American Society Of Heating , Refrigerating And Air-Conditioning Engineers Research Articles

Analysis of supplemental dehumidification for increased energy efficiency of shoulder seasons based on climate change predictions in Austin Texas

This research project compared a standard vapor compression system and a standard desiccant dehumidification system with heat wheel to determine if there was some potential energy savings for “shoulder season” hours in Austin Texas. “Shoulder season” hours as defined in the paper are hours during which the dry bulb temperature falls within the American Society of Heating Refrigeration and Air Conditioning Engineers (ASHRAE) comfort bound but the humidity is above the comfortable humidity point. These hours are normally addressed with vapor compression systems which dehumidify by cooling the air under the comfort setpoint to dehumidify, which is wasteful of energy. The study found that for these shoulder season hours a desiccant dehumidification system was around 4.5 times more energy efficient at reaching comfort setpoints if free heating was used for drying the desiccant.

A comparative study of gender differences in thermal comfort and environmental satisfaction in air-conditioned offices in Qatar, India, and Japan

Gender differences in the assessment of thermal comfort and indoor environmental quality (IEQ) in the Gulf Cooperation Countries (GCC) have not previously been investigated, despite the prevalence of the overcooling of indoor spaces. This study investigated the effect of sex, age and body mass index on subjective thermal comfort perceptions, comfort temperature and IEQ satisfaction in offices using our thermal comfort surveys in Qatar, India, and Japan. Data from the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) databases were used for comparison. We found that females were twice as likely to feel dissatisfied with thermal sensation than males in Doha. Overall, females felt colder than men, and were less satisfied with all IEQ parameters. In Doha, females, younger subjects, and high-BMI subjects had lower comfort temperatures than their counterparts.Increased indoor air speeds and the provision of personal environmental controls could effectively reduce female dissatisfaction and save energy in Qatar. Women's more stringent thermal comfort preferences could be used to evaluate occupant control provisions and IEQ standards. A robust IEQ complaint redressal system may also be required in offices. This study highlights the need to consider female perspectives and thermal expectations in the environmental design of workplaces as well, not merely privacy concerns.

Multi-step building energy model calibration process based on measured data

Building energy models are a key element in regulatory compliance calculations. These energy performance calculations often do not accurately reflect actual operating conditions. Therefore, evaluation of energy performance comparing actual energy use of a building with the outcome of dynamic simulation models can be misleading, this difference is also known as the energy performance gap. The reduction of the gap is an important task aimed to provide confidence in the use of models for evaluation of energy efficiency. This paper is focused on reducing the technical issues (e.g. poorly adjusted thermal parameters in the envelope, inefficient boiler operator or lack of adjustment in parameters of heat pumps, baseboard radiators or air handling units) which are one of the main causes of the energy performance gap. The application of a multi-step, optimization-based, calibration methodology performed in a white-box simulation environment (EnergyPlus) using three months of ten minute time-step data to adjust HVAC parameter values with a genetic algorithm software (Jeplus) is validated on a real test site. Resulting in a BEM that fits the building’s hourly performance benchmark into international standards on three key levels: indoor temperature by Thermal Zone (TZ), heat production and electric consumption from heat pumps, which comprise all the components of a building energy model. A batch of 1500 h of heating operation, obtained from the building management system, has been used to calibrate the model. The results complied with the requirements of the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Guideline 14–2002 at hourly interval, with NMBE ⩽±10%,Cv(RMSE) ⩽30% and R2 ⩾75% and with the International Performance Measurement and Verification Protocol (EVO) for Cv(RMSE) ⩽20% and R2 ⩾75% in the three aforementioned levels, which can be considered a step forward in the area of calibrating white box models. In addition, to prove the strength and robustness of the results, the model has been checked in a long testing and independent period of 2.500 h of heating operations with the same level of compliance. The demonstrator is the library of a school located in Denmark. The HVAC system is composed of four air–water heat pumps that deliver heating to the whole compound with the backup support of a gas boiler. The library is heated with baseboard radiators system with the support of an air handling unit used for ventilation purposes.

