Due to the complex high-temperature characteristics of hydrocarbon fuel,the research on the long-term working process of parallel channel structure under variable working conditions,especially under high heat-mass rat...Due to the complex high-temperature characteristics of hydrocarbon fuel,the research on the long-term working process of parallel channel structure under variable working conditions,especially under high heat-mass ratio,has not been systematically carried out.In this paper,the heat transfer and flow characteristics of related high temperature fuels are studied by using typical engine parallel channel structure.Through numeri⁃cal simulation and systematic experimental verification,the flow and heat transfer characteristics of parallel chan⁃nels under typical working conditions are obtained,and the effectiveness of high-precision calculation method is preliminarily established.It is known that the stable time required for hot start of regenerative cooling engine is about 50 s,and the flow resistance of parallel channel structure first increases and then decreases with the in⁃crease of equivalence ratio(The following equivalence ratio is expressed byΦ),and there is a flow resistance peak in the range ofΦ=0.5~0.8.This is mainly caused by the coupling effect of high temperature physical proper⁃ties,flow rate and pressure of fuel in parallel channels.At the same time,the cooling and heat transfer character⁃istics of parallel channels under some conditions of high heat-mass ratio are obtained,and the main factors affect⁃ing the heat transfer of parallel channels such as improving surface roughness and strengthening heat transfer are mastered.In the experiment,whenΦis less than 0.9,the phenomenon of local heat transfer enhancement and deterioration can be obviously observed,and the temperature rise of local structures exceeds 200℃,which is the risk of structural damage.Therefore,the reliability of long-term parallel channel structure under the condition of high heat-mass ratio should be fully considered in structural design.展开更多
The work takes a new liquid-cooling plate in a power battery with pin fins inside the channel as the object.A mathematical model is established via the central composite design of the response surface to study the rel...The work takes a new liquid-cooling plate in a power battery with pin fins inside the channel as the object.A mathematical model is established via the central composite design of the response surface to study the relationships among the length,width,height,and spacing of pin fins;the maximum temperature and temperature difference of the battery module;and the pressure drop of the liquid-cooling plate.Model accuracy is verified via variance analysis.The new liquid-cooling plate enables the power battery to work within an optimal temperature range.Appropriately increasing the length,width,and height and reducing the spacing of pin fins could reduce the temperature of the power battery module and improve the temperature uniformity.However,the pressure drop of the liquid-cooling plate increases.The structural parameters of the pin fins are optimized to minimize the maximum temperature and the temperature difference of the battery module as well as the pressure drop of the liquid-cooling plate.The errors between the values predicted and actual by the simulation test are 0.58%,4%,and 0.48%,respectively,which further verifies the model accuracy.The results reveal the influence of the structural parameters of the pin fins inside the liquid-cooling plate on its heat dissipation performance and pressure drop characteristics.A theoretical basis is provided for the design of liquid-cooling plates in power batteries and the optimization of structural parameters.展开更多
For segmented detectors,surface flatness is critical as it directly influences both energy resolution and image clarity.Additionally,the limited adjustment range of the segmented detectors necessitates precise benchma...For segmented detectors,surface flatness is critical as it directly influences both energy resolution and image clarity.Additionally,the limited adjustment range of the segmented detectors necessitates precise benchmark construction.This paper proposes an architecture for detecting detector flatness based on channel spectral dispersion.By measuring the dispersion fringes for coplanar adjustment,the final adjustment residual is improved to better than 300 nm.This result validates the feasibility of the proposed technology and provides significant technical support for the development of next-generation large-aperture sky survey equipment.展开更多
