Changes in the regulatory requirements and the forthcoming Disinfectant/Disinfection By-Products （D/DBP） Rule will require that drinking water treatment facilities be operated to achieve maximum removals of particle...Changes in the regulatory requirements and the forthcoming Disinfectant/Disinfection By-Products （D/DBP） Rule will require that drinking water treatment facilities be operated to achieve maximum removals of particles and disinfectant tolerant microorganisms as well as natural organic matter （NOM）. For drinking water production, the use of membrane filtration processes such as microfiltration and ultrafiltration （MF/UF） alone to satisfy the turbidity, particle and microorganism removal a requirement of the surface water treatment regulation （SWTR） is not enough. MF/UF treatment processes can achieve only nominal （10 percent） removal of disinfection by-products （DBP） precursors （James, et al., 1995）. On the other hand, too fast fouling can make the filtration processes more difficult to carry on. To solve these problems, many authors have been interested in installing coagulation pretreatment before membrane filtration to improve membrane performance. However, previous studies reported conflicting results. Some supported the effectiveness of coagulation pretreatment, while others contended that coagulation aggravated membrane performance. This research aims to identify the effects of coagulation pretreatment on membrane filtration through a pilot study using PVDF membrane in combination with analyzing the rationale of coagulation. Another objective of this research was to evaluate the different impacts on membrane performance of using different membrane modules （the submerged module and pressured module）. The results showed that coagulation pretreatment greatly improved the membrane performance, extending the filtration time as well as reducing the permeated organic level, and that the submerged module is much more efficient than the pressured module.展开更多
We study the distributed Kalman filtering problem in relative sensing networks with rigorous analysis.The relative sensing network is modeled by an undirected graph while nodes in this network are running homogeneous ...We study the distributed Kalman filtering problem in relative sensing networks with rigorous analysis.The relative sensing network is modeled by an undirected graph while nodes in this network are running homogeneous dynamical models. The sufficient and necessary condition for the observability of the whole system is given with detailed proof. By local information and measurement communication, we design a novel distributed suboptimal estimator based on the Kalman filtering technique for comparison with a centralized optimal estimator. We present sufficient conditions for its convergence with respect to the topology of the network and the numerical solutions of n linear matrix inequality（LMI） equations combining system parameters. Finally, we perform several numerical simulations to verify the effectiveness of the given algorithms.展开更多
基金supported by National Natural Science Foundation of China(No.11171159)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD) of ChinaCNPq of Brazil
文摘Changes in the regulatory requirements and the forthcoming Disinfectant/Disinfection By-Products （D/DBP） Rule will require that drinking water treatment facilities be operated to achieve maximum removals of particles and disinfectant tolerant microorganisms as well as natural organic matter （NOM）. For drinking water production, the use of membrane filtration processes such as microfiltration and ultrafiltration （MF/UF） alone to satisfy the turbidity, particle and microorganism removal a requirement of the surface water treatment regulation （SWTR） is not enough. MF/UF treatment processes can achieve only nominal （10 percent） removal of disinfection by-products （DBP） precursors （James, et al., 1995）. On the other hand, too fast fouling can make the filtration processes more difficult to carry on. To solve these problems, many authors have been interested in installing coagulation pretreatment before membrane filtration to improve membrane performance. However, previous studies reported conflicting results. Some supported the effectiveness of coagulation pretreatment, while others contended that coagulation aggravated membrane performance. This research aims to identify the effects of coagulation pretreatment on membrane filtration through a pilot study using PVDF membrane in combination with analyzing the rationale of coagulation. Another objective of this research was to evaluate the different impacts on membrane performance of using different membrane modules （the submerged module and pressured module）. The results showed that coagulation pretreatment greatly improved the membrane performance, extending the filtration time as well as reducing the permeated organic level, and that the submerged module is much more efficient than the pressured module.
基金supported by the National Natural Science Foundation of China(No.61503335)the Key Laboratory of System Control and Information Processing,China(No.Scip201504)
文摘We study the distributed Kalman filtering problem in relative sensing networks with rigorous analysis.The relative sensing network is modeled by an undirected graph while nodes in this network are running homogeneous dynamical models. The sufficient and necessary condition for the observability of the whole system is given with detailed proof. By local information and measurement communication, we design a novel distributed suboptimal estimator based on the Kalman filtering technique for comparison with a centralized optimal estimator. We present sufficient conditions for its convergence with respect to the topology of the network and the numerical solutions of n linear matrix inequality（LMI） equations combining system parameters. Finally, we perform several numerical simulations to verify the effectiveness of the given algorithms.
