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Dergiler / Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi / 2026 / Cilt: 11 Sayı: 2

Estimating Fluid Parameters of Submarine Outfall Using Neural Networks

Engin Gücüyen(MANİSA CELÂL BAYAR ÜNİVERSİTESİ)
Recep Tuğrul Erdem(MANİSA CELÂL BAYAR ÜNİVERSİTESİ)
Sayfa
889–898
Yayın Tarihi
2020-06-15
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The correlation coefficients are calculated by using numerical and estimated values and it is observed that a strong relationship is obtained between them.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Disposal of the urban and industrial liquid waste has become important by paying attention to environmental and human health recently.
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Temel Bulgular & Veri:Submarine outfall diffusers are the major parts of the marine disposal systems.
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Sonuç & Katkı:The correlation coefficients are calculated by using numerical and estimated values and it is observed that a strong relationship is obtained between them.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Numerical Analysis · Submarine Outfalls · Finite Element

Özet

Disposal of the urban and industrial liquid waste has become important by paying attention to environmental and human health recently. Submarine outfall diffusers are the major parts of the marine disposal systems. Pipe of the diffuser, risers and ports, internal and external flows which form the discharge system are modelled and fluid-structure interaction (FSI) method is utilized by ABAQUS finite elements program. Coupled CFD & Explicit technique is performed in FSI analysis. Method of bidirectional fluid-structure interaction (FSI) is used in finite elements method (FEM). Internal and external flows constitute fluid domain and diffuser constitutes the structure domain. While internal velocity and pressure values are obtained from the program, predictions of these results are performed by Artificial Neural Network (ANN) analysis. The average discharge velocities provide to avoid water intrusion into the ports. According to results obtained by FEM it can be said that the discharge system works efficiently. Numerical and estimated values are compared and the relationship between these values is investigated. The correlation coefficients are calculated by using numerical and estimated values and it is observed that a strong relationship is obtained between them.

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Bu Makaleye Atıf Yap

Gücüyen, E., Erdem, R. T. (2020). Estimating Fluid Parameters of Submarine Outfall Using Neural Networks. Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi, Cilt: 11 Sayı: 2, 889–898. https://doi.org/10.24012/dumf.650657

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