High-speed maglev trains(HSMTs)can run at high running speeds due to their unique design.The pressure waves that these trains generate while passing each other are therefore very intense,and can even have safety impli...High-speed maglev trains(HSMTs)can run at high running speeds due to their unique design.The pressure waves that these trains generate while passing each other are therefore very intense,and can even have safety implications.In order to reduce the transient impact of such waves,the standard k-ε turbulence model is used in this work to assess the effect of railway spacing on the aerodynamic loads,pressure and surrounding flow field of 600 km/h maglev trains passing each other in open air.The sliding mesh technique is used to determine the relative motion between the considered trains.The results show that the surface pressure is approximately linearly correlated with the square of the speed while the amplitude of the pressure wave on the train surface,side force,and rolling moment all have negative exponential relationships with the railway spacing.展开更多
The Mountain Pass mine is recognized as one of the world's primary sources of rare earth minerals.These rare earth minerals mainly consist of bastnaesite and a small amount of monazite phosphate,which cannot be de...The Mountain Pass mine is recognized as one of the world's primary sources of rare earth minerals.These rare earth minerals mainly consist of bastnaesite and a small amount of monazite phosphate,which cannot be decomposed and recovered through conventional oxidative roasting and hydrochloric acid leaching process.An efficient,clean,and economical process called the"combined method"was proposed for the utilization of the Mountain Pass mine to extract rare earths from Mountain Pass rare earth concentrate(MPREC).The main steps of this process include weak oxidation atmosphere roasting,step leaching of hydrochloric acid,solid-liquid separation,the monazite slag with sulfuric acid roasting water leaching,etc.In this paper,the roasting process of MPREC under a weak oxidation atmosphere was investigated.The study examines the thermal decomposition kinetics,phase transition process,and leaching behavior of MPREC in air/CO_(2)atmosphere.Results show that,the activation energy(Ea)for MPREC thermal decomposition in air and CO_(2)atmosphere are 146 and 320 kJ/mol,respectively.At temperature above 500℃in air or above 700℃in CO_(2)atmosphere,REOF are generated from bastnaesite through an in-situ reaction with CaO,which is decomposed from CaCO_(3),to form CaF_(2)and rare earth oxide(REO).Thus,F is regulated into solid phase.In an oxidizing atmosphere,the thermal decomposition of bastnaesite is accompanied by the rapid oxidation of Ce(Ⅲ).In co ntrast,the oxidation of Ce(Ⅲ)in a CO_(2)atmosphere is significantly inhibited.At 700℃,the oxidation rate of Ce in air is 74.09%,while in a CO_(2)atmosphere,it is only 33.83%.The hydrochloric acid leaching experiment shows that,the leaching rate of rare earth after roasting at 600℃under an air atmosphere reaches to 82.9%,and it reaches 87%after roasting at 800℃under a CO_(2)atmosphere.The reduction of Ce oxidation in a weak oxidizing atmosphere significantly improves the leaching rate of Ce.展开更多
In this paper,the multi cross-rolling and cryogenic treatment were adopted to process the AZ31 Mg alloy to study the influence of passes and cryogenic treatment on cross-rolled AZ31 Mg alloy.The tensile properties and...In this paper,the multi cross-rolling and cryogenic treatment were adopted to process the AZ31 Mg alloy to study the influence of passes and cryogenic treatment on cross-rolled AZ31 Mg alloy.The tensile properties and hardness were tested.The microstructure was characterized using electron backscatter diffraction(EBSD),transmission electron microscopy(TEM),and scanning electron microscopy(SEM)in order to elucidate the influencing mechanism.The results indicate that the treatment method can significantly improve the mechanical properties of AZ31 Mg alloy.The 3-pass sample processed by cryogenic treatment shows the highest strength(351 MPa)and has the highest hardness(76.1HV)and best hardness uniformity(standard deviation=0.9HV).The 2-pass sample has the highest ductility among all the samples but poor hardness evenness.The strengthening mechanism of 3-pass sample can be attributed to the fine grains,bimodal structure,high dislocation density,and precipitation strengthening.Due to repeated heat preservation of 4-pass and 5-pass,their comprehensive performances decrease.展开更多
The former Vice-President of the International Council of Ophthalmology(ICO).Professor of Ophthalmology Emeritus Johns Hopkins University School of Medicine,Wilmer Eye Institute,USA.The first Director of the Departmen...The former Vice-President of the International Council of Ophthalmology(ICO).Professor of Ophthalmology Emeritus Johns Hopkins University School of Medicine,Wilmer Eye Institute,USA.The first Director of the Department of Ophthalmology and Visual Sciences,The Chinese University of Hong Kong China.The first Director of the Peking University Eye Center,China.展开更多
