As the performance of an air-cooled condenser is apt to be affected by the fluctuating ambient condition, some difficulties are brought to the use of a steam feeding water pump in an air-cooled unit. This paper introd...As the performance of an air-cooled condenser is apt to be affected by the fluctuating ambient condition, some difficulties are brought to the use of a steam feeding water pump in an air-cooled unit. This paper introduces a new design of for steam feeding the water pump of an air-cooled unit using the back-pressure steam turbine as the prime motor. Using variable condition analysis on a 600 MW direct air-cooled unit, and with consideration of the effect on the ambient conditions, the feasibility, economy, and adaptability of the design are verified.展开更多
In this work, datasets of water and carbon fluxes measured with eddy covariance technique above a summer maize field in the North China Plain were simulated with artificial neural networks (ANNs) to explore the fluxes...In this work, datasets of water and carbon fluxes measured with eddy covariance technique above a summer maize field in the North China Plain were simulated with artificial neural networks (ANNs) to explore the fluxes responses to local environmental variables. The results showed that photosynthetically active radiation (PAR), vapor pressure deficit (VPD), air temperature (T) and leaf area index (LAI) were primary factors regulating both water vapor and carbon dioxide fluxes. Three-layer back-propagation neural networks (BP) could be applied to model fluxes exchange between cropland surface and atmosphere without using detailed physiological information or specific parameters of the plant.展开更多
It is of great significance to analyze the chemical indexes of mine water and develop a rapid identification system of water source, which can quickly and accurately distinguish the causes of water inrush and identify...It is of great significance to analyze the chemical indexes of mine water and develop a rapid identification system of water source, which can quickly and accurately distinguish the causes of water inrush and identify the source of water inrush, so as to reduce casualties and economic losses and prevent and control water inrush disasters. Taking Ca<sup>2+</sup>, Mg<sup>2+</sup>, Na<sup>+</sup> + K<sup>+</sup>, , , Cl<sup>-</sup>, pH value and TDS as discriminant indexes, the principal component analysis method was used to reduce the dimension of data, and the identification model of mine water inrush source based on PCA-BP neural network was established. 96 sets of data of different aquifers in Panxie mining area were selected for prediction analysis, and 20 sets of randomly selected data were tested, with an accuracy rate of 95%. The model can effectively reduce data redundancy, has a high recognition rate, and can accurately and quickly identify the water source of mine water inrush.展开更多
Back-streaming electrons gain significant energy due to the high voltage of the extraction system for a high-current ion source.By theoretical calculation,the particle flux accounts for 13.88% of the total beam curren...Back-streaming electrons gain significant energy due to the high voltage of the extraction system for a high-current ion source.By theoretical calculation,the particle flux accounts for 13.88% of the total beam current,and the power flux accounts for about 7.5% of the total beam power.This shows that back-streaming electrons are very destructive to the plate of electron absorption that is installed opposite of the accelerator.At the same time,as particles impinge on grids,the energy level that the grids absorb will be really high.Compared with the water flow calorimetry data of ion sources on the ASIPP-NBI testbed,it can be found that,as the high voltage of the extraction system rises,the particle flux and the power flux of the back-streaming electrons are essentially in the same proportions.Therefore,the corresponding energy deposited on the components of the ion source will grow by the same percentage with the increase in high voltage,which demonstrates strong inhibition to improving the neutral beam power injected into a tokamak.展开更多
A new method applying an artificial neural network （ANN） to retrieve water vapor profiles in the troposphere is presented. In this paper, a fully-connected, three-layer network based on the backpropagation algorithm...A new method applying an artificial neural network （ANN） to retrieve water vapor profiles in the troposphere is presented. In this paper, a fully-connected, three-layer network based on the backpropagation algorithm is constructed. Month, latitude, altitude and bending angle are chosen as the input vectors and water vapor pressure as the output vector. There are 130 groups of occultation measurements from June to November 2002 in the dataset. Seventy pairs of bending angles and water vapor pressure profiles are used to train the ANN, and the sixty remaining pairs of profiles are applied to the validation of the retrieval. By comparing the retrieved profiles with the corresponding ones from the Information System and Data Center of the Challenging Mini-Satellite Payload for Geoscientific Research and Application （CHAMP-ISDC）, it can be concluded that the ANN is relatively convenient and accurate. Its results can be provided as the first guess for the iterative methods or the non-linear optimal estimation inverse method.展开更多
