Browsing by Author "Ozbey, Mehmet Furkan"

Now showing 1 - 13 of 13

Citation - WoS: 16
Citation - Scopus: 18
A Comprehensive Comparison and Accuracy of Different Methods To Obtain Mean Radiant Temperature in Indoor Environment
(Elsevier, 2022) Ozbey, Mehmet Furkan; Turhan, Cihan
Thermal comfort is defined as "the state of mind which expresses satisfaction with the thermal environment" by the American Society of Heating, Refrigerating and Air Conditioning Engineers in the standard of the ASHRAE55. Thermal comfort is affected by six main parameters which are split into two categories; personal (basic clothing insulation value and metabolic rate) and environmental (air temperature, relative humidity, air velocity, and mean radiant temperature) parameters. The mean radiant temperature is a problematic parameter in thermal comfort studies due to its complexity. The mean radiant temperature approaches are based on different techniques such as calculation methods, measurement methods, and assumptions. Although the assumptions are utilized by researchers to abstain complexity, their accuracies are uncertain. To this aim, this study purposes to find the accuracies of calculation and assumption methods by comparing with reference measurement method. An office building in a temperate climate zone is selected as a case study. Two calculation methods and eight assumptions on obtaining mean radiant temperature are compared via in-situ measurements. The results revealed that using assumptions or calculation methods to obtain the mean radiant temperature caused a significant error compared to the reference method and researchers should consider accuracies of these methods before utilizing them in their applications.
Citation - WoS: 17
Citation - Scopus: 18
Effect of Pre-And Post-Exam Stress Levels on Thermal Sensation of Students
(Elsevier Science Sa, 2021) Turhan, Cihan; Ozbey, Mehmet Furkan
The Predicted Mean Vote and Predicted Percentage of Dissatisfied (PMV/PPD) method is used worldwide to assess thermal comfort. The PMV/PPD method traditionally depends on four environmental parameters; air temperature, relative humidity, mean radiant temperature and air velocity, and two personal parameters; metabolic rate and clothing insulation. However, accurate modelling of thermal comfort requires consideration of psychological impacts, as well as associated physical responses to the environment. This paper investigates the effect of one of the psychological parameters; stress level on the thermal sensation of students for male and female which can be a sufficient limitation of the accuracy of thermal comfort/sensation models. Actual Thermal Sensation (ATS) and Profile of Mood States (POMS) are used to examine the effect of stress level on the thermal sensation. Pre-test-Post-test Control (PPC) experimental design is conducted on the students in a university, Ankara, Turkey, which has a Csb type climate zone according to Koppen-Geiger climate classification. First, students are split into two random groups; control and experimental groups. The students in experimental group are requested to attend exam while the students in control group read their favourite books. Then, students are subjected to pre-and post-exam surveys in order to understand the relationship between stress level and ATS. As a supportive analysis, Heart Rate (HR) and Skin Temperature (ST) are also included in the study as sympathetic responses of occupants to the thermal discomfort due to stress. Smart wristbands and infrared thermometers are used to measure Heart Rate and Skin Temperature of the students. Results showed that there is a difference between control group and experimental group before the exam (pre-test) except the ST of females. After the exam (post-test), there are no significant differences between two groups. (C) 2020 Elsevier B.V. All rights reserved.
Estimation of the Mean Radiant Temperature in Office Buildings Using an Artificial Neural Network Developed in a Phyton Environment
(Taylor & Francis Ltd, 2025) Ozbey, Mehmet Furkan; Lotfi, Bahram; Turhan, Cihan
Thermal comfort describes an occupant's state of mind in a thermal environment, influenced by six parameters: air velocity, relative humidity, air temperature, mean radiant temperature (MRT), clothing value, and metabolic rate. MRT is the most problematic parameter since the obtaining process is difficult and time-consuming. MRT can be acquired by several methods such as calculations, measurements, assumptions, and software programmes. However, the methods have complexities and uncertainties. Comprehensive models are needed to obtain MRT. To this aim, this study presents an alternative method using one of the artificial intelligence methods, Artificial Neural Network (ANN), to predict MRT for indoor environments to abstain from the difficulties and complexities. A case building is selected in a university office building in Ankara, T & uuml;rkiye. The proposed model is developed and coded in a Python programming environment to predict the MRT using ANN. The results indicate that the ANN model, using only four inputs, predicts MRT with an R-2 value of 0.94 compared to the globe thermometer measurement method. The model's advantages over methods include simplicity, time efficiency and learning from the limited datasets such as difficulty in calculating terms like MRT.
