Article
Environmental Sciences
Joana Carneiro, Dalia Loureiro, Didia Covas
Summary: This study compares and discusses the adequacy of surrogate resilience metrics proposed in the literature for resilience assessment of drinking water systems. Different layouts and demand scenarios are considered in a sensitivity analysis of flow rates. Surrogate resilience metrics provide vital information for drinking water systems management.
WATER RESOURCES RESEARCH
(2023)
Article
Multidisciplinary Sciences
Jesus Felix Bayta Valenzuela, Erika Fille Tupas Legara, Christopher Pineda Monterola
Summary: This study investigates the network properties and response to damage of road networks in cities worldwide using OpenStreetMap data. It finds a strong linear correlation between the average shortest time needed to reach all nodes in a road network and the fraction of road network segments damaged. Additionally, it identifies three families of road networks based on their damage response, and highlights the importance of average shortest path length and average node degree in assessing damage susceptibility.
Article
Computer Science, Artificial Intelligence
Yongqi Wang, Penghui Lin, Limao Zhang, Hongbo Yu, Tiong Lee Kong Robert
Summary: A systematic research framework is proposed to analyze and optimize the resilience of a Mechanical, Electrical, and Plumbing (MEP) system under random and intentional attacks. The results show that the framework can effectively analyze the MEP system and optimize its design by adding new edges.
ADVANCED ENGINEERING INFORMATICS
(2023)
Article
Environmental Sciences
Amrita Namtirtha, K. R. Sheetal Kumar, Sejal Jain, Yogesh Simmhan, M. S. Mohan Kumar
Summary: Water quality sensors are important for detecting contamination in water distribution systems. Existing methods for sensor placement either have limitations or require extensive computational resources and system knowledge. This study proposes a new method, EQ-Water, based on complex network theory and minimal hydraulic information, to identify optimal sensor locations for different types of water distribution systems.
WATER RESOURCES RESEARCH
(2023)
Article
Engineering, Civil
Jaewoo Son, Ijung Kim, Jeryang Park
Summary: A complex network approach is used to analyze water distribution networks (WDNs) by establishing a random network with varying proportions of grids (p(g)). The results show that the system functioning of WDNs changes non-linearly as the network transitions from a loop to a branched structure, with a threshold point below which the network can be effectively improved with low resource inputs. The study also identifies threshold points for network efficiency, decentralization, availability, normalized efficiency, and vulnerability.
KSCE JOURNAL OF CIVIL ENGINEERING
(2023)
Article
Engineering, Civil
Alessandro Pagano, Raffaele Giordano, Ivan Portoghese
Summary: Resilience assessment is crucial for infrastructures, including water supply and distribution networks. The use of graph-theory metrics can provide reliable information on complex network performance. This study aims to identify relevant metrics connected to network resilience, perform network degradation analysis, and rank critical pipes using a Bayesian Belief Network.
WATER RESOURCES MANAGEMENT
(2022)
Article
Engineering, Civil
Ahmad Momeni, Varsha Chauhan, Abdulrahman Bin Mahmoud, Kalyan R. Piratla, Ilya Safro
Summary: This study proposes a comprehensive approach to generate and optimize synthetic water distribution system infrastructure data. It employs graph-theory concepts to generate diverse WDS skeleton layouts and uses a multiobjective genetic algorithm to assign component sizes and operational features to these layouts. The proposed modeling approach allows for extensive access to representative synthetic networks for academic and industrial purposes.
JOURNAL OF PIPELINE SYSTEMS ENGINEERING AND PRACTICE
(2023)
Article
Construction & Building Technology
Sina Hesarkazzazi, Mohsen Hajibabaei, Amin E. Bakhshipour, Ulrich Dittmer, Ali Haghighi, Robert Sitzenfrei
Summary: Recent research has shown the suitability and effectiveness of decentralized paradigms in the field of underground conveyance drainage infrastructures for addressing sustainability and resilience demands. A scheme is proposed in this study to create and optimize decentralization scenarios for sewer layout configurations, reducing design construction costs and improving network resilience.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Construction & Building Technology
Ariele Zanfei, Andrea Menapace, Bruno M. Brentan, Maurizio Righetti, Manuel Herrera
Summary: The sustainable management of water resources is crucial for the well-being and security of society worldwide. This study proposes a novel water distribution system (WDS) management framework based on graph convolutional neural networks (GCN) for efficient detection of anomalies like leaks and pipe bursts.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Computer Science, Information Systems
Ali Moradi Amani, Mahdi Jalili
Summary: This manuscript provides a focused overview of modelling power grids as complex networks and their resilience and reliability analysis. The review critically examines vitality metrics in power grid resilience analysis and demonstrates the applicability of these concepts through simulations on benchmark and real power grids.
