Browsing by Author "Dede, Tayfun"
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Item Artificial intelligence applications in civil engineering(Hindawi, 2019) Dede, Tayfun; Vosoughi, Ali Reza; Grzywinski, Maksym; Kripka, Moacir; Kankal, Murat; Uludağ Üniversitesi/Mühendislik Fakültesi/İnşaat Mühendisliği.; 0000-0003-0897-4742; AAZ-6851-2020; 24471611900Item Estimates of energy consumption in Turkey using neural networks with the teaching-learning-based optimization algorithm(Pergamon-Elsevier, 2014-10-01) Uzlu, Ergun; Kankal, Murat; Dede, Tayfun; Akpınar, Adem; Uludağ Üniversitesi/Mühendislik Fakültesi/İnşaat Mühendisliği Bölümü.; 0000-0002-9042-6851; AAC-6763-2019; 23026855400The main objective of the present study was to apply the ANN (artificial neural network) model with the TLBO (teaching-learning-based optimization) algorithm to estimate energy consumption in Turkey. Gross domestic product, population, import, and export data were selected as independent variables in the model. Performances of the ANN-TLBO model and the classical back propagation-trained ANN model (ANN-BP (teaching learning-based optimization) model) were compared by using various error criteria to evaluate the model accuracy. Errors of the training and testing datasets showed that the ANN-TLBO model better predicted the energy consumption compared to the ANN-BP model. After determining the best configuration for the ANN-TLBO model, the energy consumption values for Turkey were predicted under three scenarios. The forecasted results were compared between scenarios and with projections by the MENR (Ministry of Energy and Natural Resources). Compared to the MENR projections, all of the analyzed scenarios gave lower estimates of energy consumption and predicted that Turkey's energy consumption would vary between 142.7 and 158.0 Mtoe (million tons of oil equivalent) in 2020.Item Identification material properties by modal calibration method based on ambient vibration tests(Bursa Uludağ Üniversitesi, 2020-02-25) Yanık, Yusuf; Türker, Temel; Yıldırım, Ömer; Dede, TayfunNowadays, different structural members can be used in structures. The mechanical properties of the materials are variable. For this reason, it is very important to identify the material properties correctly. The main parameter used to define the material properties is the elasticity modulus. In this study, the elasticity modulus of structural members was determined by Model Calibration Method using dynamic characteristics obtained from Ambient Vibration Test data. The application of the proposed method was presented on a steel structure member. First of all, experimental natural frequencies were obtained by conducting Environmental Vibration Test on the selected model. A measurement system consisting of accelerometers for experimental measurements and an electronic circuit used as signal collection unit are designed. The data obtained from this measurement system were transferred to the computer environment and analyzed in the Matlab program. Using the SAP2000 package program, the theoretical natural frequencies were found by Finite Element Method. The difference between the experimental and theoretical results was reduced to the lowest as a result of repeated analysis by modifying the elasticity modulus in the Finite Element model created in SAP2000 program via software generated in Matlab. The calibrated finite element model and the elasticity modulus of the steel structural member are determined by the process.Item Rao_1 optimizasyon algoritması kullanılarak taban plağı dişli betonarme konsol istinat duvarı tasarımı(Bursa Uludağ Üniversitesi, 2019-11-06) Kalemci, Elif Nur; İkizler, Sabriye Banu; Dede, Tayfun; Angın, ZekaiBu çalışmada, düşük ağırlığa sahip, tabanında diş kesit bulunan betonarme bir konsol istinat duvarı tasarımı optimizasyonu konu edilmiştir. Optimizasyon süreci için, daha önce istinat duvarı problemine uygulanmamış bir algoritma olan Rao_1 algoritması kullanılmıştır. İstinat duvarı optimizasyonunda, problemi tanımlamak için 12 tasarım değişkeni ve 26 kısıt kullanılmıştır. Tasarım, Rankine yanal basınç teorisi yardımıyla, duvarın geoteknik stabilitesini korumak amacıyla duvarın kayma, dönme ve temelin taşıma gücüne karşı güvenlik katsayıları ile sınırlandırılmıştır. Betonarme tasarımın iç stabilitesini sağlamak üzere moment ve kayma kapasitesi için ACI 318-05 standardından faydalanılmıştır. Tasarım, taban plağı dişli ve dişsiz konsol istinat duvarları olan iki ayrı sayısal örnekle desteklenmiştir.