User community

This page is intended to capture research using WNTR and will be updated periodically. If you have related software or a publication that you’d like to add to this page, please let us know or submit a pull request with the update.

Publications

  • Abdel-Mottaleb, N., Ghasemi Saghand, P., Charkhgard, H., & Zhang, Q. (2019). An exact multiobjective optimization approach for evaluating water distribution infrastructure criticality and geospatial interdependence. Water Resources Research, 55(7), 5255-5276.

  • Antonowicz, A., Bałut, A., Urbaniak, A., & Zakrzewski, P. (2019). Algorithm for Early Warning System for Contamination in Water Network. In 2019 20th International Carpathian Control Conference (ICCC) (pp. 1-5). IEEE.

  • Antonowicz, A., & Urbaniak, A. (2022). Optimization of the process of restoring the continuity of the WDS based on the matrix and genetic algorithm approach. Bulletin of the Polish Academy of Sciences: Technical Sciences, e141594-e141594.

  • Bjerke, M. (2019). Leak Detection in Water Distribution Networks using Gated Recurrent Neural Networks, Master’s thesis, Norwegian University of Science and Technology (NTNU)

  • Bunn, B. B. (2018). An operational model of interdependent water and power distribution infrastructure systems. Naval Postgraduate School, Monterey, CA

  • Fan, X., Zhang, X., & Yu, X. B. (2021). Machine learning model and strategy for fast and accurate detection of leaks in water supply network. Journal of Infrastructure Preservation and Resilience, 2(1), 1-21.

  • Han, Q., Eguchi, R., Mehrotra, S., & Venkatasubramanian, N. (2018). Enabling state estimation for fault identification in water distribution systems under large disasters. In 2018 IEEE 37th Symposium on Reliable Distributed Systems (SRDS) (pp. 161-170). IEEE.

  • Han, Q., Mehrotra, S., & Venkatasubramanian, N. (2019). Aquaeis: Middleware support for event identification in community water infrastructures. In Proceedings of the 20th International Middleware Conference (pp. 293-305).

  • Huang, H., & Burton, H. V. (2022). Dynamic seismic damage assessment of distributed infrastructure systems using graph neural networks and semi-supervised machine learning. Advances in Engineering Software, 168, 103113.

  • Iannacone, L., Sharma, N., Tabandeh, A., & Gardoni, P. (2022). Modeling time-varying reliability and resilience of deteriorating infrastructure. Reliability Engineering & System Safety, 217, 108074.

  • Kammoun, M., Kammoun, A., & Abid, M. (2022). Experiments based comparative evaluations of machine learning techniques for leak detection in water distribution systems. Water Supply, 22(1), 628-642.

  • Liu, J., & Kang, Y. (2022). Segment-based resilience response and intervention evaluation of water distribution systems. AQUA—Water Infrastructure, Ecosystems and Society, 71(1), 100-119.

  • Liu, Y., Barrows, C., Macknick, J., & Mauter, M. (2020). Optimization Framework to Assess the Demand Response Capacity of a Water Distribution System. Journal of Water Resources Planning and Management, 146(8), 04020063.

  • Logan, K. T., Lestakova, M., Thiessen, N., Engels, J. I., & Pelz, P. F. (2021). Water Distribution in a Socio-Technical System: Resilience Assessment for Critical Events Causing Demand Relocation. Water, 13(15), 2062.

  • Lorenz, I. S., & Pelz, P. F. (2020). Optimal resilience enhancement of water distribution systems. Water, 12(9), 2602.

  • Marlim, M. S., & Kang, D. (2022). Contaminant Flushing in Water Distribution Networks Incorporating Customer Faucet Control. Sustainability, 14(4), 2249.

  • Mazumder, R. K., Salman, A. M., Li, Y., & Yu, X. (2019). A Decision-making Framework for Water Distribution Systems using Fuzzy Inference and Centrality Analysis. 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP13, Seoul, South Korea, May 26-30, 2019

  • Mazumder, R. K., Salman, A. M., & Li, Y. (2020). Post-disaster sequential recovery planning for water distribution systems using topological and hydraulic metrics. Structure and Infrastructure Engineering, 1-16.

