Using a digital twin to explore water infrastructure impacts during the COVID-19 pandemic
TLDR
In this paper , the authors developed a digital twin to couple Advanced Metering Infrastructure (AMI) data with a hydraulic model to assess impacts on infrastructure due to changes in water demands associated with the COVID-19 pandemic for a case study.About:
This article is published in Sustainable Cities and Society.The article was published on 2022-02-01 and is currently open access. It has received 30 citations till now. The article focuses on the topics: Water supply.read more
Citations
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Toward the Next Generation of Digitalization in Agriculture Based on Digital Twin Paradigm
Abozar Nasirahmadi,Oliver Hensel +1 more
TL;DR: In this paper , the authors present a general framework of digital twins in soil, irrigation, robotics, farm machineries, and food post-harvest processing in agricultural field, which can support farmers as a next generation of digitalization paradigm by continuous and real-time monitoring of physical world (farm) and updating the state of virtual world.
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The role of deep learning in urban water management: A critical review.
TL;DR: In this article , a review of the current state of deep learning applications and an examination of potential directions where deep learning can contribute to solving urban water challenges is provided, covering water demand forecasting, leakage and contamination detection, sewer defect assessment, wastewater system state prediction, asset monitoring and urban flooding.
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New Challenges towards Smart Systems’ Efficiency by Digital Twin in Water Distribution Networks
Helena M. Ramos,Maria Cristina Morani,Armando Carravetta,Oreste Fecarrotta,Kemi Adeyeye,P. Amparo López-Jiménez,Modesto Pérez-Sánchez +6 more
TL;DR: In this article , the authors defined a new methodology for an efficient application of Digital Twins (DT) expertise within water distribution networks and demonstrated that a fast detection of leakage along with an optimal setting of pressure control valves by means of DT together with an optimization procedure can ensure up to 28% of water savings, contributing to significantly increase the efficiency of the whole system.
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Progress and prospects in planning: A bibliometric review of literature in Urban Studies and Regional and Urban Planning, 1956–2022
TL;DR: In this article , the authors analyzed data related to more than 100,000 articles indexed under the "Urban Studies" and "Regional & Urban Planning" subject categories of the Web of Science to identify the key defining thematic areas of the field and examine how they have evolved.
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Effects of the COVID-19 Pandemic on Water Utility Operations and Vulnerability
TL;DR: In this paper , the authors report on how the operations of 27 water utilities worldwide were affected by the COVID-19 pandemic, and survey questions focused on the effects of the pandemic on water system operation, demand, revenues, system vulnerabilities, and the use and development of emergency response plans.
References
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Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case
TL;DR: The results of a simulation study that opens some new research tensions on the impact of COVID-19 (SARS-CoV-2) on the global SCs are presented and an analysis for observing and predicting both short-term and long-term impacts of epidemic outbreaks on the SCs along with managerial insights are offered.
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Changes in U.S. air pollution during the COVID-19 pandemic.
Jesse D. Berman,Keita Ebisu +1 more
TL;DR: In this paper, the authors assessed air quality during the COVID-19 pandemic for fine particulate matter (PM2.5) and nitrogen dioxide (NO2) in the continental United States from January 8th-April 21st in 2017-2020.
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Make more digital twins.
Fei Tao,Qinglin Qi +1 more
TL;DR: Virtual models boost smart manufacturing by simulating decisions and optimization, from design to operations, explain Fei Tao and Qinglin Qi.
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Simulating Residential Water Demand with a Stochastic End-Use Model
TL;DR: In this article, a water demand end-use model was developed to predict water demand patterns with a small time scale (1 s) and small spatial scale (residence level).
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Benefits and challenges of using smart meters for advancing residential water demand modeling and management
TL;DR: This manuscript is the first comprehensive review of the literature in this quickly evolving water research domain and contributes a general framework for the classification of residential water demand modeling studies, which allows revising consolidated approaches, describing emerging trends, and identifying potential future developments.
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