A Tool for Global Resilience Analysis of Water Distribution Systems

This is a joint publication in collaboration with Centre for Water Systems at University of Exeter. This research is based on my previous work for Prof. Butler's project of "Safe and SuRe: A New Paradigm for Urban Water Management".A comprehensive assessment of resilience requires consideration of system performance under exceptional conditions, including those that are unforeseen, and can be achieved using a previously developed methodology called ‘global resilience analysis’ (GRA). GRA captures the effects of both probable and highly improbable (unknown probability) system failures and requires no knowledge of threats. Here, a simple, user-friendly tool that automates the simulations required for GRA of a water distribution system and assists comprehension of the results is presented. Provided the user can supply an Epanet .inp file for the system and that this contains demand data (an understanding of Epanet and system failure modelling is not necessary), the tool can be used to quantify the resilience of the system to pipe failure, pump failure, demand increase and contaminant intrusion. An interactive results explorer allows the user to easily identify critical system components based on the selected level of service type and failure measure (e.g. pressure, supply or contamination and failure magnitude or duration). A map of the network can be used to either color-code components based on their criticality in a single component failure analysis or to identify specific combinations of components which result in the greatest level of service failure magnitude or duration when failed simultaneously. ‘Stress-strain’ type response curves can also be automatically generated and key findings automatically extracted. Additionally, the tool enables systems to be compared on a like-for-like basis, enabling the effects of proposed interventions on resilience to be quantified and visualized

Attribute-based intervention development for increasing resilience of urban drainage systems

© IWA Publishing 2018. Resilience building commonly focuses on attributes such as redundancy. Whilst this may be effective in some cases, provision of specific attributes does not guarantee resilient performance and research is required to determine the suitability of such approaches. This study uses 250 combined sewer system virtual case studies to explore the effects of two attribute-based interventions (increasing distributed storage and reducing imperviousness) on performance-based resilience measures. These are found to provide improvement in performance under system failure in the majority of case studies, but it is also shown that attribute-based intervention development can result in reduced resilience

Design and operation of urban wastewater systems considering reliability, risk and resilience

Reliability, risk and resilience are strongly related concepts and have been widely utilised in the context of water infrastructure performance analysis. However, there are many ways in which each measure can be formulated (depending on the reliability of what, risk to what from what, and resilience of what to what) and the relationships will differ depending on the formulations used. This research has developed a framework to explore the ways in which reliability, risk and resilience may be formulated, identifying possible components and knowledge required for calculation of each and formalising the conceptual relationships between specified and general resilience. This utilises the Safe & SuRe framework, which shows how threats to a water system can result in consequences for society, the economy and the environment, to enable the formulations to be derived in a logical manner and to ensure consistency in any comparisons. The framework is used to investigate the relationship between levels of reliability, risk and resilience provided by multiple operational control and design strategies for an urban wastewater system case study. The results highlight that, although reliability, risk and resilience values may exhibit correlations, designing for just one is insufficient: reliability, risk and resilience are complementary rather than interchangeable measures and one cannot be used as a substitute for another. Furthermore, it is shown that commonly used formulations address only a small fraction of the possibilities and a more comprehensive assessment of a system’s response to threats is necessary to provide a comprehensive understanding of risk and resilience

