Studies of atmospheric dispersion are essential to both the site selection of a nuclear power plant and the evaluation of the environmental impacts of nuclear operations. Atmospheric stability plays the most important...Studies of atmospheric dispersion are essential to both the site selection of a nuclear power plant and the evaluation of the environmental impacts of nuclear operations. Atmospheric stability plays the most important role in the dispersion of air pollutants. The focus of attention in the present study is the estimation of the degree of stability of the atmosphere for the north coast of Egypt to evaluate the ability of the atmosphere to disperse pollutants. A FORTRAN program （Appendix 1） is presented to determine atmospheric stability using the Pasquill-Tunner Method PTM, which defines the turbulent state of the atmosphere and also reflects upon the dispersion capabilities of the atmosphere at the site. This method used several meteorological factors such as wind speed, insulation, cloud cover height and type. Meteorological data from Matrouh stations in Egypt is applied for a simulated model. The total patterns of stability classification, both monthly and seasonal patterns, are determined, also the stability-wind rose and stability-wind summary are provided. Finally prediction of Iodine surface air concentration is reported as well as the annual effective dose for I- 131 as a case study.展开更多
The purpose of this study is to investigate the Classification of Synoptic Circulation Patterns for Fog in the Urumqi Airport in Xinjiang, China. By using relevant climate statistical method, the hourly ground observa...The purpose of this study is to investigate the Classification of Synoptic Circulation Patterns for Fog in the Urumqi Airport in Xinjiang, China. By using relevant climate statistical method, the hourly ground observation data and four times per day and NCEP/NCAR reanalysis data (1° × 1°) from 1985 to 2014 were analyzed. The results showed that: 1) The occurrence of fog significantly increased during 1985 and 2014;There are two stages of the airport fog in the 30 years, less-fog period (1985-2002) and more-fog period (2002-2014), the fog focused occurred in November to March of the following year, most in December and least in March;2) Based on Lamb-Jenkinson method, the dominant types of fog in Urumqi Airport are C, E, SE, W, A types (Among them, A, C, E, W, SE are the circulation types. C is Cyclone, A is Anti-cyclone, E is East, W is West, SE is Southeast), and the international distribution of each type is also different;3) The dominant types of persistence fog are A, C, E, SE types, A type appears in the afternoon to the nighttime, in the morning less frequent, on the other hand, C type is just the opposite;4) Atmospheric circulation characteristics for persistence fog profile can be divided into four series: A, C, E, SE series, and climatic characteristics in different series are different.展开更多
The vector vortex beam(VVB)has attracted significant attention due to its intrinsic diversity of information and has found great applications in both classical and quantum communications.However,a VVB is unavoidably a...The vector vortex beam(VVB)has attracted significant attention due to its intrinsic diversity of information and has found great applications in both classical and quantum communications.However,a VVB is unavoidably affected by atmospheric turbulence(AT)when it propagates through the free-space optical communication environment,which results in detection errors at the receiver.In this paper,we propose a VVB classification scheme to detect VVBs with continuously changing polarization states under AT,where a diffractive deep neural network(DDNN)is designed and trained to classify the intensity distribution of the input distorted VVBs,and the horizontal direction of polarization of the input distorted beam is adopted as the feature for the classification through the DDNN.The numerical simulations and experimental results demonstrate that the proposed scheme has high accuracy in classification tasks.The energy distribution percentage remains above 95%from weak to medium AT,and the classification accuracy can remain above 95%for various strengths of turbulence.It has a faster convergence and better accuracy than that based on a convolutional neural network.展开更多
Stability parameters (Monin-Obukhov length L, gradient Richardson number Ri and bulk Rischardson number Ri), which are applicable in urban environment, were discussed for ways of calculating classification standards. ...Stability parameters (Monin-Obukhov length L, gradient Richardson number Ri and bulk Rischardson number Ri), which are applicable in urban environment, were discussed for ways of calculating classification standards. Gradient observations from a 325-m meteorological tower in Beijing are used to categorize Rib based on three different standards of stability proposed by D. Golder, Irwin and Houghton. The results show that it is relatively reasonable for the region of Beijing to apply the classification standard by Irwin.展开更多
