WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Citation - WoS: 1Citation - Scopus: 1The Comparison of Fragility Curves of Moment-Resisting and Braced Frames Used in Steel Structures Under Varying Wind Load(Turkish Chamber Civil Engineers, 2025-03-01) Ozalp, Abdulkadir; Gokdemir, Hande; Ciftci, CihanIn this study, the performance of two different steel structure types (moment-resisting frame and braced frame) under wind loading was compared by addressing the fragility curves of these structure types. To perform this comparison, the dimensions of the members of these structural systems were first determined. Then, nonlinear static pushover analyses were conducted to assess the performance levels of each frame type. After applying these analyses, time-history analyses were performed with 100 different wind loads for each varying equivalent mean wind speed. Afterwards, the probability of exceeding the predetermined structural performance limits of the structure types was determined using Monte Carlo simulation method. Finally, the results of the simulation method were used to adapt the maximum likelihood estimation method to obtain the fragility curves of the structures. To conclude, it has been revealed that the material cost of the structure doubles when diagonal elements are used, but the wind speed required for a 100% collapse probability to occur in the braced frame is twice as high compared to the moment-resisting frame.Article Citation - WoS: 1Estimating the Power Draw of Grizzly Feeders Used in Crushing-Screening Plants Through Soft Computing Algorithms(Konya Teknik Univ, 2024-01-02) Koken, EkinIn this study, the power draw (P) of several grizzly feeders used in the Turkish Mining Industry (TMI) is investigated by considering the classification and regression tree (CART), random forest (RF) and adaptive neuro-fuzzy inference system (ANFIS) algorithms. For this purpose, a comprehensive field survey is performed to collect quantitative data, including power draw (P) of some grizzly feeders and their working conditions such as feeder width (W), feeder length (L), feeder capacity (Q), and characteristic feed size (F80). 80 ). Before applying the soft computing methodologies, correlation analyses are performed between the input parameters and the output (P). According to these analyses, it is found that W and L are highly associated with P. On the other hand, Q is moderately correlated with P. Consequently, numerous soft computing models were run to estimate the P of the grizzly feeders. Soft computing analysis results demonstrate no superiority between the performances of RF and CART models. The RF analysis results indicate that the W is necessary for evaluating P for grizzly feeders. On the other hand, the ANFIS-based predictive model is found to be the best tool to estimate varying P values, and it satisfies promising results with a correlation of determination value (R2) of 0.97. It is believed that the findings obtained from the present study can guide relevant engineers in selecting the proper motors propelling grizzly feeders.