Modeling of unsteady aerodynamic loads at high angles of attack using a small amount of experimental or simulation data to construct predictive models for unknown states can greatly improve the efficiency of aircraft ...Modeling of unsteady aerodynamic loads at high angles of attack using a small amount of experimental or simulation data to construct predictive models for unknown states can greatly improve the efficiency of aircraft unsteady aerodynamic design and flight dynamics analysis.In this paper,aiming at the problems of poor generalization of traditional aerodynamic models and intelligent models,an intelligent aerodynamic modeling method based on gated neural units is proposed.The time memory characteristics of the gated neural unit is fully utilized,thus the nonlinear flow field characterization ability of the learning and training process is enhanced,and the generalization ability of the whole prediction model is improved.The prediction and verification of the model are carried out under the maneuvering flight condition of NACA0015 airfoil.The results show that the model has good adaptability.In the interpolation prediction,the maximum prediction error of the lift and drag coefficients and the moment coefficient does not exceed 10%,which can basically represent the variation characteristics of the entire flow field.In the construction of extrapolation models,the training model based on the strong nonlinear data has good accuracy for weak nonlinear prediction.Furthermore,the error is larger,even exceeding 20%,which indicates that the extrapolation and generalization capabilities need to be further optimized by integrating physical models.Compared with the conventional state space equation model,the proposed method can improve the extrapolation accuracy and efficiency by 78%and 60%,respectively,which demonstrates the applied potential of this method in aerodynamic modeling.展开更多
An experimental study of thermal de-NOx using NH3 as reductant in 02/C02 atmosphere with the effect of S02 and different additives was performed in a drop tube furnace. Results show that the optimum temperature win- d...An experimental study of thermal de-NOx using NH3 as reductant in 02/C02 atmosphere with the effect of S02 and different additives was performed in a drop tube furnace. Results show that the optimum temperature win- dow is 841-1184 ℃, and the optimum reaction temperature is about 900 ℃ with a de-NOx efficiency of 95.4%. A certain amount of S02 has an inhibiting effect on NO reduction. The effect of additives, including Na2C03, C2H5OH and FeCI3, on NO reduction by NH3 is also explored. The addition of Na2CO3 and FeCI3 is useful to widen the tem- perature window and shift the reaction to lower temperature for the efficiency is increased from 30.5% to 74.0% and 67.4% respectively at 800 ℃. Qualitatively, the modeling results using a detailed kinetic modeling mecha- nism represent well most of the process features. The effect of Na2CO3, C2H5OH and FeCI3 addition can be reproduced well by the Na2C03, C2H5OH and Fe（CO）5 sub-mechanism respectively. The reaction mechanism analysis shows that the effects of these additives on NO reduction are achieved mainly by promoting the produc- tion of OH radicals at lower temperature.展开更多
The PPNH （non-homogenous Poisson processes） are frequently used as models for events that come about randomly in a given time period, for example, failure times, time of accidents occurrences, etc. In this work, PPN...The PPNH （non-homogenous Poisson processes） are frequently used as models for events that come about randomly in a given time period, for example, failure times, time of accidents occurrences, etc. In this work, PPNH is used to model monthly maximum observations of urban ozone corresponding to a period of five years from the meteorological stations of Merced, Pedregal and Plateros, located in the metropolitan area of Mexico City. The interest data are the times in which the observations surpassed the permissible level of ozone of 0.11 ppm, settled by the Mexican Official Norm （NOM-020-SSA 1-1993） to preserve public health.展开更多
The aim of this work is the assessment of the behavior of the radiation over studied area at the different seasons of the year using mathematical model. To achieve this purpose, the dispersion factor has been calculat...The aim of this work is the assessment of the behavior of the radiation over studied area at the different seasons of the year using mathematical model. To achieve this purpose, the dispersion factor has been calculated. The calculated dispersion factor gives an indication about the behavior and the distribution of pollutants in the atmosphere. Since the used model requires specific measuring hourly metrological data over long periods of time at least one year such as wind speed, incoming solar, radiation and wind direction for studied area. Also terrain information and population distribution should be taken into consideration. The atmospheric parameters such as monthly wind rose, hourly stability classes and joint frequency have been determined using developed computer programs. The results of wind rose shown that the prevailing wind direction for studied area is northeast direction in winter. This situation give us a primary knowledge about months （months of winter） at which the studied area may be affected by the air coming from the east borders. The results of dispersion factor indicate that the sectors S, SSE and SE for the studying area are greatly exposed to air which may be polluted.展开更多
