Comfort Parameters Research Articles

Dynamic Indoor Environmental Quality Assessment in Residential Buildings: Real-Time Monitoring of Comfort Parameters Using LoRaWAN

This study addresses an identified literature gap regarding indoor environmental quality in residential buildings, where the primary focus has traditionally been on energy performance rather than comfort optimization. Leveraging the low-cost and easy-to-implement LoRaWAN protocol, this research collects and analyses real-time data on comfort parameters, including temperature, CO2 levels, humidity, lighting, atmospheric pressure, and total volatile organic compounds (TVOC) across various buildings within the INCUBE EU project. The results highlight the dynamic nature of the parameters and emphasize the importance of continuous monitoring to enhance comfort and energy efficiency in smart residential buildings. The findings advocate for integrating technologies like LoRaWAN to optimize indoor environmental quality, ultimately improving residential comfort and occupant well-being.

Machine learning-based predictive model for temperature and comfort parameters in indoor enviroment using experimantal data

The research introduces an artificial neural network model that predicts temperature and assesses thermal comfort metrics for a cooling room, demonstrating how machine learning advancements can enhance thermal efficiency and cost-effectiveness in building design. The study utilized the Levenberg-Marquardt (LM) artificial neural network (ANN) approach to derive the average temperature and thermal comfort metrics collected under actual operating settings. The Predicted Mean Vote (PMV) and Predicted Percentage Dissatisfied (PPD)values were measured at three distinct sites and then compared to the trial findings. The model uses a dataset of 205 observations, with 143 cases used for training and 31 examples for testing and validation. The ANN model demonstrated effective training, with negligible errors in estimated error values. The mean squared error values for average temperature and thermal comfort parameters were 0.0342, 0.0376, 0.0571, 0.0029, and 0.2296. The R values for temperature measurements are 0.9947 and 0.9923, 0.9847 and 0.9437, and 0.9737, demonstrating a highly effective engineering method. The ANN model provided precise predictions for temperature and thermal comfort metrics, such as PMV and PPD in a cooling chamber, with a tolerance of ± 15 %. The LM approach, a machine learning methodology, produced excellent outcomes, particularly at lower temperatures, with 15 % of the data exceeding this range.

Comprehensive analysis of particulate matter, gaseous pollutants, and microbiological contamination in an international chain supermarket

Indoor environmental quality is of utmost importance since urban populations spend a large proportion of their life in confined spaces. Supermarkets offer a wide range of products and services that are prone to emitting several air pollutants. This study aimed to perform a comprehensive characterisation of the indoor and outdoor air quality in a multinational supermarket, encompassing not only criteria parameters but also unregulated pollutants of concern. Monitoring included measurements of comfort parameters, CO2, multiple gaseous pollutants, particulate matter (PM10) and bioburden. PM10, volatile organic compounds (VOCs) and carbonyls were subject to chemical speciation. Globally, the supermarket presented CO2, VOCs, and PM10 values below the limits imposed by international regulations. The PM10 concentration in the supermarket was 33.5±23.2 μg/m3, and the indoor-to-outdoor PM10 ratio was 1.76. Carbonaceous constituents represented PM10 mass fractions of 21.6% indoors and 15.3% outdoors. Due to the use of stainless-steel utensils, flour and fermentation processes, the bakery proved to be a pollution hotspot, presenting the highest concentrations of PM10 (73.1±9.16 μg/m3), PM10-bound elements (S, Cl, K, Ca, Ti, and Cr) and acetaldehyde (42.7 μg/m3). The maximum tetrachloroethylene level (130 μg/m3) was obtained in the cleaning products section. The highest values of colony-forming units of bacteria and fungi were recorded in the bakery, and fruit and vegetable section. The most prevalent fungal species was Penicillium sp., corresponding to 56.9% of the total colonies. In addition, other fungal species/sections with toxicological or pathogenic potential were detected (Aspergillus sections Aspergilli, Circumdati, Flavi, Mucor and Fusarium sp.).

