Architecture / Mimarlık
Permanent URI for this collectionhttps://hdl.handle.net/11147/24
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Conference Object Citation - Scopus: 1Daylight Performance and Lighting Energy Savings of Amorphous and Crystalline Silicon Solar Cells in an Architecture Studio(IEEE, 2023) Taşer, Aybüke; Kazanasmaz, Zehra TuğçeSemi-transparent photovoltaic (PV) glass increased its popularity due to its energy and environmental advantages, which can generate electricity on-site and utilize natural daylight. They use thin-film solar cells to allow daylight to enter space and generate electrical energy. Crystalline and amorphous silicon (a-Si) solar cells are the most prominent in literature and industry due to their high efficiency and sufficient transparency. This study aims to assess the daylight and lighting energy-saving potential of thin-film crystalline and a-Si photovoltaic glass in an architecture studio in Izmir, Turkey. The simulation engine applied two types of solar cells on existing windows to evaluate the advantage of such glass for daylight performance and lighting energy consumption. Spatial Daylight Autonomy (sDA), a climate-based annual daylight performance metric, evaluates the daylight performance of the studio. Research findings note that such solar cells enhance the visual comfort of occupants and the daylight performance of the studio. In addition, crystalline silicon solar cells can cover the studio's whole lighting loads in the summer and fall seasons and balance them up to 66% and 23% in the spring and winter seasons, respectively. These have higher transmittance and peak power, thus; resulting in higher energy and daylight performance. © 2023 IEEE.Article Citation - WoS: 3Citation - Scopus: 5Deterioration of Pre-War and Rehabilitation of Post-War Urbanscapes Using Generative Adversarial Networks(SAGE Publications, 2023) Çiçek, Selen; Turhan, Gözde Damla; Taşer, AybükeThe urban built environment of contemporary cities confronts a constant risk of deterioration due to natural or artificial reasons. Especially political aggression and war conflicts have significant destructive effects on architectural and cultural heritage buildings. The post-war urbanscapes demonstrate the striking effects of the armed conflicts during the hot war encounters. However, the residues of the urbanscapes become the actual indicators of damage and loss. Since today we can make future predictions using a variety of machine learning algorithms, it is possible to represent hybrid projections of urban heterotopias. In this context, this research proposes to explore dystopian post-war projections for modern cities based on their architectural styles and demonstrate the utopian scenarios of rehabilitation possibilities for the damaged urban built environment of post-war cities by using generative adversarial network (GAN) algorithms. Two primary datasets containing the post-war and pre-war building facades have been given as the input data for the CycleGAN and pix2pix GAN models. Thus, two different image-to-image GAN models have been compared regarding their ability to produce legible building facade projections in architectural features. Besides, the machine learning process results have been discussed in terms of cities' utopian and dystopian future predictions, demonstrating the war conflicts' immense effects on the built environment. Moreover, the immediate consequence of the destructive aggression on tangible and intangible architectural heritage would become visible to inhabitants and policymakers when the AI-generated rehabilitation potentials have been exposed.