Article
Engineering, Civil
Mohammad Reza Shekofteh, Ehsan Yousefi-Khoshqalb, Kalyan R. Piratla
Summary: This paper presents a practical approach for managing water supply infrastructure by effectively partitioning water distribution networks into district metered areas using graph theoretic algorithms and multi-objective optimization. The approach optimizes the dynamic layouts of DMAs based on flow meters and gate valves, minimizing installation costs and enhancing water loss monitoring. The effectiveness of this approach is demonstrated through successful implementation on six benchmark WDNs, offering a cost-effective means for efficient water management.
WATER RESOURCES MANAGEMENT
(2023)
Article
Green & Sustainable Science & Technology
Xiangyu Ma, Huijie Zhou, Zhiyi Li
Summary: This paper provides a comprehensive literature review on the application of complex network theories in resilience evaluation and enhancement of modern power systems. It decomposes resilience into structural and operational aspects, discussing structural resilience through graph modeling and analyzing static and dynamic characteristics, and investigating operational resilience through the progression of preventive, corrective, and restorative strategies in extreme events. It also extends the discussion to multilayer networks as modern power systems are increasingly interconnected with communication networks and other energy carriers. Overall, complex network theories are found to be effective in understanding and improving the structural and operational resilience of modern power systems.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Geosciences, Multidisciplinary
Benwei Hou, Jinmei Huang, Huiquan Miao, Xudong Zhao, Shan Wu
Summary: This study presents a seismic resilience evaluation framework of water distribution systems (WDSs) that integrates hydraulic with water quality simulation, providing an essential basis for resilience enhancement and disaster mitigation in urban communities.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2023)
Article
Engineering, Environmental
Sina Hesarkazzazi, Amin E. Bakhshipour, Mohsen Hajibabaei, Ulrich Dittmer, Ali Haghighi, Robert Sitzenfrei
Summary: This study investigates the effectiveness of topological decentralization for urban stormwater networks (USNs) during the planning stage. It proposes a framework to understand the impact of adding redundant flow paths on resilience and introduces a tailored graph-theory based measure. The results show that layout decentralization and the implementation of redundant paths can enhance the resilience of USNs without changing the network's major structural characteristics.
Article
Mathematics
Nor Kamariah Kasmin, Tahir Ahmad, Amidora Idris, Siti Rahmah Awang, Mujahid Abdullahi
Summary: The motion of solid objects or fluids can be described using mathematics, namely mathematical modelling. Different techniques such as ODE, PDE, statistical methods, and NN are commonly used. However, these techniques require large amounts of data or an initial governing equation. Therefore, a new concept called multidigraph autocatalytic set (MACS) is introduced, which allows modelling multiple relations between components of a system. This concept is applied to the vector borne disease network system and successfully identifies the main sources of the outbreak based on their reproduction number, R-0.
Article
Agronomy
Boran Ekin Aydin, Gualbert H. P. Oude Essink, Joost R. Delsman, Nick van de Giesen, Edo Abraham
Summary: A significant increase in surface water salinization is expected in low-lying deltas worldwide, which leads to the increased demand for freshwater flushing. To address this issue, this paper proposes a novel network model-based approach to optimize the control of water level and salinity, aiming to reduce the demand for scarce freshwater.
AGRICULTURAL WATER MANAGEMENT
(2022)
Article
Engineering, Civil
David B. Steffelbauer, Jochen Deuerlein, Denis Gilbert, Edo Abraham, Olivier Piller
Summary: In this study, multiple leaks in a water distribution network are detected simultaneously by optimizing the hydraulic model. A hierarchical decision-making approach is employed to build demand models using smart meter data, calibrate roughness parameters, and transform leaks into virtual leak flow signals through a dual model. This innovative dual modeling approach achieved the highest true-positive rates for leak isolation in the competition.
JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT
(2022)
Review
Green & Sustainable Science & Technology
Azar Niknam, Hasan Khademi Zare, Hassan Hosseininasab, Ali Mostafaeipour, Manuel Herrera
Summary: The challenge for city authorities in managing growing cities is exacerbated by the increasing exposure to climate change effects. This paper provides a timely review of predictive methods for short-term water demand, offering a comprehensive guideline for selecting forecasting methods. It also emphasizes the importance of sustainable management objectives in the era of technological developments.
