Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.5
3.4
Journals
Water
Special Issues
Green and Low Carbon Development of Water Treatment Technology, 2nd...
share announcement

Green and Low Carbon Development of Water Treatment Technology, 2nd Edition

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Wastewater Treatment and Reuse".

Deadline for manuscript submissions: 30 May 2024 | Viewed by 622

Special Issue Editors

Dr. Weigao Zhao

E-Mail Website
Guest Editor
School of Environmental Science and Technology, Tianjin University, Tianjin 300350, China
Interests: water treatment theory and technology; pipe network water quality research; environmental micro interface process research; colloidal pollutants; pollutant migration
Special Issues, Collections and Topics in MDPI journals
Dr. Peng Zhao

E-Mail Website
Guest Editor
School of Environment Science and Engineering, Tianjin University, Tianjin, China
Interests: research and application of smart water theory; simulation and planning of urban water supply and drainage systems; safe transmission and distribution of water supply networks; research and application of detection and diagnosis technology of drainage networks; theoretical research and technical development of water treatment
Special Issues, Collections and Topics in MDPI journals
Dr. Sen Peng

E-Mail Website
Guest Editor
School of Environmental Science and Engineering, Tianjin University, Tianjin 300350, China
Interests: hydraulic and water quality modeling of water distribution systems; ecological conservation of water environment systems; study of water quality model and its uncertainty; water supply networks; environmental system optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Effective water treatment technology is the key to achieving water safety and human health. All people having access to safe drinking water and improved water quality and wastewater management by 2030 are two of the United Nations’ Sustainable Development Goals (SDGs). Green and low-carbon technologies refer to technologies that achieve a satisfactory treatment effect under the condition of low carbon emissions and the generation of less pollutants. These technologies are considered to be essential to achieving the SDGs, so we propose focusing on these to follow the recent trends in water treatment technology. In this Special Issue, we seek submissions which focus on the interactions between green and low-carbon development and water treatment technology.

Topics of interest for this Special Issue include, but are not limited to, the following:

  • New water and wastewater treatment technologies;
  • Green and low-carbon development strategies；
  • Water environment simulation models；
  • Environmental micro interface reactions.

By focusing on novel results regarding these above mentioned topics, this Special Issue will be able to provide a series of studies on water treatment technologies.

Dr. Weigao Zhao
Dr. Peng Zhao
Dr. Sen Peng
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • water treatment
  • green development
  • low-carbon development
  • drinking water
  • environmental micro interface

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

15 pages, 3509 KiB  
Article
Burst Diagnosis Multi-Stage Model for Water Distribution Networks Based on Deep Learning Algorithms
by Sen Peng, Yuxin Wang, Xu Fang and Qing Wu
Water 2024, 16(9), 1258; https://doi.org/10.3390/w16091258 - 28 Apr 2024
Viewed by 460
Abstract
Pipe bursts in water distribution networks (WDNs) pose significant threats to the safety of distribution networks, driving attention to deep learning-based burst detection and localization. However, the applicability of different pressure features still needs to be compared and verified. A large number of [...] Read more.
Pipe bursts in water distribution networks (WDNs) pose significant threats to the safety of distribution networks, driving attention to deep learning-based burst detection and localization. However, the applicability of different pressure features still needs to be compared and verified. A large number of nodes challenges deep learning with the excessive number of classification categories and low recognition accuracy. To address these problems, this paper extracts different burst pressure features, including pressure value, pressure difference, and pressure fluctuation ratio, and inputs one of these features into a Burst Diagnosis Multi-Stage Model (BDMM) based on three CS-LSTMs (a combination of the Cuckoo Search algorithm and a long short-term memory network). The first model addresses a binary classification problem, outputting labels indicating whether a pipe burst has occurred. The second one solves a multi-classification problem, outputting the label of the burst partition, and the third model also solves a multi-classification problem, outputting the ID of the bursting junction. The model is tested on a real network and outperforms ELM. For basic burst identification tasks using CS-LSTM, differences among the three features are minimal, while pressure difference and pressure fluctuation ratio exhibit superior performance to pressure value when resolving more complex problems like burst junction localization. Full article
(This article belongs to the Special Issue Green and Low Carbon Development of Water Treatment Technology, 2nd Edition)
►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop