Kevin E Lansey

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Courses

Scholarly Contributions

Books

• Colglazier, W., Vafai, H. A., Lansey, K. E., & Bryson, M. (2021). Sustainable Development for the Americas: Science, Health, and Engineering Policy and Diplomacy. CRC Press. doi:10.1201/9781003220503

Journals/Publications

• Huizar, L., Diaz, S., Lansey, K. E., & Arnold, R. (2023). Water Supply in the Lower Colorado River Basin: Effectiveness of the 2019 Drought Contingency Plan. J. of Environmental Engineering, 149(10), 1-10.
• Jun, S., & Lansey, K. E. (2023). Comparison of AMI and SCADA systems for leak detection and localization in water distribution networks. J. of Water Resources Planning and Management, 149(11), 1-10.
• Jun, S., & Lansey, K. E. (2023). Convolutional Neural Network for Burst Detection in Smart Water Distribution Systems. Water Resources Management, 1-15.
• Jun, S., & Lansey, K. E. (2023). Linear programming models for leak detection and localization in water distribution networks. Journal of Water Resources Planning and Management, 149(5), 1-10.
• Schuck, S., Diaz, S., & Lansey, K. E. (2023). Reducing Water Age in Residential Premise Plumbing Systems. Journal of Water Resources Planning and Management, 149(8), 1-10.
• Doole, F. T., Littin, S., Myers, S. A., Somasekhar, G., Steyart, J. C., & Lansey, K. E. (2022). Experiential Learning for Training Future Science Policy and Diplomacy Experts. Journal of Science Policy and Governance, 21(1). doi:https://doi.org/10.38126/JSPG210103
• Jun, S., Arbesser-Rastburg, G. G., Fuchs-Hanusch, D., & Lansey, K. E. (2022). Response Surfaces for Water Distribution System Pipe Roughness Calibration. ASCE Journal of Water Resources Planning and Management, 148(3). doi:10.1061/(ASCE)WR.1943-5452.0001518
• Hwang, H., & Lansey, K. E. (2021). Isolation Valve Impact on Failure Severity and Risk Analysis. Journal of Water Resources Planning and Management, 147(3).
• Jun, S., Jung, D., & Lansey, K. E. (2021). Comparison of Imputation Methods for End-User Demands in Water Distribution Systems. Journal of Water Resources Planning and Management, 147(12). doi:10.1061/(ASCE)WR.1943-5452.0001477
• Lansey, K., Jung, D., Fu, G., Farmani, R., Diao, K., & Butler, D. (2021). Modular interdependency analysis for water distribution systems.. Water research, 201, 117320. doi:10.1016/j.watres.2021.117320
  More info

  Complexity in water distribution systems (WDSs) poses a challenge for analysis and management of the systems. To reduce the complexity, the recent development of complex network science provides a system decomposition technique that converts a complex WDS with a large number of components into a simple system with a set of interconnected modules. Each module is a subsystem with stronger internal connections than external connections. Thus far, the topological features of the modular structure in WDS have been extensively studied but not the behavioural features, e.g. the hydraulic interdependencies among modules. Therefore, this paper aims to quantitatively measure and graphically visualize the module interdependency in WDSs, which helps understanding the behavioural complexity of WDSs and thus various WDS analyses, such as pipe maintenance, model calibration, rehabilitation, and District Metered Areas planning. Specifically, this study first identifies the WDS's modular structure then measures how changes in the state of one module (i.e. any single pipe failure or perturbed demand within each module) affect the state of another module. Modular interdependencies are summarized in an interdependency matrix and visualized by the digraph. Four real-world systems are analysed, and three of them shows low interdependencies among most of the modules and there are only a few critical modules whose status changes will substantially affect a number of other modules. Hence, highly interconnected topologies may not result in strong and complex module interdependency, which is a fact that simplifies several WDS analysis for practical applications as discussed in this paper.
• Lansey, K. E., Evans, T., Mayer, B. M., Gerlak, A. K., & Zuniga Teran, A. A. (2020). A multidimensional assessment of urban resilience from green infrastructure systems. Current Opinion in Environmental Sustainability.
• Liu, J., & Lansey, K. E. (2020). Multiphase DMA Design Methodology Based on Graph Theory and Many-Objective Optimization. Multiphase DMA Design Methodology Based on Graph Theory and Many-Objective Optimization, 146(8).
• Scott, C. A., Pincetl, S., Meixner, T., Lansey, K. E., Duan, J. G., Daigger, G. T., Cath, T. Y., Boccelli, D., Shrestha, P. P., Albrecht, T., Mack, E. A., Zuniga Teran, A. A., Achilli, A., & Crosson, C. (2020). Net Zero Urban Water from Concept to Applications: Integrating Natural, Built, and Social Systems for Responsive and Adaptive Solutions. ACS ES&T Water.
• Zuniga Teran, A. A., Gerlak, A. K., Mayer, B. M., Evans, T., & Lansey, K. E. (2020). A multidimensional assessment of urban resilience from green infrastructure systems. Current Opinion in Environmental Sustainability, 44, 42-47.
• Chee, R., Lansey, K., & Chee, E. (2018). Estimation of Water Pipe Installation Construction Costs. JOURNAL OF PIPELINE SYSTEMS ENGINEERING AND PRACTICE, 9(3).
• Huizar, L., Lansey, K. E., & Arnold, R. G. (2018). Sustainability, robustness, and resilience metrics for water and other infrastructure systems. SUSTAINABLE AND RESILIENT INFRASTRUCTURE, 3(1), 16-35. doi:10.1080/23789689.2017.1345252
• Hwang, H., Jung, D., & Lansey, K. (2018).

