γ-Al2O3 supported Ni-Mn bimetallic catalysts for CO2 reforming of methane were prepared by impregnation method. The reforming reactions were conducted at 500-700℃ and atmospheric pressure using CO2/CH4/N2 with feed ...γ-Al2O3 supported Ni-Mn bimetallic catalysts for CO2 reforming of methane were prepared by impregnation method. The reforming reactions were conducted at 500-700℃ and atmospheric pressure using CO2/CH4/N2 with feed ratio of 17/17/2, at total flow rate of 36 mL/min. The catalytic performance was assessed through CH4 and CO2 conversions, synthesis gas ratio （H2/CO） and long term stability. Catalytic activity and stability tests revealed that addition of Mn improved catalytic performance and led to higher stability of bimetallic catalysts which presented better coke suppression than monometallic catalyst. In this work, the optimum loading of Mn which exhibited the most stable performance and least coke deposition was 0.5wt%. The fresh and spent catalysts were characterized by various techniques such as Brunauer-Emmett-Teller, the temperature programmed desorption CO2- TPD, thermogravimetric analysis, X-ray diffraction, scanning electron microscope, EDX, and infrared spectroscopy.展开更多
In this paper,a novel design of the flower pollination algorithm is presented for model identification problems in nonlinear active noise control systems.The recently introduced flower pollination based heuristics is ...In this paper,a novel design of the flower pollination algorithm is presented for model identification problems in nonlinear active noise control systems.The recently introduced flower pollination based heuristics is implemented to minimize the mean squared error based merit/cost function representing the scenarios of active noise control system with linear/nonlinear and primary/secondary paths based on the sinusoidal signal,random and complex random signals as noise interferences.The flower pollination heuristics based active noise controllers are formulated through exploitation of nonlinear filtering with Volterra series.The comparative study on statistical observations in terms of accuracy,convergence and complexity measures demonstrates that the proposed meta-heuristic of flower pollination algorithm is reliable,accurate,stable as well as robust for active noise control system.The accuracy of the proposed nature inspired computing of flower pollination is in good agreement with the state of the art counterpart solvers based on variants of genetic algorithms,particle swarm optimization,backtracking search optimization algorithm,fireworks optimization algorithm along with their memetic combination with local search methodologies.Moreover,the central tendency and variation based statistical indices further validate the consistency and reliability of the proposed scheme mimic the mathematical model for the process of flower pollination systems.展开更多
In this study, hybrid computational frameworks are developed for active noise control（ANC） systems using an evolutionary computing technique based on genetic algorithms（GAs） and interior-point method（IPM）, follo...In this study, hybrid computational frameworks are developed for active noise control（ANC） systems using an evolutionary computing technique based on genetic algorithms（GAs） and interior-point method（IPM）, following an integrated approach, GA-IPM. Standard ANC systems are usually implemented with the filtered extended least mean square algorithm for optimization of coefficients for the linear finite-impulse response filter, but are likely to become trapped in local minima（LM）. This issue is addressed with the proposed GA-IPM computing approach which is considerably less prone to the LM problem. Also, there is no requirement to identify a secondary path for the ANC system used in the scheme. The design method is evaluated using an ANC model of a headset with sinusoidal, random, and complex random noise interferences under several scenarios based on linear and nonlinear primary and secondary paths. The accuracy and convergence of the proposed scheme are validated based on the results of statistical analysis of a large number of independent runs of the algorithm.展开更多
文摘γ-Al2O3 supported Ni-Mn bimetallic catalysts for CO2 reforming of methane were prepared by impregnation method. The reforming reactions were conducted at 500-700℃ and atmospheric pressure using CO2/CH4/N2 with feed ratio of 17/17/2, at total flow rate of 36 mL/min. The catalytic performance was assessed through CH4 and CO2 conversions, synthesis gas ratio （H2/CO） and long term stability. Catalytic activity and stability tests revealed that addition of Mn improved catalytic performance and led to higher stability of bimetallic catalysts which presented better coke suppression than monometallic catalyst. In this work, the optimum loading of Mn which exhibited the most stable performance and least coke deposition was 0.5wt%. The fresh and spent catalysts were characterized by various techniques such as Brunauer-Emmett-Teller, the temperature programmed desorption CO2- TPD, thermogravimetric analysis, X-ray diffraction, scanning electron microscope, EDX, and infrared spectroscopy.
基金supported by the National Natural Science Foundation of China under Grant Nos.51977153,51977161,51577046State Key Program of National Natural Science Foundation of China under Grant Nos.51637004+1 种基金National Key Research and Development Plan“important scientific instruments and equipment development”Grant No.2016YFF010220Equipment research project in advance Grant No.41402040301.
文摘In this paper,a novel design of the flower pollination algorithm is presented for model identification problems in nonlinear active noise control systems.The recently introduced flower pollination based heuristics is implemented to minimize the mean squared error based merit/cost function representing the scenarios of active noise control system with linear/nonlinear and primary/secondary paths based on the sinusoidal signal,random and complex random signals as noise interferences.The flower pollination heuristics based active noise controllers are formulated through exploitation of nonlinear filtering with Volterra series.The comparative study on statistical observations in terms of accuracy,convergence and complexity measures demonstrates that the proposed meta-heuristic of flower pollination algorithm is reliable,accurate,stable as well as robust for active noise control system.The accuracy of the proposed nature inspired computing of flower pollination is in good agreement with the state of the art counterpart solvers based on variants of genetic algorithms,particle swarm optimization,backtracking search optimization algorithm,fireworks optimization algorithm along with their memetic combination with local search methodologies.Moreover,the central tendency and variation based statistical indices further validate the consistency and reliability of the proposed scheme mimic the mathematical model for the process of flower pollination systems.
文摘In this study, hybrid computational frameworks are developed for active noise control（ANC） systems using an evolutionary computing technique based on genetic algorithms（GAs） and interior-point method（IPM）, following an integrated approach, GA-IPM. Standard ANC systems are usually implemented with the filtered extended least mean square algorithm for optimization of coefficients for the linear finite-impulse response filter, but are likely to become trapped in local minima（LM）. This issue is addressed with the proposed GA-IPM computing approach which is considerably less prone to the LM problem. Also, there is no requirement to identify a secondary path for the ANC system used in the scheme. The design method is evaluated using an ANC model of a headset with sinusoidal, random, and complex random noise interferences under several scenarios based on linear and nonlinear primary and secondary paths. The accuracy and convergence of the proposed scheme are validated based on the results of statistical analysis of a large number of independent runs of the algorithm.
