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1.
Environ Res ; 203: 111765, 2022 01.
Artigo em Inglês | MEDLINE | ID: mdl-34331921

RESUMO

COVID-19 forced the human population to rethink its way of living. The threat posed by the potential spread of the virus via an airborne transmission mode through ventilation systems in buildings and enclosed spaces has been recognized as a major concern. To mitigate this threat, researchers have explored different technologies and methods that can remove or decrease the concentration of the virus in ventilation systems and enclosed spaces. Although many technologies and methods have already been researched, some are currently available on the market, but their effectiveness and safety concerns have not been fully investigated. To acquire a broader view and collective perspective of the current research and development status, this paper discusses a comprehensive review of various workable technologies and methods to combat airborne viruses, e.g., COVID-19, in ventilation systems and enclosed spaces. These technologies and methods include an increase in ventilation, high-efficiency air filtration, ionization of the air, environmental condition control, ultraviolet germicidal irradiation, non-thermal plasma and reactive oxygen species, filter coatings, chemical disinfectants, and heat inactivation. Research gaps have been identified and discussed, and recommendations for applying such technologies and methods have also been provided in this article.


Assuntos
COVID-19 , Ar Condicionado , Humanos , Probabilidade , SARS-CoV-2 , Ventilação
2.
Sci Total Environ ; 804: 150249, 2022 Jan 15.
Artigo em Inglês | MEDLINE | ID: mdl-34798754

RESUMO

Occupancy schedules and density can have a substantial influence on building plug, lighting, and air conditioning energy usage. In recent years, the study related to occupancy and its impact on building energy consumption has gained momentum and is also promoted by ASHRAE as it has created a multi-disciplinary group to encourage a comprehensive study of occupant behaviour in buildings. Past studies suggest that building systems do not consume the same energy and provide similar Indoor Environmental Quality (IEQ) to their designed specifications due to inaccurate assumptions of occupants and their behaviour. Supplying ASHRAE 62.1 specified minimum required ventilation based on accurate occupancy may lead to significant air-conditioning energy savings. However, the same strategy is not suitable in the current time since minimum required ventilation may not be sufficient to mitigate the SARS-CoV-2 virus spread in confined spaces. High-temperature cooling augmented with elevated air movement across an acceptable range of velocity can maintain the health and comfort of occupants by providing higher ventilation and without an energy penalty. The analysis of the literature highlights strengths, weaknesses, and key observations about the existing occupancy monitoring and occupancy-based building system control methods to help in the direction of future occupancy-based research.


Assuntos
Poluição do Ar em Ambientes Fechados , COVID-19 , Ar Condicionado , Humanos , SARS-CoV-2 , Ventilação
3.
Sci Total Environ ; 807(Pt 1): 150754, 2022 Feb 10.
Artigo em Inglês | MEDLINE | ID: mdl-34619223

RESUMO

The role of air filters is becoming increasingly important due to the threat of air pollution to public health. Understanding the lifetime of air filters is essential for assessing air pollution exposure. However, the effects of common environmental chemicals on filter performance have not been explored. Air filters in ventilation systems and air purifiers are commonly exposed to cigarette smoke aerosols. Moreover, due to the coronavirus pandemic, people are more likely to be in close proximity with smokers while wearing face masks, such that their masks will be exposed to cigarette aerosols. In this study, we applied a stepwise approach to analyze the effects of cigarette smoke on the filtration performance of electret melt-blown filter media that are commonly used to create face masks. We found that cigarette aerosols dramatically reduced filtration efficiency, while standard test particles of a similar loading weight did not affect filtration efficiency. After loading up to 204 µg/cm2 of cigarette smoke on 100 cm2 of electret filter medium, the filtration efficiency of some filters decreased from 92.5% to 33.3% (-Δ59.2%). Interestingly, we founded no changes in pressure drop following cigarette smoke exposure despite the reduction in filtration efficiency, suggesting that cigarette smoke aerosols significantly impact the electrostatic charge properties of the filters. Our results indicate that the lifetime of commonly-used air filters may be much shorter than expected and that people may unknowingly be directly exposed to airborne pollutants.


