Ventilation systems are critical for improving the cabin environment in high-speed trains,and their interest has increased significantly.However,whether air supply non-verticality deteriorates the cabin air environmen...Ventilation systems are critical for improving the cabin environment in high-speed trains,and their interest has increased significantly.However,whether air supply non-verticality deteriorates the cabin air environment,and the flow mechanism behind it and the degree of deterioration are not known.This study first analyzes the interaction between deflection angle and cabin flow field characteristics and ventilation performance.The results revealed that the interior temperature and pollutant concentration decreased slightly with increasing deflection angle,but resulted in significant deterioration of thermal comfort and air quality.This is evidenced by an increase in both draught rate and non-uniformity coefficient,an increase in the number of measurement points that do not satisfy the micro-wind speed and temperature difference requirements by about 5% and 15%,respectively,and an increase in longitudinal penetration of pollutants by a factor of about 5 and the appearance of locking regions at the ends of cabin.The results also show that changing the deflection pattern only affects the region of deterioration and does not essentially improve this deterioration.This study can provide reference and help for the ventilation design of high-speed trains.展开更多
Accurate forecasting of wind velocity can improve the economic dispatch and safe operation of the power system. Support vector machine (SVM) has been proved to be an efficient approach for forecasting. According to th...Accurate forecasting of wind velocity can improve the economic dispatch and safe operation of the power system. Support vector machine (SVM) has been proved to be an efficient approach for forecasting. According to the analysis with support vector machine method, the drawback of determining the parameters only by experts' experience should be improved. After a detailed description of the methodology of SVM and simulated annealing, an improved algorithm was proposed for the automatic optimization of parameters using SVM method. An example has proved that the proposed method can efficiently select the parameters of the SVM method. And by optimizing the parameters, the forecasting accuracy of the max wind velocity increases by 34.45%, which indicates that the new SASVM model improves the forecasting accuracy.展开更多
The probability distributions of wind speeds and the availability of wind turbines were investigated by considering the vertical wind shear. Based on the wind speed data at the standard height observed at a wind farm,...The probability distributions of wind speeds and the availability of wind turbines were investigated by considering the vertical wind shear. Based on the wind speed data at the standard height observed at a wind farm, the power-law process was used to simulate the wind speeds at a hub height of 60 m. The Weibull and Rayleigh distributions were chosen to express the wind speeds at two different heights. The parameters in the model were estimated via the least square(LS) method and the maximum likelihood estimation(MLE) method, respectively. An adjusted MLE approach was also presented for parameter estimation. The main indices of wind energy characteristics were calculated based on observational wind speed data. A case study based on the data of Hexi area, Gansu Province of China was given. The results show that MLE method generally outperforms LS method for parameter estimation, and Weibull distribution is more appropriate to describe the wind speed at the hub height.展开更多
Natural ventilation is driven by either buoyancy forces or wind pressure forces or their combinations that inherit stochastic variation into ventilation rates. Since the ventilation rate is a nonlinear function of mul...Natural ventilation is driven by either buoyancy forces or wind pressure forces or their combinations that inherit stochastic variation into ventilation rates. Since the ventilation rate is a nonlinear function of multiple variable factors including wind speed, wind direction, internal heat source and building structural thermal mass, the conventional methods for quantifying ventilation rate simply using dominant wind direction and average wind speed may not accurately describe the characteristic performance of natural ventilation. From a new point of view, the natural ventilation performance of a single room building under fluctuating wind speed condition using the Monte-Carlo simulation approach was investigated by incorporating building facade thermal mass effect. Given a same hourly turbulence intensity distribution, the wind speeds with 1 rain frequency fluctuations were generated using a stochastic model, the modified GARCH model. Comparisons of natural ventilation profiles, effective ventilation rates, and air conditioning electricity use for a three-month period show statistically significant differences （for 80% confidence interval） between the new calculations and the traditional methods based on hourly average wind speed.展开更多
To protect trains against strong cross-wind along Qinghai-Tibet railway, a strong wind speed monitoring and warning system was developed. And to obtain high-precision wind speed short-term forecasting values for the s...To protect trains against strong cross-wind along Qinghai-Tibet railway, a strong wind speed monitoring and warning system was developed. And to obtain high-precision wind speed short-term forecasting values for the system to make more accurate scheduling decision, two optimization algorithms were proposed. Using them to make calculative examples for actual wind speed time series from the 18th meteorological station, the results show that: the optimization algorithm based on wavelet analysis method and improved time series analysis method can attain high-precision multi-step forecasting values, the mean relative errors of one-step, three-step, five-step and ten-step forecasting are only 0.30%, 0.75%, 1.15% and 1.65%, respectively. The optimization algorithm based on wavelet analysis method and Kalman time series analysis method can obtain high-precision one-step forecasting values, the mean relative error of one-step forecasting is reduced by 61.67% to 0.115%. The two optimization algorithms both maintain the modeling simple character, and can attain prediction explicit equations after modeling calculation.展开更多
基金Project(12372049)supported by the National Natural Science Foundation of ChinaProject(2682023ZTPY036)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(2023TPL-T06)supported by the Independent Project of State Key Laboratory of Rail Transit Vehicle System,China。
文摘Ventilation systems are critical for improving the cabin environment in high-speed trains,and their interest has increased significantly.However,whether air supply non-verticality deteriorates the cabin air environment,and the flow mechanism behind it and the degree of deterioration are not known.This study first analyzes the interaction between deflection angle and cabin flow field characteristics and ventilation performance.The results revealed that the interior temperature and pollutant concentration decreased slightly with increasing deflection angle,but resulted in significant deterioration of thermal comfort and air quality.This is evidenced by an increase in both draught rate and non-uniformity coefficient,an increase in the number of measurement points that do not satisfy the micro-wind speed and temperature difference requirements by about 5% and 15%,respectively,and an increase in longitudinal penetration of pollutants by a factor of about 5 and the appearance of locking regions at the ends of cabin.The results also show that changing the deflection pattern only affects the region of deterioration and does not essentially improve this deterioration.This study can provide reference and help for the ventilation design of high-speed trains.
