet the humidity comfort needs of the users.

(5)

Wind speed felt voting value

A frequency distribution of the wind speed sensation voting values of the participants in the indoor spaces of the industrial heritage buildings before and after reuse during winter is shown in Figure 12. The comparison of the wind speed sensation voting values in the three different indoor spaces reveals that during winter, before reuse, in the welding workshop, the voting values for 1~3 (slight to strong) accounted for 65.79%, indicating that more than half of the participants in the welding workshop before reuse perceived the indoor wind speed as strong. After reuse, in both the welding workshop and the cylinder casting workshop, the voting values for 0~1 (not felt to slightly felt) exceeded 95%, meaning that in both spaces, the participants believed there was no noticeable air flow or only a slight perception of air movement. This suggests that there was no significant wind speed variation in these two types of indoor environments.

(6)

Expected wind speed voting value

A frequency distribution of the participants’ expected wind speed voting values in the indoor spaces of the industrial heritage buildings before and after reuse during winter is shown in Figure 13. The comparison of expected wind speed voting values from the three spaces reveals that before reuse, in the welding workshop, more than 75% of the voting values chose option 0 (no change), indicating that the majority of participants believed that the indoor air flow should remain unchanged. After reuse, both the welding workshop and the cylinder casting workshop had 100% of the voting numbers choosing either no change or an increase in indoor air flow. In conjunction with the wind speed sensation voting values, this suggests that the wind speed environment in the reused welding workshop and cylinder casting workshop during winter mostly meets the comfort requirements of users.

(7)

Comfort level voting value

A frequency distribution of the participants’ comfort level voting values in the indoor spaces of the industrial heritage buildings before and after reuse during winter is shown in Figure 14. A comparison of the voting values from the participants across the three sample spaces reveals that, before reuse in the welding workshop, 58.01% of the participants regarded the indoor thermal environment as −3 to −1 (very uncomfortable to somewhat uncomfortable), indicating that there is considerable room for improvement in the comfort level of the winter space environment in the before reuse welding workshop. After reuse, both in the welding workshop and the cylinder casting workshop, over 90% of the votes were cast for levels 1 to 3 (somewhat comfortable to very comfortable), suggesting that the indoor spaces of the reused industrial heritage buildings can provide a relatively comfortable space environment for users during winter.

3.3. Winter Thermal Comfort Comparison Survey

3.3.1. Analysis of the Actual Mean Thermal Sensation (MTS) Model

To explore the relationship between the subjective thermal sensation and operational temperatures in the indoor spaces of industrial architectural heritage before and after reuse, a linear regression analysis is commonly employed. In this method, the indoor spaces of industrial architectural heritage before and after reuse, specifically the before reuse welding workshop, the after reuse welding workshop, and the post-reuse cylinder casting workshop, are treated as three sample spaces. The objective physical parameters of operational temperatures at different time periods in these spaces are used as the independent variable x, while the thermal sensation voting values of the corresponding participants during the same time periods are considered as the dependent variable y. Subsequently, both variables are subjected to a linear regression analysis.

However, in actual research and analysis of the relationship between the two, directly using the previously measured thermal sensation voting values and operational temperatures for linear regression analysis often results in a low R2 value for the regression equation. To improve the fitting effect of the regression equation, the temperature frequency method (Bin method) [51] is generally adopted. This method involves redefining the measured operational temperatures, dividing them into several temperature intervals with a 0.5 °C increment, and using the average operational temperature of each interval to replace the original operational temperature as the independent variable x ($Top$). Similarly, the average thermal sensation voting value (MTS) of each interval is used to replace the original initial voting values as the dependent variable y (MTS). A regression analysis of the two variables leads to Equation (5).

$$y_{\left(MTS\right)}=a\times x_{\left(Top\right)}+b$$

(5)

An actual average thermal sensation model for the indoor spaces of industrial architectural heritage before and after winter reuse was established. The processed average operational temperatures and actual average thermal sensation voting values were then subjected to linear regression (

Table 6. Linear regression analysis of indoor thermal sensation and operating temperature in welding workshop before reuse in winter.

Linear Regression Analysis (n = 17)
	Non-standardized coefficients		Standardized coefficients	t	p	VIF
	B	standard error	β
Constant	−3.491	0.382	-	−9.136	0.000 **	-
Operational temperature	0.181	0.026	0.876	7.044	0.000 **	1.000
$R^2$	0.768
Adjusted $R^2$	0.752
F	F(1,15) = 49.625, p = 0.000
D-W statistic	2.031

Note: ** p < 0.01.

