Pub Date : 2023-08-09DOI: 10.1080/23744731.2023.2247947
Youngbo Won, Donghyun Rim, R. Mistrick, W. Bahnfleth
Ultraviolet germicidal irradiation (UVGI) systems inactivate microorganisms indoors. Upper-room UVGI systems use wall- or ceiling-mounted fixtures to create an air disinfection zone above the occupied zone. The performance of upper-room UVGI systems varies with indoor airflow patterns induced by mechanical ventilation and thermal plumes from indoor heat sources. Little information is available on the effects of ventilation strategies on upper-room UVGI system performance for the control of viral aerosols in occupied spaces. This study simulated the effects of ventilation system characteristics in an office space on the ability of an upper-room UVGI system to inactivate viral aerosols with UV-C susceptibility representative of coronaviruses. UVGI reduced viral aerosol concentration by two orders of magnitude relative to the concentration without UVGI. Air change rates and air distribution strategy (mixing vs. displacement) had notable effects on the effectiveness of the UVGI system. For mixing ventilation, as the recirculation airflow rate increased from 0 to 5.3 h−1 for a room volume of 108 m3 with a fixed outdoor air change rate of 0.7 h−1, UVGI inactivation increased by 96.7%. Mixing ventilation with 100% outdoor air of 0.7 h−1 yielded airborne virus inactivation that was double that of displacement ventilation, due to enhanced air mixing.
{"title":"CFD modeling of room airflow effects on inactivation of aerosol SARS-CoV-2 by an upper-room ultraviolet germicidal irradiation (UVGI) system","authors":"Youngbo Won, Donghyun Rim, R. Mistrick, W. Bahnfleth","doi":"10.1080/23744731.2023.2247947","DOIUrl":"https://doi.org/10.1080/23744731.2023.2247947","url":null,"abstract":"Ultraviolet germicidal irradiation (UVGI) systems inactivate microorganisms indoors. Upper-room UVGI systems use wall- or ceiling-mounted fixtures to create an air disinfection zone above the occupied zone. The performance of upper-room UVGI systems varies with indoor airflow patterns induced by mechanical ventilation and thermal plumes from indoor heat sources. Little information is available on the effects of ventilation strategies on upper-room UVGI system performance for the control of viral aerosols in occupied spaces. This study simulated the effects of ventilation system characteristics in an office space on the ability of an upper-room UVGI system to inactivate viral aerosols with UV-C susceptibility representative of coronaviruses. UVGI reduced viral aerosol concentration by two orders of magnitude relative to the concentration without UVGI. Air change rates and air distribution strategy (mixing vs. displacement) had notable effects on the effectiveness of the UVGI system. For mixing ventilation, as the recirculation airflow rate increased from 0 to 5.3 h−1 for a room volume of 108 m3 with a fixed outdoor air change rate of 0.7 h−1, UVGI inactivation increased by 96.7%. Mixing ventilation with 100% outdoor air of 0.7 h−1 yielded airborne virus inactivation that was double that of displacement ventilation, due to enhanced air mixing.","PeriodicalId":21556,"journal":{"name":"Science and Technology for the Built Environment","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42018499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-07DOI: 10.1080/23744731.2023.2244337
Yilin Jiang, Junke Wang, Li Song
Many utility companies in the United States have introduced time-of-use (TOU) rates for homeowners with the goal of regulating electricity consumption during peak hours. The electrical appliances in homes include various thermostatically controlled devices, such as air conditioners (AC) for thermal comfort, and nonthermostatically controlled devices such as clothes washers. As a result, homeowners face the complicated challenge of economically operating multiple electrical appliances in their homes while maintaining comfort and convenience. This is usually due to the lack of an explicit understanding of the correlation between cost saving and the users’ comfort. To understand the correlation, this article is designed to construct a framework by integrating three major components: a multi-objective optimization method accommodating multiple competing goals with different weights, a learning-based system modeling approach describing the dynamics and thermal coupling effects of appliances, and a novel comfort index method differentiating preferred and acceptable thermal comfort. Our proposed framework can allow the indoor air temperature to fall into the "preferred" range with a marginal cost increase. The simulation result shows that an additional 8 h for the preferred thermal comfort can be achieved with a cost increase of only 1.77%.
