The optimal design of heating and cooling systems must take into account heat radiation which is a non-linear process.In this study,the mixed convection in a radiative magnetohydrodynamic Eyring-Powell copperwater nan...The optimal design of heating and cooling systems must take into account heat radiation which is a non-linear process.In this study,the mixed convection in a radiative magnetohydrodynamic Eyring-Powell copperwater nanofluid over a stretching cylinder was investigated.The energy balance is modeled,taking into account the non-linear thermal radiation and a thermal slip condition.The effects of the embedded flow parameters on the fluid properties,as well as on the skin friction coefficient and heat transfer rate,are analyzed.Unlike in many existing studies,the recent spectral quasi-linearization method is used to solve the coupled nonlinear boundary-value problem.The computational result shows that increasing the nanoparticle volume fraction,thermal radiation parameter and heat generation parameter enhances temperature profile.We found that the velocity slip parameter and the fluid material parameter enhance the skin friction.A comparison of the current numerical results with existing literature for some limiting cases shows excellent agreement.展开更多
Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributio...Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributions,and it is difficult to identify such signals using traditional time-frequency analysis methods.To solve this problem,this paper proposes an algorithm for automatic recognition of quasi-LFM radar waveforms based on fractional Fourier transform and time-frequency analysis.First of all,fractional Fourier transform and the Wigner-Ville distribution(WVD)are used to determine the number of main ridgelines and the tilt angle of the target component in WVD.Next,the standard deviation of the target component's width in the signal's WVD is calculated.Finally,an assembled classifier using neural network is built to recognize different waveforms by automatically combining the three features.Simulation results show that the overall recognition rate of the proposed algorithm reaches 94.17%under 0 dB.When the training data set and the test data set are mixed with noise,the recognition rate reaches 89.93%.The best recognition accuracy is achieved when the size of the training set is taken as 400.The algorithm complexity can meet the requirements of real-time recognition.展开更多
文摘The optimal design of heating and cooling systems must take into account heat radiation which is a non-linear process.In this study,the mixed convection in a radiative magnetohydrodynamic Eyring-Powell copperwater nanofluid over a stretching cylinder was investigated.The energy balance is modeled,taking into account the non-linear thermal radiation and a thermal slip condition.The effects of the embedded flow parameters on the fluid properties,as well as on the skin friction coefficient and heat transfer rate,are analyzed.Unlike in many existing studies,the recent spectral quasi-linearization method is used to solve the coupled nonlinear boundary-value problem.The computational result shows that increasing the nanoparticle volume fraction,thermal radiation parameter and heat generation parameter enhances temperature profile.We found that the velocity slip parameter and the fluid material parameter enhance the skin friction.A comparison of the current numerical results with existing literature for some limiting cases shows excellent agreement.
基金This work was supported by the National Natural Science Foundation of China(91538201)the Taishan Scholar Project of Shandong Province(ts201511020)the project supported by Chinese National Key Laboratory of Science and Technology on Information System Security(6142111190404).
文摘Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributions,and it is difficult to identify such signals using traditional time-frequency analysis methods.To solve this problem,this paper proposes an algorithm for automatic recognition of quasi-LFM radar waveforms based on fractional Fourier transform and time-frequency analysis.First of all,fractional Fourier transform and the Wigner-Ville distribution(WVD)are used to determine the number of main ridgelines and the tilt angle of the target component in WVD.Next,the standard deviation of the target component's width in the signal's WVD is calculated.Finally,an assembled classifier using neural network is built to recognize different waveforms by automatically combining the three features.Simulation results show that the overall recognition rate of the proposed algorithm reaches 94.17%under 0 dB.When the training data set and the test data set are mixed with noise,the recognition rate reaches 89.93%.The best recognition accuracy is achieved when the size of the training set is taken as 400.The algorithm complexity can meet the requirements of real-time recognition.