,

Table 7. Linear regression analysis of indoor thermal sensation and operating temperature in welding workshop after reuse in winter.

Linear Regression Analysis (n = 16)
	Non-standardized coefficients		Standardized coefficients	t	p	VIF
	B	standard error	β
Constant	−3.680	0.346	-	−10.630	0.000 **	-
Operational temperature	0.166	0.017	0.936	9.951	0.000 **	1.000
$R^2$	0.876
Adjusted $R^2$	0.867
F	F(1,14) = 99.013, p = 0.000
D-W statistic	2.277

Note: ** p < 0.01.

and

Table 8. Linear regression analysis of indoor thermal sensation and operating temperature in cylinder casting workshop after reuse in winter.

Linear Regression Analysis (n = 18)
	Non-standardized coefficients		Standardized coefficients	t	p	VIF
	B	standard error	β
Constant	−2.516	0.310	-	−8.113	0.000 **	-
Operational temperature	0.113	0.016	0.873	7.154	0.000 **	1.000
$R^2$	0.762
Adjusted $R^2$	0.747
F	F(1,16) = 51.180, p = 0.000
D-W statistic	2.585

Note: ** p < 0.01.

), resulting in the corresponding equations (Equations (6)–(8)). Finally, regression plots for the thermal sensation versus operational temperatures in the winter before and after reuse of the industrial architectural heritage indoor spaces were generated (Figure 15).

$$y_{(MTS Welding workshop before reuse)}=0.1814\times x_{\left(Top\right)}-3.4908(R^2=0.7679)$$

(6)

Table 6 indicates that the R2 value of the actual average thermal sensation MTS model for the welding workshop before winter reuse is 0.7679. This suggests that in this winter environment, the operational temperature can explain 76.79% of the variability in the thermal sensation voting values of the workshop before reuse, indicating a good fitting effect. The F-test of the model reveals that the model passes the F-test (F = 49.625, p = 0.000 < 0.05), which means that the operational temperature will definitely have an impact on the thermal sensation voting values of the workshop before reuse. Additionally, the regression coefficient for operational temperature is 0.181 (t = 7.044, p = 0.000 < 0.01), showing a significant positive relationship between operational temperature and the thermal sensation voting values of the workshop before reuse. By setting the dependent variable to 0 in the equation, the indoor neutral temperature of the welding workshop before winter reuse is calculated to be 19.25 °C.

$$y_{(MTS Welding workshop after reuse)}=0.1663\times x_{\left(Top\right)}-3.6081(R^2=0.8761)$$

(7)

Table 7 shows that the R2 value of the actual average thermal sensation MTS model for the welding workshop after winter reuse is 0.8761, indicating that in this winter environment, the operational temperature can account for 87.61% of the variation in the thermal sensation voting values of the workshop after reuse. The F-test of the model reveals that the model passes the F-test (F = 99.013, p = 0.000 < 0.05), which means that the operational temperature will definitely affect the thermal sensation voting values of the workshop after reuse. Furthermore, the regression coefficient for operational temperature is 0.166 (t = 9.951, p = 0.000 < 0.01), demonstrating a significant positive influence of operational temperature on the thermal sensation voting values of the workshop after reuse. By setting the dependent variable to 0 in the formula, the indoor neutral temperature of the welding workshop after winter reuse is calculated to be 22.13 °C.

$$y_{(MTS Cylinder casting workshop after reuse)}=0.1126\times x_{\left(Top\right)}-2.5156(R^2=0.7618)$$

(8)

Table 8 reveals that the R2 value of the actual average thermal sensation MTS model for the cylinder casting workshop after winter reuse is 0.7618, indicating that in this environment, the operational temperature can account for 76.18% of the variation in the thermal sensation voting values of the workshop before reuse, demonstrating a good fitting effect. The F-test of the model shows that the model passes the F-test (F = 51.180, p = 0.000 < 0.005), which means that the operational temperature will definitely affect the thermal sensation voting values of the workshop before reuse. Moreover, the regression coefficient for operational temperature is 0.113 (t = 7.154, p = 0.000 < 0.01), indicating a significant positive influence of operational temperature on the thermal sensation voting values of the workshop before reuse. By setting the dependent variable to 0 in the formula, the indoor neutral temperature of the cylinder casting workshop after winter reuse is calculated to be 22.34 °C.