Citation - WoS: 19
Citation - Scopus: 21
Gender Inequity in Thermal Sensation Based on Emotional Intensity for Participants in a Warm Mediterranean Climate Zone
(Elsevier France-editions Scientifiques Medicales Elsevier, 2023) Ceter, Aydin Ege; Ozbey, Mehmet Furkan; Turhan, Cihan
The deficiencies of the one of the most preferred conventional thermal comfort models, the Predicted Mean Vote/ Percentage of Predicted Dissatisfied (PMV/PPD) method have emerged over time since the model does not take psychological parameters such as personal traits, mood states and adaptation into account. Therefore, re-searchers have focused on Adaptive Thermal Comfort models that integrate human behaviours into the model for better prediction of thermal comfort. In addition to the influence of the behaviours of occupants, thermal comfort may be evaluated as a subjective term, thus, the effect of one of the psychological parameters, current mood state, on thermal sensation cannot be ignored for predictions. Although, the effect of current mood state on thermal sensation is a vital concept, the findings of the studies are not effective and comprehensive in the literature. For this reason, the aim of this study is to examine the relationship between current mood state and thermal sensation in gender difference aspect. Therefore, a series of experiments were conducted in a university study hall between August 16th, 2021 and August 1st, 2022. The current mood states of the participants were evaluated with the Profile of Mood States (POMS) questionnaire and the results were represented by a novel approach called Emotional Intensity Score (EIS). One tailed t-test was applied for investigating the relationship between the EIS and the thermal sensation. Findings of the research showed that a significant association exists between the EIS and thermal sensation for male participants while no relationship was found for female.
Citation - WoS: 2
Citation - Scopus: 2
Impact of Green Wall and Roof Applications on Energy Consumption and Thermal Comfort for Climate Resilient Buildings
(Mdpi, 2025) Turhan, Cihan; Carpino, Cristina; Austin, Miguel Chen; Ozbey, Mehmet Furkan; Akkurt, Gulden Gokcen
Nowadays, reducing energy consumption and obtaining thermal comfort are significant for making educational buildings more climate resilient, more sustainable, and more comfortable. To achieve these goals, a sustainable passive method is that of applying green walls and roofs that provide extra thermal insulation, evaporative cooling, a shadowing effect, and the blockage of wind on buildings. Therefore, the objective of this study is to evaluate the impact of green wall and roof applications on energy consumption and thermal comfort in an educational building. For this purpose, a university building in the Csb climate zone is selected and monitored during one year, as a case study. Then, the case building is modelled in a well-calibrated dynamic building energy simulation tool and twenty-one different plant species, which are mostly used for green walls and roofs, are applied to the envelope of the building in order to determine a reduction in energy consumption and an increase in thermal comfort. The Hedera canariensis gomera (an ivy species) plant is used for green walls due to its aesthetic appeal, versatility, and functional benefits while twenty-one different plants including Ophiopogon japonicus (Mando-Grass), Phyllanthus bourgeoisii (Waterfall Plant), and Phoenix roebelenii (Phoenix Palm) are simulated for the green roof applications. The results show that deploying Hedera canariensis gomera to the walls and Phyllanthus bourgeoisii to the roof could simultaneously reduce the energy consumption by 9.31% and increase thermal comfort by 23.55% in the case building. The authors acknowledge that this study is solely based on simulations due to the high cost of all scenarios, and there are inherent differences between simulated and real-world conditions. Therefore, the future work will be analysing scenarios in real life. Considering the limited studies on the effect of different plant species on energy performance and comfort, this study also contributes to sustainable building design strategies.