Building envelopes toward energy‐efficient buildings: A balanced multi‐approach decision making

The worldwide environmentally friendly trend has focused the last decade on emphasizing the value of energy conservation and reducing the carbon footprint in buildings, achieving zero energy buildings. Presently, viable building techniques, in developing countries, are insufficient to achieve zero energy buildings. Thus, authorities should implement policies mandating new developments and renovations to establish “energy-efficient buildings”; nevertheless, design solutions should be properly evaluated and assessed preceding execution. The conservation of energy without jeopardizing human comfortability is a huge challenge for any designer. Occupants are less interested in making a major investment to save some expenses over the next two decades, especially nowadays that energy is still affordable. Therefore, improved indoor environmental conditions are perhaps another important parameter toward energy-efficient buildings. Through dynamic simulations, this study examines the energy efficiency and thermal comfort achieved by integrating retrofitting strategies in an institutional building in three different American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) hot climate zones represented by three cities of Egypt (Aswan, Cairo, and Alexandria). The built-up baseline model is validated using actual energy usage data. The validated baseline model is then subjected to local sensitivity analysis to determine the driving parameters influencing the building's energy demand. The study at hand focuses on a broader perspective on sustainability. With a multiapproach decision-making methodology based on the most recent measures, the study highlights the outcomes through an environmental–economic assessment and indoor thermal comfort depending on experts' weighting, responses, and recommendations. The outcomes postulate that the implementation of reflective paints solutions would achieve the highest percentages of whole-building energy savings with 21%, 19%, and 17% for Aswan, Cairo, and Alexandria, respectively, improving indoor thermal comfort levels.

Climatic Effect on the Exergetic Performance of Conventional to Hybrid Evaporative Coolers With Varying Dead-State Temperatures in India

Abstract A comprehensive exergy, exergo-economic, and sustainability assessment of seven conventional to hybrid air-conditioning systems comprising direct and indirect evaporative coolers with direct expansion system and their several combinations integrated into an eight-story domestic building for five different cities corresponding to arid, semi-arid, humid subtropical, tropical wet and dry, and tropical wet climatic zones across India are investigated based on simulation output from energyplus. The exergetic performances are reported for varying dead state temperatures ranging from 5 °C to 40 °C, while the saturated humidity ratio and pressure at system outlet are two other dead state properties. The results reveal that the specific exergy of moist air and exergetic efficiency decreases with increasing dead state temperature and becomes least at a dead state temperature near American Society of Heating, Refrigerating and Air-conditioning Engineers (ASHRAE) comfort temperature of 23 °C. In arid, semi-arid, and humid subtropical climates, the three-stage evaporative cooling system exhibits the lowest exergy destruction of 100 J/kg1 and the highest exergy efficiency of 90% at a dead state temperature of 40 °C. The two-stage direct evaporative-direct expansion cooling system exhibits superior exergy efficiency in tropical wet and dry and tropical wet zones. Furthermore, the Grassmann diagram based on the climate of Hyderabad indicates that the three-stage cooling system is energetically and exergetically optimum with exergy destruction of 28.86%.

The effect of aspect ratio on the inerstion loss of lined ducts

The American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) Handbook provides tabulated information that can be used to determine the insertion loss of a variety of lined and unlined ducts. However, the tabulated cross-sections are primarily for square ducts. Not surprisingly, there is a need for information on the insertion loss of ducts having different aspect ratio cross-sections. Hence, the insertion loss for large aspect ratio cross-sections are investigated using a previously validated finite element simulation approach. A coupled structural-acoustic finite element analysis is performed, and data is compared to measurement results from the literature for a few configurations. An analysis campaign is then performed which better explains the effect of aspect ratio on duct insertion loss.

Study the Impact of Engineering Ventilation on Indoor Air Quality in Hospitals during COVID-19

This study investigates the importance of using engineering ventilation in healthcare settings, especially during widespread disease outbreaks such as COVID-19. Ventilation can be used to improve indoor air quality in care homes, hospitals, and quarantine locations. In the research, two scenarios of engineering ventilation are simulated using a Fire Dynamic Simulator (FDS), with sulfur hexafluoride employed as the contaminant emitted by the patient in the hospital room. The volume of the room selected for the present study is 60 m3, and the ventilation mode is designed according to the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), with 12 air changes per hour and negative pressure. The mean concentration of the pollutants is estimated for both scenarios, giving concentrations in the range of 920 ± 397 to 1260±580 ppm. The estimated indoor air quality (IAQ) values varied from 2.06 to 2.90. According to the obtained results, ventilation plays a critical role in eliminating pollutants, indicating that suitably engineered ventilation strategies can reduce the impact of COVID-19 spread in closed buildings. © 2021

An Instance Segmentation and Clustering Model for Energy Audit Assessments in Built Environments: A Multi-Stage Approach.