A study of the relationship between human thermal comfort and negative emotions in quarantine environments

The thermal environment is closely related to emotion. The thermal environment affects emotional experiences and can enhance them by adjusting its parameters. This study examines three common negative emotions—boredom, anxiety, and irritability—in a controlled environment. We experimentally investigated how these emotions affect thermal sensation, thermal comfort, and physiological parameters under varying temperature and humidity conditions. Results indicated that emotions significantly influenced thermal sensation (TSV) and thermal comfort (TCV) under moderate to high humidity conditions, demonstrating how temperature and humidity moderate the relationship between emotion and thermal comfort. Changes in physiological parameters further reveal how the interaction between emotion and environmental conditions affects physiological responses. A regression model was created using the response surface method to analyze thermal comfort in relation to temperature and humidity under different emotions, identifying the optimal indoor conditions as 22.8 °C and 46.7 % humidity. These findings help reduce negative emotions, improve thermal comfort, enhance our understanding of human thermal comfort, and provide scientific guidance for managing negative emotions during public health emergencies.

Comparison of the effectiveness of 0.5% and 0.25% proparacaine hydrochloride eye drops as topical anesthetics in routine ocular investigations and procedures.

To compare the effectiveness of 0.5% and 0.25% proparacaine eye drops in providing topical anesthesia for routine ocular procedures. 137 patients (274 eyes) were included in this study. They were categorized into two groups. Group A patients received 0.5% and Group B received 0.25% proparacaine drops. A single surgeon performed all the procedures. Intraprocedural and postprocedural pain scores, surgeon comfort, supplemental anesthesia, and vital parameters, were noted. The mean age of the participants was 69.42 years (±12.05). An equal number of procedures were performed (n = 30) for applanation tonometry, lacrimal sac syringing, and A-scan biometry. The other procedures performed were removal of the conjunctiva (n = 5) and corneal foreign bodies (n = 16 per group), corneal scraping (n = 8 per group), and corneal suture removal (n = 18 per group).The mean visual analog pain score during the procedure was 6.9663 in Group A and 8.0803 in Group B (P = 0.66). The mean postprocedural pain score was not significant (P = 0.21). None of the patients required any additional anesthesia during or after the procedure. The average surgeon's experience was 0.152±0.507 in Group A and 0.111±0.402 in Group B (P = 0.07).In Group A, 133 of 137 patients (97.08%), and in Group B, 132 out of 137 patients (96.35%) preferred to use the same anesthetic for future procedures. None of the patients experienced a vasovagal attack or any change in vital parameters. The present study aimed to establish equivalence between two concentrations of proparacaine hydrochloride in which false positive and false negative errors were expected. This is the inherent challenge in the equivalence and inferiority trials. To mitigate these risks, the present study was carefully designed with specific statistical methods, sample size calculation, and rigorous methodology. Nevertheless, it is crucial to recognize that the risk of false positive errors remains, and the results should be interpreted with this in mind. These findings indicated that 0.25% proparacaine is a viable alternative to the standard 0.5% concentration in routine ophthalmic procedures, with the potential for improved patient comfort.

Sunlight exposure conditions for buildings in European localities

Sunlight exposure represents one of key parameters of indoor climate comfort, especially for residential buildings, schools and care homes. It depends on the sunlight time in specific design situations like a locality, building type, window size, position and orientation. A practical evaluation of sunlight access into buildings is based on a standard methodology in EN 17037. The methodology based on parameters of minimum solar altitude is specified for given geographical locality and time of the sunlight exposure evaluation. The aim of this study is to compare how the sunlight exposure is changed in European regions. The evaluation is based on the standard limitations to specify potentials for the building insolation assessments in different geographical localities. Research value of the study deals with the general overview of the sunlight potential of building insolation in different European climatic regions. It can be important for building design and urban planning process in those localities. The research is focused on determining the minimum solar altitude for 33 capitals and for all days from 1st February to 21st March specified by the standard to ensure the required minimum insolation time.

