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Keywords = fan-assisted ventilation

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17 pages, 7271 KiB  
Article
Microclimate Investigation in a Conference Room with Thermal Stratification: An Investigation of Different Air Conditioning Systems
by Andrea Longhitano, Vincenzo Costanzo, Gianpiero Evola and Francesco Nocera
Energies 2024, 17(5), 1188; https://doi.org/10.3390/en17051188 - 1 Mar 2024
Viewed by 939
Abstract
This paper investigates the microclimate in a conference room with thermal stratification, taking as a case study the chapel of Villa San Saverio, now the seat of the “Scuola Superiore” of the University of Catania (Italy). Surveys of the former chapel were conducted [...] Read more.
This paper investigates the microclimate in a conference room with thermal stratification, taking as a case study the chapel of Villa San Saverio, now the seat of the “Scuola Superiore” of the University of Catania (Italy). Surveys of the former chapel were conducted to monitor air temperature and relative humidity. Subsequently, the investigation relied on numerical simulations of a simplified computational fluid dynamics (CFD) model built with the DesignBuilder v7.0 software and validated by comparison with measured values. Simulations were then carried out considering three different scenarios: the current state without any HVAC system and two possible HVAC system configurations providing both air conditioning and ventilation. The results show that, from a comfort perspective, a lightweight radiant floor heating system, assisted by an appropriate ventilation system for air renewal placed at the floor level near the occupants, is preferable to floor-level fan coils and high ventilation channels. Furthermore, this was also confirmed by a preliminary energy analysis of the two HVAC options, where the ventilation effectiveness of the winter period, the temperature of the water the emitters are fed, the consequent COP value of the heat pump, and the electricity consumption were taken into consideration. Full article
(This article belongs to the Section G: Energy and Buildings)
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<p>Workflow of the methodology.</p>
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<p>Façade (<b>a</b>) and interior view illustrating the verticality of the space (<b>b</b>) of the former chapel.</p>
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<p>Plan view (<b>a</b>) and longitudinal section (<b>b</b>) of the former chapel with indication of the instruments’ locations.</p>
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<p>Wöhler CDL 210 datalogger.</p>
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<p>TESTO 435 heat flow meter.</p>
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<p>Three-dimensional model of the former chapel with different construction assemblies highlighted with different colors.</p>
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<p>Position of the HVAC systems (“Case 1”).</p>
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<p>Position of the HVAC systems (“Case 2”).</p>
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<p>Outdoor air temperature and solar irradiance from 4 to 7 March 2022.</p>
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<p>CFD simulation results at 14:00 on 6 March.</p>
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<p>Difference between simulated and measured temperatures at different heights.</p>
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<p>Air velocity distribution on 23 December (first row) and 1 July (second row) at 21:00.</p>
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<p>Air temperature distribution on a typical winter day (23 December at 21:00).</p>
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<p>Air temperature distribution on a typical summer day (1 July at 21:00).</p>
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<p>PMV distribution on 23 December (left column) and 1 July (right column) at 21:00.</p>
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20 pages, 17796 KiB  
Article
Comparison of Local Mean Age of Air between Displacement Ventilation System and Mixing Ventilation System in Office Heating Conditions during Winter
by Ik-Hyun An, Su-Hoon Park, Yong-Ho Lee, Chang-Hoon Lee, Sang-Bum Seo, Sang-Hyun Cho, Hyun-Woo Lee and Se-Jin Yook
Buildings 2024, 14(1), 115; https://doi.org/10.3390/buildings14010115 - 1 Jan 2024
Cited by 1 | Viewed by 1800
Abstract
A novel displacement ventilation system (DVS) was designed using a four-way cassette fan coil unit (FCU) and air purifiers (APs) for supplying clean air. The proposed DVS in this study involved drawing indoor air through the FCU and diffusers installed in the ceiling, [...] Read more.