Reliable, resilient and sustainable water management: The Safe & SuRe approach

Global threats such as climate change, population growth, and rapid urbanization pose a huge future challenge to water management, and, to ensure the ongoing reliability, resilience and sustainability of service provision, a paradigm shift is required. This paper presents an overarching framework that supports the development of strategies for reliable provision of services while explicitly addressing the need for greater resilience to emerging threats, leading to more sustainable solutions. The framework logically relates global threats, the water system (in its broadest sense), impacts on system performance, and social, economic, and environmental consequences. It identifies multiple opportunities for intervention, illustrating how mitigation, adaptation, coping, and learning each address different elements of the framework. This provides greater clarity to decision makers and will enable better informed choices to be made. The framework facilitates four types of analysis and evaluation to support the development of reliable, resilient, and sustainable solutions: “top‐down,” “bottom‐up,” “middle based,” and “circular” and provides a clear, visual representation of how/when each may be used. In particular, the potential benefits of a middle‐based analysis, which focuses on system failure modes and their impacts and enables the effects of unknown threats to be accounted for, are highlighted. The disparate themes of reliability, resilience and sustainability are also logically integrated and their relationships explored in terms of properties and performance. Although these latter two terms are often conflated in resilience and sustainability metrics, the argument is made in this work that the performance of a reliable, resilient, or sustainable system must be distinguished from the properties that enable this performance to be achieved

Global resilience analysis of water distribution systems

© 2016 Evaluating and enhancing resilience in water infrastructure is a crucial step towards more sustainable urban water management. As a prerequisite to enhancing resilience, a detailed understanding is required of the inherent resilience of the underlying system. Differing from traditional risk analysis, here we propose a global resilience analysis (GRA) approach that shifts the objective from analysing multiple and unknown threats to analysing the more identifiable and measurable system responses to extreme conditions, i.e. potential failure modes. GRA aims to evaluate a system's resilience to a possible failure mode regardless of the causal threat(s) (known or unknown, external or internal). The method is applied to test the resilience of four water distribution systems (WDSs) with various features to three typical failure modes (pipe failure, excess demand, and substance intrusion). The study reveals GRA provides an overview of a water system's resilience to various failure modes. For each failure mode, it identifies the range of corresponding failure impacts and reveals extreme scenarios (e.g. the complete loss of water supply with only 5% pipe failure, or still meeting 80% of demand despite over 70% of pipes failing). GRA also reveals that increased resilience to one failure mode may decrease resilience to another and increasing system capacity may delay the system's recovery in some situations. It is also shown that selecting an appropriate level of detail for hydraulic models is of great importance in resilience analysis. The method can be used as a comprehensive diagnostic framework to evaluate a range of interventions for improving system resilience in future studies

