The Experts below are selected from a list of 267705 Experts worldwide ranked by ideXlab platform
Zaoxiao Zhang - One of the best experts on this subject based on the ideXlab platform.
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application and improvement of swarm intelligence optimization algorithm in gas Emission Source identification in atmosphere
Journal of Loss Prevention in The Process Industries, 2018Co-Authors: Wei Tan, Xiaoqiao Wang, Qingsheng Wang, Zaoxiao Zhang, Jianmin Gao, Qunfeng Zeng, Fengshe Xia, Xingmin ShiAbstract:Abstract Hazardous gas Emissions could cause serious consequences for ecology, environment, human life and even society. Thus gas Emission Source term identification is crucial for emergency response and safety management. Based on experimental data, swarm intelligent optimization (SIO) algorithms including particle swarm optimization (PSO), ant colony optimization algorithm (ACO) and firefly algorithm (FA), are compared to identify the gas Emission Source parameters including Source strength and location parameters. The results show that all three SIO methods used in this work have similar performances in terms of Source parameter estimation, and all of them depend slightly on initial range set for individuals in the population. However, PSO method is superior in computational efficiency compared with ACO and FA methods. The convergence rate of FA is faster than that of ACO. PSO method can obtain satisfied estimation results under different boundary constraints, while the estimation results of FA and ACO will become unrealistic under too wide boundary constraints. The impact of atmospheric conditions on estimated results is also discussed. The results under extreme atmospheric conditions are worse than that in other conditions. Finally, SIO method coupled with a new model, correlated matching of concentration distribution (CMCD) model, is applied to the Source location estimation. Test results prove that SIO-CMCD model can obtain a satisfied estimation as well as greatly enhanced computational efficiency when only location parameters are required to be determined. Hence, SIO is a useful tool to estimate Emission Source term for the storage and transportation process of hazardous gas or volatile materials.
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location of contaminant Emission Source in atmosphere based on optimal correlated matching of concentration distribution
Process Safety and Environmental Protection, 2018Co-Authors: Qingsheng Wang, Zaoxiao Zhang, Xiaoqiao WangAbstract:Abstract Source location is crucial to manage contaminant Emissions in atmosphere, In order to determine the Source location without dependence on the absolute measurement data, a method based on optimal correlated matching of concentration distribution (OCMCD) was proposed. First, the estimation efficiency, accuracy and dependence on Source strength of OCMCD were compared with the common method which estimates multiple parameters of the Source term simultaneously. The results show that the method of OCMCD performs better than the common multiple parameters estimation method based on the mean errors between prediction and measurement in both estimation accuracy and efficiency. The test results with different sets of Source strength manifest that OCMCD relies minimally on the Source strength Then, a wind direction correction parameter and a weighted term of normalization concentration error were introduced into the model to compensate some missed information and improve the location results. The influence of data noises on the estimation accuracy of OCMCD method was also verified by adding extra manual noises on the measurement data. Then, the dependence of estimation performance with OCMCD method on atmosphere conditions were investigated statistically with experiment release cases. The results showed that Source location was identified well in most of cases. Finally, OCMCD method was extended to determine the Source location during the Source trace process with a mobile sensor. The test results with a simulation scenario based on Zigzag search strategy demonstrate that the Source location determined by OCMCD Source criterion is much closer to the real Source position than that determined by the criterion of the maximum concentration. Therefore, the results have proven the feasibility and superiority of OCMCD proposed in this paper to estimate Source location in cases of both static sensor distribution and mobile sensors. OCMCD will be a potentially useful method to identify Emission Source location in atmosphere.
