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Published on: March 13, 2017
Augmenting water quality resilience in water distribution systems: A stress-driven model for ice slurry pigging
Jiamin Hu1, David Fernandes Del Pozo2, Saba Daneshgar3
1College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; BIOMATH, Department of Data Analysis and Mathematical Modelling, Ghent University, Coupure Links 653, Ghent 9000, Belgium.
None:
Pipeline cleaning is essential for maintaining water quality and safeguarding public health within water distribution networks. Although ice slurry pigging is widely adopted due to its effectiveness and environmental advantages, challenges remain in accurately quantifying cleaning efficacy and optimising maintenance intervals. This study develops a stress-driven wall material removal model calibrated using field-measured turbidity data, allowing for a comprehensive assessment of cleaning effectiveness based on post-cleaning shear resistance. The shear stress distribution induced by ice slurry along the pipeline is characterised using Computational Fluid Dynamics simulations combined with field-measured conductivity data. Validation through two real-world case studies confirms the model's capability to characterise wall material conditions, objectively evaluate cleaning performance, and determine optimal cleaning intervals. Results indicate that an optimal cleaning interval of approximately 24 months is achievable when integrating a post-cleaning shear resistance of 5.2 Pa with operational cost considerations. Proposed optimisation strategies, including increasing ice slurry volume fraction and cleaning velocity, significantly enhance the effectiveness of the cleaning process, extending the maintenance interval by up to 12 months compared to conventional practices. Overall, the findings establish a robust quantitative framework for systematic pipeline maintenance, contributing critical technical insights for augmenting water quality resilience in municipal water networks.
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