Battle of Postdisaster Response and Restoration

[EN] The paper presents the results of the Battle of Postdisaster Response and Restoration (BPDRR) presented in a special session at the first International water distribution systems analysis & computing and control in the water industry (WDSA/CCWI) Joint Conference, held in Kingston, Ontario, Canada, in July 2018. The BPDRR problem focused on how to respond and restore water service after the occurrence of five earthquake scenarios that cause structural damage in a water distribution system. Participants were required to propose a prioritization schedule to fix the damages of each scenario while following restrictions on visibility/nonvisibility of damages. Each team/approach was evaluated against six performance criteria: (1) time without supply for hospital/firefighting, (2) rapidity of recovery, (3) resilience loss, (4) average time of no user service, (5) number of users without service for eight consecutive hours, and (6) water loss. Three main types of approaches were identified from the submissions: (1) general-purpose metaheuristic algorithms, (2) greedy algorithms, and (3) ranking-based prioritizations. All three approaches showed potential to solve the challenge efficiently. The results of the participants showed that for this network, the impact of a large-diameter pipe failure on the network is more significant than several smaller pipes failures. The location of isolation valves and the size of hydraulic segments influenced the resilience of the system during emergencies. On average, the interruptions to water supply (hospitals and firefighting) varied considerably among solutions and emergency scenarios, highlighting the importance of private water storage for emergencies. The effects of damages and repair work were more noticeable during the peak demand periods (morning and noontime) than during the low-flow periods; and tank storage helped to preserve functionality of the network in the first few hours after a simulated event. (C) 2020 American Society of Civil Engineers.Paez, D.; Filion, Y.; Castro-Gama, M.; Quintiliani, C.; Santopietro, S.; Sweetapple, C.; Meng, F.... (2020). Battle of Postdisaster Response and Restoration. Journal of Water Resources Planning and Management. 146(8):1-13. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001239S1131468Balut A. R. Brodziak J. Bylka and P. Zakrzewski. 2018. “Battle of post-disaster response and restauration (BPDRR).” In Proc. 1st Int. WDSA/CCWI 2018 Joint Conf. 14. Kingston Canada: Open Journal Systems.Bibok A. 2018. “Near-optimal restoration scheduling of damaged drinking water distribution systems using machine learning.” In Proc. 1st Int. WDSA/CCWI 2018 Joint Conf. 14. Kingston Canada: Open Journal Systems.Castro-Gama M. C. Quintiliani and S. Santopietro. 2018. “After earthquake post-disaster response using a many-objective approach a greedy and engineering interventions.” In Proc. 1st Int. WDSA/CCWI 2018 Joint Conf. 14. Kingston Canada: Open Journal Systems.Cimellaro, G. P., Tinebra, A., Renschler, C., & Fragiadakis, M. (2016). New Resilience Index for Urban Water Distribution Networks. Journal of Structural Engineering, 142(8). doi:10.1061/(asce)st.1943-541x.0001433Cover, T., & Hart, P. (1967). Nearest neighbor pattern classification. IEEE Transactions on Information Theory, 13(1), 21-27. doi:10.1109/tit.1967.1053964Creaco, E., Franchini, M., & Alvisi, S. (2010). Optimal Placement of Isolation Valves in Water Distribution Systems Based on Valve Cost and Weighted Average Demand Shortfall. Water Resources Management, 24(15), 4317-4338. doi:10.1007/s11269-010-9661-5Deb, K., Mohan, M., & Mishra, S. (2005). Evaluating the ε-Domination Based Multi-Objective Evolutionary Algorithm for a Quick Computation of Pareto-Optimal Solutions. Evolutionary Computation, 13(4), 501-525. doi:10.1162/106365605774666895Deuerlein J. D. Gilbert E. Abraham and O. Piller. 2018. “A greedy scheduling of post-disaster response and restoration using pressure-driven models and graph segment analysis.” In Proc. 1st Int. WDSA/CCWI 2018 Joint Conf. 14. Kingston Canada: Open Journal Systems.Deuerlein, J. W. (2008). Decomposition Model of a General Water Supply Network Graph. Journal of Hydraulic Engineering, 134(6), 822-832. doi:10.1061/(asce)0733-9429(2008)134:6(822)Di Nardo, A., Di Natale, M., Giudicianni, C., Santonastaso, G. F., & Savic, D. (2018). Simplified Approach to Water Distribution System Management via Identification of a Primary Network. Journal of Water Resources Planning and Management, 144(2), 04017089. doi:10.1061/(asce)wr.1943-5452.0000885Eliades D. G. M. Kyriakou S. Vrachimis and M. M. Polycarpou. 