Picture of person typing on laptop with programming code visible on the laptop screen

World class computing and information science research at Strathclyde...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by researchers from the Department of Computer & Information Sciences involved in mathematically structured programming, similarity and metric search, computer security, software systems, combinatronics and digital health.

The Department also includes the iSchool Research Group, which performs leading research into socio-technical phenomena and topics such as information retrieval and information seeking behaviour.

Explore

Peaking demand factor-based reliability analysis of water distribution system

Surendran, S. and Tanyimboh, T. and Tabesh, M. (2005) Peaking demand factor-based reliability analysis of water distribution system. Advances in Engineering Software, 36 (11-12). pp. 789-796. ISSN 0965-9978

Full text not available in this repository. Request a copy from the Strathclyde author

Abstract

Water demands vary and consideration of the probabilistic nature of the variations should lead to more instructive assessments of the performance of water distribution systems. Water consumption data for several households were analysed using the chi-square technique and it was found that distributions worth considering under certain circumstances include the normal and lognormal. Reliability values were calculated for a range of critical demand values and the corresponding confidence levels determined from the probability distributions. Water consumption was assumed to be pressure dependent and the modelling of the water distribution system was carried out accordingly. This peaking factor approach coupled with the statistical modelling of demands provides a more realistic way of incorporating variations in demands in the evaluation and reporting of system performance than the traditional single demand value approach in that the extent to which a network can satisfy any demand and the probability that the demand will occur can be recognized explicitly. The method is illustrated by an example.