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2023 Vol. 41, No. 11
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2023, 41(11): 1-5.
doi: 10.13205/j.hjgc.202311001
Abstract:
In the era of digital economy, digital transformation has become a consensus and direction of joint efforts in the water industry. This article systematically analyzed the background, internal and external driving forces, main problems, and specific implementation paths of digital transformation of water enterprises, providing a reference for the digital transformation of water enterprises, as well as the intelligent development of the water industry.
In the era of digital economy, digital transformation has become a consensus and direction of joint efforts in the water industry. This article systematically analyzed the background, internal and external driving forces, main problems, and specific implementation paths of digital transformation of water enterprises, providing a reference for the digital transformation of water enterprises, as well as the intelligent development of the water industry.
2023, 41(11): 6-13.
doi: 10.13205/j.hjgc.202311002
Abstract:
With the continuous deepening of ecological civilization construction in China, the urban water systems tend to collaborative governance, coordinative promotion in the "14th Five-Year Plan" period. Given the common problems of urban water system operation and management, such as inadequate systems, imperfect standards, low operational quality and efficiency, and difficulties in promoting experience and making use of data and other issues, we sorted out the operation logic based on business scenarios, reconstructed the operation process based on digital features, explored the implementation path of intelligent operation of the urban water system, constructed the top-level design of the intelligent operation of the urban water system based on the asset with systematic thinking, and clarified the core elements and key links, and developed the intelligent operation platform for the deep integration of environmental protection operation and information technology. By constructing a full-process operation management workflow consisting of "information collection, asset assessment, hierarchical maintenance, refined management, monitoring and early warning, and comprehensive scheduling", it provides new ideas for realizing the long-term operation of urban water systems, and promotes urban water system standardization, refinement, intelligent operation, and creates long-term value for the ecological environment.
With the continuous deepening of ecological civilization construction in China, the urban water systems tend to collaborative governance, coordinative promotion in the "14th Five-Year Plan" period. Given the common problems of urban water system operation and management, such as inadequate systems, imperfect standards, low operational quality and efficiency, and difficulties in promoting experience and making use of data and other issues, we sorted out the operation logic based on business scenarios, reconstructed the operation process based on digital features, explored the implementation path of intelligent operation of the urban water system, constructed the top-level design of the intelligent operation of the urban water system based on the asset with systematic thinking, and clarified the core elements and key links, and developed the intelligent operation platform for the deep integration of environmental protection operation and information technology. By constructing a full-process operation management workflow consisting of "information collection, asset assessment, hierarchical maintenance, refined management, monitoring and early warning, and comprehensive scheduling", it provides new ideas for realizing the long-term operation of urban water systems, and promotes urban water system standardization, refinement, intelligent operation, and creates long-term value for the ecological environment.
2023, 41(11): 14-18,33.
doi: 10.13205/j.hjgc.202311003
Abstract:
The water industry is an important sector that involves people's livelihood and the environment. With the advent of the big data era, water enterprises are gradually establishing information systems and accumulating a large amount of data resources. Firstly, this paper elaborates on the concept and characteristics of the water industry data economy. Secondly, it explores the value and application scenarios of the water industry data economy, including improving efficiency, optimizing decision-making, innovating services, reducing risks, and promoting sustainable development. Next, it analyzes the challenges faced by the water industry data economy, such as data quality, data security, data sharing, and data innovation, and proposes corresponding strategies. Finally, it discusses the development prospects of the water industry data economy, including technological advancements, policy support, innovative applications, industry collaboration, social awareness and acceptance. The research on the water industry data economy indicates that water data is an important strategic resource with great potential and value. With the continuous progress of technology and the increasing societal demands, the water industry data economy will bring more opportunities and innovations, driving the water industry towards intelligence, greenness, and sustainable development, providing valuable insights and guidance for water companies and relevant government departments.
The water industry is an important sector that involves people's livelihood and the environment. With the advent of the big data era, water enterprises are gradually establishing information systems and accumulating a large amount of data resources. Firstly, this paper elaborates on the concept and characteristics of the water industry data economy. Secondly, it explores the value and application scenarios of the water industry data economy, including improving efficiency, optimizing decision-making, innovating services, reducing risks, and promoting sustainable development. Next, it analyzes the challenges faced by the water industry data economy, such as data quality, data security, data sharing, and data innovation, and proposes corresponding strategies. Finally, it discusses the development prospects of the water industry data economy, including technological advancements, policy support, innovative applications, industry collaboration, social awareness and acceptance. The research on the water industry data economy indicates that water data is an important strategic resource with great potential and value. With the continuous progress of technology and the increasing societal demands, the water industry data economy will bring more opportunities and innovations, driving the water industry towards intelligence, greenness, and sustainable development, providing valuable insights and guidance for water companies and relevant government departments.
2023, 41(11): 19-24.
doi: 10.13205/j.hjgc.202311004
Abstract:
With the frequent introduction of favorable policies to promote the digital transformation of water companies and information technology improvement by leaps and bounds, water companies are faced with a large number of data governance requirements. How to conduct effective data governance becomes the focal point of their digital transformation. However, the water industry has relatively traditional and dispersed features, and data governance knowledge is relatively abstract. Therefore, there are certain challenges in the practical implementation of data governance in water companies. Based on the design perspective of the water companies' governance frameworks, the paper discussed nine aspects, including core business process combing and modeling, business models, data models, data asset catalogs, reporting systems, data standard systems, IT governance guarantee systems, data security systems, and data application systems. A set of feasible and executable frameworks were formed. Through the design of a data governance framework, the implementation efficiency and success rate of data governance projects of water companies can be improved, and powerful support can be provided for the high-quality development of water companies.
