Building Thermal Environment: Improving Indoor Comfort by Optimizing Ventilation Systems

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Energy, Physics, Environment, and Systems".

Deadline for manuscript submissions: 30 April 2025 | Viewed by 5178

Special Issue Editors


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Guest Editor
School of Environment and Energy Engineering, Beijing University of Civil Engineering and Architecture, Beijing 102616, China
Interests: building environment; building ventilation; CFD; building green energy
Berkeley Education Alliance for Research in Singapore, Singapore 138602, Singapore
Interests: indoor air quality; indoor airflow dynamics; building ventilation; bioaerosols
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Guest Editor
School of Mechanical Engineering, Tianjin University of Commerce, Tianjin 300134, China
Interests: indoor environment control; ventilation and purification; energy-saving building designs; optimal control of HVAC; fault detection and diagnosis of HVAC

Special Issue Information

Dear Colleagues,

This Special Issue, titled "Building Thermal Environment: Improving Indoor Comfort by Optimizing Ventilation Systems", offers an insightful exploration of the critical relationship between indoor thermal comfort and the efficient operation of ventilation systems. With a primary focus on elevating the quality of indoor spaces, this collection of articles brings to the forefront the latest strategies, technologies, and innovative approaches dedicated to optimizing ventilation systems.

Encompassing a wide spectrum of topics, this Special Issue delves into cutting-edge HVAC systems, passive ventilation techniques, and advanced sensor-driven control systems. These components collectively work towards creating healthier and more comfortable indoor environments while simultaneously improving energy efficiency.

The integration of natural ventilation strategies alongside mechanical systems is a central theme, illustrating the harmonious balance between sustainable, energy-efficient building designs and occupant well-being.

This Special Issue is an indispensable resource for architects, engineers, and environmental professionals, providing comprehensive insights and practical solutions for enhancing building sustainability, energy efficiency, and overall quality of life for those who occupy these spaces.

Dr. Congcong Wang
Dr. Jiayu Li
Dr. Lizhi Jia
Guest Editors

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Keywords

  • indoor environment
  • ventilation
  • airflow distribution
  • HVAC
  • thermal comfort
  • CFD
  • airflow structure
  • energy saving

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Published Papers (4 papers)