Optimal Control of a Semi-Active Suspension System Collaborated by an Active Aerodynamic Surface Based on a Quarter-Car Model

This paper addresses the trade-off between ride comfort and road-holding capability of a quarter-car semi-active suspension system, collaborated by an active aerodynamic surface (AAS), using an optimal control policy. The semi-active suspension system is more practical to implement due to its low energy consumption than the active suspension system while significantly improving ride comfort. First, a model of the two-DOF quarter-car semi-active suspension in the presence of an active airfoil with two weighting sets based on ride comfort and road-holding preferences is presented. Then, a comprehensive comparative study of the improved target performance indices with various suspension systems is performed to evaluate the proposed suspension performance. Time-domain and frequency-domain analyses are conducted in MATLAB® (R2024a). From the time-domain analysis, the total performance measure is enhanced by about 50% and 35 to 45%, respectively, compared to passive and active suspension systems. The results demonstrate that a semi-active suspension system with an active aerodynamic control surface simultaneously improves the conflicting target parameters of passenger comfort and road holding. Utilizing the aerodynamic effect, the proposed system enhances the vehicle’s dynamic stability and passenger comfort compared to other suspension systems.

Extension of a low-tech Model Predictive Control (MPC) algorithm for grid-supportive heat pump operation

This paper presents the further development of a low-tech Model Predictive Control (MPC) for the grid-friendly operation of heat pumps. The developed algorithm is already available in the literature [1] and successfully implemented in multiple buildings. The overall goal is, to predictively optimize comfort parameters taking into account weather forecast data for 48 h. A simple mathematical building model and an optimization function are used to calculate the heating (or cooling) requirement and determine the optimum heating (cooling) output curve over time.Based on the initial results, the algorithm is extended to include an energy price forecast. This modification enables the simultaneous optimization of comfort and heat supply costs. This forecast-based cost & comfort function is designed for the use of heat pumps in buildings with thermally activated components (TAB). The extension enables the MPC to process day-ahead electricity prices or other price signals in addition to weather forecast data. This means that the operation of heat pumps can be shifted to periods that are beneficial to the grid.The algorithm is analysed and validated in a Matlab/Simulink building simulation for a heating period of one sample month. A case study with different price scenarios is the main part of this paper. Depending on the assumed price fluctuation, the simulation leads to cost savings between 6.65 % and 12.5 % for the observation period of one month. The simulation results thus show that heat generation can be shifted to times with lower electricity prices, which leads to a significant reduction in heating costs without any significant loss of comfort. In conclusion, the developed low-tech MPC enables grid-supportive operation of heat pumps.

Investigating the Effects of PU-Based Back-Coating with Boric Acid and Titanium Dioxide Additives on Flame Retardancy Levels and Comfort Properties of 100% Cotton Denim Fabric

Abstract This study aimed to develop a cost-effective and resource-efficient application to enhance the thermal stability, flame retardancy, self-cleaning, and antibacterial properties of cotton denim fabrics through a single-step, flexible, and simple polyurethane (PU) based back-coating method, ultimately increasing the use of denim fabrics in daily and work clothes thanks to the increased functionality. This method utilizes boric acid (H3BO3) and a binary composite of H3BO3-titanium dioxide (TiO2) as functional additives while considering comfort parameters. Limiting oxygen index (LOI) and vertical burning tests were conducted to explore the thermal stability and flame retardancy of the samples, while assessments of air permeability, water vapour permeability, thermal resistance, and thermal absorptivity were performed to investigate the comfort properties. Comparing two kinds of back-coated denim fabrics, H3BO3-TiO2 back-coated cotton fabric showed the best flame retardancy with the lowest char length (45 mm) and highest LOI (27%). The air permeability values of back-coated fabrics decreased by approximately half compared to the untreated denim fabric. Although the water vapour permeability values decreased, they were less affected by the coating. Coating application reduced thermal conductivity and thermal absorbency, resulting in more thermally resistant denim fabric. This study demonstrates the potential utility of a PU-based coating incorporating TiO2 and H3BO3 on traditional cotton denim fabrics to enhance flame resistance while minimizing any adverse effects on the overall thermal comfort of the fabric.

Influence of Human Activity on Radon Concentration, Indoor Air Quality, and Thermal Comfort in Small Office Spaces.