In this paper,we focus on the channel estimation for multi-user MIMO-OFDM systems in rich scattering environments.We find that channel sparsity in the delay-angle domain is severely compromised in rich scattering envi...In this paper,we focus on the channel estimation for multi-user MIMO-OFDM systems in rich scattering environments.We find that channel sparsity in the delay-angle domain is severely compromised in rich scattering environments,so that most existing compressed sensing(CS)based techniques can harvest a very limited gain(if any)in reducing the channel estimation overhead.To address the problem,we propose the learning-based turbo message passing(LTMP)algorithm.Instead of exploiting the channel sparsity,LTMP is able to efficiently extract the channel feature via deep learning as well as to exploit the channel continuity in the frequency domain via block-wise linear modelling.More specifically,as a component of LTMP,we develop a multi-scale parallel dilated convolutional neural network(MPDCNN),which leverages frequency-space channel correlation in different scales for channel denoising.We evaluate the LTMP’s performance in MIMO-OFDM channels using the 3rd generation partnership project(3GPP)clustered delay line(CDL)channel models.Simulation results show that the proposed channel estimation method has more than 5 dB power gain than the existing algorithms when the normalized mean-square error of the channel estimation is-20 dB.The proposed algorithm also exhibits strong robustness in various environments.展开更多
基金supported by the National Natural Science Foundation of China(12372049)Fundamental Research Funds for the Central Universities(2682023ZTPY036)Research and Development Project of JDD For HTS Maglev Transportation System(JDDKYCF2024002).
文摘High-speed maglev trains(HSMTs)can run at high running speeds due to their unique design.The pressure waves that these trains generate while passing each other are therefore very intense,and can even have safety implications.In order to reduce the transient impact of such waves,the standard k-ε turbulence model is used in this work to assess the effect of railway spacing on the aerodynamic loads,pressure and surrounding flow field of 600 km/h maglev trains passing each other in open air.The sliding mesh technique is used to determine the relative motion between the considered trains.The results show that the surface pressure is approximately linearly correlated with the square of the speed while the amplitude of the pressure wave on the train surface,side force,and rolling moment all have negative exponential relationships with the railway spacing.
基金supported by the National Key Research and Development Program of China(2020YFC1909104)National Natural Science Foundation of China(52274355)Major Science and Technology Project of Inner Mongolia Autonomous Region(2021ZD0016)。
文摘The Mountain Pass mine is recognized as one of the world's primary sources of rare earth minerals.These rare earth minerals mainly consist of bastnaesite and a small amount of monazite phosphate,which cannot be decomposed and recovered through conventional oxidative roasting and hydrochloric acid leaching process.An efficient,clean,and economical process called the"combined method"was proposed for the utilization of the Mountain Pass mine to extract rare earths from Mountain Pass rare earth concentrate(MPREC).The main steps of this process include weak oxidation atmosphere roasting,step leaching of hydrochloric acid,solid-liquid separation,the monazite slag with sulfuric acid roasting water leaching,etc.In this paper,the roasting process of MPREC under a weak oxidation atmosphere was investigated.The study examines the thermal decomposition kinetics,phase transition process,and leaching behavior of MPREC in air/CO_(2)atmosphere.Results show that,the activation energy(Ea)for MPREC thermal decomposition in air and CO_(2)atmosphere are 146 and 320 kJ/mol,respectively.At temperature above 500℃in air or above 700℃in CO_(2)atmosphere,REOF are generated from bastnaesite through an in-situ reaction with CaO,which is decomposed from CaCO_(3),to form CaF_(2)and rare earth oxide(REO).Thus,F is regulated into solid phase.In an oxidizing atmosphere,the thermal decomposition of bastnaesite is accompanied by the rapid oxidation of Ce(Ⅲ).In co ntrast,the oxidation of Ce(Ⅲ)in a CO_(2)atmosphere is significantly inhibited.At 700℃,the oxidation rate of Ce in air is 74.09%,while in a CO_(2)atmosphere,it is only 33.83%.The hydrochloric acid leaching experiment shows that,the leaching rate of rare earth after roasting at 600℃under an air atmosphere reaches to 82.9%,and it reaches 87%after roasting at 800℃under a CO_(2)atmosphere.The reduction of Ce oxidation in a weak oxidizing atmosphere significantly improves the leaching rate of Ce.
