J.H.G. Vreeburg

TL;DR: In this article, the use of particle counters to monitor the particle quantity is investigated in two Amsterdam drinking water distribution networks and it is found that particle counters are far superior to turbidimeters, as the greater amount of qualitative and quantitative data obtained by particle counters allowed determination of particle size distributions and residence times.

TL;DR: In this paper, a bottom-up approach of demand allocation for drinking water distribution system was proposed. But the authors did not consider the variability of residence times as an added feature beyond the conventional way of modelling, and showed that the bottomup approach leads to realistic water demand patterns and residence times.

TL;DR: Stochastic demand patterns from SIMDEUM were applied in a small network model of 550 demand nodes in a residential area in the Netherlands, and the actual measurements agree well with the simulations.

TL;DR: In this paper, the authors provided a mathematical approach to model the heating of drinking water within the domestic water supply system and found that residence time influences the drinking water temperature more than the ambient temperature itself.

TL;DR: In this paper, the value of on-line particle counting in determining the particulate volume load fed to and developing in a distribution system is discussed and analyzed, and the overall conclusion of the authors is that online particle counters, in combination with pre-concentration methods, are very effective and useful tools in understanding the water quality processes in distribution systems.