A novel displacement ventilation system (DVS) was designed using a four-way cassette fan coil unit (FCU) and air purifiers (APs) for supplying clean air. The proposed DVS in this study involved drawing indoor air through the FCU and diffusers installed in the ceiling, controlling air temperature using the FCU, and then discharging it back into the office through the APs placed on the floor. The comparative ventilation system considered was the typical mixing ventilation system (MVS) that intakes and exhausts indoor air using diffusers installed on the ceiling. The local mean age of air was used as an index to compare indoor air quality between DVS and MVS under winter heating conditions. It was found that the DVS was more effective in improving indoor air quality in winter than the MVS. Moreover, compared to the MVS, utilizing the DVS designed in this study resulted in the advantage of a much more uniform air temperature variation in the office space. Therefore, it is anticipated that modifying the structure of an indoor space with an FCU installed in the ceiling and APs on the floor to use the DVS designed in this study would greatly assist in enhancing indoor air quality. Full article
(This article belongs to the Topic Indoor Air Quality and Built Environment)
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<p>Schematic of ventilation systems: (<b>a</b>) DVS; (<b>b</b>) MVS.</p>
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<p>Schematic of an office with DVS: (<b>a</b>) isometric view; (<b>b</b>) top view.</p>
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<p>Schematic of an office with Improved DVS: (<b>a</b>) isometric view; (<b>b</b>) top view.</p>
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<p>Schematic of an office with MVS: (<b>a</b>) isometric view; (<b>b</b>) top view.</p>
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<p>Grid independent test result according to grid type and number of cells.</p>
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<p>Grid system used for simulation: (<b>a</b>) office space; (<b>b</b>) diffuser.</p>
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<p>Decay of particle number concentration with time (Case C).</p>
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<p>Comparison of temperature distribution between experiment and simulation: (<b>a</b>) Point a; (<b>b</b>) Point b; (<b>c</b>) Point c.</p>
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<p>Comparison of the age of air between experiment and simulation: (<b>a</b>) Case C; (<b>b</b>) Case D.</p>
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<p>Simulation results of temperature distribution in the office: (<b>a</b>) Case C with DVS; (<b>b</b>) Case D with DVS; (<b>c</b>) Case C with Improved DVS; (<b>d</b>) Case D with Improved DVS; (<b>e</b>) Case I with MVS; and (<b>f</b>) Case J with MVS.</p>
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<p>Simulation results of temperature distribution in the office: (<b>a</b>) Case C with DVS; (<b>b</b>) Case D with DVS; (<b>c</b>) Case C with Improved DVS; (<b>d</b>) Case D with Improved DVS; (<b>e</b>) Case I with MVS; and (<b>f</b>) Case J with MVS.</p>
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<p>Simulation results of the distribution of the age of air in the office: (<b>a</b>) Case C with DVS; (<b>b</b>) Case D with DVS; (<b>c</b>) Case C with Improved DVS; (<b>d</b>) Case D with Improved DVS; (<b>e</b>) Case I with MVS; and (<b>f</b>) Case J with MVS.</p>
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<p>Simulation results of the distribution of the age of air in the office: (<b>a</b>) Case C with DVS; (<b>b</b>) Case D with DVS; (<b>c</b>) Case C with Improved DVS; (<b>d</b>) Case D with Improved DVS; (<b>e</b>) Case I with MVS; and (<b>f</b>) Case J with MVS.</p>
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<p>Comparison of the area-averaged age of air between Improved DVS and MVS according to ventilation flowrate: (<b>a</b>) at 1.1 m height; (<b>b</b>) at 1.7 m height.</p>
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<p>Comparison of the area-averaged age of air between Improved DVS and MVS according to ventilation flowrate: (<b>a</b>) at 1.1 m height; (<b>b</b>) at 1.7 m height.</p>
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<p>Comparison of the volume-averaged age of air between Improved DVS and MVS according to ventilation flowrate (in the height range 0–1.8 m).</p>
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24 pages, 1656 KiB  
Article
Comfort and Economic Viability of Personal Ceiling Fans Assisted by Night Ventilation in a Renovated Office Building
by Mattis Knudsen, Romina Rissetto, Nicolas Carbonare, Andreas Wagner and Marcel Schweiker
Buildings 2023, 13(3), 589; https://doi.org/10.3390/buildings13030589 - 23 Feb 2023
Cited by 4 | Viewed by 2941
Abstract
An expected increase in the use of air conditioning by 2050 will significantly increase electricity demand and come at a cost to the environment. Implementing passive cooling strategies and focusing on personal environmental control systems (PECSs) could help to address this issue. While [...] Read more.