2016. “EPANET-MATLAB toolkit: An open-source software for interfacing EPANET with MATLAB.” In Proc. 14th Int. Conf. on Computing and Control for the Water Industry (CCWI) 8. The Hague The Netherlands: International Water Conferences. https://doi.org/10.5281/zenodo.831493.Fragiadakis, M., Christodoulou, S. E., & Vamvatsikos, D. (2013). Reliability Assessment of Urban Water Distribution Networks Under Seismic Loads. Water Resources Management, 27(10), 3739-3764. doi:10.1007/s11269-013-0378-0Gilbert, D., Abraham, E., Montalvo, I., & Piller, O. (2017). Iterative Multistage Method for a Large Water Network Sectorization into DMAs under Multiple Design Objectives. Journal of Water Resources Planning and Management, 143(11), 04017067. doi:10.1061/(asce)wr.1943-5452.0000835Hill, D., Kerkez, B., Rasekh, A., Ostfeld, A., Minsker, B., & Banks, M. K. (2014). Sensing and Cyberinfrastructure for Smarter Water Management: The Promise and Challenge of Ubiquity. 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B. 1967. “Some methods for classification and analysis of multivariate observations.” In Vol. 1 of Proc. 5th Berkeley Symp. on Mathematical Statistics and Probability 281–297. Berkeley: University of California Press.Mahmoud, H. A., Kapelan, Z., & Savić, D. (2018). Real-Time Operational Response Methodology for Reducing Failure Impacts in Water Distribution Systems. Journal of Water Resources Planning and Management, 144(7), 04018029. doi:10.1061/(asce)wr.1943-5452.0000956Meng, F., Fu, G., Farmani, R., Sweetapple, C., & Butler, D. (2018). Topological attributes of network resilience: A study in water distribution systems. Water Research, 143, 376-386. doi:10.1016/j.watres.2018.06.048Ostfeld, A., Uber, J. G., Salomons, E., Berry, J. W., Hart, W. E., Phillips, C. A., … Walski, T. (2008). The Battle of the Water Sensor Networks (BWSN): A Design Challenge for Engineers and Algorithms. Journal of Water Resources Planning and Management, 134(6), 556-568. doi:10.1061/(asce)0733-9496(2008)134:6(556)Paez D. Y. Filion and M. Hulley. 2018a. “Battle of post-disaster response and restoration (BPDRR)—Problem description and rules.” Accessed June 14 2019. https://www.queensu.ca/wdsa-ccwi2018/problem-description-and-files.Paez, D., Suribabu, C. R., & Filion, Y. (2018). Method for Extended Period Simulation of Water Distribution Networks with Pressure Driven Demands. Water Resources Management, 32(8), 2837-2846. doi:10.1007/s11269-018-1961-1Salcedo C. A. Aguilar P. Cuero S. Gonzalez S. Muñoz J. Pérez A. Posada J. Robles and K. Vargas. 2018. “Determination of the hydraulic restoration capacity of b-city involving a multi-criteria decision support model.” In Proc. 1st Int. WDSA/CCWI 2018 Joint Conf. 14. Kingston Canada: Open Journal Systems.Santonastaso G. F. E. Creaco A. Di Nardo and M. Di Natale. 2018. “Post-disaster response and restauration of B-town network based on primary network.” In Vol. 1 of Proc. 1st Int. WDSA/CCWI 2018 Joint Conf. Kingston Canada: Open Journal Systems.Sophocleous S. E. Nikoloudi H. A. Mahmoud K. Woodward and M. Romano. 2018. “Simulation-based framework for the restoration of earthquake-damaged water distribution networks using a genetic algorithm.” In Proc. 1st Int. WDSA/CCWI 2018 Joint Conf. 14. Kingston Canada: Open Journal Systems.Sweetapple C. F. Meng R. Farmani G. Fu and D. Butler. 2018. “A heuristic approach to water network post-disaster response and restoration.” In Proc. 1st Int. WDSA/CCWI 2018 Joint Conf. 14. Kingston Canada: Open Journal Systems.Tabucchi, T., Davidson, R., & Brink, S. (2010). Simulation of post-earthquake water supply system restoration. Civil Engineering and Environmental Systems, 27(4), 263-279. doi:10.1080/10286600902862615Taormina, R., Galelli, S., Tippenhauer, N. O., Salomons, E., Ostfeld, A., Eliades, D. G., … Ohar, Z. (2018). Battle of the Attack Detection Algorithms: Disclosing Cyber Attacks on Water Distribution Networks. Journal of Water Resources Planning and Management, 144(8), 04018048. doi:10.1061/(asce)wr.1943-5452.0000969Walski, T. M. (1993). Water distribution valve topology for reliability analysis. Reliability Engineering & System Safety, 42(1), 21-27. doi:10.1016/0951-8320(93)90051-yWang, Y., Au, S.-K., & Fu, Q. (2010). Seismic Risk Assessment and Mitigation of Water Supply Systems. Earthquake Spectra, 26(1), 257-274. doi:10.1193/1.3276900Yoo, D. G., Kang, D., & Kim, J. H. (2016). Optimal design of water supply networks for enhancing seismic reliability. Reliability Engineering & System Safety, 146, 79-88. doi:10.1016/j.ress.2015.10.001Zhang Q. F. Zheng K. Diao B. Ulanicki and Y. Huang. 2018. “Solving the battle of post-disaster response and restauration (BPDRR) problem with the aid of multi-phase optimization framework.” In Proc. 1st Int. WDSA/CCWI 2018 Joint Conf. 14. Kingston Canada: Open Journal Systems