{"title":"Quantitative analysis of cost savings and occupants’ preferences in grid-interactive smart home operation","authors":"Yilin Jiang, Junke Wang, Li Song","doi":"10.1080/23744731.2023.2244337","DOIUrl":"https://doi.org/10.1080/23744731.2023.2244337","url":null,"abstract":"Many utility companies in the United States have introduced time-of-use (TOU) rates for homeowners with the goal of regulating electricity consumption during peak hours. The electrical appliances in homes include various thermostatically controlled devices, such as air conditioners (AC) for thermal comfort, and nonthermostatically controlled devices such as clothes washers. As a result, homeowners face the complicated challenge of economically operating multiple electrical appliances in their homes while maintaining comfort and convenience. This is usually due to the lack of an explicit understanding of the correlation between cost saving and the users’ comfort. To understand the correlation, this article is designed to construct a framework by integrating three major components: a multi-objective optimization method accommodating multiple competing goals with different weights, a learning-based system modeling approach describing the dynamics and thermal coupling effects of appliances, and a novel comfort index method differentiating preferred and acceptable thermal comfort. Our proposed framework can allow the indoor air temperature to fall into the \"preferred\" range with a marginal cost increase. The simulation result shows that an additional 8 h for the preferred thermal comfort can be achieved with a cost increase of only 1.77%.","PeriodicalId":21556,"journal":{"name":"Science and Technology for the Built Environment","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43057398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-25DOI: 10.1080/23744731.2023.2239081
Jianqiao Mao, Dr Ryan Grammenos, K. Karagiannis
Energy efficiency and thermal comfort levels are key attributes to be considered in the design and implementation of a Heating, Ventilation and Air Conditioning (HVAC) system. With the increased availability of Internet of Things (IoT) devices, it is now possible to continuously monitor multiple variables that influence a user’s thermal comfort and the system’s energy efficiency, thus acting preemptively to optimize these factors. To this end, this paper reports on a case study with a two-fold aim; first, to analyze the performance of a conventional HVAC system through data analytics; secondly, to explore the use of interpretable machine learning techniques for HVAC predictive control. A new Interpretable Machine Learning (IML) algorithm called Permutation Feature-based Frequency Response Analysis (PF-FRA) is also proposed. Results demonstrate that the proposed model can generate accurate forecasts of Room Temperature (RT) levels by taking into account historical RT information, as well as additional environmental and time-series features. Our proposed model achieves 0.4017 °C and 0.9417 °C of Mean Absolute Error (MAE) for 1-h and 8-h ahead RT prediction, respectively. Tools such as surrogate models and Shapley graphs are employed to interpret the model’s global and local behaviors with the aim of increasing trust in the model.
{"title":"Data analysis and interpretable machine learning for HVAC predictive control: A case-study based implementation","authors":"Jianqiao Mao, Dr Ryan Grammenos, K. Karagiannis","doi":"10.1080/23744731.2023.2239081","DOIUrl":"https://doi.org/10.1080/23744731.2023.2239081","url":null,"abstract":"Energy efficiency and thermal comfort levels are key attributes to be considered in the design and implementation of a Heating, Ventilation and Air Conditioning (HVAC) system. With the increased availability of Internet of Things (IoT) devices, it is now possible to continuously monitor multiple variables that influence a user’s thermal comfort and the system’s energy efficiency, thus acting preemptively to optimize these factors. To this end, this paper reports on a case study with a two-fold aim; first, to analyze the performance of a conventional HVAC system through data analytics; secondly, to explore the use of interpretable machine learning techniques for HVAC predictive control. A new Interpretable Machine Learning (IML) algorithm called Permutation Feature-based Frequency Response Analysis (PF-FRA) is also proposed. Results demonstrate that the proposed model can generate accurate forecasts of Room Temperature (RT) levels by taking into account historical RT information, as well as additional environmental and time-series features. Our proposed model achieves 0.4017 °C and 0.9417 °C of Mean Absolute Error (MAE) for 1-h and 8-h ahead RT prediction, respectively. Tools such as surrogate models and Shapley graphs are employed to interpret the model’s global and local behaviors with the aim of increasing trust in the model.","PeriodicalId":21556,"journal":{"name":"Science and Technology for the Built Environment","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47950823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-21DOI: 10.1080/23744731.2023.2239080
I. Pittana, F. Morandi, F. Cappelletti, A. Gasparella, Athanasios Tzempelikos
Students in classrooms are exposed to environmental stimuli in the thermal, visual, acoustic and air quality domains, which affect their overall comfort and performance. Therefore, in recent studies, questionnaires are used to collect information about subjective perceptions and investigate links with physical parameters. Most field studies in educational buildings either focus on a single comfort domain, or consider multiple domains but provide inconsistent questions among the 4 domains (i.e., IAQ, thermal, visual and acoustic). Very few studies have investigated cross-domain effects in a consistent manner, considering satisfaction, comfort and perception aspects. To address this research gap, a survey with consistent questions among the 4 comfort domains was designed and used to collect more than 900 subjective responses from students. The analysis of subjective data together with objective measurements allows: (i) correlating the environmental physical parameters and students’ perception in each of the comfort domains; (ii) understanding the students’ preferred environmental conditions; and (iii) understanding cross-domain effects, i.e., the effects between the average conditions and the mean vote expressed for another domain. The results show that air temperature, illuminance and sound pressure level are correlated with the sensation in the respective domains, in contrast to CO2 concentration. Regarding cross-effects, the study confirms interference of CO2 concentration and illuminance on thermal sensation as well as the effect of sound pressure level on visual sensation.
