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Research on Cascading Fault Location of Chemical Material Networks Based on BFS-Time-Reversal Backpropagation Algorithm. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2022. [DOI: 10.1007/s13369-022-06967-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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Dong R, Wang Z, Liu R, Li H, Jia X, Wang F. Robustness analysis of chemical process systems based on complex network non‐linear load capacity model. CAN J CHEM ENG 2022. [DOI: 10.1002/cjce.24427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Ran Dong
- College of Chemical Engineering Qingdao University of Science and Technology Qingdao Shandong China
| | - Zheng Wang
- College of Chemical Engineering Qingdao University of Science and Technology Qingdao Shandong China
| | - Ruijie Liu
- College of Chemical Engineering Qingdao University of Science and Technology Qingdao Shandong China
| | - Huapeng Li
- College of Chemical Engineering Qingdao University of Science and Technology Qingdao Shandong China
| | - Xiaoping Jia
- College of Environment and Safety Engineering Qingdao University of Science and Technology Qingdao Shandong China
| | - Fang Wang
- College of Environment and Safety Engineering Qingdao University of Science and Technology Qingdao Shandong China
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Controllability robustness of heat exchanger network based on complex network theory. ASIA-PAC J CHEM ENG 2021. [DOI: 10.1002/apj.2711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Wu Y, Du D, Mao Z. Actuator fault detection for a two‐stage chemical reactor based on the functional observer approach. CAN J CHEM ENG 2021. [DOI: 10.1002/cjce.24198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Yu Wu
- Faculty of Automation Huaiyin Institute of Technology Huaian People's Republic of China
| | - Dongsheng Du
- Faculty of Automation Huaiyin Institute of Technology Huaian People's Republic of China
| | - Zehui Mao
- College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing People's Republic of China
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Functional Safety Concept to Support Hazard Assessment and Risk Management in Water-Supply Systems. ENERGIES 2021. [DOI: 10.3390/en14040947] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Within the frame of upgrading and modernisation of the Water Supply System (WSS), our work is focussing on the safety systems/devices implemented or that should be implemented in the WSS. The implementation of safety systems is supposed to reduce hazard occurrence and hazardous consequences in case of a WSS unsafe disruption. To assess this reduction, we preconise the use of the safety integrity levels standards. The implementation of the safety systems/devices is undertaken on the ground of the multi-barriers safeguard approach. The “Water Contamination Hazard” is considered in the paper. A case study is presented, assessed and conclusions are drawn. The methodology presented in the paper and the results of the case study assessment will contribute to the decision-making regarding the upgrading of the safety and the performance of the WSS.
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Abstract
This paper first presents the results of polling on the subject of potable water in crisis situations, with respondents from south-eastern Poland’s Subcarpathian region asked for their opinions on the level of nuisance associated with water supply interruptions and water quality, levels of consumption and water companies’ quality of service. Among the respondents 53% regard the quality of the water they receive as satisfactory, while a quarter see it as only average. However, respondents are relatively satisfied with the corporate response when supplies are interrupted, as methods and means of notification are judged effective by 60%. Continuing with work to assess possibilities for water companies to improve their performance in crisis situations, the present study generates an Analytical Hierarchy Process allowing recipients to determine importance criteria where quality of service is concerned. This could facilitate management by water companies, providing for centralised control and comparison that help secure services of appropriate quality. The process can also help protect different groups of recipients, as safety is evaluated through analysis of functioning, and of failures and losses.
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Abstract
The water-supply system is one of the basic and most important critical infrastructures. Water supply service disruption (water quality or quantity) may have serious consequences in modern societies. Water supply service is subject to various failure modes. Failure modes are specified by their degradation mechanisms, criticality, occurrence frequency and intensity. These failure modes have a random nature that impacts on the network disruption indicators, such as disruption frequency, network downtime, network repair time and network back-to-service time, i.e., the network resilience. This paper focuses on the water leakage failure mode. The water leakage failure mode assessment considers the unavoidable annual real water losses and the infrastructure leakage index recommended by the International Water Association’s Water Loss Task Force specialist group. Probabilistic statistical modelling was implemented to assess the seasonal index, the failure rates and the expectation value of the “mean time between failures.” The assessment is based on real operational data of the network. Specific attention is paid to the sensitivity of failures to seasonal variations. The presented methodology of the analysis of the water leakage failure mode is extendable to other failure modes and can help in developing new strategies in the management of the water-supply system in normal operation and crisis situations.
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Zhu J, Shi H, Song B, Tan S, Tao Y. Deep neural network based recursive feature learning for nonlinear dynamic process monitoring. CAN J CHEM ENG 2019. [DOI: 10.1002/cjce.23669] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- Jiazhen Zhu
- Key Laboratory of Advanced Control and Optimization for Chemical Processes of the Ministry of EducationEast China University of Science and Technology Shanghai P. R. China
| | - Hongbo Shi
- Key Laboratory of Advanced Control and Optimization for Chemical Processes of the Ministry of EducationEast China University of Science and Technology Shanghai P. R. China
| | - Bing Song
- Key Laboratory of Advanced Control and Optimization for Chemical Processes of the Ministry of EducationEast China University of Science and Technology Shanghai P. R. China
| | - Shuai Tan
- Key Laboratory of Advanced Control and Optimization for Chemical Processes of the Ministry of EducationEast China University of Science and Technology Shanghai P. R. China
| | - Yang Tao
- Key Laboratory of Advanced Control and Optimization for Chemical Processes of the Ministry of EducationEast China University of Science and Technology Shanghai P. R. China
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Geng Z, Chen N, Han Y, Ma B. An improved intelligent early warning method based on MWSPCA and its application in complex chemical processes. CAN J CHEM ENG 2019. [DOI: 10.1002/cjce.23674] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Zhiqiang Geng
- College of Information Science & TechnologyBeijing University of Chemical Technology Beijing China
- Engineering Research Center of Intelligent PSEMinistry of Education in China Beijing China
| | - Ning Chen
- College of Information Science & TechnologyBeijing University of Chemical Technology Beijing China
- Engineering Research Center of Intelligent PSEMinistry of Education in China Beijing China
| | - Yongming Han
- College of Information Science & TechnologyBeijing University of Chemical Technology Beijing China
- Engineering Research Center of Intelligent PSEMinistry of Education in China Beijing China
| | - Bo Ma
- Key Laboratory of Ministry of Education for Engine Health Monitoring and NetworkingBeijing University of Chemical Technology Beijing China
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