Heat loss quantification (HLQ) is an essential step in improving a building’s thermal performance and optimizing its energy usage. While this problem is well-studied in the literature, most of the existing studies are either qualitative or minimally driven quantitative studies that rely on localized building envelope points and are, thus, not suitable for automated solutions in energy audit applications. This research work is an attempt to fill this gap of knowledge by utilizing intensive thermal data (on the order of 100,000 plus images) and constitutes a relatively new area of analysis in energy audit applications. Specifically, we demonstrate a novel process using deep-learning methods to segment more than 100,000 thermal images collected from an unmanned aerial system (UAS). To quantify the heat loss for a building envelope, multiple stages of computations need to be performed: object detection (using Mask-RCNN/Faster R-CNN), estimating the surface temperature (using two clustering methods), and finally calculating the overall heat transfer coefficient (e.g., the U-value). The proposed model was applied to eleven academic campuses across the state of North Dakota. The preliminary findings indicate that Mask R-CNN outperformed other instance segmentation models with an mIOU of 73% for facades, 55% for windows, 67% for roofs, 24% for doors, and 11% for HVACs. Two clustering methods, namely K-means and threshold-based clustering (TBC), were deployed to estimate surface temperatures with TBC providing consistent estimates across all times of the day over K-means. Our analysis demonstrated that thermal efficiency not only depended on the accurate acquisition of thermal images but also relied on other factors, such as the building geometry and seasonal weather parameters, such as the outside/inside building temperatures, wind, time of day, and indoor heating/cooling conditions. Finally, the resultant U-values of various building envelopes were compared with recommendations from the American Society of Heating, Refrigerating, and Air-conditioning Engineers (ASHRAE) building standards.

An adaptive thermal comfort model for naturally ventilated classrooms of technical institutions in Madurai

PurposeOccupants dwelling in hot climatic regions of India for a longer term are tolerable to high temperature levels than predicted by American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) standards. The purpose of this study is to evaluate the thermal sensations (TS) and neutral temperature of the occupants in naturally ventilated (NV) and air-conditioned (AC) classrooms of two technical institutions located in the same premises in the suburbs of Madurai. The main focus of this study is to understand the occupants’ behaviour in response to the thermal conditions of the educational buildings particularly in the warm and humid climatic zone of Madurai.Design/methodology/approachThis research collected data through field studies. The data included 383 survey questionnaires from NV classrooms and 285 from AC classrooms, as well as on-site measurements of interior and exterior weather conditions. The TS results show that the students preferred well-designed NV classrooms than AC classrooms. A new adaptive comfort equation derived from this study can be applied to NV classrooms in warm and humid climates where mean outdoor temperature exceeds 40°C.FindingsThe neutral temperature derived for NV classrooms in Madurai ranged from 29°C to 34°C. Thus, the occupants in the NV classrooms of the higher learning educational institutions in the warm and humid climatic region of Madurai can adapt well to higher indoor temperature levels than predicted by ASHRAE comfort levels with minimum adjustments.Research limitations/implicationsThe study was limited to only occupants in two premier higher learning technical educational institutions located in Madurai region within 5–10 km within the city limits to understand the implications of microclimate with respect to the urban context. Thus, further research is required to examine the tendency under local conditions in other regions beyond those applied to this study.Social implicationsThe findings of this study showed that occupants in higher learning educational intuitions in Madurai prefer NV classrooms than AC classrooms. Therefore, with rising demands of energy use for mechanical ventilation and the associated high cost for running AC buildings, architects should prioritize the design of energy efficient buildings through the optimal use of passive design strategies for ventilation and thermal comfort. This study gives a base data for architects to understand the adaptive limitations of occupants and design NV buildings that can promote natural ventilation and provide better thermal environments that can help increase the productivity of students.Originality/valueThis paper was an attempt to develop the adaptive comfort model for NV classrooms in Madurai regions. There has been no attempt to identify the adaptive comfort levels of occupants in higher learning technical educational institutions located in warm and humid climatic region of India.

