A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Water distribution pipe replacement optimization based on spatial clustering
Pipe groups divided by physical attributes often include many individual pipes that are scattered over a large geographical area, meaning the replacement of these pipes requires frequent service interruptions and additional costs due to the scattered delivery of repair resources. To address this issue, this paper proposes a framework for pipe replacement optimization on pipe groups divided by spatial clustering, aiming to reduce the number of scattered individual pipes in the replacement scheme. The proposed framework integrates spatial autocorrelation analysis for spatial clustering of pipe groups as replacement candidates, the pipe failure model to predict potential failures of pipe groups, and the replacement optimization model of pipe groups. The optimization model aims to minimize the number of potential failures within the constraints of the annual budget. The framework was implemented in a real WDN and pipe replacement schemes obtained by the proposed framework are compared with two other methods, namely, pipe attribute clustering-based optimization and pipe risk-based ranking. The results show that the spatial clustering-based helps reduce the number of spatially scattered individual pipes by 37.4 and 64.6%, respectively, compared to the other two methods. The proposed framework is expected to provide more cost–benefit schemes for pipe replacement. HIGHLIGHTS The spatial clustering of pipe groups is integrated into the replacement optimization of water distribution pipes.; The spatial patterns of pipe failures are investigated by spatial autocorrelation analysis.; The spatial clustering of pipe groups is able to reduce the number of spatially scattered individual pipes in the replacement scheme.;
Water distribution pipe replacement optimization based on spatial clustering
Pipe groups divided by physical attributes often include many individual pipes that are scattered over a large geographical area, meaning the replacement of these pipes requires frequent service interruptions and additional costs due to the scattered delivery of repair resources. To address this issue, this paper proposes a framework for pipe replacement optimization on pipe groups divided by spatial clustering, aiming to reduce the number of scattered individual pipes in the replacement scheme. The proposed framework integrates spatial autocorrelation analysis for spatial clustering of pipe groups as replacement candidates, the pipe failure model to predict potential failures of pipe groups, and the replacement optimization model of pipe groups. The optimization model aims to minimize the number of potential failures within the constraints of the annual budget. The framework was implemented in a real WDN and pipe replacement schemes obtained by the proposed framework are compared with two other methods, namely, pipe attribute clustering-based optimization and pipe risk-based ranking. The results show that the spatial clustering-based helps reduce the number of spatially scattered individual pipes by 37.4 and 64.6%, respectively, compared to the other two methods. The proposed framework is expected to provide more cost–benefit schemes for pipe replacement. HIGHLIGHTS The spatial clustering of pipe groups is integrated into the replacement optimization of water distribution pipes.; The spatial patterns of pipe failures are investigated by spatial autocorrelation analysis.; The spatial clustering of pipe groups is able to reduce the number of spatially scattered individual pipes in the replacement scheme.;
Water distribution pipe replacement optimization based on spatial clustering
Xiwei Zhu (author) / Benwei Hou (author) / Shan Wu (author)
2023
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
| Taylor & Francis Verlag | 2023
Distribution Pipe Measurement to Inform Pipe Replacement Plans
| TIBKAT | 2019
Water Pipe Replacement Scheduling Based on Life Cycle Cost Assessment and Optimization Algorithm
| DOAJ | 2021
A neurofuzzy spatial decision support system for pipe replacement prioritisation
| Taylor & Francis Verlag | 2005