An expected increase in the use of air conditioning by 2050 will significantly increase electricity demand and come at a cost to the environment. Implementing passive cooling strategies and focusing on personal environmental control systems (PECSs) could help to address this issue. While numerous studies have investigated the positive impact of PECSs on thermal comfort and energy savings, their overall economic benefit has been poorly addressed. We present an economic evaluation of personal fans for an office building in Germany. Building performance simulation was used to compare passive and active cooling concepts, and sensitivity analysis was performed for different climate scenarios. A cost-benefit analysis was carried out, including an assessment of investment and operating costs and the monetary value of relative performance. The transferability of comfort and productivity into costs is the novelty of this paper. The results showed that by supplementing night ventilation with personal fans, discomfort hours could be reduced by up to 50%. However, the initial investment of the fan is not compensated by savings in productivity losses compared to night ventilation alone. A reduction in the cost of the technology could help to economically offset the investment. The results contribute to the literature on the economic evaluation of a PECS by proposing a framework to motivate its implementation in buildings. Full article
(This article belongs to the Special Issue Indoor Environment and Thermal Comfort Performance of Buildings)
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<p>Methodology flowchart.</p>
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<p>Example of an office room, showing the new window system (<b>left</b>) and integrated personal ceiling fan in an acoustic panel with a removable grid to adjust the airflow direction (<b>right</b>). Copyright (left image): 2021, Bergische Universität Wuppertal.</p>
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<p>Thermal zones plan on the ground floor. Numbers indicate each thermal zone.</p>
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<p>PMV (ACS) and PTS (NoCooling, NV, NVandCF) values vs. indoor air temperature using the ATHB model (black points). The grey points correspond to the data when the ceiling fan was active.</p>
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<p>Interest rate and salary for <math display="inline"><semantics> <mo>Δ</mo> </semantics></math>NPV = 0.</p>
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<p>Cumulative outdoor air temperature distribution for the selected locations and climate scenarios.</p>
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<p>Energy use and percentage of discomfort hours for PMV/PTS greater than 1 (“slightly warm”) for all locations and climate scenarios.</p>
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<p>Cumulative PMV (ACS) and PTS (NoCooling, NV, NVandCF) values for all climate scenarios, using the ATHB model.</p>
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<p><math display="inline"><semantics> <mo>Δ</mo> </semantics></math>NPV sensitivity to salary changes.</p>
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<p><math display="inline"><semantics> <mo>Δ</mo> </semantics></math>NPV sensitivity to costs changes.</p>
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<p><math display="inline"><semantics> <mo>Δ</mo> </semantics></math>NPV of the ceiling fan strategy against night ventilation for the three representative locations and climatic scenarios.</p>
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17 pages, 6158 KiB  
Article
Machine Learning Framework for the Sustainable Maintenance of Building Facilities
by Valentina Villa, Giulia Bruno, Khurshid Aliev, Paolo Piantanida, Alessandra Corneli and Dario Antonelli
Sustainability 2022, 14(2), 681; https://doi.org/10.3390/su14020681 - 8 Jan 2022
Cited by 13 | Viewed by 3290
Abstract
The importance of sustainable building maintenance is growing as part of the Sustainable Building concept. The integration and implementation of new technologies such as the Internet of Things (IoT), smart sensors, and information and communication technology (ICT) into building facilities generate a large [...] Read more.