Detailed experimental investigations were carried out for microwave pre-treatment of high ash Indian coal at high power level(900 W) in microwave oven. The microwave exposure times were fixed at60 s and 120 s. A rheol...Detailed experimental investigations were carried out for microwave pre-treatment of high ash Indian coal at high power level(900 W) in microwave oven. The microwave exposure times were fixed at60 s and 120 s. A rheology characteristic for microwave pre-treatment of coal-water slurry(CWS) was performed in an online Bohlin viscometer. The non-Newtonian character of the slurry follows the rheological model of Ostwald de Waele. The values of n and k vary from 0.31 to 0.64 and 0.19 to 0.81 Pa·sn,respectively. This paper presents an artificial neural network(ANN) model to predict the effects of operational parameters on apparent viscosity of CWS. A 4-2-1 topology with Levenberg-Marquardt training algorithm(trainlm) was selected as the controlled ANN. Mean squared error(MSE) of 0.002 and coefficient of multiple determinations(R^2) of 0.99 were obtained for the outperforming model. The promising values of correlation coefficient further confirm the robustness and satisfactory performance of the proposed ANN model.展开更多
An effective approach for describing complicated water quality processes is very important for river water quality management. We built two artificial neural network(ANN) models,a feed-forward back-propagation(BP) mod...An effective approach for describing complicated water quality processes is very important for river water quality management. We built two artificial neural network(ANN) models,a feed-forward back-propagation(BP) model and a radial basis function(RBF) model,to simulate the water quality of the Yangtze and Jialing Rivers in reaches crossing the city of Chongqing,P. R. China. Our models used the historical monitoring data of biological oxygen demand,dissolved oxygen,ammonia,oil and volatile phenolic compounds. Comparison with the one-dimensional traditional water quality model suggest that both BP and RBF models are superior; their higher accuracy and better goodness-of-fit indicate that the ANN calculation of water quality agrees better with measurement. It is demonstrated that ANN modeling can be a tool for estimating the water quality of the Yangtze River. Of the two ANN models,the RBF model calculates with a smaller mean error,but a larger root mean square error. More effort to identify out the causes of these differences would help optimize the structures of neural network water-quality models.展开更多
This paper reviewed studies on remote sensing of water depth retrieval. Four water depth retrieval models （single-band, dou- ble-ratio-band, multi-band, and BP network models） were evaluated using TM image and water...This paper reviewed studies on remote sensing of water depth retrieval. Four water depth retrieval models （single-band, dou- ble-ratio-band, multi-band, and BP network models） were evaluated using TM image and water data from Bangong Co Lake, which is located in China＇s Tibet Autonomous Region and Indian Kashmir. Tested by independent data, comparison of these four models demonstrates that BP network model performed better than the multi-band model, with the single-band model performing the worst. To sum up, this study demonstrates that first, BP network model performed better than the traditional model; second, precise atmospheric correction and radiation study, affected by different water level sand sediment, could improve the precision of water depth retrieval.展开更多
文摘As the performance of an air-cooled condenser is apt to be affected by the fluctuating ambient condition, some difficulties are brought to the use of a steam feeding water pump in an air-cooled unit. This paper introduces a new design of for steam feeding the water pump of an air-cooled unit using the back-pressure steam turbine as the prime motor. Using variable condition analysis on a 600 MW direct air-cooled unit, and with consideration of the effect on the ambient conditions, the feasibility, economy, and adaptability of the design are verified.
基金Project (No. 40328001) supported by the National Science Fund forOutstanding Youth Overseas China
文摘In this work, datasets of water and carbon fluxes measured with eddy covariance technique above a summer maize field in the North China Plain were simulated with artificial neural networks (ANNs) to explore the fluxes responses to local environmental variables. The results showed that photosynthetically active radiation (PAR), vapor pressure deficit (VPD), air temperature (T) and leaf area index (LAI) were primary factors regulating both water vapor and carbon dioxide fluxes. Three-layer back-propagation neural networks (BP) could be applied to model fluxes exchange between cropland surface and atmosphere without using detailed physiological information or specific parameters of the plant.
文摘It is of great significance to analyze the chemical indexes of mine water and develop a rapid identification system of water source, which can quickly and accurately distinguish the causes of water inrush and identify the source of water inrush, so as to reduce casualties and economic losses and prevent and control water inrush disasters. Taking Ca<sup>2+</sup>, Mg<sup>2+</sup>, Na<sup>+</sup> + K<sup>+</sup>, , , Cl<sup>-</sup>, pH value and TDS as discriminant indexes, the principal component analysis method was used to reduce the dimension of data, and the identification model of mine water inrush source based on PCA-BP neural network was established. 96 sets of data of different aquifers in Panxie mining area were selected for prediction analysis, and 20 sets of randomly selected data were tested, with an accuracy rate of 95%. The model can effectively reduce data redundancy, has a high recognition rate, and can accurately and quickly identify the water source of mine water inrush.
