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Turhan, Cihan
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03.10. Department of Mechanical Engineering
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Current Staff
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Sustainable Development Goals
1NO POVERTY
0
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2ZERO HUNGER
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3GOOD HEALTH AND WELL-BEING
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4QUALITY EDUCATION
1
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5GENDER EQUALITY
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6CLEAN WATER AND SANITATION
1
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7AFFORDABLE AND CLEAN ENERGY
5
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8DECENT WORK AND ECONOMIC GROWTH
1
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9INDUSTRY, INNOVATION AND INFRASTRUCTURE
8
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10REDUCED INEQUALITIES
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11SUSTAINABLE CITIES AND COMMUNITIES
5
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12RESPONSIBLE CONSUMPTION AND PRODUCTION
2
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13CLIMATE ACTION
6
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14LIFE BELOW WATER
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15LIFE ON LAND
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16PEACE, JUSTICE AND STRONG INSTITUTIONS
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17PARTNERSHIPS FOR THE GOALS
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Scholarly Output
27
Articles
19
Views / Downloads
66485/10690
Supervised MSc Theses
3
Supervised PhD Theses
1
WoS Citation Count
319
Scopus Citation Count
361
Patents
0
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1
WoS Citations per Publication
11.81
Scopus Citations per Publication
13.37
Open Access Source
22
Supervised Theses
4
| Journal | Count |
|---|---|
| Energy and Buildings | 5 |
| Buildings | 3 |
| Journal of Thermal Engineering | 2 |
| IFAC-PapersOnLine | 2 |
| Energies | 1 |
Current Page: 1 / 3
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27 results
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Now showing 1 - 10 of 27
Conference Object Citation - WoS: 1Citation - Scopus: 2Analysis and Application of Advanced Control Strategies To a Heating Element Nonlinear Model(IOP Publishing Ltd., 2017) Turhan, Cihan; Turhan, Cihan; Zajic, Ivan; Gökçen Akkurt, Gülden; 03.10. Department of Mechanical Engineering; 03.06. Department of Energy Systems Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyThis paper presents the design of different control strategies applied to a heating element nonlinear model. The description of this heating element was obtained exploiting a data-driven and physically meaningful nonlinear continuous-time model, which represents a test-bed used in passive air conditioning for sustainable housing applications. This model has low complexity while achieving high simulation performance. The physical meaningfulness of the model provides an enhanced insight into the performance and functionality of the system. In return, this information can be used during the system simulation and improved model- based and data-driven control designs for tight temperature regulation. The main purpose of this study is thus to give several examples of viable and practical designs of control schemes with application to this heating element model. Moreover, extensive simulations and Monte- Carlo analysis are the tools for assessing experimentally the main features of the proposed control schemes, in the presence of modelling and measurement errors. These developed control methods are also compared in order to evaluate advantages and drawbacks of the considered solutions. Finally, the exploited simulation tools can serve to highlight the potential application of the proposed control strategies to real air conditioning systems.Article Citation - WoS: 7Citation - Scopus: 7The Importance of Internal Heat Gains for Building Cooling Design(Yıldız Teknik Üniversitesi, 2017) Durmuş Arsan, Zeynep; Turhan, Cihan; Durmuş Arsan, Zeynep; Coşkun, Turgay; Turhan, Cihan; Gökçen Akkurt, Gülden; 02.02. Department of Architecture; 03.10. Department of Mechanical Engineering; 03.06. Department of Energy Systems Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology; 02. Faculty of ArchitectureThis paper aims to investigate the effect of internal heat gains on the cooling load of a building. The house occupied by three adult men is selected as the case study for paper. The house is in the third floor of the apartment. The apartment has four flats and it has no insulation around the external walls. The heat dissipation from lighting devices, electrical equipment and the occupants are calculated by using the DesignBuilder v4 Beta release simulation program. The temperature of the house is observed during three weeks by using hobo data loggers and calibration of the measurements is made with respect to weather data file of the flat. Detailed schedule based on time of operation and occupancy is prepared to get more accurate results. Annual energy consumption and cooling load of the house is determined by using the dynamic simulation program.Article Citation - WoS: 7Citation - Scopus: 8Performance Indices of Soft Computing Models To Predict the Heat Load of Buildings in Terms of Architectural Indicators(Yıldız Teknik Üniversitesi, 2017) Turhan, Cihan; Kazanasmaz, Zehra Tuğçe; Gökçen Akkurt, Gülden; Kazanasmaz, Zehra Tuğçe; Turhan, Cihan; 02.02. Department of Architecture; 03.10. Department of Mechanical Engineering; 03.06. Department of Energy Systems Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology; 02. Faculty of ArchitectureThis study estimates the heat load of buildings in Izmir/Turkey by three soft computing (SC) methods; Artificial