Modelling regrowth in the distribution network

Regrowth in the distribution network is a complex phenomenon. Measures to manage regrowth in the distribution network have hitherto been based on a trial-and-error approach. We need a model-based description of the process, which would enhance our understanding and render the effect of different factors that influence the process more quantifiable.

In this project we translate the relationships found in the literature, lab and field for regrowth in the distribution network into a numerical model, which can describe this regrowth and be implemented in a hydraulic distribution network model. In the first instance, the model focuses on the risk of regrowth, that is, the probability of a disturbance in the normal equilibrium and the impact of the disturbance on the network. By modelling the regrowth in the distribution network, we can identify the key knowledge gaps. Follow-up research could aim to develop more situation-specific data or to achieve a better understanding of a process. The ultimate objective is to determine the expected impact of management measures.

Programing and implementing numerical model

We develop a problem definition and conduct a literature study on the subject of regrowth during distribution. We also collect existing data and knowledge, and we describe the phenomena that occur. We translate lab-scale or field research results into a conceptual model and model parameters. And we make an inventory of missing data. We program a numerical model and implement it in a hydraulic distribution network model of a test area. We conduct a sensitivity analysis. The results are published in a report and presented at a congress.

More targeted search for measures

We provide the first applications to be carried out in a follow-up research project, in which the model is applied in different sections between source and tap: distribution network, connecting pipes, drinking water installation. The objective is to assess the contribution of the different sections between the water treatment and the tap; and also to search for measures in a more targeted manner.

Subsequently, the model can also be used by water companies to identify the parts of their networks where most regrowth occurs. In principle, the method can be applied to the water companies’ own models; the numerical model would therefore have to be prepared for application in InfoWorks and Synergi.