  • Murillo, A., Taormina, R., Tippenhauer, N., & Galelli, S. (2020). Co-Simulating Physical Processes and Network Data for High-Fidelity Cyber-Security Experiments. In Sixth Annual Industrial Control System Security (ICSS) Workshop (pp. 13-20).

  • Nikolopoulos, D., Moraitis, G., Bouziotas, D., Lykou, A., Karavokiros, G., & Makropoulos, C. (2020). Cyber-physical stress-testing platform for water distribution networks. Journal of Environmental Engineering, 146(7), 04020061.

  • Nikolopoulos, D., Ostfeld, A., Salomons, E., & Makropoulos, C. (2021). Resilience Assessment of Water Quality Sensor Designs under Cyber-Physical Attacks. Water, 13(5), 647.

  • Nikolopoulos, D., Kossieris, P., Tsoukalas, I., & Makropoulos, C. (2022). Stress-testing framework for urban water systems: A source to tap approach for stochastic resilience assessment. Water, 14(2), 154.

  • Nikolopoulos, D., & Makropoulos, C. (2022). Stress-testing water distribution networks for cyber-physical attacks on water quality. Urban Water Journal, 19(3), 256-270.

  • Nyahora, P. P., Babel, M. S., Ferras, D., & Emen, A. (2020). Multi-objective optimization for improving equity and reliability in intermittent water supply systems. Water Supply, 20(5), 1592-1603.

  • Pagani, A., Wei, Z., Silva, R., & Guo, W. (2020). Neural Network Approximation of Graph Fourier Transforms for Sparse Sampling of Networked Flow Dynamics. arXiv preprint arXiv:2002.05508.

  • Rahimi-Golkhandan, A., Aslani, B., & Mohebbi, S. (2022). Predictive resilience of interdependent water and transportation infrastructures: A sociotechnical approach. Socio-Economic Planning Sciences, 80, 101166.

  • Randeniya, A., Radhakrishnan, M., Sirisena, T. A. J. G., Maish, I., & Pathirana, A. (2022). Equity–performance trade-off in water rationing regimes with domestic storage. Water Supply, 22(5), 4781-4797.

  • Sharma, N., Tabandeh, A., & Gardoni, P. (2019). Recovery optimization of interdependent infrastructure: a multi-scale approach. 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP13

  • Sharma, N., Tabandeh, A., & Gardoni, P. (2020). Regional resilience analysis: A multiscale approach to optimize the resilience of interdependent infrastructure. Computer‐Aided Civil and Infrastructure Engineering, 35(12), 1315-1330.

  • Tabandeh, S. (2018). Societal risk and resilience analysis: A multi-scale approach to model the dynamics of infrastructure-social systems (Doctoral dissertation, University of Illinois at Urbana-Champaign).

  • Tabandeh, A., Sharma, N., & Gardoni, P. (2022). Uncertainty propagation in risk and resilience analysis of hierarchical systems. Reliability Engineering & System Safety, 219, 108208.

  • Tomar, A., Burton, H. V., Mosleh, A., & Yun Lee, J. (2020). Hindcasting the Functional Loss and Restoration of the Napa Water System Following the 2014 Earthquake Using Discrete-Event Simulation. Journal of Infrastructure Systems, 26(4), 04020035.

  • Vrachimis, S. G., & Kyriakou, M. S. (2018). LeakDB: A benchmark dataset for leakage diagnosis in water distribution networks. In WDSA/CCWI Joint Conference Proceedings (Vol. 1).

  • Vrachimis, S. G., Eliades, D. G., & Polycarpou, M. M. (2018). Leak detection in water distribution systems using hydraulic interval state estimation. In 2018 IEEE Conference on Control Technology and Applications (CCTA) (pp. 565-570). IEEE.

  • Wille, D. (2019). Simulation-optimization for operational resilience of interdependent water-power systems in the US Virgin Islands (Doctoral dissertation, Monterey, CA; Naval Postgraduate School).

  • Xing, L., & Sela, L. (2020). Transient simulations in water distribution networks: TSNet python package. Advances in Engineering Software, 149, 102884.