{"title":"Within- and cross-domain effects of environmental factors on students’ perception in educational buildings","authors":"I. Pittana, F. Morandi, F. Cappelletti, A. Gasparella, Athanasios Tzempelikos","doi":"10.1080/23744731.2023.2239080","DOIUrl":"https://doi.org/10.1080/23744731.2023.2239080","url":null,"abstract":"Students in classrooms are exposed to environmental stimuli in the thermal, visual, acoustic and air quality domains, which affect their overall comfort and performance. Therefore, in recent studies, questionnaires are used to collect information about subjective perceptions and investigate links with physical parameters. Most field studies in educational buildings either focus on a single comfort domain, or consider multiple domains but provide inconsistent questions among the 4 domains (i.e., IAQ, thermal, visual and acoustic). Very few studies have investigated cross-domain effects in a consistent manner, considering satisfaction, comfort and perception aspects. To address this research gap, a survey with consistent questions among the 4 comfort domains was designed and used to collect more than 900 subjective responses from students. The analysis of subjective data together with objective measurements allows: (i) correlating the environmental physical parameters and students’ perception in each of the comfort domains; (ii) understanding the students’ preferred environmental conditions; and (iii) understanding cross-domain effects, i.e., the effects between the average conditions and the mean vote expressed for another domain. The results show that air temperature, illuminance and sound pressure level are correlated with the sensation in the respective domains, in contrast to CO2 concentration. Regarding cross-effects, the study confirms interference of CO2 concentration and illuminance on thermal sensation as well as the effect of sound pressure level on visual sensation.","PeriodicalId":21556,"journal":{"name":"Science and Technology for the Built Environment","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46832438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-14DOI: 10.1080/23744731.2023.2235971
Yapan Liu, Bing Dong, Tianzhen Hong, B. Olesen, Tom Lawrence, Zheng O’Neill
In developed countries, people spend nearly 90% of their time in buildings or during transportation. Recent research studies demonstrated that occupant behaviors have a significant impact on building performance in relation to the indoor environment and energy use. This paper presents the ASHRAE Global Occupant Behavior Database which aims to advance the knowledge and understanding of realistic occupancy patterns and human-building interactions with building systems. This database includes 34 field-measured occupant behavior datasets for both commercial and residential buildings, contributed by researchers from 15 countries and 39 institutions covering 10 different climate zones. It includes occupancy patterns, occupant behaviors, indoor and outdoor environment measurements. The database is open source, a public website was developed for the users to interactively explore, query, and download datasets. This paper focuses on a detailed data analysis to investigate patterns of nine occupant behavior types, examining impacted factors such as building type, country, and climate zone. EnergyPlus simulations have been implemented based on the occupancy profiles derived from this database, and results showed overall building electricity consumption can be reduced up to around 27% in Summer and around 10% in Winter.