In this study,the interaction between deformation and precipitates during multiple equal channel angular pressing(ECAP)deformations and inter-pass aging combination and its effect on the mechanical properties of 7050 ...In this study,the interaction between deformation and precipitates during multiple equal channel angular pressing(ECAP)deformations and inter-pass aging combination and its effect on the mechanical properties of 7050 aluminum alloy are studied.The result show that ECAP induces numerous substructures and dislocations,effectively promoting the precipitation of theηʹphase exhibiting a bimodal structure during inter-pass aging.Following inter-pass aging and subsequent ECAP,the decrease in grain size(4.8μm)is together with the increase in dislocation density(1.24×10^(15) m^(−2))due to the pinning effect of the precipitated phase.Simultaneously,the dislocation motion causes the second phase particles to become even finer and more diffuse.The synergistic effects of precipitation strengthening,fine grain strengthening,and dislocation strengthening collectively enhance the high strength of aluminum alloys,with ultimate tensile strength and yield strength reaching approximately 610 and 565 MPa,respectively.Meanwhile,ductility remains largely unchanged,primarily due to coordinated grain boundary sliding and the uniform and fine dispersion of second phase particles.展开更多
Hypersonic Glide Vehicles(HGVs)are advanced aircraft that can achieve extremely high speeds(generally over 5 Mach)and maneuverability within the Earth's atmosphere.HGV trajectory prediction is crucial for effectiv...Hypersonic Glide Vehicles(HGVs)are advanced aircraft that can achieve extremely high speeds(generally over 5 Mach)and maneuverability within the Earth's atmosphere.HGV trajectory prediction is crucial for effective defense planning and interception strategies.In recent years,HGV trajectory prediction methods based on deep learning have the great potential to significantly enhance prediction accuracy and efficiency.However,it's still challenging to strike a balance between improving prediction performance and reducing computation costs of the deep learning trajectory prediction models.To solve this problem,we propose a new deep learning framework(FECA-LSMN)for efficient HGV trajectory prediction.The model first uses a Frequency Enhanced Channel Attention(FECA)module to facilitate the fusion of different HGV trajectory features,and then subsequently employs a Light Sampling-oriented Multi-Layer Perceptron Network(LSMN)based on simple MLP-based structures to extract long/shortterm HGV trajectory features for accurate trajectory prediction.Also,we employ a new data normalization method called reversible instance normalization(RevIN)to enhance the prediction accuracy and training stability of the network.Compared to other popular trajectory prediction models based on LSTM,GRU and Transformer,our FECA-LSMN model achieves leading or comparable performance in terms of RMSE,MAE and MAPE metrics while demonstrating notably faster computation time.The ablation experiments show that the incorporation of the FECA module significantly improves the prediction performance of the network.The RevIN data normalization technique outperforms traditional min-max normalization as well.展开更多
The fifth-generation (5G) communication requires a highly accurate estimation of the channel state information (CSI)to take advantage of the massive multiple-input multiple-output(MIMO) system. However, traditional ch...The fifth-generation (5G) communication requires a highly accurate estimation of the channel state information (CSI)to take advantage of the massive multiple-input multiple-output(MIMO) system. However, traditional channel estimation methods do not always yield reliable estimates. The methodology of this paper consists of deep residual shrinkage network (DRSN)neural network-based method that is used to solve this problem.Thus, the channel estimation approach, based on DRSN with its learning ability of noise-containing data, is first introduced. Then,the DRSN is used to train the noise reduction process based on the results of the least square (LS) channel estimation while applying the pilot frequency subcarriers, where the initially estimated subcarrier channel matrix is considered as a three-dimensional tensor of the DRSN input. Afterward, a mixed signal to noise ratio (SNR) training data strategy is proposed based on the learning ability of DRSN under different SNRs. Moreover, a joint mixed scenario training strategy is carried out to test the multi scenarios robustness of DRSN. As for the findings, the numerical results indicate that the DRSN method outperforms the spatial-frequency-temporal convolutional neural networks (SF-CNN)with similar computational complexity and achieves better advantages in the full SNR range than the minimum mean squared error (MMSE) estimator with a limited dataset. Moreover, the DRSN approach shows robustness in different propagation environments.展开更多