Assuntos
Filtros de Ar , Ar Condicionado , Filtração , Humanos , Fumaça/efeitos adversos , Fumar
4.
Viruses ; 13(12)2021 12 17.
Artigo em Inglês | MEDLINE | ID: mdl-34960804

RESUMO

There is strong evidence associating the indoor environment with transmission of SARS-CoV-2, the virus that causes COVID-19. SARS-CoV-2 can spread by exposure to droplets and very fine aerosol particles from respiratory fluids that are released by infected persons. Layered mitigation strategies, including but not limited to maintaining physical distancing, adequate ventilation, universal masking, avoiding overcrowding, and vaccination, have shown to be effective in reducing the spread of SARS-CoV-2 within the indoor environment. Here, we examine the effect of mitigation strategies on reducing the risk of exposure to simulated respiratory aerosol particles within a classroom-style meeting room. To quantify exposure of uninfected individuals (Recipients), surrogate respiratory aerosol particles were generated by a breathing simulator with a headform (Source) that mimicked breath exhalations. Recipients, represented by three breathing simulators with manikin headforms, were placed in a meeting room and affixed with optical particle counters to measure 0.3-3 µm aerosol particles. Universal masking of all breathing simulators with a 3-ply cotton mask reduced aerosol exposure by 50% or more compared to scenarios with simulators unmasked. While evaluating the effect of Source placement, Recipients had the highest exposure at 0.9 m in a face-to-face orientation. Ventilation reduced exposure by approximately 5% per unit increase in air change per hour (ACH), irrespective of whether increases in ACH were by the HVAC system or portable HEPA air cleaners. The results demonstrate that mitigation strategies, such as universal masking and increasing ventilation, reduce personal exposure to respiratory aerosols within a meeting room. While universal masking remains a key component of a layered mitigation strategy of exposure reduction, increasing ventilation via system HVAC or portable HEPA air cleaners further reduces exposure.


Assuntos
Poluição do Ar em Ambientes Fechados/prevenção & controle , Exposição por Inalação/prevenção & controle , Máscaras , Distanciamento Físico , Ventilação , Ar Condicionado , COVID-19/prevenção & controle , Humanos , SARS-CoV-2/isolamento & purificação
5.
Sensors (Basel) ; 21(24)2021 Dec 07.
Artigo em Inglês | MEDLINE | ID: mdl-34960257

RESUMO

The malfunctioning of the heating, ventilating, and air conditioning (HVAC) system is considered to be one of the main challenges in modern buildings. Due to the complexity of the building management system (BMS) with operational data input from a large number of sensors used in HVAC system, the faults can be very difficult to detect in the early stage. While numerous fault detection and diagnosis (FDD) methods with the use of statistical modeling and machine learning have revealed prominent results in recent years, early detection remains a challenging task since many current approaches are unfeasible for diagnosing some HVAC faults and have accuracy performance issues. In view of this, this study presents a novel hybrid FDD approach by combining random forest (RF) and support vector machine (SVM) classifiers for the application of FDD for the HVAC system. Experimental results demonstrate that our proposed hybrid random forest-support vector machine (HRF-SVM) outperforms other methods with higher prediction accuracy (98%), despite that the fault symptoms were insignificant. Furthermore, the proposed framework can reduce the significant number of sensors required and work well with the small number of faulty training data samples available in real-world applications.