Citation - WoS: 7
Citation - Scopus: 6
The Importance of the Calculation of Angle Factors To Determine the Mean Radiant Temperature in Temperate Climate Zone: a University Office Building Case
(Sage Publications Ltd, 2022) Ozbey, Mehmet Furkan; Turhan, Cihan
Thermal comfort depends on four environmental (air velocity, relative humidity, air temperature, mean radiant temperature) and two personal (clothing insulation and metabolic rate) parameters. Among all parameters, the mean radiant temperature (t(r)) is the most problematic variable in thermal comfort studies due to its complexity. Measurement methods, calculation methods and assumptions are mostly used to obtain the t(r). Researchers mainly prefer to obtain the t(r) via measurement methods or assumptions due to their easiness compared to the calculation methods. Besides, some researchers use constant values of angle factors in calculation methods. However, using constant values is not proper for every indoor environment, and it causes wrong estimations in the t(r) and thus the thermal comfort. This paper gives the importance of calculation of angle factors, with an example of a university office building in temperate climate zone, according to the ISO 7726. The angle factors of the room were calculated for a seated occupant from the centre of gravity in three different locations and compared with the constant angle factors. The results indicate that a significant difference (MAPE of 1.02) was found in the t(r) values, which were obtained by calculation of constant values of angle factors.
Citation - WoS: 12
Citation - Scopus: 13
Integration of Psychological Parameters Into a Thermal Sensation Prediction Model for Intelligent Control of the Hvac Systems
(Elsevier Science Sa, 2023) Turhan, Cihan; Ozbey, Mehmet Furkan; Lotfi, Bahram; Akkurt, Gulden Gokcen
Conventional thermal comfort models take physiological parameters into account on thermal comfort models. On the other hand, psychological behaviors are also proven as a vital parameter which affects the thermal sensation. In the literature, limited studies which combine both physiological and psychological parameters on the thermal sensation models are exist. To this aim, this study develops a novel Thermal Sensation Prediction Model (TSPM) in order to control the HVAC system by considering both parameters. A data-driven TSPM, which includes Fuzzy Logic (FL) model, is developed and coded using Phyton language by the authors. Two physiological parameters (Mean Radiant Temperature and External Temperature) and one psychological parameter (Emotional Intensity Score (EIS) including Vigour, Depression, Tension with total of 32 subscales) are selected as inputs of the model. Besides the physiological parameters which are decided intentionally considering a manual ventilated building property, the most influencing three sub- psychological parameters on thermal sensation are also selected in the study. While the physiological parameters are measured via environmental data loggers, the psychological parameters are collected simultaneously by the Profile of Mood States questionnaire. A total of 1159 students are participated to the questionnaire at a university study hall between 15th of August 2021 and 15th of September 2022. The results showed that the novel model predicted Thermal Sensation Vote (TSV) with an accuracy of 0.92 of R2. The output of this study may help to develop an integrated Heating Ventilating and Air Conditioning (HVAC) system with Artificial Intelligence - enabled Emulators that also includes psychological parameters.
Citation - WoS: 1
Citation - Scopus: 1
Latent Psychological Pathways in Thermal Comfort Perception: The Mediating Role of Cognitive Uncertainty on Depression and Vigour
(MDPI, 2025) Ozbey, Mehmet Furkan; Turhan, Cihan; Alkan, Nese; Akkurt, Gulden Gokcen
Thermal comfort is the condition of mind that expresses satisfaction with the thermal environment, and it is assessed through subjective evaluation, according to the American Society of Heating, Refrigerating, and Air-Conditioning Engineers. While research has traditionally emphasised physical factors, growing evidence highlights the role of the state of mind in shaping thermal perception. In a prior Monte Carlo sensitivity analysis, six mood subscales-Anger, Confusion, Vigour, Tension, Depression, and Fatigue-were examined for how they affect the absolute difference between actual and predicted thermal sensation. Depression and vigour were found to be the most influential, while confusion appeared least impactful. However, to accurately assess the role of confusion, it is necessary to consider its potential interactions with other mood subscales. To this end, a mediation analysis was conducted using Hayes' PROCESS tool. The mediation analyses revealed that confusion partially mediated depression's effect in males and vigour's effect in females. These results suggest that, despite a weak direct impact, confusion critically influences thermal perception by altering the effects of key mood states. Accounting for the indirect effects of mood states may lead to more accurate predictions of human sensory experiences and improve the design of occupant-centred environments.