In this paper,equal channel angular pressing and thermomechanical treatment was employed to improve the strength and electrical conductivity of an aging strengthened Cu-Ti-Cr-Mg alloy,and the microstructure and proper...In this paper,equal channel angular pressing and thermomechanical treatment was employed to improve the strength and electrical conductivity of an aging strengthened Cu-Ti-Cr-Mg alloy,and the microstructure and properties of the alloy were investigated in detail.The results showed that the samples deformed by the combination of cryogenic equal channel angular pressing(ECAP)and rolling had good comprehensive properties after aging at 400℃.The tensile strength of the peak-aged and over-aged samples was 1120 MPa and 940 MPa,with their corresponding electrical conductivity of 14.7%IACS and 22.1%IACS,respectively.ECAP and cryogenic rolling introduced high density dislocations,leading to the inhibition of the softening effects and refinement of the grains.After a long time aging at 400℃,the alloy exhibited ultra-high strength with obvious increasing electrical conductivity.The high strength was attributed to the synergistic effect of work hardening,grain refinement strengthening and precipitation strengthening.The precipitation of a large amount of Ti atoms from the matrix led to the high electrical conductivity of the over-aged sample.展开更多
Alkaline water electrolysis(AWE)is the most mature technology for hydrogen production by water electrolysis.Alkaline water electrolyzer consists of multiple electrolysis cells,and a single cell consists of a diaphragm...Alkaline water electrolysis(AWE)is the most mature technology for hydrogen production by water electrolysis.Alkaline water electrolyzer consists of multiple electrolysis cells,and a single cell consists of a diaphragm,electrodes,bipolar plates and end plates,etc.The existing industrial bipolar plate channel is concave-convex structure,which is manufactured by complicated and high-cost mold punching.This structure still results in uneven electrolyte flow and low current density in the electrolytic cell,further increasing in energy consumption and cost of AWE.Thereby,in this article,the electrochemical and flow model is firstly constructed,based on the existing industrial concave and convex flow channel structure of bipolar plate,to study the current density,electrolyte flow and bubble distribution in the electrolysis cell.The reliability of the model was verified by comparison with experimental data in literature.Among which,the electrochemical current density affects the bubble yield,on the other hand,the generated bubbles cover the electrode surface,affecting the active specific surface area and ohmic resistance,which in turn affects the electrochemical reaction.The result indicates that the flow velocity near the bottom of the concave ball approaches zero,while the flow velocity on the convex ball surface is significantly higher.Additionally,vortices are observed within the flow channel structure,leading to an uneven distribution of electrolyte.Next,modelling is used to optimize the bipolar plate structure of AWE by simulating the electrochemistry and fluid flow performances of four kinds of structures,namely,concave and convex,rhombus,wedge and expanded mesh,in the bipolar plate of alkaline water electrolyzer.The results show that the expanded mesh channel structure has the largest current density of 3330 A/m^(2)and electrolyte flow velocity of 0.507 m/s in the electrolytic cell.Under the same current density,the electrolytic cell with the expanded mesh runner structure has the smallest potential and energy consumption.This work provides a useful guide for the comprehensive understanding and optimization of channel structures,and a theoretical basis for the design of large-scale electrolyzer.展开更多