Assuntos
Ar Condicionado , Máquina de Vetores de Suporte , Calefação , Aprendizado de Máquina , Modelos Estatísticos
6.
PLoS One ; 16(11): e0257549, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34758032

RESUMO

Particulate generation occurs during exercise-induced exhalation, and research on this topic is scarce. Moreover, infection-control measures are inadequately implemented to avoid particulate generation. A laminar airflow ventilation system (LFVS) was developed to remove respiratory droplets released during treadmill exercise. This study aimed to investigate the relationship between the number of aerosols during training on a treadmill and exercise intensity and to elucidate the effect of the LFVS on aerosol removal during anaerobic exercise. In this single-center observational study, the exercise tests were performed on a treadmill at Running Science Lab in Japan on 20 healthy subjects (age: 29±12 years, men: 80%). The subjects had a broad spectrum of aerobic capacities and fitness levels, including athletes, and had no comorbidities. All of them received no medication. The exercise intensity was increased by 1-km/h increments until the heart rate reached 85% of the expected maximum rate and then maintained for 10 min. The first 10 subjects were analyzed to examine whether exercise increased the concentration of airborne particulates in the exhaled air. For the remaining 10 subjects, the LFVS was activated during constant-load exercise to compare the number of respiratory droplets before and after LFVS use. During exercise, a steady amount of particulates before the lactate threshold (LT) was followed by a significant and gradual increase in respiratory droplets after the LT, particularly during anaerobic exercise. Furthermore, respiratory droplets ≥0.3 µm significantly decreased after using LFVS (2120800±759700 vs. 560 ± 170, p<0.001). The amount of respiratory droplets significantly increased after LT. The LFVS enabled a significant decrease in respiratory droplets during anaerobic exercise in healthy subjects. This study's findings will aid in exercising safely during this pandemic.


Assuntos
Ar Condicionado/métodos , COVID-19/prevenção & controle , Exercício Físico/fisiologia , Material Particulado/química , Adulto , Aerossóis/química , Filtros de Ar , Limiar Anaeróbio/fisiologia , COVID-19/metabolismo , Teste de Esforço/métodos , Expiração/fisiologia , Feminino , Frequência Cardíaca/fisiologia , Humanos , Japão , Ácido Láctico/metabolismo , Masculino , Consumo de Oxigênio/fisiologia , Respiração , Sistema Respiratório/fisiopatologia , Corrida/fisiologia , SARS-CoV-2/patogenicidade , Ventilação/métodos
7.
PLoS Comput Biol ; 17(10): e1009474, 2021 10.
Artigo em Inglês | MEDLINE | ID: mdl-34662342

RESUMO

The role of heating, ventilation, and air-conditioning (HVAC) systems in the transmission of SARS-CoV-2 is unclear. To address this gap, we simulated the release of SARS-CoV-2 in a multistory office building and three social gathering settings (bar/restaurant, nightclub, wedding venue) using a well-mixed, multi-zone building model similar to those used by Wells, Riley, and others. We varied key factors of HVAC systems, such as the Air Changes Per Hour rate (ACH), Fraction of Outside Air (FOA), and Minimum Efficiency Reporting Values (MERV) to examine their effect on viral transmission, and additionally simulated the protective effects of in-unit ultraviolet light decontamination (UVC) and separate in-room air filtration. In all building types, increasing the ACH reduced simulated infections, and the effects were seen even with low aerosol emission rates. However, the benefits of increasing the fraction of outside air and filter efficiency rating were greatest when the aerosol emission rate was high. UVC filtration improved the performance of typical HVAC systems. In-room filtration in an office setting similarly reduced overall infections but worked better when placed in every room. Overall, we found little evidence that HVAC systems facilitate SARS-CoV-2 transmission; most infections in the simulated office occurred near the emission source, with some infections in individuals temporarily visiting the release zone. HVAC systems only increased infections in one scenario involving a marginal increase in airflow in a poorly ventilated space, which slightly increased the likelihood of transmission outside the release zone. We found that improving air circulation rates, increasing filter MERV rating, increasing the fraction of outside air, and applying UVC radiation and in-room filtration may reduce SARS-CoV-2 transmission indoors. However, these mitigation measures are unlikely to provide a protective benefit unless SARS-CoV-2 aerosol emission rates are high (>1,000 Plaque-forming units (PFU) / min).


