Reduction of losses and an efficient management of water distribution systems need also an understanding of the phenomena that cause pipe breaks. The latter aspect is extremely complex to predict because it depends on many factors as the physical properties of the pipes, the working conditions and the environmental aspects. This paper has attempted to highlight how weather conditions are an important factor in the pipes breaks. This was done through the study of data of breakings, which derive from eleven years of measurements in an Italian water distribution system. The data analysis given the possibility to highlight how the link between the breakings and the environmental conditions is very strong especially for some materials, such as the polyethylene, where the correlation between the temperature and the number of breakages is mostly significant. This aspect was also investigated using a neural network model which showed a good ability to reconstruct the development of the breakings.
M. Maglionico, S. Cipolla, I. Stojkov, M. Tavernelli (2012). VARIATIONS AND TREND IN WATER DISTRIBUTION NETWORKS BREAKS. ADELAIDE : Engineers Australia.
VARIATIONS AND TREND IN WATER DISTRIBUTION NETWORKS BREAKS
MAGLIONICO, MARCO;CIPOLLA, SARA SIMONA;STOJKOV, IRENA;
2012
Abstract
Reduction of losses and an efficient management of water distribution systems need also an understanding of the phenomena that cause pipe breaks. The latter aspect is extremely complex to predict because it depends on many factors as the physical properties of the pipes, the working conditions and the environmental aspects. This paper has attempted to highlight how weather conditions are an important factor in the pipes breaks. This was done through the study of data of breakings, which derive from eleven years of measurements in an Italian water distribution system. The data analysis given the possibility to highlight how the link between the breakings and the environmental conditions is very strong especially for some materials, such as the polyethylene, where the correlation between the temperature and the number of breakages is mostly significant. This aspect was also investigated using a neural network model which showed a good ability to reconstruct the development of the breakings.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.