Formalized control logic fault definition with ontological reasoning for air handling units

Control logic programs determine the behavior of Heating, Ventilation, and Air Conditioning (HVAC) systems under different operating conditions. Faults in control logic account for more than 15% of all HVAC system problems, causing energy waste and occupancy discomfort. The first step towards systematically detecting and diagnosing control logic faults is to have an unambiguous control logic fault definition so that the existence of control logic faults in an HVAC system can be discovered from its operational data. In order to have high level of fault detection accuracy, the control logic fault definition needs to be customized for different HVAC systems as they have different components and control sequences. In this paper, we propose an object-oriented classification approach to systematically define customized control logic faults in terms of control logic input/output variable expressions. Focusing on air handling unit (AHU) systems, and their general operation objectives of energy efficiency and occupancy comfort, we elaborated four control goals and developed corresponding reasoning mechanisms to derive fault definitions. We also developed an HVAC component and control information ontology to be used in these reasoning mechanisms by extending existing HVAC information models. The prototype of the developed approach was tested with 27 common AHUs specified by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), and the results show that using the developed approach, it is possible to define a customized set of control logic faults applicable to each specific AHU with an overall precision of 94.2% and recall of 83.0%. This demonstrates the generality of our proposed approach in providing customized control logic fault definitions for different types of AHUs.

Capsimax Increases Resting Energy Expenditure in Males Under Fasting State: A Randomized, Double-Blind, Placebo Controlled, Cross-Over Study

Abstract Objectives Obesity is caused by an imbalance between energy intake and energy expenditure. Resting energy expenditure (REE) represents the calories burned at rest and accounts for > 60% of total energy expenditure. Energy expenditure plays an important role in obesity development, hence an increase in REE could facilitate body weight reduction. Capsaicinoids, extracted from capsicum annuum have been known to increase metabolism, lipolysis & induce satiety. The study objective was to evaluate the effects of Capsimax™ on REE and thermal sensation. Methods This was a randomized, double-blind, placebo controlled, cross-over study. Efficacy analysis included subsets of 17 males and 7 females who received single dose of Capsimax™ 100 mg (2 mg total capsaicinoids) and placebo in a cross-over fashion with washout period of 3–6 days as per randomization schedule. REE was measured using Cosmed Q-NRG by indirect calorimetry. Secondary objectives were Area under curve (AUC) for REE, VO2, VCO2 & subject's innate thermal sensation using American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) scale. REE, VO2, VCO2, ASHRAE scale were evaluated at 0 (pre-dose), 1, 2, 3 & 4 hours and additional measures for ASHRAE scale at 0.5 & 1.5 hours post-dose. Safety was assessed throughout the study with measurements of ECG, blood pressure, pulse rate, body temperature & adverse event occurrences. Results In males, CapsimaxTM consumption significantly increased (p < 0.05) the change in REE at 1 hr (+90.19 ± 36.99 kcal Vs -92.97 ± 35.95 kcal), 2 hr (+77.17 ± 35.12 kcal Vs -41.90 ± 35.12 kcal), 3 hr (+48.47 ± 38.60 kcal Vs −51.74 ± 37.69 kcal) & 4 hr (+30.17 ± 40.37 kcal Vs −43.88 ± 40.37 kcal) as compared to placebo. Significant differences (p < 0.05) were also seen for AUC0–2 REE, VO2 at 1, 2 & 3 hrs and VCO2 at 3 hrs for CapsimaxTM versus placebo. Although not significantly different, subject's in CapsimaxTM group showed higher feelings of warmth at all time points post dose based on ASHRAE score versus placebo. No significant differences were observed for any of the endpoints in females. No safety issues or adverse events were seen. Conclusions Our study findings demonstrate that CapsimaxTM supplementation increases REE in males and may represent a useful nutritional strategy to help weight management efforts. Funding Sources OmniActive Health Technologies Ltd.