Assuntos
Ar Condicionado , COVID-19/transmissão , Calefação , SARS-CoV-2 , Ventilação , Aerossóis , Microbiologia do Ar , Movimentos do Ar , COVID-19/prevenção & controle , COVID-19/virologia , Biologia Computacional , Simulação por Computador , Humanos , Modelos Biológicos , Pandemias , SARS-CoV-2/efeitos da radiação , Interação Social , Raios Ultravioleta , Local de Trabalho
8.
BMJ Open ; 11(10): e047772, 2021 10 12.
Artigo em Inglês | MEDLINE | ID: mdl-34642190

RESUMO

OBJECTIVES: In COVID-19, transfer of respiratory materials transmits disease and drives the pandemic but the interplay of droplet and aerosol physics, physiology and environment is not fully understood. To advance understanding of disease transmission mechanisms and to find novel exposure minimisation strategies, we studied cough-driven material transport modes and the efficacy of control strategies. DESIGN: Computer simulations and real-world experiments were used for integrating an intensive care setting, multiphysics and physiology. Patient-focused airflow management and air purification strategies were examined computationally and validated by submicron particle exhalation imaging in volunteers. SETTING: Hospital setting during a respiratory virus pandemic with transmission by respiratory droplets and aerosols. PARTICIPANTS: Healthy volunteers. OUTCOME MEASURES: Distribution of, and exposure to, potentially infectious respiratory secretions. RESULTS: Respiratory materials ejected by cough exhibited four transport modes: long-distance ballistic, short-distance ballistic, 'jet rider' and aerosol modes. Interaction with air conditioning driven flow contaminated a hospital room rapidly. Different than large droplets or aerosols, jet rider droplets travelled with the turbulent air jet initially, but fell out at a distance, were not well eliminated by air conditioning and exposed bystanders at larger distance and longer time; their size predisposes them to preferential capture in the nasal mucosa, the primordial COVID-19 infection site. 'Cough shields' captured large droplets but induced lateral dispersion of aerosols and jet riders. An air purification device alone had limited efficacy. A 'Shield and Sink' approach combining cough shields with 'virus sinks' minimised exposure to all secretions in modelling and real-life experiments. CONCLUSIONS: Jet riders have characteristics of highly efficient respiratory infection vectors and may play a role in COVID-19 transmission. Exposure to all droplet types can be minimised through an easily implemented Shield and Sink strategy.


Assuntos
Ar Condicionado , COVID-19 , Aerossóis , Hospitais , Humanos , SARS-CoV-2
9.
Nature ; 598(7880): 308-314, 2021 10.
Artigo em Inglês | MEDLINE | ID: mdl-34646000

RESUMO

Estimates of global economic damage caused by carbon dioxide (CO2) emissions can inform climate policy1-3. The social cost of carbon (SCC) quantifies these damages by characterizing how additional CO2 emissions today impact future economic outcomes through altering the climate4-6. Previous estimates have suggested that large, warming-driven increases in energy expenditures could dominate the SCC7,8, but they rely on models9-11 that are spatially coarse and not tightly linked to data2,3,6,7,12,13. Here we show that the release of one ton of CO2 today is projected to reduce total future energy expenditures, with most estimates valued between -US$3 and -US$1, depending on discount rates. Our results are based on an architecture that integrates global data, econometrics and climate science to estimate local damages worldwide. Notably, we project that emerging economies in the tropics will dramatically increase electricity consumption owing to warming, which requires critical infrastructure planning. However, heating reductions in colder countries offset this increase globally. We estimate that 2099 annual global electricity consumption increases by about 4.5 exajoules (7 per cent of current global consumption) per one-degree-Celsius increase in global mean surface temperature (GMST), whereas direct consumption of other fuels declines by about 11.3 exajoules (7 per cent of current global consumption) per one-degree-Celsius increase in GMST. Our finding of net savings contradicts previous research7,8, because global data indicate that many populations will remain too poor for most of the twenty-first century to substantially increase energy consumption in response to warming. Importantly, damage estimates would differ if poorer populations were given greater weight14.


Assuntos
Dióxido de Carbono/economia , Mudança Climática/economia , Mudança Climática/estatística & dados numéricos , Fontes Geradoras de Energia/economia , Fontes Geradoras de Energia/estatística & dados numéricos , Fatores Socioeconômicos , Temperatura , Ar Condicionado/economia , Ar Condicionado/estatística & dados numéricos , Ciclo do Carbono , Dióxido de Carbono/metabolismo , Eletricidade , Calefação/economia , Calefação/estatística & dados numéricos , História do Século XXI , Atividades Humanas , Pobreza/economia , Pobreza/estatística & dados numéricos , Ciências Sociais
10.
Sensors (Basel) ; 21(19)2021 Sep 29.
Artigo em Inglês | MEDLINE | ID: mdl-34640847

RESUMO

Research on optimal markers for infrared imaging and differences in their characteristics in the presence of heat sources has not yet been performed. This study investigates optimal material combinations for developing an accurate and detachable infrared marker for multiple conditions in the medium wave infrared (MWIR) region. Based on four requirements, 11 material combinations are systematically evaluated. Consequently, the optimal marker differs in relation to the presence of specular reflection components. Metal-insulator markers are suitable under non-heating and hot-air heating conditions without reflection components, although a printed marker made of copier paper is captured more clearly than metal-insulator markers during heating, using an optical radiation heating source with reflection components. Our findings can be applied in structural health monitoring and multi-modal projection involving heat sources.


Assuntos
Calefação , Temperatura Alta , Ar Condicionado
11.
J Acoust Soc Am ; 150(4): 3149, 2021 10.
Artigo em Inglês | MEDLINE | ID: mdl-34717455

RESUMO

Exposure to noise-or unwanted sound-is considered a major public health issue in the United States and internationally. Previous work has shown that even acute noise exposure can influence physiological response in humans and that individuals differ markedly in their susceptibility to noise. Recent research also suggests that specific acoustic properties of noise may have distinct effects on human physiological response. Much of the existing research on physiological response to noise consists of laboratory studies using very simple acoustic stimuli-like white noise or tone bursts-or field studies of longer-term workplace noise exposure that may neglect acoustic properties of the noise entirely. By using laboratory exposure to realistic heating, ventilation, and air conditioning (HVAC) noise, the current study explores the interaction between acoustic properties of annoying noise and individual response to working in occupational noise. This study assessed autonomic response to two acoustically distinct noises while participants performed cognitively demanding work. Results showed that the two HVAC noises affected physiological arousal in different ways. Individual differences in physiological response to noise as a function of noise sensitivity were also observed. Further research is necessary to link specific acoustic characteristics with differential physiological responses in humans.


Assuntos
Ar Condicionado , Ruído Ocupacional , Estimulação Acústica , Calefação , Humanos , Ventilação
12.
Sensors (Basel) ; 21(18)2021 Sep 09.
Artigo em Inglês | MEDLINE | ID: mdl-34577257

RESUMO

In modern smarthomes, temperature regulation is achieved through a mix of traditional and emergent technologies including air conditioning, heating, intelligent utilization of the effects of sun, wind, and shade as well as using stored heat and cold. To achieve the desired comfort for the inhabitants while minimizing environmental impact and cost, the home controller must predict how its actions will impact the temperature and other environmental factors in various parts of the home. The question we are investigating in this paper is whether the temperature values in different rooms in a home are predictable based on readings from sensors in the home. We are also interested in whether increased accuracy can be achieved by adding sensors to capture the state of doors and windows of the given room and/or the whole home, and what type of machine learning algorithms can take advantage of the additional information. As experimentation on real-world homes is highly expensive, we use ScaledHome, a 1:12 scale, IoT-enabled model of a smart home for data acquisition. Our experiments show that while additional data can improve the accuracy of the prediction, the type of machine learning models needs to be carefully adapted to the number of data features available.