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

A Framework for Comparing Multi-Objective Optimization Approaches for a Stormwater Drainage Pumping System to Reduce Energy Consumption and Maintenance Costs

Reducing energy consumption and maintenance costs of a pumping system is seen as an important but difficult multi-objective optimization problem. Many evolutionary algorithms, such as particle swarm optimization (PSO), multi-objective particle swarm optimization (MOPSO), and non-dominated sorting genetic algorithm II (NSGA-II) have been used. However, a lack of comparison between these approaches poses a challenge to the selection of optimization approach for stormwater drainage pumping stations. In this paper, a new framework for comparing multi-objective approaches is proposed. Two kinds of evolutionary approaches, single-objective optimization and multi-objective optimization, are considered. Three approaches representing these two types are selected for comparison, including PSO with linear weighted sum method (PSO-LWSM), MOPSO with technique for order preference by similarity to an ideal solution (MOPSO-TOPSIS), and NSGA-II with TOPSIS (NSGA-II-TOPSIS). Four optimization objectives based on the number of pump startups/shutoffs, working hours, energy consumption, and drainage capacity are considered, of which the first two are new ones quantified in terms of operational economy in this paper. Two comparison methods—TOPSIS and operational economy and drainage capacity (E&C)—are used. The framework is demonstrated and tested by a case in China. The average values of the TOPSIS comprehensive evaluation index of the three approaches are 0.021, 0.154, and 0.375, respectively, and for E&C are 0.785, 0.813, and 0.839, respectively. The results show that the PSO-LWSM has better optimization results. The results validate the efficiency of the framework. The proposed framework will help to find a better optimization approach for pumping systems to reduce energy consumption and maintenance costs

A Framework for Comparing Multi-Objective Optimization Approaches for a Stormwater Drainage Pumping System to Reduce Energy Consumption and Maintenance Costs

Reducing energy consumption and maintenance costs of a pumping system is seen as an important but difficult multi-objective optimization problem. Many evolutionary algorithms, such as particle swarm optimization (PSO), multi-objective particle swarm optimization (MOPSO), and non-dominated sorting genetic algorithm II (NSGA-II) have been used. However, a lack of comparison between these approaches poses a challenge to the selection of optimization approach for stormwater drainage pumping stations. In this paper, a new framework for comparing multi-objective approaches is proposed. Two kinds of evolutionary approaches, single-objective optimization and multi-objective optimization, are considered. Three approaches representing these two types are selected for comparison, including PSO with linear weighted sum method (PSO-LWSM), MOPSO with technique for order preference by similarity to an ideal solution (MOPSO-TOPSIS), and NSGA-II with TOPSIS (NSGA-II-TOPSIS). Four optimization objectives based on the number of pump startups/shutoffs, working hours, energy consumption, and drainage capacity are considered, of which the first two are new ones quantified in terms of operational economy in this paper. Two comparison methods—TOPSIS and operational economy and drainage capacity (E&C)—are used. The framework is demonstrated and tested by a case in China. The average values of the TOPSIS comprehensive evaluation index of the three approaches are 0.021, 0.154, and 0.375, respectively, and for E&C are 0.785, 0.813, and 0.839, respectively. The results show that the PSO-LWSM has better optimization results. The results validate the efficiency of the framework. The proposed framework will help to find a better optimization approach for pumping systems to reduce energy consumption and maintenance costs