基金supported by National Natural Science Foundation of China(No.11405207,No.11505225 and No.11675215)partly supported by the International Science and Technology Cooperation Program of China(No. 2014DFG61950)the Sciences foundation of ASIPP(No. DSJJ-15-GC03)
文摘Back-streaming electrons gain significant energy due to the high voltage of the extraction system for a high-current ion source.By theoretical calculation,the particle flux accounts for 13.88% of the total beam current,and the power flux accounts for about 7.5% of the total beam power.This shows that back-streaming electrons are very destructive to the plate of electron absorption that is installed opposite of the accelerator.At the same time,as particles impinge on grids,the energy level that the grids absorb will be really high.Compared with the water flow calorimetry data of ion sources on the ASIPP-NBI testbed,it can be found that,as the high voltage of the extraction system rises,the particle flux and the power flux of the back-streaming electrons are essentially in the same proportions.Therefore,the corresponding energy deposited on the components of the ion source will grow by the same percentage with the increase in high voltage,which demonstrates strong inhibition to improving the neutral beam power injected into a tokamak.
基金The authors wish to thank the anonymous reviewers who gave us useful suggestions，and we also thank CHAMP—ISDC for providing the occultation data This work was supported by the National Science Foundation of China under No．40333034 an d the Chinese Academy of Science under No．KZCX3-S、v_217．
文摘A new method applying an artificial neural network （ANN） to retrieve water vapor profiles in the troposphere is presented. In this paper, a fully-connected, three-layer network based on the backpropagation algorithm is constructed. Month, latitude, altitude and bending angle are chosen as the input vectors and water vapor pressure as the output vector. There are 130 groups of occultation measurements from June to November 2002 in the dataset. Seventy pairs of bending angles and water vapor pressure profiles are used to train the ANN, and the sixty remaining pairs of profiles are applied to the validation of the retrieval. By comparing the retrieved profiles with the corresponding ones from the Information System and Data Center of the Challenging Mini-Satellite Payload for Geoscientific Research and Application （CHAMP-ISDC）, it can be concluded that the ANN is relatively convenient and accurate. Its results can be provided as the first guess for the iterative methods or the non-linear optimal estimation inverse method.
基金the sponsor CSIR (Council of Scientific and Industrial Research), New Delhi for their financial grant to carry out the present research work
文摘Detailed experimental investigations were carried out for microwave pre-treatment of high ash Indian coal at high power level(900 W) in microwave oven. The microwave exposure times were fixed at60 s and 120 s. A rheology characteristic for microwave pre-treatment of coal-water slurry(CWS) was performed in an online Bohlin viscometer. The non-Newtonian character of the slurry follows the rheological model of Ostwald de Waele. The values of n and k vary from 0.31 to 0.64 and 0.19 to 0.81 Pa·sn,respectively. This paper presents an artificial neural network(ANN) model to predict the effects of operational parameters on apparent viscosity of CWS. A 4-2-1 topology with Levenberg-Marquardt training algorithm(trainlm) was selected as the controlled ANN. Mean squared error(MSE) of 0.002 and coefficient of multiple determinations(R^2) of 0.99 were obtained for the outperforming model. The promising values of correlation coefficient further confirm the robustness and satisfactory performance of the proposed ANN model.
基金Funded by the Natural Science Foundation of China (No. 59778021)
文摘An effective approach for describing complicated water quality processes is very important for river water quality management. We built two artificial neural network(ANN) models,a feed-forward back-propagation(BP) model and a radial basis function(RBF) model,to simulate the water quality of the Yangtze and Jialing Rivers in reaches crossing the city of Chongqing,P. R. China. Our models used the historical monitoring data of biological oxygen demand,dissolved oxygen,ammonia,oil and volatile phenolic compounds. Comparison with the one-dimensional traditional water quality model suggest that both BP and RBF models are superior; their higher accuracy and better goodness-of-fit indicate that the ANN calculation of water quality agrees better with measurement. It is demonstrated that ANN modeling can be a tool for estimating the water quality of the Yangtze River. Of the two ANN models,the RBF model calculates with a smaller mean error,but a larger root mean square error. More effort to identify out the causes of these differences would help optimize the structures of neural network water-quality models.
基金supported by the projection of China Geographic Survey (12120113099800)the projection of "863" (2012AA062601)
文摘This paper reviewed studies on remote sensing of water depth retrieval. Four water depth retrieval models （single-band, dou- ble-ratio-band, multi-band, and BP network models） were evaluated using TM image and water data from Bangong Co Lake, which is located in China＇s Tibet Autonomous Region and Indian Kashmir. Tested by independent data, comparison of these four models demonstrates that BP network model performed better than the multi-band model, with the single-band model performing the worst. To sum up, this study demonstrates that first, BP network model performed better than the traditional model; second, precise atmospheric correction and radiation study, affected by different water level sand sediment, could improve the precision of water depth retrieval.