This article focuses on the influence of occupants on the concentration of contaminants (radon Rn-222 and CO2) as well as the thermal comfort parameters. A series of sensors were placed to measure the concentration of the contaminants, temperature, and relative humidity in the test room at the Institute of Nuclear Physics PAN in Krakow (IFJ PAN), Poland. The test room is an office that is typical of the offices used in the facility. The occupants that used the space kept a detailed diary of their entry, exit, and number of people entering. The results showed that the accumulation of contaminants in such spaces may be severe and risks the health and safety of occupants. The accumulation of CO2 was extremely noticeable and did not diminish to the background level between the re-entry of the occupants to the office. The same was consistent for the radon concentration. The study shows how ventilation methods and small changes in occupant work strategy may influence the contaminant concentration within a test zone.

Identification and application of the best-suited machine learning algorithm based on thermal comfort data characteristic: A data-driven approach

Integrating machine learning (ML) techniques in thermal comfort analysis is pivotal in contemporary research. This study systematically evaluates and applies ML algorithms for predicting thermal comfort parameters, emphasizing data imputation, parameter-specific behaviour analysis, and the development of an Independent Parameterised Modelling Ensemble (IPME) framework. A data-driven approach addresses missing values in the ASHRAE Global Thermal Comfort Database II using ML algorithms tailored to each thermal comfort (TC) parameter. Performance metrics, such as coefficient of determination (R2) for numerical data and accuracy for categorical data, guide the selection process, resulting in optimised ML-TC pairs for imputation. The analysis reveals parameter-specific behaviours, with numerical parameters exhibiting varying correlations with environmental conditions and parameters related to individual preferences posing challenges. ML models show improved performance with categorical data, potentially because of their ability to capture subjective aspects effectively. The IPME framework was proposed to address the conventional ML limitations by employing a hybrid ensemble strategy that selects tailored TC parameter-specific ML algorithms. This approach aims to enhance prediction accuracy by acknowledging the uniqueness of parameters and harnessing diverse ML capabilities. Future research directions include further exploration of the IPME framework and post-imputation retraining of ML models to capture actual behaviour. This study underscores the potential of ML in enhancing thermal comfort analysis, offering insights into imputation strategies, parameter-specific behaviours, and ensemble modelling approaches for more reliable predictions in building environments.

Indoor air quality in elderly care centers: A multidisciplinary approach

Studying the indoor air quality (IAQ) of elderly care centers (ECCs) has important implications for ensuring residents' health and safety. This study involves a multidisciplinary analysis of chemical and microbiological pollutants, comfort parameters and potential pathogens in five ECCs to determine the IAQ in the spaces with the longest dwell time, dining room and TV room.In general, the average concentrations of CO, CH2O, and particles were greater in the dining rooms which can be attributed to the dining room's closer location to the kitchen. The layout of these areas plays a significant role, as facilities with kitchens that are not separated from the dining room exhibited poorer IAQ.Certain pathogenic-related microbes (e.g. Cutibacterium, Sphingomonas, Fusobacterium, Malassezia) were identified in air samples. In general, such genera were positively correlated with particles, CH2O and NO2 concentrations and decreased when air purification was applied. Bacterial community composition was similar among rooms and strongly depended on ECC and purification, suggesting that human occupants are the main source of airborne bacteria. Airborne fungal communities did not depend on ECC or air purification, but particles concentrations were the main explanatory variable for their composition in indoor environments.A moderate non-carcinogenic risk due to inhalation of CH2O (2.69) and PM2.5 (1.44) was observed in the studied ECCs, so natural ventilation is not sufficient to obtain adequate IAQ. The installation of supplementary ventilation systems or the use of air purifiers would be advisable to avoid health risk, especially considering the vulnerability of the residents.

Toward occupant-centric system: Multicriteria optimization of hybrid displacement–personalized ventilation system using computational fluid dynamics with computer-simulated person