在室内可见光通信中符号间干扰和噪声会严重影响系统性能,K均值(K-means)均衡方法可以抑制光无线信道的影响,但其复杂度较高,且在聚类边界处易出现误判。提出了改进聚类中心点的K-means(Improved Center K-means,IC-Kmeans)算法,通过随...在室内可见光通信中符号间干扰和噪声会严重影响系统性能,K均值(K-means)均衡方法可以抑制光无线信道的影响,但其复杂度较高,且在聚类边界处易出现误判。提出了改进聚类中心点的K-means(Improved Center K-means,IC-Kmeans)算法,通过随机生成足够长的训练序列,然后将训练序列每一簇的均值作为K-means聚类中心,避免了传统K-means反复迭代寻找聚类中心。进一步,提出了基于神经网络的IC-Kmeans(Neural Network Based IC-Kmeans,NNIC-Kmeans)算法,使用反向传播神经网络将接收端二维数据映射至三维空间,以增加不同簇之间混合数据的距离,提高了分类准确性。蒙特卡罗误码率仿真表明,IC-Kmeans均衡和传统K-means算法的误码率性能相当,但可以显著降低复杂度,特别是在信噪比较小时。同时,在室内多径信道模型下,与IC-Kmeans和传统Kmeans均衡相比,NNIC-Kmeans均衡的光正交频分复用系统误码率性能最好。展开更多
The reverse magnetohydrodynamic(MHD)energy bypass technology is a promising energy redis⁃tribution technology in the scramjet system,in augmented with a power generation equipment to supply the neces⁃sary long-distanc...The reverse magnetohydrodynamic(MHD)energy bypass technology is a promising energy redis⁃tribution technology in the scramjet system,in augmented with a power generation equipment to supply the neces⁃sary long-distance flight airframe power.In this paper,a computational model of the scramjet magnetohydrody⁃namic channel is developed and verified by using the commercial software Fluent.It is found that when the mag⁃netic induction intensity is 1,2,3,4 T,the power generation efficiency is 22.5%,22.3%,22.0%,21.5%,and decreases with the increase of the magnetic induction intensity,and the enthalpy extraction rate is 0.026%,0.1%,0.21%,0.34%,and increases with the increase of the magnetic induction intensity.The deceleration ef⁃fect of electromagnetic action on the airflow in the power channel increases with the increase of magnetic induc⁃tion intensity.The stronger the magnetic field intensity,the more obvious the decreasing effect of fluid Mach num⁃ber in the channel.The power generation efficiency decreases as the magnetic induction intensity increases and the enthalpy extraction rate is reversed.As the local currents gathering at inlet and outlet of the power generation area,total temperature and enthalpy along the flow direction do not vary linearly,and there are maximum and minimum values at inlet and outlet.Increasing the number of electrodes can effectively regulate the percentage of Joule heat dissipation,which can improve the power generation efficiency.展开更多
A novel variable step-size modified super-exponential iteration(MSEI)decision feedback blind equalization(DFE)algorithm with second-order digital phase-locked loop is put forward to improve the convergence performance...A novel variable step-size modified super-exponential iteration(MSEI)decision feedback blind equalization(DFE)algorithm with second-order digital phase-locked loop is put forward to improve the convergence performance of super-exponential iteration DFE algorithm.Based on the MSEI-DFE algorithm,it is first proposed to develop an error function as an improvement to the error function of MSEI,which effectively achieves faster convergence speed of the algorithm.Subsequently,a hyperbolic tangent function variable step-size algorithm is developed considering the high variation rate of the hyperbolic tangent function around zero,so as to further improve the convergence speed of the algorithm.In the end,a second-order digital phase-locked loop is introduced into the decision feedback equalizer to track and compensate for the phase rotation of equalizer input signals.For the multipath underwater acoustic channel with mixed phase and phase rotation,quadrature phase shift keying(QPSK)and 16 quadrature amplitude modulation(16QAM)modulated signals are used in the computer simulation of the algorithm in terms of convergence and carrier recovery performance.The results show that the proposed algorithm can considerably improve convergence speed and steady-state error,make effective compensation for phase rotation,and efficiently facilitate carrier recovery.展开更多
To reduce the negative impact of the power amplifier(PA)nonlinear distortion caused by the orthogonal frequency division multiplexing(OFDM)waveform with high peak-to-average power ratio(PAPR)in integrated radar and co...To reduce the negative impact of the power amplifier(PA)nonlinear distortion caused by the orthogonal frequency division multiplexing(OFDM)waveform with high peak-to-average power ratio(PAPR)in integrated radar and communication(RadCom)systems is studied,the channel estimation in passive sensing scenarios.Adaptive channel estimation methods are proposed based on different pilot patterns,considering nonlinear distortion and channel sparsity.The proposed methods achieve sparse channel results by manipulating the least squares(LS)frequency-domain channel estimation results to preserve the most significant taps.The decision-aided method is used to optimize the sparse channel results to reduce the effect of nonlinear distortion.Numerical results show that the channel estimation performance of the proposed methods is better than that of the conventional methods under different pilot patterns.In addition,the bit error rate performance in communication and passive radar detection performance show that the proposed methods have good comprehensive performance.展开更多
