ORTA DERINLIKTEKI KAZILARDA TEK ANKRAJLI PALPLANŞ DUVARLARIN SAYISAL VE HIBRIT ANN–HHO TABANLI DEĞERLENDIRMESI

Öz

Bu çalışmada, 5 ila 6 metre arasında değişen orta derinlikteki kazılarda geçici istinat sistemi olarak kullanılan tek ankrajlı çelik palplanş duvarların davranışı araştırılmıştır. Kazı derinliğinin, zeminin rölatif sıkılığı ve birim hacim ağırlığının ve ankrajın düşeydeki konumunun duvar performansı üzerindeki etkilerini değerlendirmek için statik koşullar altında PLAXIS 2D kullanılarak bir dizi parametrik analiz gerçekleştirilmiştir. Sonuç olarak deplasman açısından ankrajın zemin üst yüzeyine olan optimum düşey mesafesinin 0,25 ile 0,3H arasında olduğu belirlenmiştir. Sayısal simülasyon sonuçları, maksimum yatay duvar yer değiştirmesi için bir tahmin modelinin geliştirilmesine temel oluşturmuştur. Doğru ve genelleştirilmiş tahminler elde etmek için Harris Hawks Optimizasyon (HHO) algoritması ile optimize edilmiş bir hibrit Yapay Sinir Ağı (YSA) modeli geliştirilmiştir. Bu yaklaşımda, HHO, transfer fonksiyonları ve gizli katmandaki nöron sayısı dahil olmak üzere YSA'nın hiperparametrelerini optimize etmek için kullanılmıştır. Bulgular, geçici kazılarda ankrajlı istinat sistemlerinin tasarımını ve performans değerlendirmesini iyileştirmek için sonlu elemanlar analizinin hibrit yumuşak hesaplama yaklaşımlarıyla birleştirilmesinin potansiyelini vurgulamaktadır.

Anahtar Kelimeler

• Palplanş Duvar
• Geçici Kazı
• Duvar Deplasmanı
• Yapay Sinir Ağları
• HHO Algoritması

NUMERICAL AND HYBRID ANN–HHO-BASED EVALUATION OF SINGLE-ANCHORED SHEET PILE WALLS IN MEDIUM-DEPTH EXCAVATIONS

Öz

This study investigates the behavior of single-anchored steel sheet pile walls used as temporary retaining systems in medium-depth excavations ranging from 5 to 6 meters in depth. A series of parametric analyses were performed using PLAXIS 2D under static conditions to evaluate the effects of excavation depth, soil internal friction angle, unit weight, and vertical anchor position on wall performance. Consequently, the optimum vertical distance of the anchor from the ground surface was determined to be between 0.25 and 0.3H in terms of displacement. The results of the numerical simulations provided the basis for developing a predictive model for maximum horizontal wall displacement. To obtain accurate, generalized predictions, a hybrid Artificial Neural Network (ANN) model optimized using the Harris Hawks Optimization (HHO) algorithm was developed. In this approach, HHO was used to optimize the ANN hyperparameters, including transfer functions and the number of hidden-layer neurons. The findings highlight the potential of combining finite element analysis with hybrid soft-computing approaches to enhance the design and performance evaluation of anchored retaining systems in temporary excavations.

Anahtar Kelimeler

• Sheet Pile Wall
• Temporary Excavation
• Wall Displacement
• Artificial Neural Network
• HHO Algorithm

Kaynakça

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