With the frequent introduction of favorable policies to promote the digital transformation of water companies and information technology improvement by leaps and bounds, water companies are faced with a large number of data governance requirements. How to conduct effective data governance becomes the focal point of their digital transformation. However, the water industry has relatively traditional and dispersed features, and data governance knowledge is relatively abstract. Therefore, there are certain challenges in the practical implementation of data governance in water companies. Based on the design perspective of the water companies' governance frameworks, the paper discussed nine aspects, including core business process combing and modeling, business models, data models, data asset catalogs, reporting systems, data standard systems, IT governance guarantee systems, data security systems, and data application systems. A set of feasible and executable frameworks were formed. Through the design of a data governance framework, the implementation efficiency and success rate of data governance projects of water companies can be improved, and powerful support can be provided for the high-quality development of water companies.
2023, 41(11): 25-33.
doi: 10.13205/j.hjgc.202311005
Abstract:
Drainage system is one of the important infrastructure in cities, and monitoring of its safe operation is of significant significance. To solve the problems of drainage system data management, online monitoring, business management, waterlogging warning, etc., taking Changzhou as the research object, the current situation and problems of its drainage system were analyzed in depth, and the solutions were given. Based on GIS, Internet of Things (IoT), artificial intelligence, digital twin and other technologies, the technical architecture of safe operation monitoring of drainage infrastructure was proposed, and momitoring platform for safe operation of drainage infrastructure in Changzhou were developed and applied. After the system went online, the maintenance cost of the pipeline network was reduced by 12% on average, the annual low water level operation time of sewage was increased by 10%, and the integrated scheduling efficiency of drainage was increased by 50%, so as to realize the whole life cycle management of facilities, all-round monitoring of pipe networks, urban flood prevention and emergency response, and integrated scheduling of source-network-plant-river. It effectively improves the digital and intelligent supervision level of drainage infrastructure in Changzhou, and can provide a reference for the safe operation monitoring of similar urban drainage infrastructures.
Drainage system is one of the important infrastructure in cities, and monitoring of its safe operation is of significant significance. To solve the problems of drainage system data management, online monitoring, business management, waterlogging warning, etc., taking Changzhou as the research object, the current situation and problems of its drainage system were analyzed in depth, and the solutions were given. Based on GIS, Internet of Things (IoT), artificial intelligence, digital twin and other technologies, the technical architecture of safe operation monitoring of drainage infrastructure was proposed, and momitoring platform for safe operation of drainage infrastructure in Changzhou were developed and applied. After the system went online, the maintenance cost of the pipeline network was reduced by 12% on average, the annual low water level operation time of sewage was increased by 10%, and the integrated scheduling efficiency of drainage was increased by 50%, so as to realize the whole life cycle management of facilities, all-round monitoring of pipe networks, urban flood prevention and emergency response, and integrated scheduling of source-network-plant-river. It effectively improves the digital and intelligent supervision level of drainage infrastructure in Changzhou, and can provide a reference for the safe operation monitoring of similar urban drainage infrastructures.
2023, 41(11): 34-38,45.
doi: 10.13205/j.hjgc.202311007
Abstract:
In this study, the water IoT monitoring technology is used to analyze the typical areas. Based on online monitoring data, an IoT monitoring and pipe network problem diagnosis system, with data statistical analysis as the core, was built to intelligently diagnose the operating status of pipe network, analyzed the problems of drainage pipe network such as inflow infiltration, siltation and overflow, and grasped the operating status of the entire drainage system under different working conditions. The results showed that IoT monitoring technology can help identify drainage network problems and effectively reduce the cost of troubleshooting drainage system problems. By carrying out the assessment of infiltration risk, siltation risk, and overflow risk, we can identify the pipe segments with possible problems, and provide data support for the subsequent network renovation work. The project can provide an experience for other cities to promote IoT monitoring technology.
In this study, the water IoT monitoring technology is used to analyze the typical areas. Based on online monitoring data, an IoT monitoring and pipe network problem diagnosis system, with data statistical analysis as the core, was built to intelligently diagnose the operating status of pipe network, analyzed the problems of drainage pipe network such as inflow infiltration, siltation and overflow, and grasped the operating status of the entire drainage system under different working conditions. The results showed that IoT monitoring technology can help identify drainage network problems and effectively reduce the cost of troubleshooting drainage system problems. By carrying out the assessment of infiltration risk, siltation risk, and overflow risk, we can identify the pipe segments with possible problems, and provide data support for the subsequent network renovation work. The project can provide an experience for other cities to promote IoT monitoring technology.
2023, 41(11): 39-45.
doi: 10.13205/j.hjgc.202311006
Abstract:
To realize the continuous and low-cost monitoring and assessment of extraneous water risk in urban sewage networks, this paper proposed a set of risk assessment methods based on integrated monitoring of water supply and drainage systems. The risk level was reflected by two indicators:extraneous water proportion R and grade frequency P, which can capture the spatial and temporal distribution of extraneous water. The methods were applied to the risk assessment of extraneous water in an area of City W in south China. The study area was divided into three sub-catchments by four plant pumps and three key monitoring nodes. The analysis results of data in March 2022 showed that the extraneous water risk level of subcatchment-Z1 was L2 (relatively high), the overall region and subctchment-Z3 was L3 (high), and the subcatchment-Z2 was L4 (very high). In April, the results of sub-catchments remained unchanged except that the overall region was reduced to L2. Compared to traditional methods, this method can output reliable conclusions, realize the risk distribution analysis of extraneous water with low cost, and has practical significance for improving the efficiency of sewage network management.