The importance of sustainable building maintenance is growing as part of the Sustainable Building concept. The integration and implementation of new technologies such as the Internet of Things (IoT), smart sensors, and information and communication technology (ICT) into building facilities generate a large amount of data that will be utilized to better manage the sustainable building maintenance and staff. Anomaly prediction models assist facility managers in informing operators to perform scheduled maintenance and visualizing predicted facility anomalies on building information models (BIM). This study proposes a Machine Learning (ML) anomaly prediction model for sustainable building facility maintenance using an IoT sensor network and a BIM model. The suggested framework shows the data management technique of the anomaly prediction model in the 3D building model. The case study demonstrated the framework’s competence to predict anomalies in the heating ventilation air conditioning (HVAC) system. Furthermore, data collected from various simulated conditions of the building facilities was utilized to monitor and forecast anomalies in the 3D model of the fan coil. The faults were then predicted using a classification model, and the results of the models are introduced. Finally, the IoT data from the building facility and the predicted values of the ML models are visualized in the building facility’s BIM model and the real-time monitoring dashboard, respectively. Full article
(This article belongs to the Special Issue Integration of BIM and ICT for Sustainable Building Projects)
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<p>ML-based building facility anomaly prediction framework.</p>
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<p>The connectivity block diagram of the proposed system.</p>
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<p>Functional flowchart of the framework.</p>
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<p>Simplified block diagram of RPIZCT4V3T2-piZero.</p>
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<p>(<b>A</b>) Current sensor with burden resistor connected to the ADC through amplifier; (<b>B</b>) Voltage sensor with voltage divider connected to the ADC through amplifier.</p>
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<p>IoT and ML data integration diagram into the BIM model.</p>
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<p>Expanded ML-based anomaly prediction framework for the experiment.</p>
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<p>Sensors allocation on the FC components: (<b>A</b>) FC equipped with sensors; (<b>B</b>) Connecting and measuring diagram of the current and voltage of the FC motor; (<b>C</b>) T5 sensor connected to the motor case; (<b>D</b>) T2 return pipe sensor; (<b>E</b>) T1 delivery pipe sensor; (<b>F</b>) T3 air intake sensor; (<b>G</b>) T4 air outlet sensor.</p>
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<p>Variable importance of the best performed model of the H2O AutoML.</p>
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<p>Real Power of the FC motor in three speeds: blue is unbalanced and red is balanced condition.</p>
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<p>Autodesk Navisworks custom 3D BIM model integrated with IoT and ML results data: on the left, balanced condition is colored with a “Blue” and on the right, the motor is under unbalanced condition and colored with a “Red”. Turned off FCs are colored with a “Grey” color.</p>
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<p>Node-red monitoring dashboard in real time.</p>
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16 pages, 977 KiB  
Article
Framing Future of Work Considerations through Climate and Built Environment Assessment of Volunteer Work Practices in the United States Equine Assisted Services
by Kimberly Tumlin, Sa Liu and Jae-Hong Park
Int. J. Environ. Res. Public Health 2021, 18(19), 10385; https://doi.org/10.3390/ijerph181910385 - 2 Oct 2021
Cited by 5 | Viewed by 2888
Abstract
The foundation of healthy workplace design is an understanding of work practices. Volunteers comprise the majority of the workforce in care centers using horses to address human health issues. Documentation is lacking on protections for worker well-being in equestrian microenvironments which are known [...] Read more.
The foundation of healthy workplace design is an understanding of work practices. Volunteers comprise the majority of the workforce in care centers using horses to address human health issues. Documentation is lacking on protections for worker well-being in equestrian microenvironments which are known to have the potential for dust exposures. Climate acts as a master variable in equestrian facility design and ventilation usage to address dust and temperature concerns. Using climate as an independent variable, our objective was to characterize space usage, safety, environmental control, and organizational practices through a national survey of equine assisted programs. We found that more fully enclosed indoor arena spaces were in cold/very cold and mixed-humid climates (p = 0.0114). Annually more volunteers (p = 0.0073) work in these two climate groups averaging 100 volunteers per location. A total of 34% of all facilities, regardless of climate, do not use mechanical ventilation systems (e.g., fans). As volunteer worker time in the arena increased, time in the barn microenvironment tended to decrease (p = 0.0538). We identified facility designs, ventilation usage, and worker arrangements to refine the scalability of future air contaminant monitoring and to provide frameworks for education, workplace design, and prevention of exposure to dust. Full article
(This article belongs to the Special Issue Worker Safety, Health, and Well-Being in the USA)
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<p>Recruitment flowchart for data analysis.</p>
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<p>Climate designation and states in which facilities were located.</p>
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<p>Major findings relevant to goals of the Future of Work Initiative.</p>
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28 pages, 10620 KiB  
Article
Multisensor IoT Platform for Optimising IAQ Levels in Buildings through a Smart Ventilation System
by Giacomo Chiesa, Silvia Cesari, Miguel Garcia, Mohammad Issa and Shuyang Li
Sustainability 2019, 11(20), 5777; https://doi.org/10.3390/su11205777 - 18 Oct 2019
Cited by 40 | Viewed by 6516
Abstract
Indoor Air Quality (IAQ) issues have a direct impact on the health and comfort of building occupants. In this paper, an experimental low-cost system has been developed to address IAQ issues by using a distributed internet of things platform to control and monitor [...] Read more.
Indoor Air Quality (IAQ) issues have a direct impact on the health and comfort of building occupants. In this paper, an experimental low-cost system has been developed to address IAQ issues by using a distributed internet of things platform to control and monitor the indoor environment in building spaces while adopting a data-driven approach. The system is based on several real-time sensor data to model the indoor air quality and accurately control the ventilation system through algorithms to maintain a comfortable level of IAQ by balancing indoor and outdoor pollutant concentrations using the Indoor Air Quality Index approach. This paper describes hardware and software details of the system as well as the algorithms, models, and control strategies of the proposed solution which can be integrated in detached ventilation systems. Furthermore, a mobile app has been developed to inform, in real time, different-expertise-user profiles showing indoor and outdoor IAQ conditions. The system is implemented in a small prototype box and early-validated with different test cases considering various pollutant concentrations, reaching a Technology Readiness Level (TRL) of 3–4. Full article
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<p>Overview of the developed system, considering the sample test case.</p>
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<p>(<b>a</b>) a view of the master unit used (Raspberry Pi 3B+) (<b>b</b>) one the used slave unit board used (Arduino UNO R3).</p>
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<p>(<b>a</b>) Ventilation device used to simulate the controlled ventilation system in the prototyping box used(<b>b</b>) the LCD display screen used for development phases.</p>
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<p>(<b>a</b>) the BME680 Temperature, Relative Humidity, Barometric pressure, and TVOC (Total Volatile Organic Compounds) gas sensor used; (<b>b</b>) the used Gravity Analog CO<sub>2</sub> gas sensor used.</p>
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<p>Mobile app navigation map.</p>
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<p>The relation between pulse width modulation (PWM) and air velocity measured in the prototype box.</p>
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<p>The four defined Backend levels.</p>
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<p>(<b>a</b>) Outdoor unit hardware connections; (<b>b</b>) indoor unit hardware connections; (<b>c</b>) raspberry Pi connection (master unit).</p>
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<p>Embedded software flowcharts (<b>a</b>) Indoor unit processing flowchart; (<b>b</b>) outdoor unit processing flowchart.</p>
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<p>Backend overview.</p>
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<p>Resources and Platform database schematic view.</p>
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<p>Measurements data structure.</p>
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<p>Mobile application screenshots: (<b>a</b>) real-time visualization, at the top the not-expert user view, at the bottom the expert user view; (<b>b</b>) Statistics visualization.</p>
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<p>Flowchart of the analysis algorithm.</p>
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<p>(<b>a</b>) The prototype box (note that to take this picture the inspection-side was removed); (<b>b</b>) box interior view (detail); (<b>c</b>) the prototype box in the testing location with inspection-side removed.</p>
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<p>Pollution tests: (<b>a</b>) relative humidity evolution over time; (<b>b</b>) Volatile Organic Compounds (VOC) gases concentration over time.</p>
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<p>System evolution under different pollutants.</p>
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<p>Test conditions and related monitored level of Indoor Air Quality Index (IAQI) on the developed app at the beginning of fan activation and immediately after it being turned off considering (<b>a</b>) CO<sub>2</sub>; (<b>b</b>) VOC; and (<b>c</b>) <span class="html-italic">RH</span>. Picture are taken though the inspection not-openable window.</p>
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16 pages, 8617 KiB  
Article
Optimization Scheme for Construction Ventilation in Large-Scale Underground Oil Storage Caverns
by Heng Zhang, Jianchun Sun, Fang Lin, Shougen Chen and Jiasong Yang
Appl. Sci. 2018, 8(10), 1952; https://doi.org/10.3390/app8101952 - 17 Oct 2018
Cited by 13 | Viewed by 3378
Abstract
The ventilation effect has a direct influence on the efficiency and security of the construction of an underground cavern group. Traditional forced ventilation schemes may be ineffective and result in resource wastage. Based on the construction ventilation of the Jinzhou underground oil storage [...] Read more.