文摘Due to the complex high-temperature characteristics of hydrocarbon fuel,the research on the long-term working process of parallel channel structure under variable working conditions,especially under high heat-mass ratio,has not been systematically carried out.In this paper,the heat transfer and flow characteristics of related high temperature fuels are studied by using typical engine parallel channel structure.Through numeri⁃cal simulation and systematic experimental verification,the flow and heat transfer characteristics of parallel chan⁃nels under typical working conditions are obtained,and the effectiveness of high-precision calculation method is preliminarily established.It is known that the stable time required for hot start of regenerative cooling engine is about 50 s,and the flow resistance of parallel channel structure first increases and then decreases with the in⁃crease of equivalence ratio(The following equivalence ratio is expressed byΦ),and there is a flow resistance peak in the range ofΦ=0.5~0.8.This is mainly caused by the coupling effect of high temperature physical proper⁃ties,flow rate and pressure of fuel in parallel channels.At the same time,the cooling and heat transfer character⁃istics of parallel channels under some conditions of high heat-mass ratio are obtained,and the main factors affect⁃ing the heat transfer of parallel channels such as improving surface roughness and strengthening heat transfer are mastered.In the experiment,whenΦis less than 0.9,the phenomenon of local heat transfer enhancement and deterioration can be obviously observed,and the temperature rise of local structures exceeds 200℃,which is the risk of structural damage.Therefore,the reliability of long-term parallel channel structure under the condition of high heat-mass ratio should be fully considered in structural design.
基金supported by the Education and Teaching Research Project of Universities in Fujian Province(FBJY20230167).
文摘The work takes a new liquid-cooling plate in a power battery with pin fins inside the channel as the object.A mathematical model is established via the central composite design of the response surface to study the relationships among the length,width,height,and spacing of pin fins;the maximum temperature and temperature difference of the battery module;and the pressure drop of the liquid-cooling plate.Model accuracy is verified via variance analysis.The new liquid-cooling plate enables the power battery to work within an optimal temperature range.Appropriately increasing the length,width,and height and reducing the spacing of pin fins could reduce the temperature of the power battery module and improve the temperature uniformity.However,the pressure drop of the liquid-cooling plate increases.The structural parameters of the pin fins are optimized to minimize the maximum temperature and the temperature difference of the battery module as well as the pressure drop of the liquid-cooling plate.The errors between the values predicted and actual by the simulation test are 0.58%,4%,and 0.48%,respectively,which further verifies the model accuracy.The results reveal the influence of the structural parameters of the pin fins inside the liquid-cooling plate on its heat dissipation performance and pressure drop characteristics.A theoretical basis is provided for the design of liquid-cooling plates in power batteries and the optimization of structural parameters.
文摘For segmented detectors,surface flatness is critical as it directly influences both energy resolution and image clarity.Additionally,the limited adjustment range of the segmented detectors necessitates precise benchmark construction.This paper proposes an architecture for detecting detector flatness based on channel spectral dispersion.By measuring the dispersion fringes for coplanar adjustment,the final adjustment residual is improved to better than 300 nm.This result validates the feasibility of the proposed technology and provides significant technical support for the development of next-generation large-aperture sky survey equipment.