To realize the continuous and low-cost monitoring and assessment of extraneous water risk in urban sewage networks, this paper proposed a set of risk assessment methods based on integrated monitoring of water supply and drainage systems. The risk level was reflected by two indicators:extraneous water proportion R and grade frequency P, which can capture the spatial and temporal distribution of extraneous water. The methods were applied to the risk assessment of extraneous water in an area of City W in south China. The study area was divided into three sub-catchments by four plant pumps and three key monitoring nodes. The analysis results of data in March 2022 showed that the extraneous water risk level of subcatchment-Z1 was L2 (relatively high), the overall region and subctchment-Z3 was L3 (high), and the subcatchment-Z2 was L4 (very high). In April, the results of sub-catchments remained unchanged except that the overall region was reduced to L2. Compared to traditional methods, this method can output reliable conclusions, realize the risk distribution analysis of extraneous water with low cost, and has practical significance for improving the efficiency of sewage network management.
2023, 41(11): 46-53,77.
doi: 10.13205/j.hjgc.202311009
Abstract:
The new urban areas and towns in the Guangdong-Hong Kong-Macau Greater Bay Area are characterized by huge populations, varying scales of water supply enterprises, and inconsistent management practices. Among them, pipeline leak control commonly faces operational and managerial challenges. With the strong promotion of carbon reduction at the national level, water supply enterprises need to adopt more proactive measures to meet carbon targets and achieve carbon neutrality, with leak control being a key control point. Currently, most water supply enterprises adopt traditional management measures and pipeline leak detection methods. Based on the practical experience of leakage management in Macao's water supply, the article summarizes five specific measures for leakage management. It emphasizes the integration of water leakage management, digitalization, and intelligent management approaches. Some specific new leakage management methods and their effects are introduced by examples of the application of Internet of Things (IoT) technology in leak detection and pressure transient management in the pipeline network
The new urban areas and towns in the Guangdong-Hong Kong-Macau Greater Bay Area are characterized by huge populations, varying scales of water supply enterprises, and inconsistent management practices. Among them, pipeline leak control commonly faces operational and managerial challenges. With the strong promotion of carbon reduction at the national level, water supply enterprises need to adopt more proactive measures to meet carbon targets and achieve carbon neutrality, with leak control being a key control point. Currently, most water supply enterprises adopt traditional management measures and pipeline leak detection methods. Based on the practical experience of leakage management in Macao's water supply, the article summarizes five specific measures for leakage management. It emphasizes the integration of water leakage management, digitalization, and intelligent management approaches. Some specific new leakage management methods and their effects are introduced by examples of the application of Internet of Things (IoT) technology in leak detection and pressure transient management in the pipeline network
2023, 41(11): 54-58,63.
doi: 10.13205/j.hjgc.202311011
Abstract:
From a sustainable development perspective, reducing the carbon emissions of municipal facilities is an important step towards the development of ecological civilization. Trenchless pipeline rehabilitation, which is energy-saving, environmentally friendly, and low-carbon, represents a major trend in the pipeline repairing industry. In this paper, based on a case of pipeline network repairment in Shehong City, Sichuan Province, carbon footprint tracking of the pipeline repair material production stage, material and equipment transportation stage, and construction stage was conducted. The results showed that the carbon emissions during the production stage were 11263.14 kg CO2e, while those during the transportation and construction stages were 134.78 kg CO2e and 539.12 kg CO2e, respectively, accounting for approximately 94.35%, 1.13%, and 4.52% of the total carbon emissions. Material production was found to be the largest carbon emissions stage, and thus it is the key to carbon emissions controlling in the CIPP process. Sensitivity analysis was conducted on the materials and energy used during the production. The resin was found to be the most sensitive, followed by non-woven fabric. Optimizing and controlling their usage will be important for reducing carbon emissions in cured-in-place rehabilitation of urban drainage pipeline.
From a sustainable development perspective, reducing the carbon emissions of municipal facilities is an important step towards the development of ecological civilization. Trenchless pipeline rehabilitation, which is energy-saving, environmentally friendly, and low-carbon, represents a major trend in the pipeline repairing industry. In this paper, based on a case of pipeline network repairment in Shehong City, Sichuan Province, carbon footprint tracking of the pipeline repair material production stage, material and equipment transportation stage, and construction stage was conducted. The results showed that the carbon emissions during the production stage were 11263.14 kg CO2e, while those during the transportation and construction stages were 134.78 kg CO2e and 539.12 kg CO2e, respectively, accounting for approximately 94.35%, 1.13%, and 4.52% of the total carbon emissions. Material production was found to be the largest carbon emissions stage, and thus it is the key to carbon emissions controlling in the CIPP process. Sensitivity analysis was conducted on the materials and energy used during the production. The resin was found to be the most sensitive, followed by non-woven fabric. Optimizing and controlling their usage will be important for reducing carbon emissions in cured-in-place rehabilitation of urban drainage pipeline.
