Turhan, Cihan

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Profile URL
https://hdl.handle.net/20.500.14411/6960
Name Variants
Cihan, Turhan
T.,Cihan
Turhan, Cihan
C., Turhan
T., Cihan
Turhan, C.
C.,Turhan
Turhan,C.
Turhan C.
Job Title
Doçent Doktor
Email Address
cihan.turhan@atilim.edu.tr
Main Affiliation
Energy Systems Engineering
Status
Website
ORCID ID
Scopus Author ID
56011415300
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
ABD-1880-2021

Sustainable Development Goals

2

ZERO HUNGER
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0

Research Products

11

SUSTAINABLE CITIES AND COMMUNITIES
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15

Research Products

14

LIFE BELOW WATER
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0

Research Products

6

CLEAN WATER AND SANITATION
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0

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1

NO POVERTY
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0

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5

GENDER EQUALITY
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3

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9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
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1

Research Products

16

PEACE, JUSTICE AND STRONG INSTITUTIONS
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0

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17

PARTNERSHIPS FOR THE GOALS
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0

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15

LIFE ON LAND
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0

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10

REDUCED INEQUALITIES
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1

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7

AFFORDABLE AND CLEAN ENERGY
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11

Research Products

8

DECENT WORK AND ECONOMIC GROWTH
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1

Research Products

4

QUALITY EDUCATION
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5

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12

RESPONSIBLE CONSUMPTION AND PRODUCTION
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4

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3

GOOD HEALTH AND WELL-BEING
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1

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13

CLIMATE ACTION
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1

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Documents

45

Citations

727

h-index

15

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Documents

40

Citations

634

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Scholarly Output

47

Articles

31

Views / Downloads

248/1418

Supervised MSc Theses

7

Supervised PhD Theses

0

WoS Citation Count

478

Scopus Citation Count

551

WoS h-index

13

Scopus h-index

14

Patents

0

Projects

0

WoS Citations per Publication

10.17

Scopus Citations per Publication

11.72

Open Access Source

18

Supervised Theses

7

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JournalCount
Buildings4
Energy and Buildings4
Mugla Journal of Science and Technology2
Sustainability2
Journal of Building Engineering2
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Scholarly Output Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    Article
    Citation - WoS: 13
    Citation - Scopus: 14
    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.
  • Thumbnail Image
    Article
    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.
  • Thumbnail Image
    Article
    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.