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gas Emission Source term estimation with 1 step nonlinear partial swarm optimization tikhonov regularization hybrid method
Chinese Journal of Chemical Engineering, 2017Co-Authors: Wei Tan, Zaoxiao ZhangAbstract:Abstract Source term identification is very important for the contaminant gas Emission event. Thus, it is necessary to study the Source parameter estimation method with high computation efficiency, high estimation accuracy and reasonable confidence interval. Tikhonov regularization method is a potential good tool to identify the Source parameters. However, it is invalid for nonlinear inverse problem like gas Emission process. 2-step nonlinear and linear PSO (partial swarm optimization)–Tikhonov regularization method proposed previously have estimated the Emission Source parameters successfully. But there are still some problems in computation efficiency and confidence interval. Hence, a new 1-step nonlinear method combined Tikhonov regularization and PSO algorithm with nonlinear forward dispersion model was proposed. First, the method was tested with simulation and experiment cases. The test results showed that 1-step nonlinear hybrid method is able to estimate multiple Source parameters with reasonable confidence interval. Then, the estimation performances of different methods were compared with different cases. The estimation values with 1-step nonlinear method were close to that with 2-step nonlinear and linear PSO–Tikhonov regularization method. 1-step nonlinear method even performs better than other two methods in some cases, especially for Source strength and downwind distance estimation. Compared with 2-step nonlinear method, 1-step method has higher computation efficiency. On the other hand, the confidence intervals with the method proposed in this paper seem more reasonable than that with other two methods. Finally, single PSO algorithm was compared with 1-step nonlinear PSO–Tikhonov hybrid regularization method. The results showed that the skill scores of 1-step nonlinear hybrid method to estimate Source parameters were close to that of single PSO method and even better in some cases. One more important property of 1-step nonlinear PSO–Tikhonov regularization method is its reasonable confidence interval, which is not obtained by single PSO algorithm. Therefore, 1-step nonlinear hybrid regularization method proposed in this paper is a potential good method to estimate contaminant gas Emission Source term.
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parameter identification for continuous point Emission Source based on tikhonov regularization method coupled with particle swarm optimization algorithm
Journal of Hazardous Materials, 2017Co-Authors: Wei Tan, Zaoxiao ZhangAbstract:Abstract In order to identify the parameters of hazardous gas Emission Source in atmosphere with less previous information and reliable probability estimation, a hybrid algorithm coupling Tikhonov regularization with particle swarm optimization (PSO) was proposed. When the Source location is known, the Source strength can be estimated successfully by common Tikhonov regularization method, but it is invalid when the information about both Source strength and location is absent. Therefore, a hybrid method combining linear Tikhonov regularization and PSO algorithm was designed. With this method, the nonlinear inverse dispersion model was transformed to a linear form under some assumptions, and the Source parameters including Source strength and location were identified simultaneously by linear Tikhonov-PSO regularization method. The regularization parameters were selected by L-curve method. The estimation results with different regularization matrixes showed that the confidence interval with high-order regularization matrix is narrower than that with zero-order regularization matrix. But the estimation results of different Source parameters are close to each other with different regularization matrixes. A nonlinear Tikhonov-PSO hybrid regularization was also designed with primary nonlinear dispersion model to estimate the Source parameters. The comparison results of simulation and experiment case showed that the linear Tikhonov–PSO method with transformed linear inverse model has higher computation efficiency than nonlinear Tikhonov-PSO method. The confidence intervals from linear Tikhonov-PSO are more reasonable than that from nonlinear method. The estimation results from linear Tikhonov-PSO method are similar to that from single PSO algorithm, and a reasonable confidence interval with some probability levels can be additionally given by Tikhonov-PSO method. Therefore, the presented linear Tikhonov-PSO regularization method is a good potential method for hazardous Emission Source parameters identification.
Wei Tan - One of the best experts on this subject based on the ideXlab platform.