The ventilation effect has a direct influence on the efficiency and security of the construction of an underground cavern group. Traditional forced ventilation schemes may be ineffective and result in resource wastage. Based on the construction ventilation of the Jinzhou underground oil storage project, an axial flow gallery ventilation mode using shafts as the fresh air inlet was proposed. A 3D steady RANS (Reynolds Averaged Navier-Stokes) approach with the RNG (Renormalization-group) k-ε turbulence model was used to study airflow behavior and hazardous gas dispersion when different ventilation schemes were employed. Field test values of the air velocity and CO concentration in the main cavern and construction roadway were also adopted to validate the RNG k-ε turbulence model. The results showed that the axial flow gallery ventilation mode can ensure that the direction of air flow is the same as that of heavy trucks, fresh air is always near the excavation face, and the disturbance of the construction process is greatly reduced. The scheme is suitable for large-scale caverns with a ventilation distance less than 2 km, and an intermediate construction shaft is not needed. When the ventilation distance exceeds 2 km, it is possible to use jet fans to assist the axial flow gallery ventilation mode or to completely adopt jet-flow gallery ventilation. Full article
(This article belongs to the Special Issue Monitoring and Modeling: Air Quality Evaluation Studies)
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<p>(<b>a</b>) Three-dimensional layout of underground structures; (<b>b</b>) The profile of oil storage caverns; (<b>c</b>) The shape and size of each cavern section.</p>
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<p>(<b>a</b>) The plan for the forced ventilation scheme; (<b>b</b>) The plan for axial-flow gallery ventilation scheme; (<b>c</b>) The profile of the axial-flow gallery ventilation scheme.</p>
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<p>Layout of test points in each section: (<b>a</b>) Section of the upper layer; (<b>b</b>) Section of the middle layer; (<b>c</b>) Full section of the cavern; (<b>d</b>) Construction roadway.</p>
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<p>Field test of ventilation environment in the caverns: (<b>a</b>) Test of air velocity; (<b>b</b>) Test of dust; (<b>c</b>) Air quality after ventilation.</p>
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<p>Three-dimensional geometrical model: (<b>a</b>) Forced ventilation scheme; (<b>b</b>) Axial-flow gallery ventilation scheme.</p>
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<p>Local grids. (<b>a</b>) Forced ventilation scheme; (<b>b</b>) Axial-flow gallery ventilation scheme.</p>
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<p>The comparison between the simulated result and field test: (<b>a</b>) Air velocity in the main cavern and construction roadway; and (<b>b</b>) The change of CO concentration with time.</p>
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<p>The comparison between the simulated result and field test: (<b>a</b>) Air velocity in the main cavern and construction roadway; and (<b>b</b>) The change of CO concentration with time.</p>
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<p>Distribution of airflow field near the working face: (<b>a</b>) Velocity vector at z = 5.5 m; (<b>b</b>) Velocity vector at y = 18 m.</p>
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<p>Distribution of airflow field near the working face: (<b>a</b>) Velocity vector at z = 5.5 m; (<b>b</b>) Velocity vector at y = 18 m.</p>
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<p>Air velocity distribution along the cavern.</p>
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<p>CO mass concentration distribution in the central axial plane. (<b>a</b>) Ventilation for 5 min; (<b>b</b>) Ventilation for 10 min; (<b>c</b>) Ventilation for 15 min; (<b>d</b>) Ventilation for 20 min; (<b>e</b>) Ventilation for 25 min; (<b>f</b>) Ventilation for 30 min.</p>
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<p>CO mass concentration distribution at breathing height.</p>
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<p>Air velocity distribution in the central axis of the caverns.</p>
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<p>CO concentration distribution with time in caverns under the optimized ventilation scheme: (<b>a</b>) Ventilation for 5 min; (<b>b</b>) Ventilation for 10 min; (<b>c</b>) Ventilation for 15 min; (<b>d</b>) Ventilation for 20 min; (<b>e</b>) Ventilation for 25 min; (<b>f</b>) Ventilation for 30 min.</p>