Reducing greenhouse gases (RHG) is going on actively in the international movement. In the field of architecture, RHG is an inevitable work. To establish a plan for RHG, firstly we need to reduce energy consumption. G...Reducing greenhouse gases (RHG) is going on actively in the international movement. In the field of architecture, RHG is an inevitable work. To establish a plan for RHG, firstly we need to reduce energy consumption. Greenhouse gas generated by energy consumption is the main cause of global warming. For this we should know that how much electricity consumption we use. The research targets of this study are commercial buildings with various businesses. Their electricity consumption was analyzed by business units rather than buildings. Each business was divided into 13 sectors according to industrial classification and electricity consumption was analyzed for each industry. For commercial buildings, the electricity consumption is done by the private sector and construction management is an autonomy system in private instead of an integrated management system. In this study, we classified and analyzed the electricity consumption characteristics according to collected data, analyzed the relationship between the electricity consumption with atmospheric temperature through SPSS, and developed an electricity prediction model.展开更多
Astronomical spectroscopy is crucial for exploring the physical properties,chemical composition,and kinematic behavior of celestial objects.With continuous advancements in observational technology,astronomical spectro...Astronomical spectroscopy is crucial for exploring the physical properties,chemical composition,and kinematic behavior of celestial objects.With continuous advancements in observational technology,astronomical spectroscopy faces the dual challenges of rapidly expanding data volumes and relatively lagging data processing capabilities.In this context,the rise of artificial intelligence technologies offers an innovative solution to address these challenges.This paper analyzes the latest developments in the application of machine learning for astronomical spectral data mining and discusses future research directions in AI-based spectral studies.However,the application of machine learning technologies presents several challenges.The high complexity of models often comes with insufficient interpretability,complicating scientific understanding.Moreover,the large-scale computational demands place higher requirements on hardware resources,leading to a significant increase in computational costs.AI-based astronomical spectroscopy research should advance in the following key directions.First,develop efficient data augmentation techniques to enhance model generalization capabilities.Second,explore more interpretable model designs to ensure the reliability and transparency of scientific conclusions.Third,optimize computational efficiency and reduce the threshold for deep-learning applications through collaborative innovations in algorithms and hardware.Furthermore,promoting the integration of cross-band data processing is essential to achieve seamless integration and comprehensive analysis of multi-source data,providing richer,multidimensional information to uncover the mysteries of the universe.展开更多
In this study, the classification scheme developed by Jenkinson and Collison （1977） based on a typing scheme of Lamb （1950） is applied to obtain circulation types from the mean sea-level pressure on a monthly basi...In this study, the classification scheme developed by Jenkinson and Collison （1977） based on a typing scheme of Lamb （1950） is applied to obtain circulation types from the mean sea-level pressure on a monthly basis. Monthly mean sea-level pressure data from 1951 to 2002 are used to derive six circulation indices and to provide a circulation catalogue with 27 circulation types. Five major types （N, NW, C, CSW, and SW） which occurred most frequently are analyzed to reveal their relationships with the temperature of Harbin on various time scales. Stepwise multiple regression is used to reconstruct temperature anomaly. The monthly mean rainfall of all types occurring and the composite maps of three major types （C, CSW, and SW） relevant to Harbin＇s precipitation are studied. The results show that the dominant types in winter are types N and NW. types C, CSW, and SW occur frequently in summer. Types N and NW favor a negative temperature anomaly and correspond to less rainfall, while types C, CSW, and SW often induce a positive temperature anomaly and correspond to more rainfall. Moreover, a successful statistical model can be established with only one of the six indices and large-scale mean temperature. Using the model, 77.3% of the total variance in the temperature anomaly between 1951 and 2002 can be reconstructed. Type C has a close relationship with total rainfall and type C precipitation plays a major role in determining the total rainfall of Harbin in recent years. This classification scheme is a statistical downscaling model and its relationships with temperature and precipitation can be used to forecast regional climate.展开更多