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Research

27 pages, 5429 KiB  
Article
Using the Taguchi Method and Grey Relational Analysis to Optimize Ventilation Systems for Rural Outdoor Toilets in the Post-Pandemic Era
by Chang Sun, Lianyuan Feng, Meng Guo and Xiaolei Ju
Buildings 2024, 14(9), 2692; https://doi.org/10.3390/buildings14092692 - 28 Aug 2024
Viewed by 739
Abstract
This study addresses the issue of poor air quality and thermal comfort in rural outdoor toilets by proposing a ventilation system powered by a building-applied photovoltaic (BAPV) roof. A numerical model is established and validated through comparison with the literature and experimental data. [...] Read more.
This study addresses the issue of poor air quality and thermal comfort in rural outdoor toilets by proposing a ventilation system powered by a building-applied photovoltaic (BAPV) roof. A numerical model is established and validated through comparison with the literature and experimental data. Based on a consensus, four influential variables, namely, inlet position, outlet height, supply air temperature, and ventilation rate, are selected for optimization to achieve multiple objectives: reduction in ammonia concentration, a predicted mean vote (PMV) value of 0, minimization of age of air, and energy consumption. The present study represents a pioneering effort in integrating the Taguchi method, computational fluid dynamics (CFD), and grey relational analysis to concurrently optimize the influential variables for outdoor toilet ventilation systems through design and simulation. The results indicate that all four variables exhibit nearly equal importance. Ventilation rate demonstrates a dominant effect on ammonia concentration and significantly impacts the age of air and energy consumption, while supply air temperature noticeably influences PMV. The optimal scheme features an inlet at center top position, an outlet height of 0.2 m, a supply air temperature of 12 °C and a ventilation rate of 20 times/h. This scheme improves ammonia concentration by 18.9%, PMV by 6.8%, and age of air by 30.0% at a height of 0.5 m, while achieving respective improvements by 18.9%, 5.5%, and 22.2% at a height of 1.5 m. The BAPV roof system generates an annual electricity output of 582.02 kWh, which covers the energy consumption of 358.1 kWh for toilet ventilation, achieving self-sufficiency. This study aims to develop a zero-carbon solution for outdoor toilets that provides a safe, comfortable, and sanitary environment. Full article
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19 pages, 5715 KiB  
Article
Synergistic Impact on Indoor Air Quality: The Combined Use of Air Conditioners, Air Purifiers, and Fresh Air Systems
by Lizhi Jia, Jufeng Ge, Zhiqiang Wang, Wufeng Jin, Congcong Wang, Zhanwei Dong, Cheng Wang and Ren Wang
Buildings 2024, 14(6), 1562; https://doi.org/10.3390/buildings14061562 - 28 May 2024
Viewed by 1163
Abstract
As concerns about indoor air quality increase, air purifiers and fresh air systems are increasingly being used in conjunction with air conditioners in office buildings. To study the synergistic effects of multisystem joint operation on indoor air quality, this study used a combination [...] Read more.
As concerns about indoor air quality increase, air purifiers and fresh air systems are increasingly being used in conjunction with air conditioners in office buildings. To study the synergistic effects of multisystem joint operation on indoor air quality, this study used a combination of experimental and simulation methods to study the indoor particulate matter with a diameter of less than 2.5 µm (PM2.5) and carbon dioxide (CO2) concentrations under different operation conditions. The purification time and the PM2.5 concentration distribution under different conditions were compared with the condition in which the purifier was used alone. The results showed that the purification time required for the condition that the air conditioner runs together with the purifier was shortened by 15.2%. When the fresh air system is running together with the purifier, the purification time can be reduced by 30.4%. It was reduced by 32.6% when the three systems were operating at the same time. The PM2.5 concentration distribution under the joint operating condition was much more even than that under the condition in which the purifier was running alone. To analyze the impact on the CO2 distribution, the CO2 distributions under different joint operations were compared. The results show that the fresh air system can effectively dilute CO2 below 1000 ppm in 30 min. The air conditioner and purifier could help to mix the indoor air to provide a much more uniform indoor CO2 distribution. Full article
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16 pages, 7063 KiB  
Article
Analysis of Resistance Characteristics and Research into Resistance Reduction of a Tee Based on Field Synergy
by Yajing Yan, Chongfang Song, Wuxuan Pan, Jie Wang and Yifan Bai
Buildings 2024, 14(5), 1271; https://doi.org/10.3390/buildings14051271 - 1 May 2024
Cited by 1 | Viewed by 728
Abstract
The resistance loss and energy consumption when fluid flows through a tee in an HVAC system are severe. To improve energy efficiency and reduce carbon emissions, a novel tee with a U-shaped deflector is proposed, supported by experiments and numerical simulations. The resistance [...] Read more.
The resistance loss and energy consumption when fluid flows through a tee in an HVAC system are severe. To improve energy efficiency and reduce carbon emissions, a novel tee with a U-shaped deflector is proposed, supported by experiments and numerical simulations. The resistance reduction mechanism of the U-shaped deflector was analyzed according to the viscous dissipation principle and the field synergy principle. The resistance reduction of the novel tee with different deflector angles and a traditional tee were compared. The results show that the resistance loss of the tee was mainly due to the flow separation and deformation of the fluid in the main branch. The relationship between the local resistance coefficient and the diameter ratio of the main-branch pipe was exponential, and the relationship between the local resistance coefficient and the diameter ratio of the main straight pipe was linear. The total resistance loss reduction rate of the tee with the addition of a 26° deflector was the highest, reaching 72.4%, the volume-weighted average synergy angle increased by 1°, and the viscous dissipation decreased by 21.7%. This study provides a reference for the resistance reduction design of complex local components such as tees in HVAC systems. Full article
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13 pages, 1855 KiB  
Article
Preliminary Research on Outdoor Thermal Comfort Evaluation in Severe Cold Regions by Machine Learning
by Tianyu Xi, Ming Wang, Enjia Cao, Jin Li, Yong Wang and Salanke Umar Sa’ad
Buildings 2024, 14(1), 284; https://doi.org/10.3390/buildings14010284 - 20 Jan 2024
Cited by 3 | Viewed by 1909
Abstract
The thermal comfort evaluation of the urban environment arouses widespread concern among scholars, and research in this field is mostly based on thermal comfort evaluation indexes such as PMV, PET, SET, UTCI, etc. These thermal comfort index evaluation models are complex in the [...] Read more.
The thermal comfort evaluation of the urban environment arouses widespread concern among scholars, and research in this field is mostly based on thermal comfort evaluation indexes such as PMV, PET, SET, UTCI, etc. These thermal comfort index evaluation models are complex in the calculation process and poor in operability, which makes it difficult for people who lack a relevant knowledge background to understand, calculate, and apply them. The purpose of this study is to provide a simple, efficient, and easy-to-operate outdoor thermal comfort evaluation model for severe cold areas in China using a machine learning method. In this study, the physical environment parameters are obtained by field measurement, and individual information is obtained by a field questionnaire survey. The applicability of four machine learning models in outdoor thermal comfort evaluation is studied. A total of 320 questionnaires are collected. The results show that the correlation coefficients between predicted values and voting values of the extreme gradient lifting model, gradient lifting model, random forest model, and neural network model are 0.9313, 0.7148, 0.9115, and 0.5325, respectively. Further analysis of the extreme gradient model with the highest correlation coefficient shows that individual factors (such as residence time, distance between hometown and residence, clothing, age, height, and weight) and environmental factors (such as air humidity (RH), wind speed (v), air temperature (Ta), and black bulb temperature (Tg)) have different influences on thermal comfort evaluation. In summary, using a machine learning method to evaluate outdoor thermal comfort is simpler, more direct, and more efficient, and it can make up for the lack of consideration of complex individual factors in the evaluation method of thermal comfort index. The results have reference value and application value for the research of outdoor thermal comfort evaluation in severe cold areas of China. Full article
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