Engineers have integrated general ventilation systems with personalized ventilation (PV) to achieve energy efficiency while providing good indoor air quality (IAQ) and thermal comfort. Previous studies conducted parametric analyses of PV by varying its flow rate and temperature, analyzing energy, IAQ, and thermal comfort while keeping main ventilation settings constant, even though the latter significantly affect the general flow field. Therefore, computational fluid dynamics simulation is performed to simultaneously optimize the above-mentioned three outputs in an office with displacement ventilation (DV) and PV by varying the DV supply flow rate and temperature, the fraction of outlet air being resupplied to inlet or DV recirculation, and PV supply flow rate and temperature. We utilize the Taguchi design to minimize the number of simulations as well as use the “technique for order preference by similarity to ideal solution” (TOPSIS) coupled with Taguchi's signal-to-noise ratio analysis for optimization. Four optimization cases are investigated by varying the thermal comfort and IAQ parameters from volume-averaged to occupant-centric values, such as the skin temperature and inhaled concentration. Results show that occupant-centric optimization presents low energy requirements with acceptable IAQ and thermal comfort compared with volume-averaged optimization, which can be attributed to imperfect mixing conditions. Furthermore, the DV settings and thermal plumes significantly affect the direction of jet released by the PV, which does not improve the IAQ. This underscores the importance of considering the aforementioned effects in maximizing the PV potential. Nevertheless, the PV system functions as intended under a flow rate of 6 L/s.

Clothing suggestions based on comfort extracted from physiological and emotional parameters

PurposeThe comfort of apparel is not only a feeling of perception but also a tangible measure. The fit and fabric of clothing can exert a perception of comfort for the wearer, whereas actual comfort largely depends on physiological and emotional soothing. However, there is still no solid work on connecting the bridge between physiological and emotional feelings to the comfort of clothing. In this study, we have conceptualized, formulated and proven the relation between physiological and emotional parameters with clothing fit and fabric to find the true comfort of the wearer.Design/methodology/approachA mixed-method research design using physiological and emotional parameters for different fabric and fit combinations were used for this study. The physiological comfort parameters (i.e. heart rate and respiration rate) are extracted from the subjects using gold-standard clinical devices for various fit and fabric combinations. For the emotional response, a survey was conducted for the same subjects wearing all the fit and fabric combinations. Statistical analysis and modeling were performed to obtain the results.FindingsPhysiological indicators such as heart rate are closely linked with user comfort. Due to the limitations in environmental control, the physiological changes obtained did not significantly vary for different fabric and fit combinations of the clothing. However, a significant change in emotional response indicated a definite relationship between different fabric and fit types. Based on the participants’ responses, weather conditions, size of the clothing item, types of fabrics and style also influence the participants’ choice of clothing.Originality/valueThe research was conducted to discover the relation between true comfort (physiological and emotional parameters) and clothing (fit and fabric), which is unique to the field. This study closes the gap and builds up the relationship, which can help introduce clothing comfort to users in the future. The findings of this study help us understand how fabric types (natural or synthetic) and clothing fit types (loose or fitted) can affect physiological and emotional responses, which can provide the consumer with satisfactory clothing with the suitable properties needed.

A Review of In-Flight Thermal Comfort and Air Quality Status in Civil Aircraft Cabin Environments

The civil aircraft cabin is enclosed and highly occupied, making it susceptible to a decline in indoor environmental quality. The environmental quality of civil aircraft cabins not only depends on objective factors such as temperature, relative humidity, and the presence of air pollutants such as carbon dioxide (CO2), carbon monoxide (CO), ozone (O3), particle matter (PM), and volatile organic compounds (VOCs) but also the subjective factors pertaining to the perceptions and health symptoms of passengers and crew. However, few studies have thoroughly examined the air quality and thermal comfort parameters that are measured during in-flight testing in airplane cabins, as well as the passengers’ subjective perceptions. In order to evaluate the in-flight thermal comfort and air quality status, this study conducted a review of the recent literature to compile data on primary categories, standard limits, and distribution ranges of in-flight environmental factors within civil aircraft cabins. Following a search procedure outlined in this paper, 54 papers were selected for inclusion. Utilizing the Monte Carlo method, the Predicted Mean Vote (PMV) distributions under different exercise intensities and clothing thermal resistance were measured with the in-cabin temperature and humidity from in-flight tests. Recommendations based on first-hand data were made to maintain the relative humidity in the cabin below 40%, ensure wind speed remains within the range of 0–1 m/s, and regulate the temperature between 25–27 °C (for summer) and 22–27 °C (for winter). The current estimated cabin air supply rate generally complies with the requirements of international standards. Additionally, potential carcinogenic and non-carcinogenic risks associated with formaldehyde, benzene, tetrachloroethylene, and naphthalene were calculated. The sorted data of in-flight tests and the evaluation of the subjective perception of the occupants provide an evaluation of current cabin thermal comfort and air quality status, which can serve as a reference for optimizing indoor environmental quality in future generations of civil aircraft cabins.