文摘Studies of atmospheric dispersion are essential to both the site selection of a nuclear power plant and the evaluation of the environmental impacts of nuclear operations. Atmospheric stability plays the most important role in the dispersion of air pollutants. The focus of attention in the present study is the estimation of the degree of stability of the atmosphere for the north coast of Egypt to evaluate the ability of the atmosphere to disperse pollutants. A FORTRAN program （Appendix 1） is presented to determine atmospheric stability using the Pasquill-Tunner Method PTM, which defines the turbulent state of the atmosphere and also reflects upon the dispersion capabilities of the atmosphere at the site. This method used several meteorological factors such as wind speed, insulation, cloud cover height and type. Meteorological data from Matrouh stations in Egypt is applied for a simulated model. The total patterns of stability classification, both monthly and seasonal patterns, are determined, also the stability-wind rose and stability-wind summary are provided. Finally prediction of Iodine surface air concentration is reported as well as the annual effective dose for I- 131 as a case study.
文摘The purpose of this study is to investigate the Classification of Synoptic Circulation Patterns for Fog in the Urumqi Airport in Xinjiang, China. By using relevant climate statistical method, the hourly ground observation data and four times per day and NCEP/NCAR reanalysis data (1° × 1°) from 1985 to 2014 were analyzed. The results showed that: 1) The occurrence of fog significantly increased during 1985 and 2014;There are two stages of the airport fog in the 30 years, less-fog period (1985-2002) and more-fog period (2002-2014), the fog focused occurred in November to March of the following year, most in December and least in March;2) Based on Lamb-Jenkinson method, the dominant types of fog in Urumqi Airport are C, E, SE, W, A types (Among them, A, C, E, W, SE are the circulation types. C is Cyclone, A is Anti-cyclone, E is East, W is West, SE is Southeast), and the international distribution of each type is also different;3) The dominant types of persistence fog are A, C, E, SE types, A type appears in the afternoon to the nighttime, in the morning less frequent, on the other hand, C type is just the opposite;4) Atmospheric circulation characteristics for persistence fog profile can be divided into four series: A, C, E, SE series, and climatic characteristics in different series are different.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.62375140 and 62001249)the Open Research Fund of National Laboratory of Solid State Microstructures(Grant No.M36055).
文摘The vector vortex beam(VVB)has attracted significant attention due to its intrinsic diversity of information and has found great applications in both classical and quantum communications.However,a VVB is unavoidably affected by atmospheric turbulence(AT)when it propagates through the free-space optical communication environment,which results in detection errors at the receiver.In this paper,we propose a VVB classification scheme to detect VVBs with continuously changing polarization states under AT,where a diffractive deep neural network(DDNN)is designed and trained to classify the intensity distribution of the input distorted VVBs,and the horizontal direction of polarization of the input distorted beam is adopted as the feature for the classification through the DDNN.The numerical simulations and experimental results demonstrate that the proposed scheme has high accuracy in classification tasks.The energy distribution percentage remains above 95%from weak to medium AT,and the classification accuracy can remain above 95%for various strengths of turbulence.It has a faster convergence and better accuracy than that based on a convolutional neural network.
基金Open Foundation by the Guangzhou Institute of Tropical and Marine Meteorology, CMA
文摘Stability parameters (Monin-Obukhov length L, gradient Richardson number Ri and bulk Rischardson number Ri), which are applicable in urban environment, were discussed for ways of calculating classification standards. Gradient observations from a 325-m meteorological tower in Beijing are used to categorize Rib based on three different standards of stability proposed by D. Golder, Irwin and Houghton. The results show that it is relatively reasonable for the region of Beijing to apply the classification standard by Irwin.