Assuntos
Algoritmos , Aprendizado de Máquina , Ar Condicionado , Calefação , Temperatura
13.
Environ Sci Technol ; 55(16): 10987-10993, 2021 08 17.
Artigo em Inglês | MEDLINE | ID: mdl-34342979

RESUMO

Water-soluble trace gas (WSTG) loss from indoor air via air conditioning (AC) units has been observed in several studies, but these results have been difficult to generalize. In the present study, we designed a box model that can be used to investigate and estimate WSTG removal due to partitioning to AC coil condensate. We compared the model output to measurements of a suite of organic acids cycling in an indoor environment and tested the model by varying the input AC parameters. These tests showed that WSTG loss via AC cycling is influenced by Henry's law constant of the compound in question, which is controlled by air and water temperatures and the condensate pH. Air conditioning unit specifications also impact WSTG loss through variations in the sensible heat ratio, the effective recirculation rate of air through the unit, and the timing of coil and fan operation. These findings have significant implications for indoor modeling. To accurately model the fate of indoor WSTGs, researchers must either measure or otherwise account for these unique environmental and operational characteristics.


Assuntos
Poluição do Ar em Ambientes Fechados , Ar Condicionado , Poluição do Ar em Ambientes Fechados/análise , Gases , Compostos Orgânicos , Água
14.
Lancet ; 398(10301): 709-724, 2021 08 21.
Artigo em Inglês | MEDLINE | ID: mdl-34419206

RESUMO

Heat extremes (ie, heatwaves) already have a serious impact on human health, with ageing, poverty, and chronic illnesses as aggravating factors. As the global community seeks to contend with even hotter weather in the future as a consequence of global climate change, there is a pressing need to better understand the most effective prevention and response measures that can be implemented, particularly in low-resource settings. In this Series paper, we describe how a future reliance on air conditioning is unsustainable and further marginalises the communities most vulnerable to the heat. We then show that a more holistic understanding of the thermal environment at the landscape and urban, building, and individual scales supports the identification of numerous sustainable opportunities to keep people cooler. We summarise the benefits (eg, effectiveness) and limitations of each identified cooling strategy, and recommend optimal interventions for settings such as aged care homes, slums, workplaces, mass gatherings, refugee camps, and playing sport. The integration of this information into well communicated heat action plans with robust surveillance and monitoring is essential for reducing the adverse health consequences of current and future extreme heat.


Assuntos
Ar Condicionado/tendências , Ambiente Construído , Mudança Climática , Calor Extremo/efeitos adversos , Temperatura Alta/efeitos adversos , Idoso , Envelhecimento , Água Potável , Eletricidade , Humanos
15.
J Acoust Soc Am ; 149(6): 4049, 2021 06.
Artigo em Inglês | MEDLINE | ID: mdl-34241438

RESUMO

Inside open-plan offices, background noise affects the workers' comfort, influencing their productivity. Recent approaches identify three main source categories: mechanical sources (air conditioning equipment, office devices, etc.), outdoor traffic noise, and human sources (speech). Whereas the first two groups are taken into account by technical specifications, human noise is still often neglected. The present paper proposes two procedures, based on machine-learning techniques, to identify the human and mechanical noise sources during working hours. Two unsupervised clustering methods, specifically the Gaussian mixture model and K-means clustering, were used to separate the recorded sound pressure levels that were recorded while finding the candidate models. Thus, the clustering validation was used to find the number of sound sources within the office and, then, statistical and metrical features were used to label the sources. The results were compared with the common parameters used in noise monitoring in offices, i.e., the equivalent continuous and 90th percentile levels. The spectra obtained by the two algorithms match with the expected shapes of human speech and mechanical noise tendencies. The outcomes validate the robustness and reliability of these procedures.


