Detection of Pipes Causing Pressure Loss in Water Distribution Networks via Artificial Immune Systems

Abstract

This paper proposes the optimization model using Artificial Immune Systems, depending on a model calibration, in order to determine worn out pipes with low Hazen-Williams roughness coefficient causing pressure loss in the water distribution networks. The modified Clonal Selection Algorithm, a type of Artificial Immune Systems, was used as a heuristic optimization method. In order to evaluate its performance, the model was implemented to the four-loop hypothetical water distribution network under steady-state conditions. According to the results, the model appeared to be promising in the detection of old pipes causing high pressure losses in the water distribution networks

Keywords

• Pressure loss
• Water Distribution Networks
• Optimization
• Model Calibration
• Artificial Immune Systems

Su Dağıtım Şebekelerinde Basınç Kaybına Neden Olan Boruların Yapay Bağışıklık Sistemleri ile Tespit Edilmesi

Abstract

Bu çalışmada, su dağıtım şebekelerinde basınç kaybına neden olan düşük Hazen-Williams pürüzlülük katsayısına sahip eskimiş boruların belirlenmesi için model kalibrasyonuna bağlı Yapay Bağışıklık Sistemlerini kullanan bir optimizasyon modeli önerilmektedir. Sezgisel optimizasyon yöntemi olarak Yapay Bağışıklık Sistemlerinden biri olan modifiye Klonal Seçim Algoritması kullanılmıştır. Modelin performansını test etmek için, sürekli-kararlı koşullar altında dört gözlü farazi (sanal) bir su dağıtım şebekesinde model uygulanmıştır. Elde edilen sonuçlara göre, su dağıtım şebekelerindeki yüksek basınç kayıplarına neden olan eskimiş boruların tespit edilmesinde modelin gelecek vaat ettiği görülmüştür

Keywords

• Basınç kaybı
• Su Dağıtım Şebekeleri
• Optimizasyon
• Model Kalibrasyonu
• Yapay Bağışıklık Sistemleri

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