Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 23Citation - Scopus: 27The Influence of Meteorological Parameters on Pm10: a Statistical Analysis of an Urban and Rural Environment in İzmir/Turkiye(MDPI, 2023) Birim, Necmiye Gulin; Turhan, Cihan; Atalay, Ali Serdar; Gökçen Akkurt, GüldenAir pollution is a substantial menace, especially in industrialized urban zones, which affects the balance of the environment, life of vital organisms and human health. Besides the main causes of air pollution such as dense urbanization, poor quality fuels and vehicle emissions, physical environment characteristics play an important role on air quality. Therefore, it is vital to understand the relationship between the characteristics of the natural environment and air quality. This study examines the correlations between the PM10 pollutant data and meteorological parameters such as temperature (T-air), relative humidity (RH), and wind speed (WS) and direction (WD) under the European Union's Horizon 2020 project. Two different zones (Vilayetler Evi as an urban zone and Sasali Natural Life Park as a rural zone) of Izmir Province in Turkiye are used as a case study and the PM10 data is evaluated between 1 January 2017 and 31 December 2021. A one-tailed t-test is used in order to statistically determine the relationships between the PM10 pollutant data and meteorological parameters. As a further study, practical significance of the parameters is investigated via the effect size method and the results show that the RH is found to be the most influencing parameter on the PM10 for both zones, while T-air is found to be statistically non-significant.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; Zajic, Ivan; Gökçen Akkurt, GüldenThe 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.