基金Project(52275350)supported by the National Natural Science Foundation of ChinaProject(0301006)supported by the International Cooperative Scientific Research Platform of SUES,China。
文摘In this study,the interaction between deformation and precipitates during multiple equal channel angular pressing(ECAP)deformations and inter-pass aging combination and its effect on the mechanical properties of 7050 aluminum alloy are studied.The result show that ECAP induces numerous substructures and dislocations,effectively promoting the precipitation of theηʹphase exhibiting a bimodal structure during inter-pass aging.Following inter-pass aging and subsequent ECAP,the decrease in grain size(4.8μm)is together with the increase in dislocation density(1.24×10^(15) m^(−2))due to the pinning effect of the precipitated phase.Simultaneously,the dislocation motion causes the second phase particles to become even finer and more diffuse.The synergistic effects of precipitation strengthening,fine grain strengthening,and dislocation strengthening collectively enhance the high strength of aluminum alloys,with ultimate tensile strength and yield strength reaching approximately 610 and 565 MPa,respectively.Meanwhile,ductility remains largely unchanged,primarily due to coordinated grain boundary sliding and the uniform and fine dispersion of second phase particles.
文摘Hypersonic Glide Vehicles(HGVs)are advanced aircraft that can achieve extremely high speeds(generally over 5 Mach)and maneuverability within the Earth's atmosphere.HGV trajectory prediction is crucial for effective defense planning and interception strategies.In recent years,HGV trajectory prediction methods based on deep learning have the great potential to significantly enhance prediction accuracy and efficiency.However,it's still challenging to strike a balance between improving prediction performance and reducing computation costs of the deep learning trajectory prediction models.To solve this problem,we propose a new deep learning framework(FECA-LSMN)for efficient HGV trajectory prediction.The model first uses a Frequency Enhanced Channel Attention(FECA)module to facilitate the fusion of different HGV trajectory features,and then subsequently employs a Light Sampling-oriented Multi-Layer Perceptron Network(LSMN)based on simple MLP-based structures to extract long/shortterm HGV trajectory features for accurate trajectory prediction.Also,we employ a new data normalization method called reversible instance normalization(RevIN)to enhance the prediction accuracy and training stability of the network.Compared to other popular trajectory prediction models based on LSTM,GRU and Transformer,our FECA-LSMN model achieves leading or comparable performance in terms of RMSE,MAE and MAPE metrics while demonstrating notably faster computation time.The ablation experiments show that the incorporation of the FECA module significantly improves the prediction performance of the network.The RevIN data normalization technique outperforms traditional min-max normalization as well.
基金supported by the National Key Scientific Instrument and Equipment Development Project(61827801).
文摘The fifth-generation (5G) communication requires a highly accurate estimation of the channel state information (CSI)to take advantage of the massive multiple-input multiple-output(MIMO) system. However, traditional channel estimation methods do not always yield reliable estimates. The methodology of this paper consists of deep residual shrinkage network (DRSN)neural network-based method that is used to solve this problem.Thus, the channel estimation approach, based on DRSN with its learning ability of noise-containing data, is first introduced. Then,the DRSN is used to train the noise reduction process based on the results of the least square (LS) channel estimation while applying the pilot frequency subcarriers, where the initially estimated subcarrier channel matrix is considered as a three-dimensional tensor of the DRSN input. Afterward, a mixed signal to noise ratio (SNR) training data strategy is proposed based on the learning ability of DRSN under different SNRs. Moreover, a joint mixed scenario training strategy is carried out to test the multi scenarios robustness of DRSN. As for the findings, the numerical results indicate that the DRSN method outperforms the spatial-frequency-temporal convolutional neural networks (SF-CNN)with similar computational complexity and achieves better advantages in the full SNR range than the minimum mean squared error (MMSE) estimator with a limited dataset. Moreover, the DRSN approach shows robustness in different propagation environments.