Sowing time of wheat in south eastern Australia varies from autumn to early winter, depending on the seasonal ＇break＇. Wheat yields are often reduced by frost damage at flowering time and by heat-and/or water-stress...Sowing time of wheat in south eastern Australia varies from autumn to early winter, depending on the seasonal ＇break＇. Wheat yields are often reduced by frost damage at flowering time and by heat-and/or water-stress during grain filling. Selecting suitable varieties for specific sowing times is a complex decision farmers make because these varietal phenology and climate risks have to be assessed together. In order to help farmers make decisions, they need tools that simulate and analyse agronomically-suitable sowing dates （ASSD） for a given variety of wheat. The hypothesis underlining this study is the integration of a wheat phenology model with historical climate data is an effective approach to modelling the ASSD of current varieties used in the wheat growing areas of Southern NSW. The parameters of the wheat phenology model were based on data from five years of field experimentation across 15 sites. Data from four sites were used to examine varietal suitability in relation to sowing time and its associated risks of frost and heat damage. The optimum ASSD for any variety at 72 locations across Southern NSW was investigated. The results showed that there were substantial spatial variations in the ASSD across the target region. ASSD for a late maturing wheat genotype （EGA Gregory） can range from early March to late April, while the earliest acceptable sowing date for an early maturing spring wheat genotype （H46） can range from early to late May. The wide range of spatial variation in the earliest and latest sowing dates, as well as the varied length of sowing opportunities, highlighted the importance of being able to apply a modelling approach which can integrate information on crop phenology with climate risk for a given location. This approach would allow better decision-making on suitable varieties and sowing dates in order to minimise the risk of frost and heat damage affecting crop yield.展开更多
This paper presents the estimation of Chinese emissions of HCFC-22 and CFC-11 in 2009 by an inverse modeling method based on in-situ measurement data from the Shangdianzi Global Atmosphere Watch (GAW) Regional Station...This paper presents the estimation of Chinese emissions of HCFC-22 and CFC-11 in 2009 by an inverse modeling method based on in-situ measurement data from the Shangdianzi Global Atmosphere Watch (GAW) Regional Station (SDZ) and atmospheric transport simulations. After inversion (a-posteriori) estimates of the Chinese emissions in 2009 increased by 6.6% for HCFC-22 from 91.7 (± 83.6) to 98.3 (± 47.4) kt/yr and by 22.5% for CFC-11 from 13 (±12.6) to 15.8 (±7.2) kt/yr compared to an a-priori emission. While the model simulation with a-priori emissions already captured the main features of the observed variability at the measurement site, the model performance (in terms of correlation and mean-square-error) improved using a-posteriori emissions. The inversion reduced the root-mean-square (RMS) error by 4% and 10% for HCFC-22 and CFC-11, respectively.展开更多
基金supported in part by the National Natural Science Foundation of China (No. 12202363)。
文摘Modeling of unsteady aerodynamic loads at high angles of attack using a small amount of experimental or simulation data to construct predictive models for unknown states can greatly improve the efficiency of aircraft unsteady aerodynamic design and flight dynamics analysis.In this paper,aiming at the problems of poor generalization of traditional aerodynamic models and intelligent models,an intelligent aerodynamic modeling method based on gated neural units is proposed.The time memory characteristics of the gated neural unit is fully utilized,thus the nonlinear flow field characterization ability of the learning and training process is enhanced,and the generalization ability of the whole prediction model is improved.The prediction and verification of the model are carried out under the maneuvering flight condition of NACA0015 airfoil.The results show that the model has good adaptability.In the interpolation prediction,the maximum prediction error of the lift and drag coefficients and the moment coefficient does not exceed 10%,which can basically represent the variation characteristics of the entire flow field.In the construction of extrapolation models,the training model based on the strong nonlinear data has good accuracy for weak nonlinear prediction.Furthermore,the error is larger,even exceeding 20%,which indicates that the extrapolation and generalization capabilities need to be further optimized by integrating physical models.Compared with the conventional state space equation model,the proposed method can improve the extrapolation accuracy and efficiency by 78%and 60%,respectively,which demonstrates the applied potential of this method in aerodynamic modeling.
基金Supported by the National Natural Science Foundation of China(51206096)
文摘An experimental study of thermal de-NOx using NH3 as reductant in 02/C02 atmosphere with the effect of S02 and different additives was performed in a drop tube furnace. Results show that the optimum temperature win- dow is 841-1184 ℃, and the optimum reaction temperature is about 900 ℃ with a de-NOx efficiency of 95.4%. A certain amount of S02 has an inhibiting effect on NO reduction. The effect of additives, including Na2C03, C2H5OH and FeCI3, on NO reduction by NH3 is also explored. The addition of Na2CO3 and FeCI3 is useful to widen the tem- perature window and shift the reaction to lower temperature for the efficiency is increased from 30.5% to 74.0% and 67.4% respectively at 800 ℃. Qualitatively, the modeling results using a detailed kinetic modeling mecha- nism represent well most of the process features. The effect of Na2CO3, C2H5OH and FeCI3 addition can be reproduced well by the Na2C03, C2H5OH and Fe（CO）5 sub-mechanism respectively. The reaction mechanism analysis shows that the effects of these additives on NO reduction are achieved mainly by promoting the produc- tion of OH radicals at lower temperature.