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<p>(<b>a</b>) CO concentration in monitoring section with ventilation time; (<b>b</b>) CO concentration distribution at the breathing height.</p>
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18 pages, 5208 KiB  
Article
Effects of Ventilation Improvement on Measured and Perceived Indoor Air Quality in a School Building with a Hybrid Ventilation System
by Camilla Vornanen-Winqvist, Heidi Salonen, Kati Järvi, Maria A. Andersson, Raimo Mikkola, Tamás Marik, László Kredics and Jarek Kurnitski
Int. J. Environ. Res. Public Health 2018, 15(7), 1414; https://doi.org/10.3390/ijerph15071414 - 5 Jul 2018
Cited by 26 | Viewed by 6051
Abstract
Ventilation system design and operation may significantly affect indoor air quality (IAQ). The aims of this case study were to investigate the functionality of a supply air fan-assisted hybrid ventilation system in a newly built school building with reported IAQ problems and to [...] Read more.
Ventilation system design and operation may significantly affect indoor air quality (IAQ). The aims of this case study were to investigate the functionality of a supply air fan-assisted hybrid ventilation system in a newly built school building with reported IAQ problems and to determine the effects of ventilation improvement on measured and perceived IAQ. The ventilation system function was researched simultaneously with IAQ measurements, with an analysis of total volatile organic compounds (TVOC), single volatile organic compounds (VOCs), and indoor mycobiota, and with questionnaires about perceived IAQ. At the baseline, an operational error of the ventilation system was found, which prevented the air from coming into the classrooms, except for short periods of high carbon dioxide (CO2) concentrations. After the ventilation operation was improved, a significant change in indoor mycobiota was found; the dominant, opportunistic human pathogenic species Trichoderma citrinoviride found in settled dust in the classroom before the improvement was no longer detected. In addition, the concentrations of CO2, TVOC, and some single VOCs, especially toluene and decamethylcyclopentasiloxane, decreased. The analysis of the questionnaire results indicated that the perceptions of unpleasant odors and stuffy air decreased, although a statistically significant improvement in perceived IAQ was not observed. The results provided evidence that the properly controlled hybrid ventilation system operating in mechanical supply mode provided adequate ventilation and was effective in decreasing the concentrations of some indoor-generated pollutants. With simple ventilation adjustments, microbiological exposure from building structures might be prevented. Full article
(This article belongs to the Special Issue Air Quality and Health)
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<p>The studied building section (first floor) and locations of the supply air ducts and exhaust stack. Air flow direction is shown by arrows as an example in one classroom. Measurements were conducted mainly in Classrooms 1 and 2.</p>
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<p>Location of the underground supply air chamber in relation to the studied building section (limited by a blue line): air handling unit, corridors, and terminal units of supply air ducts leading to the first- and second-floor classrooms. Direction of the supply air movement is marked with arrows.</p>
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<p>(<b>a</b>,<b>b</b>) Supply air grill and duct in the classrooms; (<b>c</b>) transfer air grilles in the partitions between classrooms and the lobby and (<b>d</b>) exhaust stack in the lobby.</p>
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<p>Supply air duct corridor and classroom-specific ducts’ terminal units in the basement. Dampers are opened 20%, as designed.</p>
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<p>Pressure differences across the envelope in Classrooms 1 (red) and 2 (blue) before and after the ventilation improvement.</p>
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<p>T, RH, and CO<sub>2</sub> of indoor air in Classrooms 1 and 2 before and after the ventilation improvement.</p>