  Accuracy of First-Order Second-Moment Approximation for Uncertainty Analysis of Water Distribution Systems

  . Journal of Water Resources Planning and Management, 144(2). doi:10.1061/(asce)wr.1943-5452.0000864
• Hwang, H., Lansey, K., & Jung, D. (2018). Accuracy of First-Order Second-Moment Approximation for Uncertainty Analysis of Water Distribution Systems. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, 144(2).
• Hwang, H., & Lansey, K. (2017). Water Distribution System Classification Using System Characteristics and Graph-Theory Metrics. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, 143(12).
• Andrade, M. A., Choi, C. Y., Lansey, K., & Jung, D. (2016). Enhanced Artificial Neural Networks Estimating Water Quality Constraints for the Optimal Water Distribution Systems Design. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, 142(9).
• Hagos, M., Jung, D., & Lansey, K. E. (2016). Optimal meter placement for pipe burst detection in water distribution systems. JOURNAL OF HYDROINFORMATICS, 18(4), 741-756.
• Jung, D., Lansey, K. E., Choi, Y. H., & Kim, J. H. (2016). Robustness-based optimal pump design and scheduling for water distribution systems. JOURNAL OF HYDROINFORMATICS, 18(3), 500-513.
• Lan, F., Bayraksan, G., & Lansey, K. (2016). Reformulation linearization technique based branch-and-reduce approach applied to regional water supply system planning. ENGINEERING OPTIMIZATION, 48(3), 454-475.
• Yoo, D. G., Jung, D., Kang, D., Kim, J. H., & Lansey, K. (2016). Seismic Hazard Assessment Model for Urban Water Supply Networks. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, 142(2).
• Lansey, K. E., & Jung, D. (2014). Burst detection in water distribution system using the extended Kalman filter. Procedia Engineering, 70, 902-906. doi:10.1016/j.proeng.2014.02.100
  More info

  Abstract A water distribution system burst from a pipe rupture results in water loss and disruptions of customer service. Numerous methods, including Statistical Process Control, time series modeling, and pattern recognition, have been applied to detect bursts. However, system changes its boundary conditions such as the set of operating pumps and valve closures greatly complicating the detection problem. Thus, to date applications have been limited to the network supplied by gravity or under constant boundary conditions. This study seeks to overcome these limitation using the Kalman filter method to estimate the system state and detect bursts.
• Lansey, K. E., Hwang, H., & Forrester, A. (2014). Decentralized Water Reuse: Regional Water Supply System Resilience Benefits. Procedia Engineering, 70, 853-856. doi:10.1016/j.proeng.2014.02.093
  More info

  Abstract Resilience is related to the system functionality loss and the failure event duration (Bruneau et al., 2003). System redundancy and robustness affect the severity or functionality loss while the recovery time is largely related to the resource available and rapidity of the response. The purpose of this study is to investigate the resilience of a regional water supply system (RWSS) through a criticality analysis of five RWSS components. The relative importance was evaluated under two management/design conditions: (1) centralized versus decentralized wastewater treatment, and (2) decentralized wastewater plant location. For this study, the regional water supply system of a portion of the Tucson metropolitan area in Arizona was modeled. A Linear Programming (LP) flow allocation model determines the optimal flow allocation from multiple sources to users by minimizing the operational cost. The RWSS resilience was quantified by the failure, that is, the volume of water that was not delivered to users during the component failure of known duration.

Proceedings Publications

• Zhang, Y., Lansey, K. E., & Liu, J. (2020, December). Detecting Burst in Water Distribution System via Penalized Functional Decomposition. In IEEE International Conference on Industrial Engineering and Engineering Management, 205-209.

Presentations

• Jun, S., Lansey, K. E., & Jung, D. (2023). Mass Balance and Pressure Integrated Model for Burst Detection and Localization in Water Distribution Networks. 2023 ASCE Environmental and Water Resources Congress. Henderson, NV: ASCE.
• Arcelay, A., Lansey, K. E., & Zhang, Y. (2023). The impact of climate mitigation strategies on localized flooding. 2023 ASCE Environmental and Water Resources Congress. Henderson, NV: ASCE.
• Kim, S., Jun, S., Jung, D., & Lansey, K. E. (2023). Introduction of Heatmap for Applications in Water Distribution Networks. 2023 ASCE Environmental and Water Resources Congress. Henderson, NV: ASCE.
• Jun, S., & Lansey, K. E. (2022, May). Linear Programming Constrained Models for Pipe Burst Detection and Localization in Water Distribution Systems. . 2022 World Environmental & Water Resources Congress. Atlanta, GA: ASCE.
• Jun, S., & Lansey, K. E. (2022, Summer).

  Combining Hydraulic Knowledge with Deep Learning for Water Distribution Burst Detection.

  . 2nd WDSA/CCWI Joint Conference.. Valencia, Spain..
• Lansey, K. E., Jun, S., & Jung, D. (2021, May). Deep Learning Convolutional Neural Network for Pipe Burst Detection in Water Distribution System. 2021 World Environmental & Water Resources Congress. Virtual: ASCE.
• Liu, J., & Lansey, K. E. (2018, August). Optimal Design of District Metered Areas Based on Graph Theory and Multi-Objective Optimization. 1st Joint WDSA/CCWI conference. Queens, Ontario.
• Schuck, S., & Lansey, K. E. (2018, August). A Micro-Scale Analysis of Pressure Dependent Analysis: Impacts on Network Scale PDA. 1st Joint WDSA/CCWI conference. Queens, Ontario.

Poster Presentations

• Kaplan, L., Vafai, H., & Lansey, K. E. (2018, September). Sowing the Seeds of Understanding and Interest: An Example of University-Sponsored Incubation and Collaboration for Science Diplomacy. Science Diplomacy 2018 SciDipEd Workshop. Washington.