The effect of music on pain, comfort, and physiological parameters during premature retinopathy examination

AimTo determine the effect of music applied during the ROP examination on pain, comfort, and physiological parameters in preterm infants. MethodsThe sample of this prospective randomized controlled double-blind experimental study consisted of 28 preterm infants who were examined for ROP of a tertiary hospital in the Neonatal Unit. Data were collected with a Questionnaire, Physiological Parameters Observation Form (PPOF), Revised-Premature Infant Pain Profile (PIPP-R), and Premature Infant Comfort Scale (PICS). ResultsThe results revealed that the crying times of the infants in the experimental group were shorter than the infants in the control group. The preterm infants in the experimental group had statistically lower PIPP-R scores during and after the procedure than the PIPP-R scores of the infants in the control group (p < 0.001) and the music applied to the preterm infants resulted in a mean decrease of 3.857 in the post-procedure and pre-procedure PIPP-R scores (p < 0.05). While there was no statistical difference between the pre-procedure and pre-procedural PICS scores of the preterm infants in the experimental and control groups (p = 0.599; p = 117), the post-procedure PICS values of the preterm infants in the experimental group were found to be lower than those of the control group (p < 0.001). It was found that the music applied to preterm infants during the ROP examination resulted in a mean decrease of 1.286 in PICS scores after the procedure and before the procedure (p < 0.05). ConclusionIt was determined that the music listened to during the ROP examination decreased the PIPP-R pain scores of preterm infants, had a positive effect on the PICS scores after the procedure, but did not affect the physiological parameters positively.Trial Registration: ClinicalTrials.gov Identifier: NCT05263973

Assessment of the impact of setting the heating curve on reducing gas consumption in a residential building while ensuring thermal comfort

Due to the large share of the residential building sector in CO2 emissions, it is necessary to look for quick-to-implement and cost-free solutions for heating systems aimed at increasing their efficiency and reducing fuel consumption. The aim of the study is a multi-aspect assessment of the proper setting of the heating curve in the weather controller of a low-temperature floor heating system with a condensing gas boiler, and an analysis of the impact of the heating curve slope on the natural gas consumption, the emission of gaseous and dust pollutants and on maintaining appropriate indoor air parameters: air temperature, operative temperature and PMV and PPD. A wide range of simulation tests were carried out using the TRNSYS software for an existing energy-efficient single-family residential building, with mechanical ventilation with heat recovery, located in north-eastern Poland in Bialystok. Changing the heating curve slope by 0.1 can reduce gas consumption and pollutant emissions by 1.6–10.3 %. Low heating curve slopes may result in failure to reach the temperature set by users (difference between the set and achieved indoor temperature up to 1.9 K), while maintaining standard thermal comfort parameters (−0.5<PMV<+0.5; PPD<10 %). Reducing the indoor air temperature by 2 K can contribute to reducing gas consumption by 11 % while maintaining standard thermal comfort parameters. Changing the heating curve slope is one of the effective methods of reducing fuel consumption in the building. Results are useful for users of buildings equipped with low-temperature heating systems with floor heating and installers of these systems.

A Systematic Review for Indoor and Outdoor Air Pollution Monitoring Systems Based on Internet of Things