基金Funded by the National Research Foundation of Korea (MEST) (NRF-2011-0000868)
文摘Reducing greenhouse gases (RHG) is going on actively in the international movement. In the field of architecture, RHG is an inevitable work. To establish a plan for RHG, firstly we need to reduce energy consumption. Greenhouse gas generated by energy consumption is the main cause of global warming. For this we should know that how much electricity consumption we use. The research targets of this study are commercial buildings with various businesses. Their electricity consumption was analyzed by business units rather than buildings. Each business was divided into 13 sectors according to industrial classification and electricity consumption was analyzed for each industry. For commercial buildings, the electricity consumption is done by the private sector and construction management is an autonomy system in private instead of an integrated management system. In this study, we classified and analyzed the electricity consumption characteristics according to collected data, analyzed the relationship between the electricity consumption with atmospheric temperature through SPSS, and developed an electricity prediction model.
基金supported by the National Key R&D Program of China(2021YFC2203502 and 2022YFF0711502)the National Natural Science Foundation of China(NSFC)(12173077)+4 种基金the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095 and 2023TSYCCX0112)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(PTYQ2022YZZD01)China National Astronomical Data Center(NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the Chinese Academy of SciencesNatural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360).
文摘Astronomical spectroscopy is crucial for exploring the physical properties,chemical composition,and kinematic behavior of celestial objects.With continuous advancements in observational technology,astronomical spectroscopy faces the dual challenges of rapidly expanding data volumes and relatively lagging data processing capabilities.In this context,the rise of artificial intelligence technologies offers an innovative solution to address these challenges.This paper analyzes the latest developments in the application of machine learning for astronomical spectral data mining and discusses future research directions in AI-based spectral studies.However,the application of machine learning technologies presents several challenges.The high complexity of models often comes with insufficient interpretability,complicating scientific understanding.Moreover,the large-scale computational demands place higher requirements on hardware resources,leading to a significant increase in computational costs.AI-based astronomical spectroscopy research should advance in the following key directions.First,develop efficient data augmentation techniques to enhance model generalization capabilities.Second,explore more interpretable model designs to ensure the reliability and transparency of scientific conclusions.Third,optimize computational efficiency and reduce the threshold for deep-learning applications through collaborative innovations in algorithms and hardware.Furthermore,promoting the integration of cross-band data processing is essential to achieve seamless integration and comprehensive analysis of multi-source data,providing richer,multidimensional information to uncover the mysteries of the universe.
基金Supported by the National Natural Science Fundation of China under Grant No.40375025 and Programme of the Ministry of Science and Technology (2001BA611B-01).
文摘In this study, the classification scheme developed by Jenkinson and Collison （1977） based on a typing scheme of Lamb （1950） is applied to obtain circulation types from the mean sea-level pressure on a monthly basis. Monthly mean sea-level pressure data from 1951 to 2002 are used to derive six circulation indices and to provide a circulation catalogue with 27 circulation types. Five major types （N, NW, C, CSW, and SW） which occurred most frequently are analyzed to reveal their relationships with the temperature of Harbin on various time scales. Stepwise multiple regression is used to reconstruct temperature anomaly. The monthly mean rainfall of all types occurring and the composite maps of three major types （C, CSW, and SW） relevant to Harbin＇s precipitation are studied. The results show that the dominant types in winter are types N and NW. types C, CSW, and SW occur frequently in summer. Types N and NW favor a negative temperature anomaly and correspond to less rainfall, while types C, CSW, and SW often induce a positive temperature anomaly and correspond to more rainfall. Moreover, a successful statistical model can be established with only one of the six indices and large-scale mean temperature. Using the model, 77.3% of the total variance in the temperature anomaly between 1951 and 2002 can be reconstructed. Type C has a close relationship with total rainfall and type C precipitation plays a major role in determining the total rainfall of Harbin in recent years. This classification scheme is a statistical downscaling model and its relationships with temperature and precipitation can be used to forecast regional climate.