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<p>Fungal colonies cultivated from settled dust sampled before (upper row) and after (lower row) the ventilation improvement. Panels (<b>A</b>–<b>C</b>,<b>E</b>–<b>G</b>) are cultures from dust samples collected from Classroom 2. Panel (<b>D</b>) is a culture from dust collected in the lobby, while Panel (<b>H</b>) is a dust culture from Classroom 1. The dust samples were cultivated on MEA and incubated for four weeks at room temperature. The plates in Panels (<b>A</b>,<b>D</b>) contained over 100 green, <span class="html-italic">Trichoderma</span>-like colonies. Colonies in Panel D overgrew the other fungal colonies within two weeks of incubation indicating potential mycoparasitism. The plates in Panels (<b>B</b>,<b>C</b>) were overgrown with <span class="html-italic">Rhizopus</span>-like colonies. The plates in the lower row (Panels (<b>E</b>–<b>H</b>)) contained mainly green <span class="html-italic">Penicillium</span> colonies (blue arrow). The plates in Panels (<b>G</b>,<b>H</b>) contained yellow <span class="html-italic">Aspergillus</span> colonies (black arrow), a black <span class="html-italic">Aspergillus</span> colony (white arrow), and a green <span class="html-italic">Eurotium</span>/<span class="html-italic">Aspergillus</span> colony (red arrow).</p>
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Article
Study of a Double-Layer Trombe Wall Assisted by a Temperature-Controlled DC Fan for Heating Seasons
by Qingsong Ma, Hiroatsu Fukuda, Takumi Kobatake and Myonghyang Lee
Sustainability 2017, 9(12), 2179; https://doi.org/10.3390/su9122179 - 25 Nov 2017
Cited by 19 | Viewed by 6189
Abstract
This paper presents a double-layer Trombe wall assisted by a temperature-controlled direct current (DC) fan. THERB for HAM, a dynamic thermal load calculation software, was used to estimate the heating ability of a double-layer Trombe wall for an office building. We designed a [...] Read more.
This paper presents a double-layer Trombe wall assisted by a temperature-controlled direct current (DC) fan. THERB for HAM, a dynamic thermal load calculation software, was used to estimate the heating ability of a double-layer Trombe wall for an office building. We designed a new double-layer Trombe wall that has two ventilated air cavities installed on the south facade of the office building, and a pipe with a temperature-controlled DC fan used to control thermo-circulation. The office building was located in Kitakyushu, Fukuoka, Japan. The temperature of the ventilated air cavity of the double-layer Trombe wall and the indoor temperature were simulated. It was more efficient for the DC fan to start when the ventilated air cavity temperature was 19 °C and the operative temperature of indoor was maintained at 20 °C. The results showed that the double-layer Trombe wall with a temperature-controlled DC fan can reduce yearly heating needs by nearly 0.6 kWh/m3 and improve the performance of a double-layer Trombe wall up to 5.6% (22.7% in November, 8.56% in December, 1.04% in January, 3.77% in February, and 3.89% in March), compared to the double-layer Trombe wall without an air supply. The ventilated (all day) double-layer Trombe wall performed better than the unventilated double-layer Trombe wall in November, December, February, and March. Thus, the potential of a double-layer Trombe wall can be improved with the assistance of a temperature-controlled DC fan. Full article
(This article belongs to the Section Energy Sustainability)
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Figure 1
<p>The composite Trombe-Michel wall [<a href="#B15-sustainability-09-02179" class="html-bibr">15</a>].</p>
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<p>Model of office with the double-layer Trombe wall.</p>
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<p>The double-layer Trombe wall assisted with a temperature-controlled DC fan for winter heating.</p>
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<p>Average hourly global solar irradiation and air temperature.</p>
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<p>The temperature of the room under different air supply strategies on January 19.</p>
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<p>Heating thermal energy consumption under different air supply strategies in November.</p>
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<p>Heating thermal energy consumption under different air supply strategies in December.</p>
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<p>Heating thermal energy consumption under different air supply strategies in January.</p>
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<p>Heating thermal energy consumption under different air supply strategies in February.</p>
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<p>Heating thermal energy consumption under different air supply strategies in March.</p>
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