Thermophysics Analysis of Office Buildings with a Temperature\u2013Humidity Coupling Strategy Under Hot-Arid Climatic Conditions

This study investigates the determining parameters of thermal comfort of office in an arid hot-arid environment of Bechar, located in the northwestern region of Algeria, in which the vertical walls of the room and the roof are subjected to solar irradiations and the floor is considered to be adiabatic. The solar flux is calculated by the ASHRAE (American Society of Heating, Refrigerating and Air-Conditioning Engineers) method. The predicted results are validated against the experimental results of the meteorological station of the ENERGARID research laboratory at the University of Bechar (Algeria). The characteristics of the ambient air flow are performed by using the computational fluid dynamics (CFD) software (Fluent). The flow fields, thermal fields, and humidity are investigated. An elaborated computer program (with Delphi language) is utilized to evaluate the temperature–humidity coupling as the most essential factors of the thermal comfort. A significant impact of dynamic temperatures and humidity on thermal comfort has been observed, especially in this hot-arid environment. Besides, a considerable effect of the flow velocity has been remarked. From the obtained results and to provide the best thermal comfort in such arid regions, the range of air velocity inside the building is recommended to be between 0.2 m·s−1 and 0.3 m·s−1.

Application of the Takagi-Sugeno Fuzzy Modeling to Forecast Energy Efficiency in Real Buildings Undergoing Thermal Improvement

Energy efficiency in the building industry is related to the amount of energy that can be saved through thermal improvement. Therefore, it is important to determine the energy saving potential of the buildings to be thermally upgraded in order to check whether the set targets for the amount of energy saved will be reached after the implementation of corrective measures. In real residential buildings, when starting to make energy calculations, one can often encounter the problem of incomplete architectural documentation and inaccurate data characterizing the object in terms of thermal (thermal resistance of partitions) and usable (number of inhabitants). Therefore, there is a need to search for methods that will be suitable for quick technical analysis of measures taken to improve energy efficiency in existing buildings. The aim of this work was to test the usefulness of the type Takagi-Sugeno fuzzy models of inference model for predicting the energy efficiency of actual residential buildings that have undergone thermal improvement. For the group of 109 buildings a specific set of important variables characterizing the examined objects was identified. The quality of the prediction models developed for various combinations of input variables has been evaluated using, among other things, statistical calibration standards developed by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE). The obtained results were compared with other prediction models (based on the same input data sets) using artificial neural networks and rough sets theory.

Heat exchanger design based on earthen materials

We propose herein the design of a heat exchanger based on clay materials in order to reduce the energy consumed due to data center cooling. Our Thermal Energy Storage (TES) system is to be placed upstream of the CRAC (Computer Room Air Conditioner) unit. A direct contact heat exchanger is thereby built as a vertical packed bed, composed of earthen spheres whose imposed heating/cooling cycles comply with ASHRAE (American Society of Heating, Refrigerating and Air-Conditioning Engineers) standards. A raw earthen material has been chosen owing to its hygrothermal characteristics, which are recognized as relevant for indoor thermal regulation, in addition to a low embodied energy required for manufacturing. Results show that the pore Reynolds number and sphere diameter exert significant effects on the energy buffering capacity. A simple relationship is thus proposed to link the mass-specific power of the energy storage system, the internal heat exchanger architecture and the pore Reynolds number for purposes of designing raw earth bricks at an elevated scale.

Human health and productivity outcomes associated with indoor air quality: a systematic review