基金Project(71071052) supported by the National Natural Science Foundation of ChinaProject(JB2011097) supported by the Fundamental Research Funds for the Central Universities of China
文摘Accurate forecasting of wind velocity can improve the economic dispatch and safe operation of the power system. Support vector machine (SVM) has been proved to be an efficient approach for forecasting. According to the analysis with support vector machine method, the drawback of determining the parameters only by experts' experience should be improved. After a detailed description of the methodology of SVM and simulated annealing, an improved algorithm was proposed for the automatic optimization of parameters using SVM method. An example has proved that the proposed method can efficiently select the parameters of the SVM method. And by optimizing the parameters, the forecasting accuracy of the max wind velocity increases by 34.45%, which indicates that the new SASVM model improves the forecasting accuracy.
基金Project(51165019)supported by the National Natural Science Foundation of ChinaProject(1308RJYA018)supported by Gansu Provincial Natural Science Fund,ChinaProject(2013-4-110)supported by Lanzhou Technology Development Program,China
文摘The probability distributions of wind speeds and the availability of wind turbines were investigated by considering the vertical wind shear. Based on the wind speed data at the standard height observed at a wind farm, the power-law process was used to simulate the wind speeds at a hub height of 60 m. The Weibull and Rayleigh distributions were chosen to express the wind speeds at two different heights. The parameters in the model were estimated via the least square(LS) method and the maximum likelihood estimation(MLE) method, respectively. An adjusted MLE approach was also presented for parameter estimation. The main indices of wind energy characteristics were calculated based on observational wind speed data. A case study based on the data of Hexi area, Gansu Province of China was given. The results show that MLE method generally outperforms LS method for parameter estimation, and Weibull distribution is more appropriate to describe the wind speed at the hub height.
文摘Natural ventilation is driven by either buoyancy forces or wind pressure forces or their combinations that inherit stochastic variation into ventilation rates. Since the ventilation rate is a nonlinear function of multiple variable factors including wind speed, wind direction, internal heat source and building structural thermal mass, the conventional methods for quantifying ventilation rate simply using dominant wind direction and average wind speed may not accurately describe the characteristic performance of natural ventilation. From a new point of view, the natural ventilation performance of a single room building under fluctuating wind speed condition using the Monte-Carlo simulation approach was investigated by incorporating building facade thermal mass effect. Given a same hourly turbulence intensity distribution, the wind speeds with 1 rain frequency fluctuations were generated using a stochastic model, the modified GARCH model. Comparisons of natural ventilation profiles, effective ventilation rates, and air conditioning electricity use for a three-month period show statistically significant differences （for 80% confidence interval） between the new calculations and the traditional methods based on hourly average wind speed.
基金Project(2006BAC07B03) supported by the National Key Technology R & D Program of ChinaProject(2006G040-A) supported by the Foundation of the Science and Technology Section of Ministry of RailwayProject(2008yb044) supported by the Foundation of Excellent Doctoral Dissertation of Central South University
文摘To protect trains against strong cross-wind along Qinghai-Tibet railway, a strong wind speed monitoring and warning system was developed. And to obtain high-precision wind speed short-term forecasting values for the system to make more accurate scheduling decision, two optimization algorithms were proposed. Using them to make calculative examples for actual wind speed time series from the 18th meteorological station, the results show that: the optimization algorithm based on wavelet analysis method and improved time series analysis method can attain high-precision multi-step forecasting values, the mean relative errors of one-step, three-step, five-step and ten-step forecasting are only 0.30%, 0.75%, 1.15% and 1.65%, respectively. The optimization algorithm based on wavelet analysis method and Kalman time series analysis method can obtain high-precision one-step forecasting values, the mean relative error of one-step forecasting is reduced by 61.67% to 0.115%. The two optimization algorithms both maintain the modeling simple character, and can attain prediction explicit equations after modeling calculation.