Assuntos
Ruído , Local de Trabalho , Ar Condicionado , Algoritmos , Humanos , Ruído/efeitos adversos , Reprodutibilidade dos Testes
16.
Environ Int ; 157: 106774, 2021 12.
Artigo em Inglês | MEDLINE | ID: mdl-34332303

RESUMO

To identify potential countermeasures for coronavirus disease (COVID-19), we determined the air exchange rates in stationary and moving train cars under various conditions in July, August, and December 2020 in Japan. When the doors were closed, the air exchange rates in both stationary and moving trains increased with increasing area of window-opening (0.23-0.78/h at 0 m2, windows closed to 2.1-10/h at 2.86 m2, fully open). The air exchange rates were one order of magnitude higher when doors were open than when closed. With doors closed, the air exchange rates were higher when the centralized air conditioning (AC) and crossflow fan systems (fan) were on than when off. The air exchange rates in moving trains increased as train speed increased, from 10/h at 20 km/h to 42/h at 57 km/h. Air exchange rates did not differ significantly between empty cars and those filled with 230 mannequins representing commuters. The air exchange rates were lower during aboveground operation than during underground. Assuming that 30-300 passengers travel in a train car for 7-60 min and that the community infection rate is 0.0050-0.30%, we estimated that commuters' infection risk on trains was reduced by 91-94% when all 12 windows were opened (to a height of 10 cm) and the AC/fan was on compared with that when windows were closed and the AC/fan was off.


Assuntos
Microbiologia do Ar , Poluição do Ar em Ambientes Fechados , COVID-19 , Ferrovias , Ventilação , Ar Condicionado , COVID-19/transmissão , Humanos , SARS-CoV-2
17.
PLoS One ; 16(7): e0255051, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34314471

RESUMO

At present, people are demanding better indoor air quality during the COVID-19 pandemic. In addition to maintaining the basic functions, new air-conditioning should also add air purification functions to improve indoor air quality and reduce the possibility of virus transmission. Nowadays, there is lack of research results on the innovation of air-conditioning. The aim of this study is to present a two-stage mathematical model for identifying critical manufacturing factors in the innovation process of air conditioning. In this paper, Kano and quality function deployment (QFD) are used to analyze the critical factors affecting air-conditioning innovation. Some studies have proposed using Kano-QFD model to analyze product innovation, but the study only studies one stage, which loses the analysis of the subsequent stages of product innovation. Based on this, this paper studies the priority method of two-stage critical factors for air-conditioning innovation. Firstly, the questionnaire survey and fuzzy sets are used to collect demand information of multi-agent (customers and professional technicians). Secondly, the Kano model is used to classify and calculate satisfaction of multi-agent. Then, QFD is used to transform multi-agent demands into engineering property indexes (first stage) and technical property indexes (second stage) and calculate the weight of each index. Finally, the applicability and superiority of this method is illustrated by taking the central air-conditioning as an example.


Assuntos
Ar Condicionado , Microbiologia do Ar , COVID-19/epidemiologia , Filtração/instrumentação , Modelos Teóricos , Pandemias , COVID-19/prevenção & controle , COVID-19/transmissão , Lógica Fuzzy
18.
Sensors (Basel) ; 21(13)2021 Jun 27.
Artigo em Inglês | MEDLINE | ID: mdl-34199042

