5 results
Search Results
Now showing 1 - 5 of 5
Article Citation - WoS: 13Citation - Scopus: 13Integration 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 GokcenConventional 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.Article Citation - WoS: 17Citation - Scopus: 18Effect of Pre-And Post-Exam Stress Levels on Thermal Sensation of Students(Elsevier Science Sa, 2021) Turhan, Cihan; Ozbey, Mehmet FurkanThe 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.Article Citation - WoS: 20Citation - Scopus: 23A 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, CihanMaintaining 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.Article Citation - WoS: 19Citation - Scopus: 21Gender 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, CihanThe 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.Article Citation - WoS: 8Citation - Scopus: 8Modeling 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, CihanPsychology 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.