{"title":"ASHRAE URP-1883: Development and Analysis of the ASHRAE Global Occupant Behavior Database","authors":"Yapan Liu, Bing Dong, Tianzhen Hong, B. Olesen, Tom Lawrence, Zheng O’Neill","doi":"10.1080/23744731.2023.2235971","DOIUrl":"https://doi.org/10.1080/23744731.2023.2235971","url":null,"abstract":"In developed countries, people spend nearly 90% of their time in buildings or during transportation. Recent research studies demonstrated that occupant behaviors have a significant impact on building performance in relation to the indoor environment and energy use. This paper presents the ASHRAE Global Occupant Behavior Database which aims to advance the knowledge and understanding of realistic occupancy patterns and human-building interactions with building systems. This database includes 34 field-measured occupant behavior datasets for both commercial and residential buildings, contributed by researchers from 15 countries and 39 institutions covering 10 different climate zones. It includes occupancy patterns, occupant behaviors, indoor and outdoor environment measurements. The database is open source, a public website was developed for the users to interactively explore, query, and download datasets. This paper focuses on a detailed data analysis to investigate patterns of nine occupant behavior types, examining impacted factors such as building type, country, and climate zone. EnergyPlus simulations have been implemented based on the occupancy profiles derived from this database, and results showed overall building electricity consumption can be reduced up to around 27% in Summer and around 10% in Winter.","PeriodicalId":21556,"journal":{"name":"Science and Technology for the Built Environment","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47948209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-12DOI: 10.1080/23744731.2023.2235970
Jian Sun, T. Kuruganti, Brian Fricke, Yanfei Li, S. Xuan, Wenhua Li
With the increasing concerns over climate change and carbon emissions, fault detection and diagnostics (FDD) of low–global warming potential (GWP) refrigerant supermarket refrigeration systems has gained great attention from academic and industrial sectors. Various FDD approaches have been developed to detect, identify, and diagnose faults to save energy, improve food quality, and protect the environment. To mitigate the difficulty of collecting high-quality steady-state operational data in field operations faced by most model-based FDD methods, this study developed dynamic models of a low–GWP refrigerant (CO2) supermarket refrigeration system. The model accuracy was validated using manufacturer data and experimental data. Simulations were conducted to predict the system dynamic response under two common operational faults—evaporator air path blockage fault and the display case door open fault—to identify fault patterns and define key dynamic behavior indexes for supporting FDD algorithm development.
{"title":"Dynamic model-based feature extraction for fault detection and diagnosis of a supermarket refrigeration system1","authors":"Jian Sun, T. Kuruganti, Brian Fricke, Yanfei Li, S. Xuan, Wenhua Li","doi":"10.1080/23744731.2023.2235970","DOIUrl":"https://doi.org/10.1080/23744731.2023.2235970","url":null,"abstract":"With the increasing concerns over climate change and carbon emissions, fault detection and diagnostics (FDD) of low–global warming potential (GWP) refrigerant supermarket refrigeration systems has gained great attention from academic and industrial sectors. Various FDD approaches have been developed to detect, identify, and diagnose faults to save energy, improve food quality, and protect the environment. To mitigate the difficulty of collecting high-quality steady-state operational data in field operations faced by most model-based FDD methods, this study developed dynamic models of a low–GWP refrigerant (CO2) supermarket refrigeration system. The model accuracy was validated using manufacturer data and experimental data. Simulations were conducted to predict the system dynamic response under two common operational faults—evaporator air path blockage fault and the display case door open fault—to identify fault patterns and define key dynamic behavior indexes for supporting FDD algorithm development.","PeriodicalId":21556,"journal":{"name":"Science and Technology for the Built Environment","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46730451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-11DOI: 10.1080/23744731.2023.2234251
Xiaozhou Wu, Hao Gao, Diqi Yu, Jiying Liu, Jie Gao, Zhen Tian, Xiangli Li
A hybrid system with a ceiling cooling (CC) system and a mechanical ventilation system has been extensively applied in modern office buildings with large sensible cooling loads. Both the chilled ceiling and supply air may greatly influence indoor air distribution in the office room. Therefore in this paper, indoor air distribution performances in a ceiling cooling room with underfloor air distribution (UFAD) or mixing ventilation (MV) were sensitively analyzed by numerical simulation. Indoor air distribution performances, which were evaluated by the heat removal effectiveness, contamination removal effectiveness and air diffusion performance index, were quantitatively analyzed by using the orthogonal experiment method. The results showed that when the supply air temperature was 18 °C-24 °C for CC + UFAD and 16 °C-21 °C for CC + MV, the heat removal effectiveness changed by 0.01 with 1 °C increment of supply air temperature or ceiling surface temperature, and the contamination removal effectiveness increased by 0.001-0.002 with 1 W/m2 increment of external sensible cooling load. Moreover, the air diffusion performance index increased by 0.6%-1.1% with 1 °C increment of supply air temperature, and it decreased by 0.02% with 1 W/m2 increment of internal sensible cooling load. Finally, formulas of heat removal effectiveness, contamination removal effectiveness and air diffusion performance index for CC + UFAD and CC + MV were obtained by fitting, and they may provide guidance for the optimal design and control of a hybrid system with a ceiling cooling system and a mechanical ventilation system.