Comparing the results of the above three (Figure 15), the growth rates of thermal sensation in the welding workshop before and after winter reuse, and in the cylinder casting workshop are 0.1814, 0.1663, and 0.1126, respectively. This indicates that the operational temperature in the welding workshop before winter reuse has a larger change range compared to the two samples after reuse. Additionally, the neutral temperatures for the welding workshop before and after winter reuse, and for the cylinder casting workshop are 19.25 °C, 22.13 °C, and 22.34 °C, respectively, with the neutral temperature in the workshop before winter reuse being the lowest. This suggests that during winter, the subjects in the welding workshop before reuse can tolerate lower indoor temperatures, indicating higher cold tolerance.

3.3.2. Comparison Analysis of Comfort Temperature Ranges

To investigate the relationship between the subjective thermal comfort of indoor spaces in industrial architectural heritage buildings before and after reuse, and the operational temperature, the operational temperatures in the welding workshop before and after reuse, and the cylinder casting workshop after reuse were pre-processed using the temperature frequency method. (In the actual operational process, the operating temperature is divided into sections for every 0.5 °C, and the average operating temperature of each temperature interval is used to replace the original operating temperature as the independent variable x_(Top). The percentage of votes for the thermal comfort level corresponding to the operational temperature of each temperature section, which ranges from −3 to −1 (very uncomfortable to moderately uncomfortable), is chosen as the percentage of thermal discomfort (PD). This thermal discomfort percentage is used as the dependent variable y_(PD), and a regression analysis is conducted on the two to obtain the following formula: $y_{\left(PD\right)}=a\times x_{\left(Top\right)}^2+b\times x+c$.) The processed average operational temperatures and percentage of thermal discomfort were subjected to nonlinear regression (

Table 9. Nonlinear regression analysis of indoor thermal unacceptability percentage and operating temperature in welding workshop before reuse in winter.

Model Parameter Estimates (n = 20)
Parameter Terms	Regression Coefficients	Standard Errors	t	p	95%CI
b1	238.793	49.781	4.797	0.000	133.763~343.823
b2	−23.206	7.460	−3.111	0.006	−38.945 to −7.468
b3	0.573	0.270	2.123	0.049	0.003~1.143

Model R² value: 0.8755.

,

Table 10. Nonlinear regression analysis of indoor thermal rejection percentage and operating temperature in welding workshop after reuse in winter.

Model Parameter Estimates (n = 19)
Parameter Terms	Regression Coefficients	Standard Errors	t	p	95%CI
b1	526.840	97.689	5.393	0.000	319.749~733.932
b2	−46.064	9.190	−5.012	0.000	−65.546 to −26.581
b3	1.022	0.213	4.788	0.000	0.569~1.474

Model R² value: 0.7128.

and

Table 11. Nonlinear regression analysis of indoor thermal rejection percentage and operating temperature in cylinder casting workshop after reuse in winter.

Model Parameter Estimates (n = 18)
Parameter Terms	Regression Coefficients	Standard Errors	t	p	95%CI
b1	616.202	133.505	4.616	0.000	331.643~900.760
b2	−53.975	12.696	−4.251	0.001	−81.035 to −26.914
b3	1.192	0.298	3.996	0.001	0.556~1.828

Model R² value: 0.723.

), and corresponding formulas were derived (Equations (9)–(11)). Finally, regression graphs showing the relationship between thermal discomfort and operational temperature in the indoor spaces of industrial architectural heritage buildings before and after winter reuse were generated (Figure 16).

Table 9 reveals that the R-squared value for the nonlinear regression model between the percentage of indoor heating non-acceptance in the welding workshop before reuse and the operating temperature is 0.8755, indicating a good fit. The three sets of parameters presented in the table demonstrate that the model is statistically significant, and Equation (9) is obtained:

$$y_{(PD Welding workshop before reuse)}=0.5733x_{\left(Top\right)}^2-23.206x+238.79(R^2=0.8755)$$

(9)

Table 10 reveals that the R-squared value for the nonlinear regression model between the percentage of indoor heating non-acceptance in the welding workshop after reuse and the operating temperature is 0.7128, indicating a good fit. The three sets of parameters presented in the table demonstrate that the model is statistically significant, and Equation (10) is obtained:

$$y_{(PD Welding workshop after reuse)}=1.0216x_{\left(Top\right)}^2-46.064x+526.84R^2=0.7128)$$