Characteristics of the indoor environmental quality directly impact humans’ ability to lead healthy and productive lives. We estimated the effects of changes in indoor air quality (namely through indoor ventilation rates and carbon dioxide levels) on health, performance, and productivity outcomes in students (primary, secondary, and university), laboratory test subjects, and workers. For this systematic review, we searched PubMed, from database inception to October 15, 2020, for relevant studies in any classroom, lab, and labor environment at any level of indoor air quality. No restrictions on language, workers’ health status, or study design were applied. Good and bad indoor air quality was defined using American Society of Heating, Refrigeration, and Air-Conditioning Engineers (ASHRAE) standards. We excluded studies that calculated effects focusing on air temperature, humidity levels, systematic reviews on similar topics to avoid duplication, and any grey literature. Of 101 reports identified through our systematic search, 42 studies conducted in 10 countries and 3 continents, including 6,850 subjects were eligible for analysis. Our review showed that individuals exposed to indoor air quality settings above ASHRAE minimum standards (defined as ventilation rates 17 CFM per person and Carbon Dioxide (CO2) steady states of 1000 parts per million (ppm)) were more likely to experience increased poor levels of health, performance and productivity under these conditions. Overall, this analysis includes a variety of populations, exposures, and occupations to comply with a wider adoption of evidence synthesis but resulted in large heterogeneity. Poor indoor air quality has important human health, performance, and productivity outcomes and should be recognized as a public health problem. Inversely, improved indoor environmental conditions delivered through enhanced ventilation strategies should be considered a health, performance, and productivity opportunity for both students and workers. This study addresses these areas of concern and opportunity. However, given the lack of standardized methodologies, results reporting criteria across conducted air quality analyses, and a lack of international case studies, a concerted global effort is needed to conduct and compare research with standardized metrics. Furthermore, a majority of studies are conducted in school classrooms or laboratory environments or provide no remuneration to incentivize good performance - a condition not reflective of real-world office settings. To better understand the implication on office workers, additional field research can serve to enhance our understanding of indoor environmental factors on employee health and productivity in a setting where remuneration incentives may impact performance.

Self-shaping building skin: Comparative environmental performance investigation of shape-memory-alloy (SMA) response and artificial-intelligence (AI) kinetic control

This paper presents the first controlled experimental investigation on the environmental performance of self-shaping adaptive façade, which is a kinetically-responsive building skin activated by smart material. Although adaptive façade is an emerging subject in architectural design and research, its effectiveness has been rarely addressed in terms of building performance. Thus, in this study, we investigated indoor temperature and daylight illuminance of a thermo-responsive skin actuated by shape-memory alloy (SMA). For comparative analysis in a controlled situation, two identical lab-scale (1:20) building models with kinetic louver shading were designed, representing a south-oriented living room of 3.4 m✕5.2 m. The shadings were climate-adaptively operated by a conventional electromagnetic motor (baseline) and an SMA actuator (test case), respectively, for the same time period. The mechanical characterization and simulation of SMA-bias coil spring actuation were studied, and an artificial neural networks (ANNs) model was employed for the baseline's optimal dynamic control to approximate the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) Standard for thermal comfort (19.4–27.8 °C) and a minimum illuminance level of 500 lx. The study's findings indicate that SMA actuation is effective for controlling indoor daylight intensity, thereby improving overall indoor environmental conditions. Nevertheless, the climate-responsive self-shaping was not as instantaneous as the optimal kinetic control. Average performance was probabilistically different; however, a significant correlation was found in illuminance variation.

A Novel Air Balancing Method for HVAC Systems by a Full Data-Driven Duct System Model

Air balancing is an important technique in heating, ventilation, and air conditioning (HVAC) applications to achieve accurate air supply for satisfactory indoor air quality and better energy saving performance. The existing air balancing methods are usually based on a hybrid duct system model, which includes a data-driven duct system model between terminal flow and static pressure, and an American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) damper model between static pressure and terminal damper angle. Most of the existing methods just focus on how to improve the accuracy of the former part (i.e., the data-driven duct system model), whereas neglecting the latter. However, it is found that the ASHRAE damper model cannot exactly reflect the characteristics of the actual dampers in practice and may lead to unavoidable modeling errors. To fix this issue, this article develops a full data-driven duct system (FD <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> S) model to directly reveal the relationship between the terminal flow and terminal damper angle in the whole duct system. As a result, the desired terminal damper angle under the design flow conditions can be more accurately predicted. Besides, since the proposed method directly models the relationship between terminal flow and terminal damper angle, it avoids installing extra pressure sensors and reduces the operating cost. Besides, the proposed FD <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> S model greatly reduces the model complexity compared with the previous hybrid model. The proposed FD <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> S model-based air balancing method is fully tested on three real duct systems, and the results proved the effectiveness and generality of the proposed FD <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> S model-based air balancing method.

