The Response Surface Methodology (RSM) has been applied to explore the thermal structure of the experimentally studied catalytic combustion of stabilized confined turbulent gaseous diffusion flames. The Pt/γAl2O3 and...The Response Surface Methodology (RSM) has been applied to explore the thermal structure of the experimentally studied catalytic combustion of stabilized confined turbulent gaseous diffusion flames. The Pt/γAl2O3 and Pd/γAl2O3 disc burners were situated in the combustion domain and the experiments were performed under both fuel-rich and fuel-lean conditions at a modified equivalence (fuel/air) ratio (ø) of 0.75 and 0.25 respectively. The thermal structure of these catalytic flames developed over the Pt and Pd disc burners were inspected via measuring the mean temperature profiles in the radial direction at different discrete axial locations along the flames. The RSM considers the effect of the two operating parameters explicitly (r), the radial distance from the center line of the flame, and (x), axial distance along the flame over the disc, on the measured temperature of the flames and finds the predicted maximum temperature and the corresponding process variables. Also the RSM has been employed to elucidate such effects in the three and two dimensions and displays the location of the predicted maximum temperature.展开更多
Modeling, predictive and generalization capabilities of response surface methodology (RSM) and artificial neural network (ANN) have been performed to assess the thermal structure of the experimentally studied cat...Modeling, predictive and generalization capabilities of response surface methodology (RSM) and artificial neural network (ANN) have been performed to assess the thermal structure of the experimentally studied catalytic combustion of stabilized confined turbulent gaseous diffusion flames. The Pt/<i>γ</i>Al<sub>2</sub>O<sub>3</sub> and Pd/<i>γ</i>Al<sub>2</sub>O<sub>3</sub> disc burners were located in the combustion domain and the experiments were accomplished under both fuel-rich and fuel-lean conditions at a modified equivalence (fuel/air) ratio (<i><span style="white-space:nowrap;"><span style="font-family:Verdana, Helvetica, Arial;white-space:normal;background-color:#FFFFFF;">ø</span></span></i>) of 0.75 and 0.25, respectively. The thermal structure of these catalytic flames developed over the Pt and Pd disc burners w<span style="white-space:normal;font-family:;" "="">as</span><span style="white-space:normal;font-family:;" "=""> scrutinized via measuring the mean temperature profiles in the radial direction at different discrete axial locations along with the flames. The RSM and ANN methods investigated the effect of the two operating parameters namely (<i>r</i>), the radial distance from the center line of the flame, and (<i>x</i>), axial distance along with the flame over the disc, on the measured temperature of the flames and predicted the corresponding temperatures beside predicting the maximum temperature and the corresponding input process variables. A three</span><span style="white-space:normal;font-family:;" "="">-</span><span style="white-space:normal;font-family:;" "="">layered Feed Forward Neural Network was developed in conjugation with the hyperbolic tangent sigmoid (tansig) transfer function and an optimized topology of 2:10:1 (input neurons:hidden neurons:output neurons). Also the ANN method has been exploited to illustrate </span><span style="white-space:normal;font-family:;" "="">the </span><span style="white-space:normal;font-family:;" "="">effects of coded <i>R</i> and <i>X</i> input variables on the response in the three and two dimensions and to locate the predicted maximum temperature. The results indicated the superiority of ANN in the prediction capability as the ranges of & F_Ratio are 0.9181</span><span style="white-space:normal;font-family:;" "=""> </span><span style="white-space:normal;font-family:;" "="">- 0.9809 & 634.5</span><span style="white-space:normal;font-family:;" "=""> </span><span style="white-space:normal;font-family:;" "="">- 3528.8 for RSM method compared to 0.9857</span><span style="white-space:normal;font-family:;" "=""> </span><span style="white-space:normal;font-family:;" "="">- 0.9951 & 7636.4</span><span style="white-space:normal;font-family:;" "=""> </span><span style="white-space:normal;font-family:;" "="">- 24</span><span style="white-space:normal;font-family:;" "="">,</span><span style="white-space:normal;font-family:;" "="">028.4 for ANN method beside lower values </span><span style="white-space:normal;font-family:;" "="">for error analysis terms.</span>展开更多
As a prominent contributor to air pollution,nitric oxide(NO)has emerged as a critical agent causing detrimental environmental and health ramifications.To mitigate emissions and facilitate downstream utilization,adsorp...As a prominent contributor to air pollution,nitric oxide(NO)has emerged as a critical agent causing detrimental environmental and health ramifications.To mitigate emissions and facilitate downstream utilization,adsorption-based techniques offer a compelling approach for direct NO capture from both stationary and mobile sources.In this study,a comprehensive exploration of NO capture under oxygen-lean and oxygenrich conditions was conducted,employing Ni ion-exchanged chabazite(CHA-type)zeolites as the adsorbents.Remarkably,Ni/Na-CHA zeolites,with Ni loadings ranging from 3 to 4 wt%,demonstrate remarkable dynamic uptake capacities and exhibit exceptional NO capture efficiencies(NO-to-Ni ratio)for both oxygen-lean(0.17-0.31 mmol/g,0.32-0.43 of NO/Ni)and oxygen-rich(1.64-1.18 mmol/g)under ambient conditions.An NH3 reduction methodology was designed for the regeneration of absorbents at a relatively low temperature of 673 K.Comprehensive insights into the NO_(x) adsorption mechanism were obtained through temperature-programmed desorption experiments,in situ Fourier transform infrared spectroscopy,and density functional theory calculations.It is unveiled that NO and NO_(2) exhibit propensity to coordinate with Ni^(2+) via N-terminal or O-terminal,yielding thermally stable complexes and metastable species,respectively,while the low-temperature desorption substances are generated in close proximity to Na^(+).This study not only offers micro-level perspectives but imparts crucial insights for the advancement of capture and reduction technologies utilizing precious-metal-free materials.展开更多
文摘The Response Surface Methodology (RSM) has been applied to explore the thermal structure of the experimentally studied catalytic combustion of stabilized confined turbulent gaseous diffusion flames. The Pt/γAl2O3 and Pd/γAl2O3 disc burners were situated in the combustion domain and the experiments were performed under both fuel-rich and fuel-lean conditions at a modified equivalence (fuel/air) ratio (ø) of 0.75 and 0.25 respectively. The thermal structure of these catalytic flames developed over the Pt and Pd disc burners were inspected via measuring the mean temperature profiles in the radial direction at different discrete axial locations along the flames. The RSM considers the effect of the two operating parameters explicitly (r), the radial distance from the center line of the flame, and (x), axial distance along the flame over the disc, on the measured temperature of the flames and finds the predicted maximum temperature and the corresponding process variables. Also the RSM has been employed to elucidate such effects in the three and two dimensions and displays the location of the predicted maximum temperature.