(10)

Table 11 reveals that the R-squared value for the nonlinear regression model between the percentage of indoor heating non-acceptance in the cylinder casting workshop after reuse and the operating temperature is 0.723, indicating a good fit. The three sets of parameters presented in the table demonstrate that the model is statistically significant, and Equation (11) is obtained:

$$y_{(PD Cylinder casting workshop after reuse)}=1.192x_{\left(Top\right)}^2-53.975x+616.2 (R^2=0.723)$$

(11)

Based on the obtained nonlinear regression equation formula, the thermal acceptable temperature ranges for the three sample spaces during the winter can be determined as shown in

Table 12. Acceptable temperature range of indoor space of industrial building heritage before and after reuse in winter.

Name of Measured Sample	Acceptable Temperature Range/°C
Welding workshop (before reuse)	14.95~25.53
Welding workshop (after reuse)	19.06~26.03
Cylinder casting workshop (after reuse)	19.11~26.17

: The thermal acceptable temperature range for the welding workshop before winter reuse is 14.95–25.53 °C, for the welding workshop after winter reuse is 19.06–26.03 °C, and for the cylinder casting workshop after winter reuse is 19.11–26.17 °C. Comparing the three, it can be seen that the acceptable temperature range is the largest for the welding workshop before winter reuse (10.58 °C), and the lower limit of the thermal acceptable temperature for the welding workshop before winter reuse is lower than those of the welding workshop and the cylinder casting workshop. This indicates that the winter occupants of this space have better thermal adaptability. Figure 16 shows the relationship between the thermal non-acceptance and operating temperature of industrial architectural heritage before and after winter reuse.

3.3.3. Comparison Analysis of Thermal Comfort Duration

To categorize and statistically analyze the calculated thermal acceptable temperature range of indoor spaces in winter for the industrial architectural heritage base on the operating temperatures for various sample spaces (

Table 13. Comparison of main physical parameters of interior space of industrial building heritage before and after reuse.

Season	Main Physical Parameters (°C)	Welding Workshop (Before Reuse)	Welding Workshop (After Reuse)	Cylinder Casting Workshop (After Reuse)
Winter	Actual Operating Temperature Range of the Environment	9.67~18.54	19.12~22.78	15.74~20.51
	Acceptable Temperature Range	14.95~25.53	19.06~26.03	19.11~26.17
	Environmental Average Operating Temperature	15.22	20.79	18.28
	Neutral Temperature	19.25	22.13	22.34

), the following specific operational procedure was followed: Firstly, the original experimental testing time (from 8:00 to 18:00) was divided into 18 time intervals, with each interval being half an hour apart. Then, for each of the 18 time intervals, the measured sample indoor operating temperature was compared with the calculated acceptable thermal range. Finally, we determined the duration of time for which the sample space was acceptable and unacceptable during the winter, thereby judging the thermal comfort of different sample spaces indoors during the winter season. This analysis helps to judge the indoor winter thermal comfort conditions in different sample spaces, as shown in Figure 17. The duration percentages of operating temperatures within the acceptable temperature range for the welding workshop before reuse, the welding workshop after reuse, and the cylinder casting workshop after reuse are 35.27%, 100%, and 82.76%, respectively. The data show that for the welding workshop before reuse, more than 60% of the operating temperatures during the test period are not within the thermal comfort range, indicating that the indoor environment comfort level in the welding workshop before reuse is relatively low for most of the winter. The welding workshop after reuse meets the thermal comfort requirements of the occupants throughout the test period. The cylinder casting workshop after reuse has a relatively high indoor environment comfort level for most of the winter, but there is still room for improvement.

4. Discussion

At present, the focus of the reuse of industrial architectural heritage is mainly on the inheritance of cultural memory and the insertion of new functions, with relatively less research on the indoor thermal environment of buildings. This study, based on the current situation of industrial architectural heritage, explores the influence of factors such as indoor temperature, humidity, and air circulation on human comfort from the perspective of optimizing the thermal environment and improving human thermal comfort. Compared to the traditional approach that solely focuses on building energy saving, insulation, and noise reduction, this research, which starts from the thermal comfort needs of the occupants in the reused spaces, is more in line with human pursuits of health, safety, and comfort and provides new ideas and methods for the reuse of industrial architectural heritage.