2023, 41(11): 59-63.
doi: 10.13205/j.hjgc.202311010
Abstract:
The geological conditions along urban underground pipe galleries and water pipelines are complex, and the traditional manual inspection mode has low efficiency in inspecting underground water supply network, making it impossible to detect abnormal events, such as pipe gallery deformation and pipeline leakage, in real time. In this paper, by analyzing the application of distributed fiber optic sensing and video AI (artificial intelligence) in the unmanned inspection of an underground pipeline network of Hangzhou Water Group, the scenario architecture and construction effectiveness of this technology were elaborated, which has certain reference significance for the intelligent development of water inspection mode.
The geological conditions along urban underground pipe galleries and water pipelines are complex, and the traditional manual inspection mode has low efficiency in inspecting underground water supply network, making it impossible to detect abnormal events, such as pipe gallery deformation and pipeline leakage, in real time. In this paper, by analyzing the application of distributed fiber optic sensing and video AI (artificial intelligence) in the unmanned inspection of an underground pipeline network of Hangzhou Water Group, the scenario architecture and construction effectiveness of this technology were elaborated, which has certain reference significance for the intelligent development of water inspection mode.
2023, 41(11): 64-68.
doi: 10.13205/j.hjgc.202311012
Abstract:
Unsupervised learning with K-means clustering is used to identify pollution characteristics of urban drainage pumping outflow during wet weather. Indicators including pumping station asset property and behavior data are chosen and then profiled for over 200 pumping stations of Shanghai downtown area. It shows that these pumping stations are classified into 4 clusters including low-frequency high-concentration, high-frequency low-concentration, high-frequency high-pollution, and medium-frequency medium-pollution, and the last 2 clusters are of higher priority for pollution control measures. The method used to profile pumping stations shows reasonable results and is of great value for policymakers to deploy drainage quality improving and efficiency enhancing measures.
Unsupervised learning with K-means clustering is used to identify pollution characteristics of urban drainage pumping outflow during wet weather. Indicators including pumping station asset property and behavior data are chosen and then profiled for over 200 pumping stations of Shanghai downtown area. It shows that these pumping stations are classified into 4 clusters including low-frequency high-concentration, high-frequency low-concentration, high-frequency high-pollution, and medium-frequency medium-pollution, and the last 2 clusters are of higher priority for pollution control measures. The method used to profile pumping stations shows reasonable results and is of great value for policymakers to deploy drainage quality improving and efficiency enhancing measures.
2023, 41(11): 69-77.
doi: 10.13205/j.hjgc.202311013
Abstract:
When sewage is transported in municipal sewer pipes, a large amount of hydrogen sulfide (H2S) will be released. This toxic and harmful gas is easy to cause odor, poisoning, and pipeline corrosion. Using a reasonable prediction model to predict the generation of H2S in the pipeline can provide a basis for the subsequent adoption of relevant H2S control measures, and has important practical significance for the planning of the sewage pipeline network. In this paper, the main factors affecting the generation of H2S in the sewage pipeline are analyzed; H2S generation prediction models are classified into two types of traditional statistics and machine learning, and their research progress is summarized; the potential research hotspots and difficulties of H2S prediction model are explored to provide a reference for establishment of H2S prediction model of municipal sewage pipeline.
When sewage is transported in municipal sewer pipes, a large amount of hydrogen sulfide (H2S) will be released. This toxic and harmful gas is easy to cause odor, poisoning, and pipeline corrosion. Using a reasonable prediction model to predict the generation of H2S in the pipeline can provide a basis for the subsequent adoption of relevant H2S control measures, and has important practical significance for the planning of the sewage pipeline network. In this paper, the main factors affecting the generation of H2S in the sewage pipeline are analyzed; H2S generation prediction models are classified into two types of traditional statistics and machine learning, and their research progress is summarized; the potential research hotspots and difficulties of H2S prediction model are explored to provide a reference for establishment of H2S prediction model of municipal sewage pipeline.
2023, 41(11): 78-83,122.
doi: 10.13205/j.hjgc.202311014
Abstract:
All kinds of pollutants are inevitably produced in the production process of industrial and mining enterprises, among which the discharge of water pollutants has been always an important work of monitoring and prevention. The traditional monitoring methods adopted by current industrial and mining enterprises, such as video or online equipment monitoring, are often weak in adaptability to the randomness, contingency, and uncertainty of sudden water pollution accidents, and have problems such as low efficiency, high cost, and poor accuracy. Combined with the time/space continuum image information self-check method to analyze the water image online, a universal water pollution monitoring method was proposed, and a dynamic water pollution monitoring system based on intelligent vision was developed, to realize the efficient and accurate qualitative judgment of the pollution state. After the industrial and mining enterprises put the system into use, the operation and maintenance were simple. Compared with the traditional manual video pollution monitoring method, the pollution identification accuracy was increased by 13%, the effective recognition rate was more than 99%, the average pollution identification time was reduced by 3 to 5 hours, the rapid response of sudden water pollution accidents was realized, and the incidence of environmental protection accidents was greatly reduced. This method can effectively reduce the labor intensity of personnel, and save enterprise operating cost.