文摘Modeling, predictive and generalization capabilities of response surface methodology (RSM) and artificial neural network (ANN) have been performed to assess the thermal structure of the experimentally studied catalytic combustion of stabilized confined turbulent gaseous diffusion flames. The Pt/<i>γ</i>Al<sub>2</sub>O<sub>3</sub> and Pd/<i>γ</i>Al<sub>2</sub>O<sub>3</sub> disc burners were located in the combustion domain and the experiments were accomplished under both fuel-rich and fuel-lean conditions at a modified equivalence (fuel/air) ratio (<i><span style="white-space:nowrap;"><span style="font-family:Verdana, Helvetica, Arial;white-space:normal;background-color:#FFFFFF;">ø</span></span></i>) of 0.75 and 0.25, respectively. The thermal structure of these catalytic flames developed over the Pt and Pd disc burners w<span style="white-space:normal;font-family:;" "="">as</span><span style="white-space:normal;font-family:;" "=""> scrutinized via measuring the mean temperature profiles in the radial direction at different discrete axial locations along with the flames. The RSM and ANN methods investigated the effect of the two operating parameters namely (<i>r</i>), the radial distance from the center line of the flame, and (<i>x</i>), axial distance along with the flame over the disc, on the measured temperature of the flames and predicted the corresponding temperatures beside predicting the maximum temperature and the corresponding input process variables. A three</span><span style="white-space:normal;font-family:;" "="">-</span><span style="white-space:normal;font-family:;" "="">layered Feed Forward Neural Network was developed in conjugation with the hyperbolic tangent sigmoid (tansig) transfer function and an optimized topology of 2:10:1 (input neurons:hidden neurons:output neurons). Also the ANN method has been exploited to illustrate </span><span style="white-space:normal;font-family:;" "="">the </span><span style="white-space:normal;font-family:;" "="">effects of coded <i>R</i> and <i>X</i> input variables on the response in the three and two dimensions and to locate the predicted maximum temperature. The results indicated the superiority of ANN in the prediction capability as the ranges of & F_Ratio are 0.9181</span><span style="white-space:normal;font-family:;" "=""> </span><span style="white-space:normal;font-family:;" "="">- 0.9809 & 634.5</span><span style="white-space:normal;font-family:;" "=""> </span><span style="white-space:normal;font-family:;" "="">- 3528.8 for RSM method compared to 0.9857</span><span style="white-space:normal;font-family:;" "=""> </span><span style="white-space:normal;font-family:;" "="">- 0.9951 & 7636.4</span><span style="white-space:normal;font-family:;" "=""> </span><span style="white-space:normal;font-family:;" "="">- 24</span><span style="white-space:normal;font-family:;" "="">,</span><span style="white-space:normal;font-family:;" "="">028.4 for ANN method beside lower values </span><span style="white-space:normal;font-family:;" "="">for error analysis terms.</span>
基金supported by the National Natural Science Foundation of China(22302100,22025203,22121005)the Fundamental Research Funds for the Central Universities(Nankai University).
文摘As a prominent contributor to air pollution,nitric oxide(NO)has emerged as a critical agent causing detrimental environmental and health ramifications.To mitigate emissions and facilitate downstream utilization,adsorption-based techniques offer a compelling approach for direct NO capture from both stationary and mobile sources.In this study,a comprehensive exploration of NO capture under oxygen-lean and oxygenrich conditions was conducted,employing Ni ion-exchanged chabazite(CHA-type)zeolites as the adsorbents.Remarkably,Ni/Na-CHA zeolites,with Ni loadings ranging from 3 to 4 wt%,demonstrate remarkable dynamic uptake capacities and exhibit exceptional NO capture efficiencies(NO-to-Ni ratio)for both oxygen-lean(0.17-0.31 mmol/g,0.32-0.43 of NO/Ni)and oxygen-rich(1.64-1.18 mmol/g)under ambient conditions.An NH3 reduction methodology was designed for the regeneration of absorbents at a relatively low temperature of 673 K.Comprehensive insights into the NO_(x) adsorption mechanism were obtained through temperature-programmed desorption experiments,in situ Fourier transform infrared spectroscopy,and density functional theory calculations.It is unveiled that NO and NO_(2) exhibit propensity to coordinate with Ni^(2+) via N-terminal or O-terminal,yielding thermally stable complexes and metastable species,respectively,while the low-temperature desorption substances are generated in close proximity to Na^(+).This study not only offers micro-level perspectives but imparts crucial insights for the advancement of capture and reduction technologies utilizing precious-metal-free materials.