{"title":"Sensitivity Analysis of Indoor Air Distribution Performances in an Office Room with Ceiling Cooling and Mechanical Ventilation","authors":"Xiaozhou Wu, Hao Gao, Diqi Yu, Jiying Liu, Jie Gao, Zhen Tian, Xiangli Li","doi":"10.1080/23744731.2023.2234251","DOIUrl":"https://doi.org/10.1080/23744731.2023.2234251","url":null,"abstract":"A hybrid system with a ceiling cooling (CC) system and a mechanical ventilation system has been extensively applied in modern office buildings with large sensible cooling loads. Both the chilled ceiling and supply air may greatly influence indoor air distribution in the office room. Therefore in this paper, indoor air distribution performances in a ceiling cooling room with underfloor air distribution (UFAD) or mixing ventilation (MV) were sensitively analyzed by numerical simulation. Indoor air distribution performances, which were evaluated by the heat removal effectiveness, contamination removal effectiveness and air diffusion performance index, were quantitatively analyzed by using the orthogonal experiment method. The results showed that when the supply air temperature was 18 °C-24 °C for CC + UFAD and 16 °C-21 °C for CC + MV, the heat removal effectiveness changed by 0.01 with 1 °C increment of supply air temperature or ceiling surface temperature, and the contamination removal effectiveness increased by 0.001-0.002 with 1 W/m2 increment of external sensible cooling load. Moreover, the air diffusion performance index increased by 0.6%-1.1% with 1 °C increment of supply air temperature, and it decreased by 0.02% with 1 W/m2 increment of internal sensible cooling load. Finally, formulas of heat removal effectiveness, contamination removal effectiveness and air diffusion performance index for CC + UFAD and CC + MV were obtained by fitting, and they may provide guidance for the optimal design and control of a hybrid system with a ceiling cooling system and a mechanical ventilation system.","PeriodicalId":21556,"journal":{"name":"Science and Technology for the Built Environment","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44473855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-10DOI: 10.1080/23744731.2023.2234231
K. Ejenakevwe, Junke Wang, Yilin Jiang, Li Song, Kini Roshan
While automated fault detection and diagnosis (AFDD) in residential heating, ventilation, and air-conditioning (HVAC) using smart thermostat data is gaining increasing attention in recent times, it still requires in-depth investigation for market adoption, especially with real-life data. This paper proposes an Internet of Things (IoT) - based approach that adds a smart sensor to the smart thermostat data to carry out AFDD. The approach uses a model which predicts enthalpy change across the evaporator and compares the prediction to the measured enthalpy change. Deviations which exceed analytically determined thresholds then signal faults in the HVAC system. The faults detected are either installation related or degradation related. Experimental tests were carried out in four homes located in Norman, Oklahoma. From the tests, installation issues like indoor/outdoor mismatch were detected in two homes, while a 30% low charge and low indoor airflow rate were detected in one home. The results show that the proposed AFDD algorithm was able to successfully detect two prevalent faults, namely low indoor airflow and low refrigerant charge. Unlike most of the smart thermostat-based approaches, the proposed IoT-based approach can detect and diagnose both faults but only require one additional sensor which is provided by smart thermostat manufacturers.