Global population growth and increasing pollution levels are directly related. The effect does not just apply to outdoor spaces. Likewise, the low indoor air quality is also having a negative impact on the health of the building residents. According to the World Health Organization, indoor air pollution is a leading cause of 1.6 million premature deaths annually. Tackling this public health issue, due to the direct relationship between air pollution levels and mortality and morbidity rates as well as overall comfort, is mandatory. Many companies have begun to build inexpensive sensors for use in Internet of Things (IoT)-based applications to pollution monitoring. The research highlights design aspects for sustainable monitoring systems including sensor types, the selected parameters, range of sensors used, cost, microcontrollers, connectivity, communication technologies, and environments. The main contribution of this systematic paper is the synthesis of existing research, knowledge gaps, associated challenges, and future recommendations. Firstly, the IEEE database had the highest contribution to this research (48.51%). The results showed that 87.1%, 66.3%, and 36.8% of studies focused on harmful gas monitoring, thermal comfort parameters, and particulate matter levels pollution, respectively. The most studied harmful gases were CO2, CO, NO2, O3, SO2, SnO2, and volatile organic compounds. The cost of the sensors was suitable for people with limited incomes and mostly under USD 5, rising to USD 30 for specific types. Additionally, 40.35% of systems were based on ESP series (ESP8266 and ESP32) microcontrollers, with ESP8266 being preferred in 34 studies. Likewise, IoT cloud and web services were the preferred interfaces (53.28%), while the most frequent communication technology was Wi-Fi (67.37%). Indoor environments (39.60%) were the most studied ones, while the share for outdoor environments reached 20.79% of studies. This is an indication that pollution in closed environments has a direct impact on living quality. As a general conclusion, IoT-based applications may be considered as reliable and cheap alternatives for indoor and outdoor pollution monitoring.

3D CFD simulation of room air temperature and velocity with ceiling fan and exhaust fan and the resulting thermal comfort

The integration of energy-efficient solutions remains an essential hurdle in the pursuit of sustainable and comfortable indoor settings. As building energy consumption continues to climb, there is an urgent need to implement methods that reduce environmental effects, and at the same time, maintain adequate thermal comfort for occupant well-being and productivity. Ceiling fans, a standard fixture in many indoor settings, have gained popularity for their ability to provide better air movement and temperature adjustment while using substantially less energy than standard HVAC systems. This work presents a 3D Computational Fluid Dynamics (CFD) investigation of thermal comfort that can be achieved with a ceiling fan and an exhaust fan. A 3D fan zone model available in ANSYS Fluent was used to model the ceiling fan, considering the ceiling fan as a solid disc. Numerical methodology has been validated by verifying the transient simulation results against the experimental data available in the literature. The work analyzes thermal comfort parameters - temperature and velocity - in a room with a typical ceiling fan or an exhaust fan available in India. The room temperature and velocity distribution are presented for different times of a day in summer for a warm and humid climatic zone in India. The results show that the thermal comfort obtained with the exhaust fan is better than that with the ceiling fan for the evening, night, and early morning.

Research and numerical assessment of design and construction errors in the swimming pool facility structures

Swimming pools are characterized by high humidity, high temperature, an aggressive environment caused by disinfection processes, high energy consumption, and extensive technical infrastructure. As a result, these facilities are at high risk of damage, including structural damage, which can have catastrophic consequences in extreme cases. Adequate ventilation plays a critical role in natatoria. The technical condition of swimming pool facilities should be regularly inspected to ensure that they are safe for the public. Various techniques can be used for this purpose. In the present study, a numerical analysis of ventilation performance and an assessment of the risks associated with design and construction errors in the ventilation system were conducted in a swimming pool building with a volume of 116,280.7 m3 and a surface area of 20,188.6 m2 in north-eastern Poland. Two scenarios were analyzed: the performance of the originally designed ventilation system and the performance of the ventilation system installed in the examined facility. The analyses were conducted with the use of computational fluid dynamics (CFD) tools in the FloVent program. Air distribution was determined by measuring ventilation parameters and conducting smoke tests in analyzed natatorium, and the obtained data were consistent with the results of the numerical analysis. The analyzed scenarios were compared to identify the risks associated with inadequate ventilation in swimming pools. A significant decrease in air supply led to local increases in air velocity and worsened thermal comfort parameters in the real-world facility. In addition, the decrease in air supply induced changes in air distribution and prevented air streams from reaching all parts of the natatorium. Some areas were inadequately ventilated, and condensed water vapor settled on the building’s glass facade and the roof, posing a direct threat to structural elements. The results of the numerical analysis were congruent with on-site measurements, which indicates that CFD tools are highly useful for assessing ventilation systems in swimming pools. These tools can be used to analyze ventilation performance and optimize the proposed solutions already at the design stage. The applied tools enable designers to eliminate construction errors and optimize a building’s structural safety, performance, and energy efficiency.