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application and improvement of swarm intelligence optimization algorithm in gas Emission Source identification in atmosphere
Journal of Loss Prevention in The Process Industries, 2018Co-Authors: Wei Tan, Xiaoqiao Wang, Qingsheng Wang, Zaoxiao Zhang, Jianmin Gao, Qunfeng Zeng, Fengshe Xia, Xingmin ShiAbstract:Abstract Hazardous gas Emissions could cause serious consequences for ecology, environment, human life and even society. Thus gas Emission Source term identification is crucial for emergency response and safety management. Based on experimental data, swarm intelligent optimization (SIO) algorithms including particle swarm optimization (PSO), ant colony optimization algorithm (ACO) and firefly algorithm (FA), are compared to identify the gas Emission Source parameters including Source strength and location parameters. The results show that all three SIO methods used in this work have similar performances in terms of Source parameter estimation, and all of them depend slightly on initial range set for individuals in the population. However, PSO method is superior in computational efficiency compared with ACO and FA methods. The convergence rate of FA is faster than that of ACO. PSO method can obtain satisfied estimation results under different boundary constraints, while the estimation results of FA and ACO will become unrealistic under too wide boundary constraints. The impact of atmospheric conditions on estimated results is also discussed. The results under extreme atmospheric conditions are worse than that in other conditions. Finally, SIO method coupled with a new model, correlated matching of concentration distribution (CMCD) model, is applied to the Source location estimation. Test results prove that SIO-CMCD model can obtain a satisfied estimation as well as greatly enhanced computational efficiency when only location parameters are required to be determined. Hence, SIO is a useful tool to estimate Emission Source term for the storage and transportation process of hazardous gas or volatile materials.
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gas Emission Source term estimation with 1 step nonlinear partial swarm optimization tikhonov regularization hybrid method
Chinese Journal of Chemical Engineering, 2017Co-Authors: Wei Tan, Zaoxiao ZhangAbstract:Abstract Source term identification is very important for the contaminant gas Emission event. Thus, it is necessary to study the Source parameter estimation method with high computation efficiency, high estimation accuracy and reasonable confidence interval. Tikhonov regularization method is a potential good tool to identify the Source parameters. However, it is invalid for nonlinear inverse problem like gas Emission process. 2-step nonlinear and linear PSO (partial swarm optimization)–Tikhonov regularization method proposed previously have estimated the Emission Source parameters successfully. But there are still some problems in computation efficiency and confidence interval. Hence, a new 1-step nonlinear method combined Tikhonov regularization and PSO algorithm with nonlinear forward dispersion model was proposed. First, the method was tested with simulation and experiment cases. The test results showed that 1-step nonlinear hybrid method is able to estimate multiple Source parameters with reasonable confidence interval. Then, the estimation performances of different methods were compared with different cases. The estimation values with 1-step nonlinear method were close to that with 2-step nonlinear and linear PSO–Tikhonov regularization method. 1-step nonlinear method even performs better than other two methods in some cases, especially for Source strength and downwind distance estimation. Compared with 2-step nonlinear method, 1-step method has higher computation efficiency. On the other hand, the confidence intervals with the method proposed in this paper seem more reasonable than that with other two methods. Finally, single PSO algorithm was compared with 1-step nonlinear PSO–Tikhonov hybrid regularization method. The results showed that the skill scores of 1-step nonlinear hybrid method to estimate Source parameters were close to that of single PSO method and even better in some cases. One more important property of 1-step nonlinear PSO–Tikhonov regularization method is its reasonable confidence interval, which is not obtained by single PSO algorithm. Therefore, 1-step nonlinear hybrid regularization method proposed in this paper is a potential good method to estimate contaminant gas Emission Source term.
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parameter identification for continuous point Emission Source based on tikhonov regularization method coupled with particle swarm optimization algorithm
Journal of Hazardous Materials, 2017Co-Authors: Wei Tan, Zaoxiao ZhangAbstract:Abstract In order to identify the parameters of hazardous gas Emission Source in atmosphere with less previous information and reliable probability estimation, a hybrid algorithm coupling Tikhonov regularization with particle swarm optimization (PSO) was proposed. When the Source location is known, the Source strength can be estimated successfully by common Tikhonov regularization method, but it is invalid when the information about both Source strength and location is absent. Therefore, a hybrid method combining linear Tikhonov regularization and PSO algorithm was designed. With this method, the nonlinear inverse dispersion model was transformed to a linear form under some assumptions, and the Source parameters including Source strength and location were identified simultaneously by linear Tikhonov-PSO regularization method. The regularization parameters were selected by L-curve method. The estimation results with different regularization matrixes showed that the confidence interval with high-order regularization matrix is narrower than that with zero-order regularization matrix. But the estimation results of different Source parameters are close to each other with different regularization matrixes. A nonlinear Tikhonov-PSO hybrid regularization was also designed with primary nonlinear dispersion model to estimate the Source parameters. The comparison results of simulation and experiment case showed that the linear Tikhonov–PSO method with transformed linear inverse model has higher computation efficiency than nonlinear Tikhonov-PSO method. The confidence intervals from linear Tikhonov-PSO are more reasonable than that from nonlinear method. The estimation results from linear Tikhonov-PSO method are similar to that from single PSO algorithm, and a reasonable confidence interval with some probability levels can be additionally given by Tikhonov-PSO method. Therefore, the presented linear Tikhonov-PSO regularization method is a good potential method for hazardous Emission Source parameters identification.