{"title":"Automated Fault Detection and Diagnosis of Airflow and Refrigerant Charge Faults in Residential HVAC systems using IoT-Enabled Measurements","authors":"K. Ejenakevwe, Junke Wang, Yilin Jiang, Li Song, Kini Roshan","doi":"10.1080/23744731.2023.2234231","DOIUrl":"https://doi.org/10.1080/23744731.2023.2234231","url":null,"abstract":"While automated fault detection and diagnosis (AFDD) in residential heating, ventilation, and air-conditioning (HVAC) using smart thermostat data is gaining increasing attention in recent times, it still requires in-depth investigation for market adoption, especially with real-life data. This paper proposes an Internet of Things (IoT) - based approach that adds a smart sensor to the smart thermostat data to carry out AFDD. The approach uses a model which predicts enthalpy change across the evaporator and compares the prediction to the measured enthalpy change. Deviations which exceed analytically determined thresholds then signal faults in the HVAC system. The faults detected are either installation related or degradation related. Experimental tests were carried out in four homes located in Norman, Oklahoma. From the tests, installation issues like indoor/outdoor mismatch were detected in two homes, while a 30% low charge and low indoor airflow rate were detected in one home. The results show that the proposed AFDD algorithm was able to successfully detect two prevalent faults, namely low indoor airflow and low refrigerant charge. Unlike most of the smart thermostat-based approaches, the proposed IoT-based approach can detect and diagnose both faults but only require one additional sensor which is provided by smart thermostat manufacturers.","PeriodicalId":21556,"journal":{"name":"Science and Technology for the Built Environment","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49389813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Local exhaust systems based on range hoods are widely used to reduce cooking oil fumes (COF) of kitchen spaces. This work proposes a range-hood-integrated air cleaner to improve air distribution in residential kitchens and reduce individual inhalation exposure to COF. Effects of hood exhaust rates, cooking–heating intensities, and airflow parameters of the air cleaner on the volume-averaged concentration (VAC) of kitchen space and the intake fraction (IF) are discussed through orthogonal experimental design, and significant factors are the hood exhaust rate, the air supply velocity, and angle of the air cleaner by evaluating significance levels. Optimal airflow parameters of the air cleaner are obtained through single-factor analysis, and VAC is reduced by approximately 90% compared with the single range-hood exhaust system. The energy-saving potential of the air cleaner is identified and evaluated using the concept of the equivalent exhaust rate. The air cleaner is more conducive to creating a comfortable kitchen environment and reducing heat transfer load. This work provides a new solution for optimizing air distribution in highly polluted kitchen environments.
{"title":"Indoor air quality and energy-saving potential improvement of a range-hood-integrated air cleaner","authors":"Yumei Hou, Yukun Xu, Zhi Liu, Ziyin Lin, Wuhao Xie, Changsheng Cao, Zhiwei Zheng, Jun Gao","doi":"10.1080/23744731.2023.2234238","DOIUrl":"https://doi.org/10.1080/23744731.2023.2234238","url":null,"abstract":"Local exhaust systems based on range hoods are widely used to reduce cooking oil fumes (COF) of kitchen spaces. This work proposes a range-hood-integrated air cleaner to improve air distribution in residential kitchens and reduce individual inhalation exposure to COF. Effects of hood exhaust rates, cooking–heating intensities, and airflow parameters of the air cleaner on the volume-averaged concentration (VAC) of kitchen space and the intake fraction (IF) are discussed through orthogonal experimental design, and significant factors are the hood exhaust rate, the air supply velocity, and angle of the air cleaner by evaluating significance levels. Optimal airflow parameters of the air cleaner are obtained through single-factor analysis, and VAC is reduced by approximately 90% compared with the single range-hood exhaust system. The energy-saving potential of the air cleaner is identified and evaluated using the concept of the equivalent exhaust rate. The air cleaner is more conducive to creating a comfortable kitchen environment and reducing heat transfer load. This work provides a new solution for optimizing air distribution in highly polluted kitchen environments.","PeriodicalId":21556,"journal":{"name":"Science and Technology for the Built Environment","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47020898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-10DOI: 10.1080/23744731.2023.2234226
Sarah Mollier, Charles-Antoine Deslauriers, J. Tamasauskas, Solange Prud’homme, M. Kegel
Heat pumps offer an efficient electrification of space heating but can significantly vary the magnitude and duration of house-level electrical demand, especially when replacing fuel-fired heating systems. This paper uses a simulation-based approach to simulate the electrical demand variations of air-source heat pumps (ASHPs) in six Canadian cities (Halifax, Montreal, Toronto, Winnipeg, Vancouver, Whitehorse) when replacing natural gas or electric baseboard heating. Detailed housing models (including a highly zoned model capturing room-based baseboard controls) are combined with a series of custom non-HVAC load profiles and an enhanced data-driven ASHP model to assess the variation that occupancy, climate, and type of heat pump integration can have on electrical demand. ASHPs are shown to increase the magnitude and duration of electrical demand when replacing natural gas furnaces, although selection of climate-appropriate systems (e.g. cold climate units in colder climates) may reduce the magnitude and coincidence of this demand. Where heat pumps replace electric baseboards, HVAC demand may decrease by up to 3.4 kW during ASHP operating periods and remain equal when the ambient temperatures are below the ASHP cutoff. A study of simple mitigation measures through varying temperature setpoints demonstrates the ability of proper controls to reduce electrical demand during high-demand periods.
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