In order to alleviate noise pollution and improve the sustainability of airport operation,it is of great significance to develop an effective method to predict airport aviation noise. A three-layer neural network is c...In order to alleviate noise pollution and improve the sustainability of airport operation,it is of great significance to develop an effective method to predict airport aviation noise. A three-layer neural network is constructed to gain computational simplicity and execution economy. With the preferred node number and transfer functions obtained in comparative tests,the constructed network is further optimized through the genetic algorithm for performance improvements in prediction. Results show that the proposed model in this paper is superior in accuracy and stability for airport aviation noise prediction,contributing to the assessment of future environmental impact and further improvement of operational sustainability for civil airports.展开更多
To improve the aerodynamic performance of small axial flow fan, in this paper the design of a small axial flow fan with splitter blades is studied. The RNG k-e turbulence model and SIMPLE algorithm were applied to the...To improve the aerodynamic performance of small axial flow fan, in this paper the design of a small axial flow fan with splitter blades is studied. The RNG k-e turbulence model and SIMPLE algorithm were applied to the steady simulation calculation of the flow field, and its result was used as the initial field of the large eddy simulation to calculate the unsteady pressure field. The FW-H noise model was adopted to predict aerodynamic noise in the six monitoring points. Fast Fourier transform algorithm was applied to process the pressure signal. Experiment of noise testing was done to further investigate the aerodynamic noise of fans. And then the results obtained from the numerical simulation and experiment were described and analyzed. The results show that the static characteristics of small axial fan with splitter blades are similar with the prototype fan, and the static characteristics are improved within a certain range of flux. The power spectral density at the six monitoring points of small axial flow fan with splitter blades have decreased to some extent. The experimental results show sound pressure level of new fan has reduced in most frequency bands by comparing with prototype fan. The research results will provide a proof for parameter optimization and noise prediction of small axial flow fans with high performance.展开更多
基金supported by the National Natural Science Foundation of China(No. 61671237)the Foundation of State Key Laboratory of Air Traffic Management System and Technology(No. SKLATM202003)the Fundamental Research Funds for Graduates of Nanjing University of Aeronautics and Astronautics (No. kfjj20200735)
文摘In order to alleviate noise pollution and improve the sustainability of airport operation,it is of great significance to develop an effective method to predict airport aviation noise. A three-layer neural network is constructed to gain computational simplicity and execution economy. With the preferred node number and transfer functions obtained in comparative tests,the constructed network is further optimized through the genetic algorithm for performance improvements in prediction. Results show that the proposed model in this paper is superior in accuracy and stability for airport aviation noise prediction,contributing to the assessment of future environmental impact and further improvement of operational sustainability for civil airports.
基金supported by grants from the National Natural Science Foundation of China (No.51076144)the Major Special Project of Technology Office in Zhejiang Province (No.2011C11073, No.2011C16038)
文摘To improve the aerodynamic performance of small axial flow fan, in this paper the design of a small axial flow fan with splitter blades is studied. The RNG k-e turbulence model and SIMPLE algorithm were applied to the steady simulation calculation of the flow field, and its result was used as the initial field of the large eddy simulation to calculate the unsteady pressure field. The FW-H noise model was adopted to predict aerodynamic noise in the six monitoring points. Fast Fourier transform algorithm was applied to process the pressure signal. Experiment of noise testing was done to further investigate the aerodynamic noise of fans. And then the results obtained from the numerical simulation and experiment were described and analyzed. The results show that the static characteristics of small axial fan with splitter blades are similar with the prototype fan, and the static characteristics are improved within a certain range of flux. The power spectral density at the six monitoring points of small axial flow fan with splitter blades have decreased to some extent. The experimental results show sound pressure level of new fan has reduced in most frequency bands by comparing with prototype fan. The research results will provide a proof for parameter optimization and noise prediction of small axial flow fans with high performance.