P Chung - One of the best experts on this subject based on the ideXlab platform.
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Three-dimensional two-pion Emission Source at RHIC-PHENIX
Journal of Physics G: Nuclear and Particle Physics, 2008Co-Authors: P ChungAbstract:The PHENIX experiment at RHIC has acquired a huge data set of Au+Au events at √S NN = 200 GeV during the year-2004 run. This high statistics data set, coupled with a state-of-the-art analysis technique, allows for the first model-independent extraction of the three-dimensional Emission Source function for pion pairs at RHIC energies. This three-dimensional pion Emission Source function provides new insights into the nature of a long-range structure in the one-dimensional Source function previously reported by PHENIX at RHIC. The new results indicate that the pion Source function displays significant non-Gaussian tails in the direction of pion pair transverse momentum and the beam. Comparison of the Source function with the Therminator model allows extraction of the Source proper breakup time and proper Emission duration.
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Evidence for a long range structure in the pion Emission Source in Au+Au collisions at RHIC
Nuclear Physics A, 2006Co-Authors: P Chung, Hans-Åke Gustafsson, Eva Haslum, Anders Oskarsson, Ingvar Otterlund, Sarah Rosendahl, Evert Stenlund, Henrik TydesjöAbstract:The PHENIX experiment has recently acquired ∼1 billion minimum bias Au+Au events at s = 200 AGeV during the year-2004 run. This high statistics data set, coupled with a state-of-the-art analysis technique, allows for the extraction of 3D Emission Sources for various particle types. These 3D Sources lend fresh insight into the nature of a long-range Source previously reported by PHENIX. The new results indicate an anisotropic pion Emission Source in the pair center of mass system (PCMS) having an extended space-time extent oriented in the outward direction. The two-proton Emission Source from the same data set is essentially isotropic in the PCMS. These results provide a “window” for viewing the evolution dynamics of the high energy density nuclear matter created at RHIC.
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Evidence for a long range structure in the pion Emission Source in Au+Au collisions at RHIC
AIP Conference Proceedings, 2006Co-Authors: P ChungAbstract:The PHENIX experiment, has recently acquired $\sim$ 1 billion minimum bias Au+Au events at $\sqrt s = 200$GeV during the year-2004 run. This high statistics data set, coupled with a state-of-the-art analysis technique, allows for the extraction of 3D Emission Sources for various particle types. These 3D Sources lend fresh insight into the nature of a long-range Source previously reported by PHENIX. The new results indicate an anisotropic pion Emission Source in the pair c.m. having an extended space-time extent oriented in the outward direction. The two-proton Emission Source from the same data set is essentially isotropic the pair c.m. frame. These results provide a "window" for viewing the evolution dynamics of the high energy density nuclear matter created at RHIC.
Florent Houdellier - One of the best experts on this subject based on the ideXlab platform.
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High brightness ultrafast transmission electron microscope based on a laser-driven cold-field Emission Source: principle and applications
Adv.Phys.X, 2019Co-Authors: G.m. Caruso, Florent Houdellier, M. Kociak, S. Weber, A. ArbouetAbstract:We report on the development of an ultrafast Transmission Electron Microscope based on a laser-driven cold-field Emission Source. We first describe the instrument before reporting on numerical simulations of the laser-driven electron Emission. These simulations predict the temporal and spectral properties of the femtosecond electron pulses generated in our ultrafast electron Source. We then discuss the effects that contribute to the spatial, temporal and spectral broadening of these electron pulses during their propagation from the electron Source to the sample and finally to the detectors of the electron microscope. The spectro-temporal properties are then characterized in an electron/photon cross-correlation experiment based on the detection of electron energy gains. We finally illustrate the potential of this instrument for ultrafast electron holography and ultrafast electron diffraction.