基金Project(U2202255)supported by the National Natural Science Foundation of ChinaProject(2024JJ2076)supported by the Hunan Provincial Natural Science Foundation of ChinaProject(2023Z092)supported by the Key Technology Research Program of Ningbo,China。
文摘In this paper,equal channel angular pressing and thermomechanical treatment was employed to improve the strength and electrical conductivity of an aging strengthened Cu-Ti-Cr-Mg alloy,and the microstructure and properties of the alloy were investigated in detail.The results showed that the samples deformed by the combination of cryogenic equal channel angular pressing(ECAP)and rolling had good comprehensive properties after aging at 400℃.The tensile strength of the peak-aged and over-aged samples was 1120 MPa and 940 MPa,with their corresponding electrical conductivity of 14.7%IACS and 22.1%IACS,respectively.ECAP and cryogenic rolling introduced high density dislocations,leading to the inhibition of the softening effects and refinement of the grains.After a long time aging at 400℃,the alloy exhibited ultra-high strength with obvious increasing electrical conductivity.The high strength was attributed to the synergistic effect of work hardening,grain refinement strengthening and precipitation strengthening.The precipitation of a large amount of Ti atoms from the matrix led to the high electrical conductivity of the over-aged sample.
基金financially supported by the National Natural Science Foundation of China(No.52074130)the Engineering Research Center of Resource Utilization of Carbon-containing Waste with Carbon Neutrality,Ministry of Education。
文摘Alkaline water electrolysis(AWE)is the most mature technology for hydrogen production by water electrolysis.Alkaline water electrolyzer consists of multiple electrolysis cells,and a single cell consists of a diaphragm,electrodes,bipolar plates and end plates,etc.The existing industrial bipolar plate channel is concave-convex structure,which is manufactured by complicated and high-cost mold punching.This structure still results in uneven electrolyte flow and low current density in the electrolytic cell,further increasing in energy consumption and cost of AWE.Thereby,in this article,the electrochemical and flow model is firstly constructed,based on the existing industrial concave and convex flow channel structure of bipolar plate,to study the current density,electrolyte flow and bubble distribution in the electrolysis cell.The reliability of the model was verified by comparison with experimental data in literature.Among which,the electrochemical current density affects the bubble yield,on the other hand,the generated bubbles cover the electrode surface,affecting the active specific surface area and ohmic resistance,which in turn affects the electrochemical reaction.The result indicates that the flow velocity near the bottom of the concave ball approaches zero,while the flow velocity on the convex ball surface is significantly higher.Additionally,vortices are observed within the flow channel structure,leading to an uneven distribution of electrolyte.Next,modelling is used to optimize the bipolar plate structure of AWE by simulating the electrochemistry and fluid flow performances of four kinds of structures,namely,concave and convex,rhombus,wedge and expanded mesh,in the bipolar plate of alkaline water electrolyzer.The results show that the expanded mesh channel structure has the largest current density of 3330 A/m^(2)and electrolyte flow velocity of 0.507 m/s in the electrolytic cell.Under the same current density,the electrolytic cell with the expanded mesh runner structure has the smallest potential and energy consumption.This work provides a useful guide for the comprehensive understanding and optimization of channel structures,and a theoretical basis for the design of large-scale electrolyzer.