Citation - WoS: 8
Citation - Scopus: 8
Modeling the Mood State on Thermal Sensation With a Data Mining Algorithm and Testing the Accuracy of Mood State Correction Factor
(Pergamon-elsevier Science Ltd, 2025) Yerlikaya-Ozkurt, Fatma; Ozbey, Mehmet Furkan; Turhan, Cihan
Psychology is proven as an influencing factor on thermal sensation. On the other hand, mood state is one of the significant parameters in psychology field. To this aim, in the literature, mood state correction factor on thermal sensation (Turhan and Ozbey coefficients) is derived utilizing with data-driven black-box model. However, novel models which present analytical form of the mood state correction factor should be derived based on the several descriptive variables on thermal sensation. Moreover, the result of this factor should also be checked with analytical model results. Therefore, this study investigates the modelling of mood state correction factor with a data mining algorithm, called Multivariate Adaptive Regression Splines (MARS). Additionally, the mood state is also taken as a thermal sensation parameter besides environmental parameters in this algorithm. The same data, which are collected from a university study hall in a temperate climate zone, are used and the model results are compared with the thermal sensation results based on mood state correction factor which is driven via black-box model. The results show that coefficient of correlation "r" between the MARS and black-box model is found as 0.9426 and 0.9420 for training and testing. Hence, the mood state is also modelled via a data mining algorithm with a high accuracy, besides the black-box model.
Citation - WoS: 1
Citation - Scopus: 1
Modelling the Positive and Negative Interaction Between Mood and Thermal Sensation in the Built Environment Using a Combined Markov Chain Monte Carlo Algorithm and Morris Method
(Sage Publications Ltd, 2025) Ozbey, Mehmet Furkan; Turhan, Cihan
Mood states, categorized into subscales such as Tension (TEN), Anger (ANG), Fatigue (FAT), Vigour (VIG), Confusion (CON), and Depression (DEP), affect occupants' perceptions of thermal environments. This study investigates the influence of these subscales on thermal sensation, exploring both positive and negative effects. Experiments were conducted in a temperate climate zone over an extended period, including both heating and cooling seasons, with 1159 volunteers. The Morris Method was used to assess the impact of psychological parameters (TEN, ANG, FAT, VIG, CON, DEP) on thermal sensation. Markov Chain Monte Carlo (MCMC) simulations, performed via Python code developed by the authors, evaluated the positive and negative impacts of these subscales across 30,000 simulations. Results showed that VIG was the most influential parameter, while CON and FAT had negative effects (feeling cooler) on thermal sensation. These findings emphasize the complex relationship between psychological factors and thermal perception, underlining the importance of mood states in designing environments that enhance thermal comfort. The study offers valuable insights into the interplay of emotional well-being and physiological responses, contributing to environmental psychology and climate-responsive design.
Citation - WoS: 20
Citation - Scopus: 23
A Novel Comfort Temperature Determination Model Based on Psychology of the Participants for Educational Buildings in a Temperate Climate Zone
(Elsevier, 2023) Ozbey, Mehmet Furkan; Turhan, Cihan
Maintaining thermal comfort in the educational buildings is vital due to the impacts on learning effectiveness of students. Therefore, development of a proper comfort temperature in educational buildings is a must. In naturally ventilated and mixed-mode buildings, the adaptive thermal comfort model, which considers additively psychological, and behavioural factors to the Fanger's PMV/PPD model, is commonly applied based on regression analyses. However, the psychological adjustments based on current mood state are very limited in these adaptive thermal comfort models. Therefore, this study focuses on the psychological adjustments in terms of Profile of Mood States in order to predict comfort temperature of students in a case building. The experiments are conducted in a university on a temperate climate zone for a long period-data including both heating and cooling seasons. In this study, the comfort temperatures for each student are determined via Griffith method for the case building. Moreover, the current mood states of students are assessed utilizing the Profile of Mood States survey, which are collected via a developed mobile application. As a conclusion, the relation between the current mood state of the students and comfort temperature are statistically investigated. The results show that a Griffith constant are found as 0.332/K and mean annual comfort temperature is found as 21.32 degrees C in the case building. Additionally, a significant difference is found in the comfort temperatures among the students who have more, or fewer concerns than typically reported. The novelty of the study is to present a comfort temperature determination model which considers human psychology as a starter study in the literature.
