Obtaining Live Load Distribution Factors Equations for Simply Supported Bridges Using Neural Networks

Yıl 2020, Cilt: 35 Sayı: 3, 609 - 622, 30.09.2020

Ö. Fatih Yalçın

https://doi.org/10.21605/cukurovaummfd.846321

Cited By: 1

Öz

Advancements in artificial intelligence have caused important transformations in many areas. Research on applications of artificial intelligence, machine-learning and neural networks in civil engineering has been growing recently. Parallel to this progress, in this study, closed-form formulas for distribution of live load among the bridge girders are obtained using artificial neural networks. In these formulas, the number of girders is also incorporated as a new parameter, which is not included in AASHTO LRFD live load distribution equations. For this purpose, numerous straight, simply supported bridge models are analyzed using the finite element method and subsequently live load distribution factors are calculated. Live load distribution factors obtained through neural networks are compared with those from finite element analyses and AASHTO LRFD formulas. These comparisons reveal that closed-form formulas can predict live load distribution factors accurately.

Anahtar Kelimeler

Artificial intelligence, Neural networks, Bridges, Live load, Load distribution

Basit Mesnetli Köprülerde Hareketli Yük Dağılım Faktörleri Denklemlerinin Yapay Sinir Ağları ile Elde Edilmesi

Öz

Yapay zekâ konusunda kaydedilen ilerlemeler günümüzde her alanda çok önemli dönüşümlere neden olmaktadır. İnşaat mühendisliği alanında da yapay zekâ, makine öğrenmesi ve yapay sinir ağları uygulamaları ve kullanımı her geçen gün artmakta ve çeşitlenmektedir. Bu gelişmelere paralel olarak, bu çalışmada, yapay sinir ağları kullanılarak köprü tasarımında kullanılan hareketli yüklerin köprü kirişlerine dağılımı için kapalı formüller elde edilmiştir. Bu formüllerde, farklı yapısal köprü parametrelerinin yanı sıra, AASHTO LRFD’de verilen denklemlerde dahil edilmemiş olan kiriş sayısı parametresi de eklenmiştir. Bu amaçla, birçok verevsiz basit mesnetli köprü modeli hazırlanarak olası tüm kamyon yükleri altında sonlu elemanlar analizleri yapılmış ve hareketli yük dağılım katsayıları elde edilmiştir.
Yapay sinir ağları ile elde edilen hareketli yük dağılım faktörleri, sonlu elemanlar analiz sonuçları ile ve AASHTO LRFD’de verilmiş olan hareketli yük dağılım katsayıları ile karşılaştırılmıştır. Bu karşılaştırmalar göstermektedir ki, sinir ağları ile elde edilen formüller dağılım faktörlerini oldukça iyi tahmin edebilmektedir.

Anahtar Kelimeler

Yapay zekâ, Yapay sinir ağları, Köprüler, Hareketli yük, Dağılım faktörleri

Kaynakça

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