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    AI-supported decision framework for sustainable reconstruction: Case study • on TOKI housing after the 2023 Kahramanmaras,earthquake
    (Pergamon-Elsevier Science Ltd, 2026) Kavuran, Gurkan; Yaman, Gonca Ozer; Basarir, Bahar; Dogan, Ebru; Ince, Beyzanur; Dagteke, Gokce
    This study presents a hybrid analytical and machine learning-based framework to evaluate and classify the electricity performance of standardized TOKI center dot housing units planned for reconstruction in the aftermath of the February 6, 2023, Kahramanmaras,earthquakes. While a standardized building model was analyzed using dynamic energy simulation (DesignBuilder) for 11 affected provinces, machine learning techniques were integrated to enhance the interpretability and decision support capabilities of the output. According to local climate data and building specifications, annual electricity consumption was simulated, and units were classified into 'low' or 'high' consumption categories using thresholds defined by T & uuml;rkiye's Energy Market Regulatory Authority (EPDK). To improve classification reliability and computational efficiency, a wrapper-based feature selection approach was employed. The Whale Optimization Algorithm (WOA), guided by K-Nearest Neighbors (KNN) fitness evaluation, was used to identify a subset of the most relevant features, and a Support Vector Machine (SVM) was trained on this reduced feature set. The WOA-KNN-SVM model outperformed the baseline SVM classifier across all performance metrics, achieving 98.2 % classification accuracy, with notable improvements in sensitivity, specificity, and Matthews Correlation Coefficient. The results demonstrate that this integrated methodology can effectively support climate-sensitive and energy-efficient design decisions for mass housing in disaster-prone regions. By providing a replicable and scalable decision-support tool aligned with real-world tariff structures, the proposed approach contributes a novel perspective to post-disaster sustainable reconstruction planning.
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    Cost-effective sodium-ion batteries using a Na0.67Mn0.9Ni0.1O2 cathode and lavender-flower-waste-derived hard carbon with a comparative presodiation approach
    (Elsevier, 2026) Dogan, Ebru; Moeez, Iqra; Whba, Rawdah; Ozcan, Sibel; Akkoc, Mitat; Altin, Emine; Altin, Serdar
    The development of cost-effective, high-performance sodium-ion batteries (SIBs) is essential for large-scale energy storage systems. In this study, low-cost SIBs are fabricated using P2-type Na0.67Mn0.9Ni0.1O2 as the cathode and hard carbon (HC) derived from lavender flower waste as the anode. The synthesis of both electrode materials from widely accessible precursors ensures scalability and environmental sustainability. To address the sodium deficiency of HC, three different presodiation strategies-electrochemical, chemical, and direct contact-are systematically investigated, and the electrochemical performances of the full cells are compared. This evaluation reveals significant variations in the initial capacity, capacity retention, Coulombic efficiency, and rate performance. Although the direct-contact method delivers the highest initial capacity, electrochemical presodiation delivers superior long-term cycling stability and enhanced energy density. This comprehensive comparison of the electrochemical performance emphasizes the vital role of presodiation in enhancing the full-cell efficiency, while highlighting the potential methods for developing cost-effective and sustainable SIBs.
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    Soil-structure interaction analysis of Celebiaga Mosque, Pertek-Turkiye
    (Pontificia Univ Catolica Chile, Escuela Construccion Civil, 2022) Yildiz, Ozgur; Dogan, Ebru
    After the construction of the Keban Dam, some settlements with historical, cultural, and natural value were flooded. A scientific committee consisting of academicians and public authorities decided to the relocation of the buildings including the historical Celebiaga Mosque. In this study, the seismic soil-structure interaction analysis of the historical Celebiaga Mosque, which was dismantled and reconstructed in a separate region due to the construction of the Keban Dam was carried out. The analysis of the masonry mosque was performed with the SAP2000 finite element analysis software. The Winkler foundation model was used to idealize the soil environment on which the historical mosque was built. The effects of soil-structure interaction on historical masonry mosque were examined in terms of transmitted acceleration, response spectra, and lateral displacement at various heights of the structure. Depending on the results of the analysis, the effects of soil-structure interaction of a reconstructed historical masonry building were investigated. PGA was obtained as 0.51g at the flag level of the minaret under the Kocaeli earthquake and 0.94g under the Sivrice earthquake. Again, the maximum horizontal displacements of the minaret at the flag level were obtained as 11 cm and 8.5 cm under the Kocaeli and Sivrice earthquakes. The behavior of historical masonry structures under earthquake loads has been interpreted by considering the geological conditions.