基金Project(52174362)supported by the National Natural Science Foundation of ChinaProject(2023JJ10020)supported by the Natural Science Foundation of Hunan Province,China+3 种基金Project(2024RC7002)supported by the Science and Technology Innovation Program of Hunan Province,ChinaProject(2024CY2-GJHX-71)supported by the Shaanxi Provincial Key R&D ProgramProject supported by the Yancheng“Talent Plan of Yellow Sea Pearl”for Leading Talent Project,ChinaProject(2019GK1012)supported by the Hunan Innovative Province Construction Special Program,China。
文摘In this paper,the multi cross-rolling and cryogenic treatment were adopted to process the AZ31 Mg alloy to study the influence of passes and cryogenic treatment on cross-rolled AZ31 Mg alloy.The tensile properties and hardness were tested.The microstructure was characterized using electron backscatter diffraction(EBSD),transmission electron microscopy(TEM),and scanning electron microscopy(SEM)in order to elucidate the influencing mechanism.The results indicate that the treatment method can significantly improve the mechanical properties of AZ31 Mg alloy.The 3-pass sample processed by cryogenic treatment shows the highest strength(351 MPa)and has the highest hardness(76.1HV)and best hardness uniformity(standard deviation=0.9HV).The 2-pass sample has the highest ductility among all the samples but poor hardness evenness.The strengthening mechanism of 3-pass sample can be attributed to the fine grains,bimodal structure,high dislocation density,and precipitation strengthening.Due to repeated heat preservation of 4-pass and 5-pass,their comprehensive performances decrease.
文摘The former Vice-President of the International Council of Ophthalmology(ICO).Professor of Ophthalmology Emeritus Johns Hopkins University School of Medicine,Wilmer Eye Institute,USA.The first Director of the Department of Ophthalmology and Visual Sciences,The Chinese University of Hong Kong China.The first Director of the Peking University Eye Center,China.
基金supported in part by the National Key Research and Development Program of China under Grant 2020YFB1804800.
文摘In this paper,we focus on the channel estimation for multi-user MIMO-OFDM systems in rich scattering environments.We find that channel sparsity in the delay-angle domain is severely compromised in rich scattering environments,so that most existing compressed sensing(CS)based techniques can harvest a very limited gain(if any)in reducing the channel estimation overhead.To address the problem,we propose the learning-based turbo message passing(LTMP)algorithm.Instead of exploiting the channel sparsity,LTMP is able to efficiently extract the channel feature via deep learning as well as to exploit the channel continuity in the frequency domain via block-wise linear modelling.More specifically,as a component of LTMP,we develop a multi-scale parallel dilated convolutional neural network(MPDCNN),which leverages frequency-space channel correlation in different scales for channel denoising.We evaluate the LTMP’s performance in MIMO-OFDM channels using the 3rd generation partnership project(3GPP)clustered delay line(CDL)channel models.Simulation results show that the proposed channel estimation method has more than 5 dB power gain than the existing algorithms when the normalized mean-square error of the channel estimation is-20 dB.The proposed algorithm also exhibits strong robustness in various environments.