Development of an IoT and BIM-based automated alert system for thermal comfort monitoring in buildings

A comfortable thermal indoor environment is crucial for occupants’ well-being and productivity. Building Management System (BMS) is usually used to monitor the thermal condition of buildings. One of BMS’s main challenges is in the data visualization stage, in which 2D vector graphics are used, which is not fully interactive and can only be manipulated by a trained operator. Building Information Modeling (BIM) has emerged as a useful tool in the construction industry, which can be applied in all stages of a project lifecycle. The use of BIM in facilities management is currently limited since BIM applications have primarily been implemented within the design and construction phases. The main objective of this study is to integrate a sensor-based alert system into BIM models for thermal comfort monitoring in buildings during the operational phase and visualize a building’s thermal condition virtually. In order to improve the performance of environmental monitoring management of buildings in smart cities, this research presents a newly developed integrated solution based on a BIM platform and Internet of Things (IoT). The designed prototype explores the integration of commercial BIM platforms with sensor data to create a self-updating BIM model to provide real-time thermal condition monitoring based on the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) Standard within an office environment. The temperature and humidity values, measured by sensors, are sent to the MySQL database server. An integrated workflow was developed to compile, standardize, integrate, and visualize monitoring data in a BIM environment to facilitate interpretation, analysis, and monitoring data exchange. The developed system was able to detect the time and location of a case study office room experiencing the levels of thermal comfort/discomfort based on the targeted thresholds. In this case, thirteen levels of thermal discomfort cases, out of forty-nine data points during the test, were detected, and the developed system was also able to generate a trigger and transmit alarms to facility managers via their wireless devices in real-time. The results demonstrate that the proposed system is a visually effective monitoring system for environmental monitoring management. The fully automated developed system is expected to provide a robust and practical tool for reliable data collection, analysis, and visualization to facilitate intelligent monitoring of the thermal condition in buildings and help decision-makers make faster and better decisions, which may help in maintaining the level of occupants’ thermal comfort to a satisfactory level.

A Systematic Review of Air Quality Sensors, Guidelines, and Measurement Studies for Indoor Air Quality Management

The existence of indoor air pollutants—such as ozone, carbon monoxide, carbon dioxide, sulfur dioxide, nitrogen dioxide, particulate matter, and total volatile organic compounds—is evidently a critical issue for human health. Over the past decade, various international agencies have continually refined and updated the quantitative air quality guidelines and standards in order to meet the requirements for indoor air quality management. This paper first provides a systematic review of the existing air quality guidelines and standards implemented by different agencies, which include the Ambient Air Quality Standards (NAAQS); the World Health Organization (WHO); the Occupational Safety and Health Administration (OSHA); the American Conference of Governmental Industrial Hygienists (ACGIH); the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE); the National Institute for Occupational Safety and Health (NIOSH); and the California ambient air quality standards (CAAQS). It then adds to this by providing a state-of-art review of the existing low-cost air quality sensor (LCAQS) technologies, and analyzes the corresponding specifications, such as the typical detection range, measurement tolerance or repeatability, data resolution, response time, supply current, and market price. Finally, it briefly reviews a sequence (array) of field measurement studies, which focuses on the technical measurement characteristics and their data analysis approaches.

The Building Data Genome Project 2, energy meter data from the ASHRAE Great Energy Predictor III competition

This paper describes an open data set of 3,053 energy meters from 1,636 non-residential buildings with a range of two full years (2016 and 2017) at an hourly frequency (17,544 measurements per meter resulting in approximately 53.6 million measurements). These meters were collected from 19 sites across North America and Europe, with one or more meters per building measuring whole building electrical, heating and cooling water, steam, and solar energy as well as water and irrigation meters. Part of these data was used in the Great Energy Predictor III (GEPIII) competition hosted by the American Society of Heating, Refrigeration, and Air-Conditioning Engineers (ASHRAE) in October-December 2019. GEPIII was a machine learning competition for long-term prediction with an application to measurement and verification. This paper describes the process of data collection, cleaning, and convergence of time-series meter data, the meta-data about the buildings, and complementary weather data. This data set can be used for further prediction benchmarking and prototyping as well as anomaly detection, energy analysis, and building type classification.