Neural Networks (ANNs), Fuzzy Logic (FL) and Adaptive Neuro-based Fuzzy Inference System (ANFIS) and compares their prediction indices. Obtaining knowledge about what the heat load of buildings would be in architectural design stage is necessary to forecast the building performance and take precautions against any possible failure. The best accuracy and prediction power of novel soft computing techniques would assist the practical way of this process. For this purpose, four inputs, namely, wall overall heat transfer coefficient, building area/ volume ratio, total external surface area and total window area/total external surface area ratio were employed in each model of this study. The predicted heat load is evaluated comparatively using simulation outputs. The ANN model estimated the heat load of the case apartments with a rate of 97.7% and the MAPE of 5.06%; while these ratios are 98.6% and 3.56% in Mamdani fuzzy inference systems (FL); 99.0% and 2.43% in ANFIS. When these values were compared, it was found that the ANFIS model has become the best learning technique among the others and can be applicable in building energy performance studies.Conference Object Citation - Scopus: 1Comfort Based Investigation on Historic Libraries for User Satisfaction and Preservation of Paper-Based Collections(IOP Publishing, 2021) Turhan, Cihan; Topan, Çağrı; Durmuş Arsan, Zeynep; Gökçen Akkurt, Gülden; Gökçen Akkurt, Gülden; Durmuş Arsan, Zeynep; 02.02. Department of Architecture; 03.10. Department of Mechanical Engineering; 03.06. Department of Energy Systems Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology; 02. Faculty of ArchitectureHistoric libraries preserve cultural heritage values while housing rare manuscripts and paper-based collections. The collections in the libraries are deteriorated chemically, biologically and mechanically due to inappropriate indoor environment conditions such as temperature and relative humidity fluctuations and microbiological conditions. Apart from preserving vulnerable paper-based collections, accommodating of a considerable thermal comfort level for visitors is essential in historic libraries. The aim of this study is to analyse indoor environment of a historic library in terms of thermal comfort and preventive conservation of paper-based collections. Izmir National Library, built in 1933, is selected as a case study. Indoor air temperature, relative humidity and air velocity in the library were monitored with a one-year measurement campaign. Meanwhile, thermal comfort of the visitors was assessed with PMV/PPD indices and thermal sensation surveys. The results show that high chemical degradation risk is detected in the library while biological and mechanical degradations are in the low risk zone. On the other hand, 87% and 93% of the visitors feel thermally satisfied in heating and cooling seasons, respectively.Article Citation - WoS: 6Citation - Scopus: 9Impact of Climate Change on Indoor Environment of Historic Libraries in Mediterranean Climate Zone(Inderscience Enterprises, 2019) Turhan, Cihan; Durmuş Arsan, Zeynep; Durmuş Arsan, Zeynep; Turhan, Cihan; Gökçen Akkurt, Gülden; Gökçen Akkurt, Gülden; 02.02. Department of Architecture; 03.10. Department of Mechanical Engineering; 03.06. Department of Energy Systems Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology; 02. Faculty of ArchitectureMost historic library buildings house valuable paper-based collections that are kept in unconditioned environments. This vulnerable cultural heritage is expected to be highly affected by climate change in the future. In this study, indoor microclimate of an unconditioned historic library, Necip Pasa Library (Izmir, Turkey) is analysed for existing conditions and future climate data. The measured and predicted indoor microclimate data from 'present' till 2080s are used to determine possible chemical degredation risk on library collection and human comfort. Comparison of periodic results of future climate data indicates an increase in temperature that could cause both an increase in chemical degredation risk on the library collection and a decline in thermal comfort conditions. Mitigation of climate change effects on library collection and human comfort requires taking some actions such as adding light and adaptive mechanical solutions.Doctoral Thesis Development of Energy-Efficient Personalized Thermal Comfort Driven Control in Hvac Systems(Izmir Institute of Technology, 2018) Turhan, Cihan; Gökçen Akkurt, Gülden; Turhan, Cihan; Gökçen Akkurt, Gülden; Simani, Silvio; 03.10. Department of Mechanical Engineering; 03.06. Department of Energy Systems Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyIncreasing thermal comfort and reducing energy consumption are two main objectives of advanced HVAC control systems. Studies conducted in the last decade show that intelligent HVAC systems can geatly affect thermal comfort, health, satisfaction, and productivity of building occupants while decreasing the energey consumption. Also, personelized thermal comfort driven control of the HVAC systems is the most effective way of saving energy and maintaining thermal comfort. In this thesis, an energy-efficient personalized thermal comfort control algorithm is developed to improve HVAC control systems. The thesis presents a complete system to control algorithm which includes the deployment of wireless sensor network. First a novel control algorithm is developed to perceived comfort conditions of occupants and to save energy. Then, a prototype of the personalized thermal comfort driven controller (PTC-DC) is manufactured an tested in a case building at İzmir Institute of Technology Campus, İzmir/Turkey. The proposed control strategy is tested betwen July 3rd, 2017 and November 1st, 2018, and compared with conventional controller in terms of energey saving and boath energetic and exergetic approaches of thermal comfort. The results showed that PTC-DC satisfies neutral thermal comfort for 