This study also has some limitations. This paper was based on the reuse patterns of the industrial architectural heritage space studied, but not all of the spaces were regulated using heating and air conditioning methods; thus, operational temperature was chosen as the parameter for the MTS model. However, the operational temperature does not take into account the effects of clothing thermal resistance and metabolic rate on humans, and it is only applicable to environments with wind velocities less than 1 m/s. Due to the limitations of the parameters, it will have some impact on the MTS model. In addition, due to the differences in the operational personnel and the subjects involved in the measurement process, to some extent, it also affects the measured data. Additionally, the research object of this paper was the Hefei Electric Machine Factory welding workshop and the Hefei Iron and Steel Plant cylinder casting workshop, which are the main industrial architectural heritage in Hefei City and has made a significant contribution to the industrial development of Hefei or has great significance. However, the Hefei area is relatively vast, and the types of industrial architectural ruins left behind are diverse, therefore, the measured objects selected cannot fully represent the current situation of industrial architectural heritage in the Hefei area. Although the data obtained in the study meet statistical significance, there is still room for further optimization.

Research on human thermal comfort is of great importance to fields such as architectural design, energy conservation, and entertainment health. In architectural design, the evaluation of thermal comfort can help designers formulate more appropriate indoor environmental parameters, thus improving the productivity and comfort of employees. In the field of energy conservation, thermal comfort models can be used to optimize the operation of air conditioning systems, reducing energy consumption. Moreover, in the field of entertainment health, researchers can develop suitable physical activities, leisure, and travel activities for different climatic conditions based on the characteristics of human thermal comfort. In summary, as human demands for environmental comfort continue to increase, research on human thermal comfort will become increasingly important.

5. Conclusions

This paper investigated the physical parameters of indoor thermal environments and human thermal comfort before and after the reuse of industrial architectural heritage in the Hefei region. Through data analysis and regression analysis, this study compared parameters such as neutral temperature, comfortable temperature range, and duration of thermal comfort between the research subjects at different times, and the following main findings were identified:

• The measurement of indoor air temperature, relative humidity, globe temperature, wind speed, mean radiant temperature, and operating temperature in the indoor spaces of the research subjects during each season shows that the welding workshop before winter reuse has a larger fluctuation range in average air temperature and relative humidity, while the fluctuations in average air temperature and relative humidity in the indoor spaces of the welding workshop and the cylinder casting workshop after reuse are smaller and tend to be more stable, indicating that relative humidity and temperature are significant factors affecting human thermal comfort in the indoor spaces of industrial heritage buildings before and after reuse.
• Through numerical comparisons of voting values for indoor cold and hot feelings, expected temperature, humidity sensation, expected humidity, wind sensation, expected wind speed, and indoor comfort level of the research subjects, it can be analyzed that the indoor thermal environment of the welding workshop and the cylinder casting workshop after reuse achieves a high level of comfort in the winter voting values, which can better meet the thermal comfort requirements of the new occupants. In contrast, the voting values for indoor comfort in the welding workshop before reuse are relatively low in winter, often resulting in a cooler indoor environment, and there is considerable room for optimization of the thermal environment.
• Through the actual mean thermal sensation (MTS) model and regression analysis, a comparison of the three research subjects shows that the welding workshop before reuse has a higher growth rate in thermal sensation, indicating a larger change range in operating temperature. Additionally, the neutral temperature of the welding workshop before reuse is the lowest, and the acceptable temperature range is the widest, suggesting that the occupants in this space have higher cold tolerance and better thermal adaptability during the winter.
• Through the comparison analysis of the duration of thermal comfort, it is indicated that the indoor space of the welding workshop after reuse can meet the thermal comfort requirements of the occupants throughout the test period. However, the welding workshop before reuse is significantly affected by the surrounding environment in winter, with relatively short comfortable durations and lower indoor temperatures. The main reasons for this indoor thermal environment are the long period of idleness in the welding workshop before reuse, poor thermal insulation and heat preservation performance of the outer walls, and severe damage to the windows and doors. The welding workshop after reuse and the cylinder casting workshop have better comfort throughout the seasons, employing a large number of passive optimization methods for thermal environment, predominantly using natural ventilation, which has significantly improved the indoor thermal comfort and is more meaningful for building transformation energy saving and the health of the occupants.