All kinds of pollutants are inevitably produced in the production process of industrial and mining enterprises, among which the discharge of water pollutants has been always an important work of monitoring and prevention. The traditional monitoring methods adopted by current industrial and mining enterprises, such as video or online equipment monitoring, are often weak in adaptability to the randomness, contingency, and uncertainty of sudden water pollution accidents, and have problems such as low efficiency, high cost, and poor accuracy. Combined with the time/space continuum image information self-check method to analyze the water image online, a universal water pollution monitoring method was proposed, and a dynamic water pollution monitoring system based on intelligent vision was developed, to realize the efficient and accurate qualitative judgment of the pollution state. After the industrial and mining enterprises put the system into use, the operation and maintenance were simple. Compared with the traditional manual video pollution monitoring method, the pollution identification accuracy was increased by 13%, the effective recognition rate was more than 99%, the average pollution identification time was reduced by 3 to 5 hours, the rapid response of sudden water pollution accidents was realized, and the incidence of environmental protection accidents was greatly reduced. This method can effectively reduce the labor intensity of personnel, and save enterprise operating cost.
2023, 41(11): 84-92,140.
doi: 10.13205/j.hjgc.202311015
Abstract:
Precise control is an effective way to solve the problems of high operating costs and substandard effluent quality of wastewater treatment plants, but due to the non-linear, time-varying, and time-lagging nature of the sewage treatment process, conventional control methods can hardly meet the demand. This study proposed a model predictive control method to achieve accurate dosing of chemicals in sewage treatment plants. The constructed model was based on the self-attention mechanism to extract valid information from the input sequence and to model the complex non-linear relationships between features, thus improving the prediction accuracy. Data from a denitrification filter at a wastewater treatment plant in Jiangsu Province were used for training and testing. Compared with CNN and LSTM, the results showed that the MER and MSE metrics of the self-attention model is the best for the prediction of effluent TN, COD and NH4+-N, achieving more accurate prediction. The predictive control model using a particle swarm optimization algorithm to calculate the dosage was applied to this wastewater treatment plant. The results showed that the effluent achieved more than 95% compliance for TN and the optimized dosage was 28.72% and 21.78% lower than the monthly average dosage of the sewage treatment plant respectively.
Precise control is an effective way to solve the problems of high operating costs and substandard effluent quality of wastewater treatment plants, but due to the non-linear, time-varying, and time-lagging nature of the sewage treatment process, conventional control methods can hardly meet the demand. This study proposed a model predictive control method to achieve accurate dosing of chemicals in sewage treatment plants. The constructed model was based on the self-attention mechanism to extract valid information from the input sequence and to model the complex non-linear relationships between features, thus improving the prediction accuracy. Data from a denitrification filter at a wastewater treatment plant in Jiangsu Province were used for training and testing. Compared with CNN and LSTM, the results showed that the MER and MSE metrics of the self-attention model is the best for the prediction of effluent TN, COD and NH4+-N, achieving more accurate prediction. The predictive control model using a particle swarm optimization algorithm to calculate the dosage was applied to this wastewater treatment plant. The results showed that the effluent achieved more than 95% compliance for TN and the optimized dosage was 28.72% and 21.78% lower than the monthly average dosage of the sewage treatment plant respectively.
2023, 41(11): 93-103,114.
doi: 10.13205/j.hjgc.202311016
Abstract:
In recent years, with the deepening research on micro/nanorobots, more and more researchers have found that self-actuated micro/nano robots have their unique advantages in sewage treatment. Self-actuated micro/nanorobots can effectively adsorb or degrade toxic chemicals in polluted water by using their tunable surface chemistry to generate large quantities of micro/nanobubbles through surface reactions and mixing liquids at microscopic scales. In particular, it has obvious advantages in cleaning sewage treatment in small pipes or cavities that are difficult to reach by traditional methods. This paper reviews the research progress of self-actuated micro/nanorobots in wastewater treatment in recent years. First, the preparation and driven mode of the self-actuated micro/nanorobot was introduced, and the applications of the self-actuated micro/nanorobot on monitoring of water environment and efficient sewage treatment were summarized, mainly including adsorption of heavy metal ions, decomposition of organic pollutants, directional transportation oil droplets and degradation of microplastic; the dependence of self-actuated micro/nanorobots on fuel materials and the limitations of practical environment applications were discussed. Combined with their advantages and disadvantages, the future development direction was further prospected and summarized. In short, with the continuous breakthroughs in relevant key technologies and the continuous research and development of new self-actuated micro-nanorobots, self-actuated micro-nanorobots will play an increasingly important role in environmental protection and other fields.
In recent years, with the deepening research on micro/nanorobots, more and more researchers have found that self-actuated micro/nano robots have their unique advantages in sewage treatment. Self-actuated micro/nanorobots can effectively adsorb or degrade toxic chemicals in polluted water by using their tunable surface chemistry to generate large quantities of micro/nanobubbles through surface reactions and mixing liquids at microscopic scales. In particular, it has obvious advantages in cleaning sewage treatment in small pipes or cavities that are difficult to reach by traditional methods. This paper reviews the research progress of self-actuated micro/nanorobots in wastewater treatment in recent years. First, the preparation and driven mode of the self-actuated micro/nanorobot was introduced, and the applications of the self-actuated micro/nanorobot on monitoring of water environment and efficient sewage treatment were summarized, mainly including adsorption of heavy metal ions, decomposition of organic pollutants, directional transportation oil droplets and degradation of microplastic; the dependence of self-actuated micro/nanorobots on fuel materials and the limitations of practical environment applications were discussed. Combined with their advantages and disadvantages, the future development direction was further prospected and summarized. In short, with the continuous breakthroughs in relevant key technologies and the continuous research and development of new self-actuated micro-nanorobots, self-actuated micro-nanorobots will play an increasingly important role in environmental protection and other fields.