Citation - WoS: 30
Citation - Scopus: 30
A Novel Data-Driven Model for the Effect of Mood State on Thermal Sensation
(Mdpi, 2023) Turhan, Cihan; Ozbey, Mehmet Furkan; Ceter, Aydin Ege; Akkurt, Gulden Gokcen
Thermal comfort has an important role in human life, considering that people spend most of their lives in indoor environments. However, the necessity of ensuring the thermal comfort of these people presents an important problem, calculating the thermal comfort accurately. The assessment of thermal comfort has always been problematic, from past to present, and the studies conducted in this field have indicated that there is a gap between thermal comfort and thermal sensation. Although recent studies have shown an effort to take human psychology into account more extensively, these studies just focused on the physiological responses of the human body under psychological disturbances. On the other hand, the mood state of people is one of the most significant parameters of human psychology. Thus, this paper investigated the effect of occupants' mood states on thermal sensation; furthermore, it introduced a novel "Mood State Correction Factor" (MSCF) to the existing thermal comfort model. To this aim, experiments were conducted at a mixed-mode building in a university between 15 August 2021 and 15 August 2022. Actual Mean Vote (AMV) and Profile of Mood States (POMS) were used to examine the effect of mood state on thermal sensation. The outcomes of this study showed that in the mood states of very pessimistic and very optimistic, the occupants felt warmer than the calculated one and the MSCFs are calculated as -0.125 and -0.114 for the very pessimistic and very optimistic mood states, respectively. It is worth our time to note that the experiments in this study were conducted during the COVID-19 Global Pandemic and the results of this study could differ in different cultural backgrounds.
Citation - WoS: 20
Citation - Scopus: 21
Sensitivity Analysis of the Effect of Current Mood States on the Thermal Sensation in Educational Buildings
(Wiley-hindawi, 2022) Ozbey, Mehmet Furkan; Ceter, Aydin Ege; Orfioglu, Sevval; Alkan, Nese; Turhan, Cihan
Adaptive thermal comfort is a model which considers behavioral and psychological adjustments apart from Fanger's Predicted Mean Vote (PMV)/Percentage of Dissatisfied (PPD) method. In the literature, the differences between the PMV/PPD method and adaptive thermal comfort were mainly considered in aspects of behavioral adjustments in an environment. Conversely, limited studies related to psychological adjustments were considered in detail for thermal comfort. This study purposes to investigate the effects of current mood state subscales on thermal sensation of the occupants for the first time in the literature. To this aim, the Profile of Mood States (POMS) questionnaire is used to determine the mood state of the occupants with six different subscales: Anger, Confusion, Vigor, Tension, Depression, and Fatigue. The experiments were conducted in a university study hall in Ankara, Turkey, which is in warm-summer Mediterranean climate (Csb) according to Koppen-Geiger Climate Classification. The distributions of each subscale were examined via Anderson Darling and Shapiro-Wilk tests accordingly given responses from the occupants. The sensitivity analysis was applied to the six subscales of the POMS with Monte Carlo simulation method by considering the distributions of each subscale. The results revealed that the current mood state has a crucial effect on the thermal sensation of the occupants. The subscales of the Depression and Vigor were found as the most vital ones among the six subscales. Only the pure effects of the Vigor and Depression would change the thermal sensation of the occupants 0.31 and 0.30, respectively. The Confusion was determined as the least effective subscale to the thermal sensation of the occupants. Moreover, with the combination of all the six subscales, the thermal sensation might change up to 1.32. Findings in this study would help researchers to develop the personalized thermal comfort systems.