Article
Computer Science, Interdisciplinary Applications
Ties van der Heijden, Dorien Lugt, Ronald van Nooijen, Peter Palensky, Edo Abraham
Summary: This manuscript proposes the use of multiple electricity spot markets for price-based demand response in open canal systems in the Netherlands. By combining day ahead and intraday electricity markets and employing a hierarchical receding horizon economic Model Predictive Control, the proposed strategy leads to a decrease in costs and provides new insights into the trade-off between CO2 emissions and operating costs, differences between German and Dutch markets, and temporal changes in market conditions due to renewable energy integration.
JOURNAL OF HYDROINFORMATICS
(2022)
Article
Engineering, Civil
Xian Bin Wee, Manuel Herrera, Georgios M. Hadjidemetriou, Ajith Kumar Parlikad
Summary: The role of urban infrastructure is becoming increasingly interdependent, resulting in new sources of vulnerability. This paper aims to bridge the gap by developing a modeling methodology using complex network theory to study asset criticality and failure propagation in urban infrastructure.
TRANSPORTATION RESEARCH RECORD
(2022)
Article
Environmental Sciences
Ariele Zanfei, Bruno M. Brentan, Andrea Menapace, Maurizio Righetti, Manuel Herrera
Summary: This paper proposes a novel graph convolutional recurrent neural network (GCRNN) for short-term water demand forecasting, which can capture the dependence among different water demand time series in both spatial and temporal aspects. The GCRNN outperforms the LSTM in the fault test, showing its ability to generate accurate and reliable predictions.
WATER RESOURCES RESEARCH
(2022)
Article
Environmental Sciences
Zarrar Khan, Edo Abraham, Srijan Aggarwal, Manal Ahmad Khan, Ricardo Arguello, Meghna Babbar-Sebens, Julia Lacal Bereslawski, Jeffrey M. Bielicki, Pietro Elia Campana, Maria Eugenia Silva Carrazzone, Homero Castanier, Fi-John Chang, Pamela Collins, Adela Conchado, Koteswara Rao Dagani, Bassel Daher, Stefan C. Dekker, Ricardo Delgado, Fabio A. Diuana, Jonathan Doelman, Amin A. Elshorbagy, Chihhao Fan, Rossana Gaudioso, Solomon H. Gebrechorkos, Hatim M. E. Geli, Emily Grubert, Daisy Huang, Tailin Huang, Ansir Ilyas, Aleksandr Ivakhnenko, Graham P. W. Jewitt, Maria Joao Ferreira dos Santos, J. Leah Jones, Elke Kellner, Elisabeth H. Krueger, Ipsita Kumar, Jonathan Lamontagne, Angelique Lansu, Sanghyun Lee, Ruopu Li, Pedro Linares, Diego Marazza, Maria Pia Mascari, Ryan A. McManamay, Measrainsey Meng, Simone Mereu, Fernando Miralles-Wilhelm, Rabi Mohtar, Abubakr Muhammad, Adenike Kafayat Opejin, Saket Pande, Simon Parkinson, Raphael Payet-Burin, Meenu Ramdas, Eunice Pereira Ramos, Sudatta Ray, Paula Roberts, Jon Sampedro, Kelly T. Sanders, Marzieh Hassanzadeh Saray, Jennifer Schmidt, Margaret Shanafield, Sauleh Siddiqui, Micaela Suriano, Makoto Taniguchi, Antonio Trabucco, Marta Tuninetti, Adriano Vinca, Bjorn Weeser, Dave D. White, Thomas B. Wild, Kamini Yadav, Nithiyanandam Yogeswaran, Tokuta Yokohata, Qin Yue
Summary: This article introduces the nexus between water, energy, and food, emphasizing the importance of understanding their interdependencies and trade-offs in solving global challenges. The article presents 10 key recommendations, highlighting the need for a nexus community of practice to facilitate communication, share standardized datasets, and develop applied case studies.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2022)
Article
Energy & Fuels
Chelsea Kaandorp, Tes Miedema, Jeroen Verhagen, Nick van de Giesen, Edo Abraham
Summary: This study proposes a computational approach to find a mix of heat options per neighborhood that minimizes cumulative carbon emissions between 2030 and 2050. The results show that ambitious measures for building insulation and decarbonization in electricity generation can significantly reduce committed emissions, with low temperature heat systems being the optimal solution.