2023, 41(11): 104-109.
doi: 10.13205/j.hjgc.202311017
Abstract:
With the vigorous development of the new generation of information technologies, the application of digital twin in various industries is also becoming increasingly deep. Faced with the problems of multiple management departments, large spatial scale, variable external environment, and difficulty in joint scheduling in watershed water environment management, this study focused on the comprehensive management projects of the Huangxiao River and Airport River water environment. Based on the five-dimensional digital twin model as the theoretical foundation, and new technologies such as model simulation prediction, BIM, Unreal Engine, etc., a digital twin platform for comprehensive management of the Huangxiao River and Jichang River water environment was established. This platform integrates key information such as weather status, water quality status, abnormal events, and scheduling instructions within the watershed, and constructs a three-level simulation system of "watershed-region-plant and station". It achieves integrated management of "source, plant, pipeline network, river, and lake", providing the managers with intelligent operation and maintenance, predictive warning, dynamic scheduling, and other application values, and achieving real-time and effective supervision and scientific decision-making assistance in water management. It can provide experience and reference for future smart water construction.
With the vigorous development of the new generation of information technologies, the application of digital twin in various industries is also becoming increasingly deep. Faced with the problems of multiple management departments, large spatial scale, variable external environment, and difficulty in joint scheduling in watershed water environment management, this study focused on the comprehensive management projects of the Huangxiao River and Airport River water environment. Based on the five-dimensional digital twin model as the theoretical foundation, and new technologies such as model simulation prediction, BIM, Unreal Engine, etc., a digital twin platform for comprehensive management of the Huangxiao River and Jichang River water environment was established. This platform integrates key information such as weather status, water quality status, abnormal events, and scheduling instructions within the watershed, and constructs a three-level simulation system of "watershed-region-plant and station". It achieves integrated management of "source, plant, pipeline network, river, and lake", providing the managers with intelligent operation and maintenance, predictive warning, dynamic scheduling, and other application values, and achieving real-time and effective supervision and scientific decision-making assistance in water management. It can provide experience and reference for future smart water construction.
2023, 41(11): 110-114.
doi: 10.13205/j.hjgc.202311018
Abstract:
The construction of sponge cities is one of the development directions for urban rainwater and flood management in China at present. Solidly promoting the construction of sponge cities is a powerful guarantee for enhancing urban flood control and drainage capabilities. As one of the first pilot cities for the construction of sponge cities in China, Guangzhou adopts the technical concept of coordinating upstream, midstream, and downstream functional areas, integrating large, medium, and small sponge systems, and enhancing the integration of gray, green, and blue facilities. It systematically promotes the construction of sponge cities with the main means of treating wastewater and rainwater together and the concept of "+sponge". This article summarizes the practical experience and effectiveness of drainage control in the central urban area of Guangzhou, and explores smart drainage control from a new perspective of sewage and flood control, consolidating the effectiveness of water control, in order to provide reference for further smart sponge construction.
The construction of sponge cities is one of the development directions for urban rainwater and flood management in China at present. Solidly promoting the construction of sponge cities is a powerful guarantee for enhancing urban flood control and drainage capabilities. As one of the first pilot cities for the construction of sponge cities in China, Guangzhou adopts the technical concept of coordinating upstream, midstream, and downstream functional areas, integrating large, medium, and small sponge systems, and enhancing the integration of gray, green, and blue facilities. It systematically promotes the construction of sponge cities with the main means of treating wastewater and rainwater together and the concept of "+sponge". This article summarizes the practical experience and effectiveness of drainage control in the central urban area of Guangzhou, and explores smart drainage control from a new perspective of sewage and flood control, consolidating the effectiveness of water control, in order to provide reference for further smart sponge construction.
2023, 41(11): 115-122.
doi: 10.13205/j.hjgc.202311019
Abstract:
According to the demand for production scheduling and operation management of Wuhan Urban Drainage Development Co., Ltd., this paper puts forward the idea of building a smart drainage data center, and builds a unified, intelligent, integrated, convenient, multi-dimensional and safe intelligent drainage comprehensive management platform to realize the integration and sharing of data resources between the company and its departments at all levels, so as to realize the integrated scheduling between the sewage plants, pump stations and pipe networks, one-stop management of coordinating rain and sewage, and effectively improve the overall information level of the company. This study explores a new model of urban drainage technology and management.
According to the demand for production scheduling and operation management of Wuhan Urban Drainage Development Co., Ltd., this paper puts forward the idea of building a smart drainage data center, and builds a unified, intelligent, integrated, convenient, multi-dimensional and safe intelligent drainage comprehensive management platform to realize the integration and sharing of data resources between the company and its departments at all levels, so as to realize the integrated scheduling between the sewage plants, pump stations and pipe networks, one-stop management of coordinating rain and sewage, and effectively improve the overall information level of the company. This study explores a new model of urban drainage technology and management.
2023, 41(11): 123-133.
doi: 10.13205/j.hjgc.202311020
Abstract:
Taking Changzhou Urban Drainage Limited Company's data asset management system as a case, this research explored the integration and development model of data and physical business. It proposed a construction approach for the data asset management system, emphasizing coordinated planning, standardized guidance, deconstruction and restoration, and deepened application. This aims to explore the architecture of data asset systems in the water industry and feasible construction pathways. Through the practice of data asset system construction, Changzhou Urban Drainage has achieved systematic management of enterprise data assets and operationalization of data business, effectively enhancing the quality and efficiency of its operations and public services. In addition, theoretical frameworks, architectures, and methods for the elementization and assetization of data in the water industry were developed, providing reference solutions for promoting the digital transformation of the water industry and harnessing the value of data production factors.
