End-of-Service Life Estimation Model for Concrete Sewers

Project Member(s): Wang, Y., Tian, H., Li, Z., Chen, F., Guo, T.

Funding or Partner Organisation: Smartcrete CRC
Smartcrete CRC

Start year: 2022

Summary: This project will develop a model combining data analytics with experimental research to determine parameters necessary to estimate corrosion rates and predict end-of-service life estimation model for concrete sewers.

Publications:

Wan, Z, Liu, X, Wang, B, Qiu, J, Li, B, Guo, T, Chen, G & Wang, Y 2024, 'Spatio-temporal Contrastive Learning-enhanced GNNs for Session-based Recommendation', ACM Transactions on Information Systems, vol. 42, no. 2, pp. 1-26.
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Li, B, Guo, T, Zhu, X, Wang, Y & Chen, F 2023, 'ConGCN: Factorized Graph Convolutional Networks for Consensus Recommendation' in Machine Learning and Knowledge Discovery in Databases: Research Track, Springer Nature Switzerland, pp. 369-386.
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FOR Codes: Pattern recognition, Water services and utilities

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.