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Development of a high brightness ultrafast Transmission Electron Microscope based on a laser-driven cold field Emission Source
Ultramicroscopy, 2018Co-Authors: Florent Houdellier, G.m. Caruso, Sébastien J. Weber, M. Kociak, A. ArbouetAbstract:We report on the development of an ultrafast Transmission Electron Microscope based on a cold field Emission Source which can operate in either DC or ultrafast mode. Electron Emission from a tungsten nanotip is triggered by femtosecond laser pulses which are tightly focused by optical components integrated inside a cold field Emission Source close to the cathode. The properties of the electron probe (brightness, angular current density, stability) are quantitatively determined. The measured brightness is the largest reported so far for UTEMs. Examples of imaging, diffraction and spectroscopy using ultrashort electron pulses are given. Finally, the potential of this instrument is illustrated by performing electron holography in the off-axis configuration using ultrashort electron pulses.
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200 keV cold field Emission Source using carbon cone nanotip: Application to scanning transmission electron microscopy
Ultramicroscopy, 2017Co-Authors: Shuichi Mamishin, Yudai Kubo, Robin Cours, Marc Monthioux, Florent HoudellierAbstract:We report the use of a pyrolytic carbon cone nanotip as field Emission cathode inside a modern 200 kV dedicated scanning transmission electron microscope. We show an unprecedented improvement in the probe current stability while maintaining all the fundamental properties of a cold field Emission Source such as a small angular current density together with a high brightness. We have also studied the influence of the low extraction voltage, as enabled by the nanosized apex of the cones, on the electron optics properties of the Source that prevent the formation of a virtual beam cross-over of the gun. We have addressed this resolution-limiting issue by coming up with a new electron optical Source design.
Alexis K H Lau - One of the best experts on this subject based on the ideXlab platform.
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long term trends of ambient particulate matter Emission Source contributions and the accountability of control strategies in hong kong over 1998 2008
Atmospheric Environment, 2013Co-Authors: Zibing Yuan, Varun Yadav, Jay R Turner, Peter K K Louie, Alexis K H LauAbstract:Abstract Despite extensive Emission control measures targeting motor vehicles and to a lesser extent other Sources, annual-average PM 10 mass concentrations in Hong Kong have remained relatively constant for the past several years and for some air quality metrics, such as the frequency of poor visibility days, conditions have degraded. The underlying drivers for these long-term trends were examined by performing Source apportionment on eleven years (1998–2008) of data for seven monitoring sites in the Hong Kong PM 10 chemical speciation network. Nine factors were resolved using Positive Matrix Factorization. These factors were assigned to Emission Source categories that were classified as local (operationally defined as within the Hong Kong Special Administrative Region) or non-local based on temporal and spatial patterns in the Source contribution estimates. This data-driven analysis provides strong evidence that local controls on motor vehicle Emissions have been effective in reducing motor vehicle-related ambient PM 10 burdens with annual-average contributions at neighborhood- and larger-scale monitoring stations decreasing by ∼6 μg m −3 over the eleven year period. However, this improvement has been offset by an increase in annual-average contributions from non-local contributions, especially secondary sulfate and nitrate, of ∼8 μg m −3 over the same time period. As a result, non-local Source contributions to urban-scale PM 10 have increased from 58% in 1998 to 70% in 2008. Most of the motor vehicle-related decrease and non-local Source driven increase occurred over the period 1998–2004 with more modest changes thereafter. Non-local contributions increased most dramatically for secondary sulfate and secondary nitrate factors and thus combustion-related control strategies, including but not limited to power plants, are needed for Sources located in the Pearl River Delta and more distant regions to improve air quality conditions in Hong Kong. PMF-resolved Source contribution estimates were also used to examine differential contributions of Emission Source categories during high PM episodes compared to study-average behavior. While contributions from all Source categories increased to some extent on high PM days, the increases were disproportionately high for the non-local Sources. Thus, controls on Emission Sources located outside the Hong Kong Special Administrative Region will be needed to effectively decrease the frequency and severity of high PM episodes.