Taking Changzhou Urban Drainage Limited Company's data asset management system as a case, this research explored the integration and development model of data and physical business. It proposed a construction approach for the data asset management system, emphasizing coordinated planning, standardized guidance, deconstruction and restoration, and deepened application. This aims to explore the architecture of data asset systems in the water industry and feasible construction pathways. Through the practice of data asset system construction, Changzhou Urban Drainage has achieved systematic management of enterprise data assets and operationalization of data business, effectively enhancing the quality and efficiency of its operations and public services. In addition, theoretical frameworks, architectures, and methods for the elementization and assetization of data in the water industry were developed, providing reference solutions for promoting the digital transformation of the water industry and harnessing the value of data production factors.
2023, 41(11): 134-140.
doi: 10.13205/j.hjgc.202311021
Abstract:
Drainage and water environment digitization is a crucial tool for achieving the quality and efficiency of drainage systems and enhancing water environments. Take the S River Bay watershed in a southern city as the case, we analyzed the key factors that trigger the sewage overflow pollution. We proposed a framework for the digital management of drainage-water environments and developed a digital solution concept encompassing basin-wide online monitoring, chain-wide closed-loop control, scene-wide intelligent analysis, joint dispatching of all elements, and system-wide supervision. Leveraging an informatization platform combined with spatial big data, Internet of Things (IoT), machine learning, and other emerging technologies, this research focused on addressing drainage issues remediation, intelligent identification of abnormal liquid level events, long-term diagnosis and treatment of small watersheds, joint scheduling of sewage operations, and "one network unified management" digital application scenarios for water environments. The results are promising and expected to provide valuable insights for the similar areas.
Drainage and water environment digitization is a crucial tool for achieving the quality and efficiency of drainage systems and enhancing water environments. Take the S River Bay watershed in a southern city as the case, we analyzed the key factors that trigger the sewage overflow pollution. We proposed a framework for the digital management of drainage-water environments and developed a digital solution concept encompassing basin-wide online monitoring, chain-wide closed-loop control, scene-wide intelligent analysis, joint dispatching of all elements, and system-wide supervision. Leveraging an informatization platform combined with spatial big data, Internet of Things (IoT), machine learning, and other emerging technologies, this research focused on addressing drainage issues remediation, intelligent identification of abnormal liquid level events, long-term diagnosis and treatment of small watersheds, joint scheduling of sewage operations, and "one network unified management" digital application scenarios for water environments. The results are promising and expected to provide valuable insights for the similar areas.
2023, 41(11): 141-147.
doi: 10.13205/j.hjgc.202311022
Abstract:
In the context of vigorously promoting the reform and innovation of the digital economy and digital technology during the "14th Five-Year Plan" period, the role of online modeling in identifying the hidden problems in the digital transformation of water supply business, improving the accuracy of business management, and enhancing the degree of perfection of digital information is explored with respect to the digital transformation of water supply business in the development of smart water services. Combined with actual engineering problems faced in water supply networks such as topological errors, pipe blockage, leakage, equipment abnormalities, and unknown valve conditions, we illustrated the role of the online model in identifying blockages and interruptions in facilities, equipment, business systems, management systems, and so on, and discussed the role of online models in promoting the digital transformation of water supply enterprises.
In the context of vigorously promoting the reform and innovation of the digital economy and digital technology during the "14th Five-Year Plan" period, the role of online modeling in identifying the hidden problems in the digital transformation of water supply business, improving the accuracy of business management, and enhancing the degree of perfection of digital information is explored with respect to the digital transformation of water supply business in the development of smart water services. Combined with actual engineering problems faced in water supply networks such as topological errors, pipe blockage, leakage, equipment abnormalities, and unknown valve conditions, we illustrated the role of the online model in identifying blockages and interruptions in facilities, equipment, business systems, management systems, and so on, and discussed the role of online models in promoting the digital transformation of water supply enterprises.
2023, 41(11): 148-153.
doi: 10.13205/j.hjgc.202311023
Abstract:
Due to the special construction process, difficult safety control, and high requirements for the effluent quality of underground sewage plants in high-density urban built-up areas, higher requirements was forward for the operation and management of these sewage plants. Through the application of information technology such as BIM technology, wireless pulse UWB positioning technology, precise dosing, and precise aeration, refined management of sewage plants was achieved, ensuring that the treated water quality meets the standards and achieves low-carbon operation. It is also an exploration of new models of digital operation management.
Due to the special construction process, difficult safety control, and high requirements for the effluent quality of underground sewage plants in high-density urban built-up areas, higher requirements was forward for the operation and management of these sewage plants. Through the application of information technology such as BIM technology, wireless pulse UWB positioning technology, precise dosing, and precise aeration, refined management of sewage plants was achieved, ensuring that the treated water quality meets the standards and achieves low-carbon operation. It is also an exploration of new models of digital operation management.