文摘The PPNH （non-homogenous Poisson processes） are frequently used as models for events that come about randomly in a given time period, for example, failure times, time of accidents occurrences, etc. In this work, PPNH is used to model monthly maximum observations of urban ozone corresponding to a period of five years from the meteorological stations of Merced, Pedregal and Plateros, located in the metropolitan area of Mexico City. The interest data are the times in which the observations surpassed the permissible level of ozone of 0.11 ppm, settled by the Mexican Official Norm （NOM-020-SSA 1-1993） to preserve public health.
文摘The aim of this work is the assessment of the behavior of the radiation over studied area at the different seasons of the year using mathematical model. To achieve this purpose, the dispersion factor has been calculated. The calculated dispersion factor gives an indication about the behavior and the distribution of pollutants in the atmosphere. Since the used model requires specific measuring hourly metrological data over long periods of time at least one year such as wind speed, incoming solar, radiation and wind direction for studied area. Also terrain information and population distribution should be taken into consideration. The atmospheric parameters such as monthly wind rose, hourly stability classes and joint frequency have been determined using developed computer programs. The results of wind rose shown that the prevailing wind direction for studied area is northeast direction in winter. This situation give us a primary knowledge about months （months of winter） at which the studied area may be affected by the air coming from the east borders. The results of dispersion factor indicate that the sectors S, SSE and SE for the studying area are greatly exposed to air which may be polluted.
文摘Sowing time of wheat in south eastern Australia varies from autumn to early winter, depending on the seasonal ＇break＇. Wheat yields are often reduced by frost damage at flowering time and by heat-and/or water-stress during grain filling. Selecting suitable varieties for specific sowing times is a complex decision farmers make because these varietal phenology and climate risks have to be assessed together. In order to help farmers make decisions, they need tools that simulate and analyse agronomically-suitable sowing dates （ASSD） for a given variety of wheat. The hypothesis underlining this study is the integration of a wheat phenology model with historical climate data is an effective approach to modelling the ASSD of current varieties used in the wheat growing areas of Southern NSW. The parameters of the wheat phenology model were based on data from five years of field experimentation across 15 sites. Data from four sites were used to examine varietal suitability in relation to sowing time and its associated risks of frost and heat damage. The optimum ASSD for any variety at 72 locations across Southern NSW was investigated. The results showed that there were substantial spatial variations in the ASSD across the target region. ASSD for a late maturing wheat genotype （EGA Gregory） can range from early March to late April, while the earliest acceptable sowing date for an early maturing spring wheat genotype （H46） can range from early to late May. The wide range of spatial variation in the earliest and latest sowing dates, as well as the varied length of sowing opportunities, highlighted the importance of being able to apply a modelling approach which can integrate information on crop phenology with climate risk for a given location. This approach would allow better decision-making on suitable varieties and sowing dates in order to minimise the risk of frost and heat damage affecting crop yield.
基金supported by the National Natural Science Foundation of China (41030107)Chinese Ministry of Science and Technology(2010CB950601)+2 种基金EUS & T Cooperative Project 2SMONGS&T Cooperation Project of the MOST and Eu (1015)CAMS Fundamental Research Funds-General Program (2010Y003)
文摘This paper presents the estimation of Chinese emissions of HCFC-22 and CFC-11 in 2009 by an inverse modeling method based on in-situ measurement data from the Shangdianzi Global Atmosphere Watch (GAW) Regional Station (SDZ) and atmospheric transport simulations. After inversion (a-posteriori) estimates of the Chinese emissions in 2009 increased by 6.6% for HCFC-22 from 91.7 (± 83.6) to 98.3 (± 47.4) kt/yr and by 22.5% for CFC-11 from 13 (±12.6) to 15.8 (±7.2) kt/yr compared to an a-priori emission. While the model simulation with a-priori emissions already captured the main features of the observed variability at the measurement site, the model performance (in terms of correlation and mean-square-error) improved using a-posteriori emissions. The inversion reduced the root-mean-square (RMS) error by 4% and 10% for HCFC-22 and CFC-11, respectively.