Article
Construction & Building Technology
Ariele Zanfei, Andrea Menapace, Bruno M. Brentan, Maurizio Righetti, Manuel Herrera
Summary: The sustainable management of water resources is crucial for the well-being and security of society worldwide. This study proposes a novel water distribution system (WDS) management framework based on graph convolutional neural networks (GCN) for efficient detection of anomalies like leaks and pipe bursts.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Energy & Fuels
Yacob Mulugetta, Youba Sokona, Philipp A. Trotter, Samuel Fankhauser, Jessica Omukuti, Lucas Somavilla Croxatto, Bjarne Steffen, Meron Tesfamichael, Edo Abraham, Jean-Paul Adam, Lawrence Agbemabiese, Churchill Agutu, Mekalia Paulos Aklilu, Olakunle Alao, Bothwell Batidzirai, Getachew Bekele, Anteneh G. Dagnachew, Ogunlade Davidson, Fatima Denton, E. Ogheneruona Diemuodeke, Florian Egli, Eshetu Gebrekidan Gebresilassie, Mulualem Gebreslassie, Mamadou Goundiam, Haruna Kachalla Gujba, Yohannes Hailu, Adam D. Hawkes, Stephanie Hirmer, Helen Hoka, Mark Howells, Abdulrasheed Isah, Daniel Kammen, Francis Kemausuor, Ismail Khennas, Wikus Kruger, Ifeoma Malo, Linus Mofor, Minette Nago, Destenie Nock, Chukwumerije Okereke, S. Nadia Ouedraogo, Benedict Probst, Maria Schmidt, Tobias S. Schmidt, Carlos Shenga, Mohamed Sokona, Jan Christoph Steckel, Sebastian Sterl, Bernard Tembo, Julia Tomei, Peter Twesigye, Jim Watson, Harald Winkler, Abdulmutalib Yussuff
Summary: Aligning development and climate goals in Africa requires country-specific approaches to energy system development, taking into account the unique starting points and uncertainties of each country. Policy, finance, and research recommendations are provided to identify suitable energy pathways for development and enable their implementation.
Article
Computer Science, Hardware & Architecture
Manuel Herrera, Manu Sasidharan, Stephen Cassidy, Ajith Kumar Parlikad
Summary: This paper presents a multilayer complex network framework that takes into account the heterogeneous redundant infrastructure for realistic network modeling and analysis. Key performance indicators for communication networks are redefined to evaluate important features of a long-haul backbone network. The study analyzes the use case of a nationwide core and metro network infrastructure and identifies critical network elements for prioritizing network management measures.
Article
Automation & Control Systems
Gert van Lagen, Edo Abraham, Peyman Mohajerin Esfahani
Summary: This article proposes an active fault isolation method for localizing leaks in water distribution networks (WDNs). The method uses classification of observed outputs and smooth kernel density estimation to approximate the output probability distribution functions (PDFs) corresponding to the considered faults. An active algorithm is introduced to minimize the overlap between output PDFs by designing optimal control inputs. Due to physical limitations and uncertainties, complete separation and fault isolation for a single observed output cannot be guaranteed, so an iterative framework is used with posterior probabilities from previous time steps serving as prior probabilities for the next time step. The method improves performance compared to the best passive method in the literature.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Engineering, Environmental
Ariele Zanfei, Andrea Menapace, Bruno M. Brentan, Robert Sitzenfrei, Manuel Herrera
Summary: This paper proposes a breakthrough approach for calibrating hydraulic models through a graph machine learning approach. The main idea is to create a graph neural network metamodel to estimate the network behaviour based on a limited number of monitoring sensors. Through this process, it is possible to estimate the uncertainty that is transferred from the few available measurements to the final hydraulic model.
Article
Environmental Sciences
Adrian Martinez, Manuel Herrera, Jesus Lopez de la Cruz, Ismael Orozco
Summary: This study focuses on the vulnerability of watersheds to climate change and develops a predictive model using a distributed hydrological model, artificial neural networks, and spatially distributed indicators. The results show that almost 50% of the watershed currently has medium and high vulnerabilities, and future urban and agricultural areas are expected to increase their vulnerability from medium to high levels.
Article
Computer Science, Information Systems
Ties Van der Heijden, Jesus Lago, Peter Palensky, Edo Abraham
Summary: This study explores the importance of European features in Day Ahead Market (DAM) price forecasting models, proposing a greedy algorithm for selecting European features and applying it to building and comparing price forecasting models for the Dutch market. The results show that integrating European features significantly improves the accuracy of the forecasts.