2023, 41(11): 154-159.
doi: 10.13205/j.hjgc.202311024
Abstract:
Water network optimization is an important method to solve the water shortage and pollution problems of industrial parks and improve the ability of water saving and emission reduction of industrial production. In recent years, the attention on carbon emission has brought new opportunites and challenges to the water network optimization under the background of the goal of "carbon peak & carbon neutrality". A water network optimization model under low-carbon constraints considering the constraints of water balance, supply and demand balance, available water supply, non-negative numbers, and carbon-water relation index was constructed and solved using genetic algorithms and ideal point methods. The objectives of the model were to minimize freshwater consumption, carbon emissions, and water treatment costs. The results showed that the water network optimization scheme under low-carbon constraints was expected to reduce fresh water consumption by 51% and carbon emissions by 65% in the Yancheng industrial park, focused on the electronic information industry. Measures for water saving and carbon reduction of the water network in industrial parks include multi-stage treatment-multi-stage reuse, optimization of process flow, optimization of pump operation, and chemical dosing. This research can provide support for the study of water saving, pollution, and carbon reduction in urban industrial parks.
Water network optimization is an important method to solve the water shortage and pollution problems of industrial parks and improve the ability of water saving and emission reduction of industrial production. In recent years, the attention on carbon emission has brought new opportunites and challenges to the water network optimization under the background of the goal of "carbon peak & carbon neutrality". A water network optimization model under low-carbon constraints considering the constraints of water balance, supply and demand balance, available water supply, non-negative numbers, and carbon-water relation index was constructed and solved using genetic algorithms and ideal point methods. The objectives of the model were to minimize freshwater consumption, carbon emissions, and water treatment costs. The results showed that the water network optimization scheme under low-carbon constraints was expected to reduce fresh water consumption by 51% and carbon emissions by 65% in the Yancheng industrial park, focused on the electronic information industry. Measures for water saving and carbon reduction of the water network in industrial parks include multi-stage treatment-multi-stage reuse, optimization of process flow, optimization of pump operation, and chemical dosing. This research can provide support for the study of water saving, pollution, and carbon reduction in urban industrial parks.
2023, 41(11): 160-164.
doi: 10.13205/j.hjgc.202311025
Abstract:
Urban rivers are the carriers of the urban water ecological environment. Due to the increasing expansion of urban areas, the ecological impact of human activities on rivers is gradually increasing. A large number of urban rivers are facing problems, such as water pollution, ecological imbalance, reduced river flow capacity, and river sedimentation. This paper took the Qianshan River Basin in Zhuhai city as an example, and designed four sets of optimization scheduling plans to meet the need for basin optimization scheduling. By constructing a joint regulation model for water quantity and quality in the Qianshan River Basin, the scheduling effectiveness of the four optimization scheduling plans was analyzed. The results showed that the optimal scheduling effect is to build new water gates in the Qianshan River and Zhizhouchong River, which can isolate the Tanzhou water system from the Zhuhai water system. Tanzhou water system will become completely closed after the closure of the water gate and not be affected by salt tides. A unidirectional flow pattern will be formed in the Zhuhai water system, with inflow by Guangchang and Hongwan water gates, and drainage by Shijiaozui water gate on the Qianshan River.
Urban rivers are the carriers of the urban water ecological environment. Due to the increasing expansion of urban areas, the ecological impact of human activities on rivers is gradually increasing. A large number of urban rivers are facing problems, such as water pollution, ecological imbalance, reduced river flow capacity, and river sedimentation. This paper took the Qianshan River Basin in Zhuhai city as an example, and designed four sets of optimization scheduling plans to meet the need for basin optimization scheduling. By constructing a joint regulation model for water quantity and quality in the Qianshan River Basin, the scheduling effectiveness of the four optimization scheduling plans was analyzed. The results showed that the optimal scheduling effect is to build new water gates in the Qianshan River and Zhizhouchong River, which can isolate the Tanzhou water system from the Zhuhai water system. Tanzhou water system will become completely closed after the closure of the water gate and not be affected by salt tides. A unidirectional flow pattern will be formed in the Zhuhai water system, with inflow by Guangchang and Hongwan water gates, and drainage by Shijiaozui water gate on the Qianshan River.
2023, 41(11): 165-171.
doi: 10.13205/j.hjgc.202311026
Abstract:
The short-range precise aeration and intelligent control process model abandons the traditional control mode that relies on single DO data to control air volume. Anchoring ammonia nitrogen at the outlet of the biochemical tank, it developed a process model algorithm and a complete set of equipment for automatic data acquisition and intelligent control. In the application practice of a sewage treatment plant with a capacity of 12,000 tons per day in Shantou, the effluent index stably complied with the standard, and the target value of ammonia nitrogen concentration was controlled within 0.7 to 2.8 mg/L. Under the same condition, the aerobic energy consumption per unit of total reductive matters after the automatic operation was better, and the oxygen utilization efficiency was increased by about 11%. In the case of low intake reduction material, the low air volume interval can be automatically matched, and the average air volume can be saved by 18.85%.
The short-range precise aeration and intelligent control process model abandons the traditional control mode that relies on single DO data to control air volume. Anchoring ammonia nitrogen at the outlet of the biochemical tank, it developed a process model algorithm and a complete set of equipment for automatic data acquisition and intelligent control. In the application practice of a sewage treatment plant with a capacity of 12,000 tons per day in Shantou, the effluent index stably complied with the standard, and the target value of ammonia nitrogen concentration was controlled within 0.7 to 2.8 mg/L. Under the same condition, the aerobic energy consumption per unit of total reductive matters after the automatic operation was better, and the oxygen utilization efficiency was increased by about 11%. In the case of low intake reduction material, the low air volume interval can be automatically matched, and the average air volume can be saved by 18.85%.