RESUMO

Mechanical ventilation comprises a significant proportion of the total energy consumed in buildings. Sufficient natural ventilation in buildings is critical in reducing the energy consumption of mechanical ventilation while maintaining a comfortable indoor environment for occupants. In this paper, a new computerized framework based on building information modelling (BIM) and machine learning data-driven models is presented to analyze the optimum thermal comfort for indoor environments with the effect of natural ventilation. BIM provides geometrical and semantic information of the built environment, which are leveraged for setting the computational domain and boundary conditions of computational fluid dynamics (CFD) simulation. CFD modelling is conducted to obtain the flow field and temperature distribution, the results of which determine the thermal comfort index in a ventilated environment. BIM-CFD provides spatial data, boundary conditions, indoor environmental parameters, and the thermal comfort index for machine learning to construct robust data-driven models to empower the predictive analysis. In the neural network, the adjacency matrix in the field of graph theory is used to represent the spatial features (such as zone adjacency and connectivity) and incorporate the potential impact of interzonal airflow in thermal comfort analysis. The results of a case study indicate that utilizing natural ventilation can save cooling power consumption, but it may not be sufficient to fulfil all the thermal comfort criteria. The performance of natural ventilation at different seasons should be considered to identify the period when both air conditioning energy use and indoor thermal comfort are achieved. With the proposed new framework, thermal comfort prediction can be examined more efficiently to study different design options, operating scenarios, and changeover strategies between various ventilation modes, such as better spatial HVAC system designs, specific room-based real-time HVAC control, and other potential applications to maximize indoor thermal comfort.


Assuntos
Poluição do Ar em Ambientes Fechados , Ventilação , Ar Condicionado , Simulação por Computador , Estações do Ano , Temperatura
19.
J Extra Corpor Technol ; 53(2): 130-136, 2021 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-34194079

RESUMO

A decrease in the infection rates in the operating room (OR) is attributable to advances in sterile technique; heating, ventilation, and air-conditioning (HVAC) filtration; and limiting the number of people entering and leaving the OR. However, some infection complications after open heart procedures have been linked to the discharge fans of surgical equipment, most notably from the LivaNova 3T. We believe that surgical infection within the OR may also be due to other devices with internal fans. The purpose of this study was to 1) identify surgical equipment with an internal fan and see how they affect the airflow in an OR, 2) use the equipment to positively affect airflow to possibly reduce the risk of surgical site infections, and 3) bring attention to the HVAC system ability to exchange air throughout the OR. By using a fog machine and multiple camera angles, we identified the devices that have an effect on the airflow. We saw that the direction of the intake vent of specific devices can change the direction of airflow and possibly help to remove air. Last, we showed how the current HVAC air exchange rate might not be enough to remove contaminated air within the OR. Understanding intake and discharge vents for all equipment is important because sterile contamination and wound infection may be minimized or mitigated completely by simply repositioning a few devices.


Assuntos
Salas Cirúrgicas , Ventilação , Ar Condicionado , Calefação , Humanos , Infecção da Ferida Cirúrgica/prevenção & controle
20.
Sensors (Basel) ; 21(13)2021 Jun 25.
Artigo em Inglês | MEDLINE | ID: mdl-34202336

RESUMO

The stable operation of air handling units (AHU) is critical to ensure high efficiency and to extend the lifetime of the heating, ventilation, and air conditioning (HVAC) systems of buildings. In this paper, an online data-driven diagnosis method for AHU in an HVAC system is proposed and elaborated. The rule-based method can roughly detect the sensor condition by setting threshold values according to prior experience. Then, an efficient feature selection method using 1D convolutional neural networks (CNNs) is proposed for fault diagnosis of AHU in HVAC systems according to the system's historical data obtained from the building management system. The new framework combines the rule-based method and CNNs-based method (RACNN) for sensor fault and complicated fault. The fault type of AHU can be accurately identified via the offline test results with an accuracy of 99.15% and fast online detection within 2 min. In the lab, the proposed RACNN method was validated on a real AHU system. The experimental results show that the proposed RACNN improves the performance of fault diagnosis.


Assuntos
Poluição do Ar em Ambientes Fechados , Ventilação , Ar Condicionado , Calefação , Redes Neurais de Computação
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