文摘在室内可见光通信中符号间干扰和噪声会严重影响系统性能,K均值(K-means)均衡方法可以抑制光无线信道的影响,但其复杂度较高,且在聚类边界处易出现误判。提出了改进聚类中心点的K-means(Improved Center K-means,IC-Kmeans)算法,通过随机生成足够长的训练序列,然后将训练序列每一簇的均值作为K-means聚类中心,避免了传统K-means反复迭代寻找聚类中心。进一步,提出了基于神经网络的IC-Kmeans(Neural Network Based IC-Kmeans,NNIC-Kmeans)算法,使用反向传播神经网络将接收端二维数据映射至三维空间,以增加不同簇之间混合数据的距离,提高了分类准确性。蒙特卡罗误码率仿真表明,IC-Kmeans均衡和传统K-means算法的误码率性能相当,但可以显著降低复杂度,特别是在信噪比较小时。同时,在室内多径信道模型下,与IC-Kmeans和传统Kmeans均衡相比,NNIC-Kmeans均衡的光正交频分复用系统误码率性能最好。
文摘The reverse magnetohydrodynamic(MHD)energy bypass technology is a promising energy redis⁃tribution technology in the scramjet system,in augmented with a power generation equipment to supply the neces⁃sary long-distance flight airframe power.In this paper,a computational model of the scramjet magnetohydrody⁃namic channel is developed and verified by using the commercial software Fluent.It is found that when the mag⁃netic induction intensity is 1,2,3,4 T,the power generation efficiency is 22.5%,22.3%,22.0%,21.5%,and decreases with the increase of the magnetic induction intensity,and the enthalpy extraction rate is 0.026%,0.1%,0.21%,0.34%,and increases with the increase of the magnetic induction intensity.The deceleration ef⁃fect of electromagnetic action on the airflow in the power channel increases with the increase of magnetic induc⁃tion intensity.The stronger the magnetic field intensity,the more obvious the decreasing effect of fluid Mach num⁃ber in the channel.The power generation efficiency decreases as the magnetic induction intensity increases and the enthalpy extraction rate is reversed.As the local currents gathering at inlet and outlet of the power generation area,total temperature and enthalpy along the flow direction do not vary linearly,and there are maximum and minimum values at inlet and outlet.Increasing the number of electrodes can effectively regulate the percentage of Joule heat dissipation,which can improve the power generation efficiency.
基金supported by the National Natural Science Foundation of China(61671461)。
文摘A novel variable step-size modified super-exponential iteration(MSEI)decision feedback blind equalization(DFE)algorithm with second-order digital phase-locked loop is put forward to improve the convergence performance of super-exponential iteration DFE algorithm.Based on the MSEI-DFE algorithm,it is first proposed to develop an error function as an improvement to the error function of MSEI,which effectively achieves faster convergence speed of the algorithm.Subsequently,a hyperbolic tangent function variable step-size algorithm is developed considering the high variation rate of the hyperbolic tangent function around zero,so as to further improve the convergence speed of the algorithm.In the end,a second-order digital phase-locked loop is introduced into the decision feedback equalizer to track and compensate for the phase rotation of equalizer input signals.For the multipath underwater acoustic channel with mixed phase and phase rotation,quadrature phase shift keying(QPSK)and 16 quadrature amplitude modulation(16QAM)modulated signals are used in the computer simulation of the algorithm in terms of convergence and carrier recovery performance.The results show that the proposed algorithm can considerably improve convergence speed and steady-state error,make effective compensation for phase rotation,and efficiently facilitate carrier recovery.
基金supported by the National Natural Science Foundation of China(61931015,62071335,62250024)the Natural Science Foundation of Hubei Province of China(2021CFA002)+1 种基金the Fundamental Research Funds for the Central Universities of China(2042022dx0001)the Science and Technology Program of Shenzhen(JCYJ20170818112037398).
文摘To reduce the negative impact of the power amplifier(PA)nonlinear distortion caused by the orthogonal frequency division multiplexing(OFDM)waveform with high peak-to-average power ratio(PAPR)in integrated radar and communication(RadCom)systems is studied,the channel estimation in passive sensing scenarios.Adaptive channel estimation methods are proposed based on different pilot patterns,considering nonlinear distortion and channel sparsity.The proposed methods achieve sparse channel results by manipulating the least squares(LS)frequency-domain channel estimation results to preserve the most significant taps.The decision-aided method is used to optimize the sparse channel results to reduce the effect of nonlinear distortion.Numerical results show that the channel estimation performance of the proposed methods is better than that of the conventional methods under different pilot patterns.In addition,the bit error rate performance in communication and passive radar detection performance show that the proposed methods have good comprehensive performance.