92% of total measurements days while AM=0 for only 6% of total measurement days for conventional controller. From energy consumption point of wiev, PTC-DC decreased energy consumption by 13.2% compared to conventional controller.Article Citation - WoS: 6Citation - Scopus: 9Performance Analysis of Data-Driven and Model-Based Control Strategies Applied To a Thermal Unit Model(MDPI Multidisciplinary Digital Publishing Institute, 2017) Turhan, Cihan; Simani, Silvio; Gökçen Akkurt, Gülden; Turhan, Cihan; 03.10. Department of Mechanical Engineering; 03.06. Department of Energy Systems Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyThe paper presents the design and the implementation of different advanced control strategies that are applied to a nonlinearmodel of a thermal unit. A data-driven grey-box identification approach provided the physically-meaningful nonlinear continuous-time model, which represents the benchmark exploited in this work. The control problem of this thermal unit is important, since it constitutes the key element of passive air conditioning systems. The advanced control schemes analysed in this paper are used to regulate the outflow air temperature of the thermal unit by exploiting the inflow air speed, whilst the inflow air temperature is considered as an external disturbance. The reliability and robustness issues of the suggested control methodologies are verified with a Monte Carlo (MC) analysis for simulating modelling uncertainty, disturbance and measurement errors. The achieved results serve to demonstrate the effectiveness and the viable application of the suggested control solutions to air conditioning systems. The benchmark model represents one of the key issues of this study, which is exploited for benchmarking different model-based and data-driven advanced control methodologies through extensive simulations. Moreover, this work highlights the main features of the proposed control schemes, while providing practitioners and heating, ventilating and air conditioning engineers with tools to design robust control strategies for air conditioning systems.Article Citation - WoS: 96Citation - Scopus: 105Comparative Study of a Building Energy Performance Software (kep-Iyte and Ann-Based Building Heat Load Estimation(Elsevier Ltd., 2014) Turhan, Cihan; Kazanasmaz, Zehra Tuğçe; Kazanasmaz, Zehra Tuğçe; Turhan, Cihan; Erlalelitepe Uygun, İlknur; Gökçen Akkurt, Gülden; Ekmen, Kenan Evren; Gökçen Akkurt, Gülden; 02.02. Department of Architecture; 03.10. Department of Mechanical Engineering; 03.06. Department of Energy Systems Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology; 02. Faculty of ArchitectureThe several parameters affect the heat load of a building; geometry, construction, layout, climate and the users. These parameters are complex and interrelated. Comprehensive models are needed to understand relationships among the parameters that can handle non-linearities. The aim of this study is to predict heat load of existing buildings benefiting from width/length ratio, wall overall heat transfer coefficient, area/volume ratio, total external surface area, total window area/total external surface area ratio by using artificial neural networks and compare the results with a building energy simulation tool called KEP-IYTE-ESS developed by Izmir Institute of Technology. A back propagation neural network algorithm has been preferred and both simulation tools were applied to 148 residential buildings selected from 3 municipalities of Izmir-Turkey. Under the given conditions, a good coherence was observed between artificial neural network and building energy simulation tool results with a mean absolute percentage error of 5.06% and successful prediction rate of 0.977. The advantages of ANN model over the energy simulation software are observed as the simplicity, the speed of calculation and learning from the limited data sets.Article Citation - WoS: 2Citation - Scopus: 2Impact of Green Wall and Roof Applications on Energy Consumption and Thermal Comfort for Climate Resilient Buildings(Mdpi, 2025) Gökçen Akkurt, Gülden; Turhan, Cihan; Austin, Miguel Chen; Ozbey, Mehmet Furkan; Akkurt, Gulden Gokcen; 03.10. Department of Mechanical Engineering; 03.06. Department of Energy Systems Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyNowadays, 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.Article Citation - WoS: 4Citation - Scopus: 8Fault Diagnosis of a Wind Turbine Simulated Model Via Neural Networks(IFAC Secretariat, 2018) Simani, Silvio; Turhan, Cihan; Turhan, Cihan; 03.10. Department of Mechanical Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyThe fault diagnosis of wind turbine systems has been proven to be a challenging task and motivates the research activities carried out through this work. Therefore, this paper deals with the fault diagnosis of wind turbines, and it proposes viable solutions to the problem of earlier fault detection and isolation. The design of the fault indicator involves a data-driven approach, as it represents an effective tool for coping with a poor analytical knowledge of the system dynamics, together with noise and disturbances. In particular, the data-driven proposed solution relies on neural networks that are used to describe the strongly nonlinear relationships between measurement and faults. The chosen network architecture belongs to the nonlinear autoregressive with exogenous input topology, as it can represent a dynamic evolution of the system along time. The developed fault diagnosis scheme is tested by means of a high-fidelity benchmark model, that simulates the normal and the faulty behaviour of a wind turbine. The achieved performances are compared with those of other control strategies, coming from the related literature. Moreover, a Monte Carlo analysis validates the robustness of the proposed solutions against the typical parameter uncertainties and disturbances.
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