High-resolution solar observations are critical for resolving small-scale dynamic solar processes.Specifically,solar continuum observations,which are used to characterize the photospheric radiative energy distribution...High-resolution solar observations are critical for resolving small-scale dynamic solar processes.Specifically,solar continuum observations,which are used to characterize the photospheric radiative energy distribution,identify atmospheric temperature gradients,and model space weather events,serve as a cornerstone of solar physics research.However,existing observational frameworks face inherent limitations:space-based instruments are constrained by diffraction limits,while ground-based data suffer from atmospheric turbulence and temporal discontinuity.To address these challenges,this study proposes a resolution enhancement method based on cross-platform data fusion between Solar Dynamics Observatory(SDO)/Helioseismic and Magnetic Imager(HMI)space-based full-disk coverage observations and Optical and Near-infrared Solar Eruption Telescope(ONSET)ground-based high-resolution local observations to overcome the physical limitations faced by single-instrument observations.Using 6537 preprocessed spatiotemporally aligned datasets(from 2022),we achieve sub-pixel registration via the scale-invariant feature transform(SIFT)algorithm and design a lightweight model called Cross-Instrument Super-Resolution(CISR)based on a residual local feature block network,optimized for feature extraction and reconstruction using the smooth L1-loss function.Experimental results demonstrate that CISR achieves a pixel-wise correlation coefficient of 0.946,a peak signal-to-noise ratio(PSNR)of 33.924 dB,and a structural similarity index of 0.855 on the test set,significantly outperforming bicubic interpolation and the Super-Resolution Convolutional Neural Network(SRCNN)baseline model.Qualitative visual assessment verifies the method’s efficacy for HMI continuum data resolution enhancement,with exceptional performance in maintaining both sunspot boundary acuity and granule structural fidelity.This work provides a novel approach for multi-source solar data synergy,with future potential to incorporate physics-driven evaluation metrics to further improve the model generalization.展开更多
The dual challenges of critical speed prediction inaccuracies and ambiguous vibration behaviors are present in high-speed flexible rotors,particularly in free turbine rotors in turboshaft engine systems.The study begi...The dual challenges of critical speed prediction inaccuracies and ambiguous vibration behaviors are present in high-speed flexible rotors,particularly in free turbine rotors in turboshaft engine systems.The study begins with an examination of the rotor-bearing bidirectional coupling mechanism,with a primary focus on the nonlinear characteristics of the bearing.An investigation is carried out on the mechanical modeling methodologies for four-point contact ball bearings(FPCBBs)and cylindrical roller bearings(CRBs).To address the issue of excessive computational time in traditional bearing calculation methods,the sled dog optimization(SDO)algorithm is substituted for the conventional Newton-Raphson method.A rotor-bearing coupling dynamics model is developed by the finite element and lumped mass methods,with experimental validation achieved through a simulator test rig.The effects of three internal bearing parameters in FPCBBs(arching width and raceway groove curvature coefficient)and CRBs(initial radial clearance)on the critical speed characteristics and vibrational behavior of rotorbearing coupled systems are examined.The numerical simulation results show some interesting conclusions.展开更多
基金supported by the National Natural Science Foundation of China(12003068)the Yunnan Key Laboratory of Solar Physics and Space Science(202205AG070009).
文摘High-resolution solar observations are critical for resolving small-scale dynamic solar processes.Specifically,solar continuum observations,which are used to characterize the photospheric radiative energy distribution,identify atmospheric temperature gradients,and model space weather events,serve as a cornerstone of solar physics research.However,existing observational frameworks face inherent limitations:space-based instruments are constrained by diffraction limits,while ground-based data suffer from atmospheric turbulence and temporal discontinuity.To address these challenges,this study proposes a resolution enhancement method based on cross-platform data fusion between Solar Dynamics Observatory(SDO)/Helioseismic and Magnetic Imager(HMI)space-based full-disk coverage observations and Optical and Near-infrared Solar Eruption Telescope(ONSET)ground-based high-resolution local observations to overcome the physical limitations faced by single-instrument observations.Using 6537 preprocessed spatiotemporally aligned datasets(from 2022),we achieve sub-pixel registration via the scale-invariant feature transform(SIFT)algorithm and design a lightweight model called Cross-Instrument Super-Resolution(CISR)based on a residual local feature block network,optimized for feature extraction and reconstruction using the smooth L1-loss function.Experimental results demonstrate that CISR achieves a pixel-wise correlation coefficient of 0.946,a peak signal-to-noise ratio(PSNR)of 33.924 dB,and a structural similarity index of 0.855 on the test set,significantly outperforming bicubic interpolation and the Super-Resolution Convolutional Neural Network(SRCNN)baseline model.Qualitative visual assessment verifies the method’s efficacy for HMI continuum data resolution enhancement,with exceptional performance in maintaining both sunspot boundary acuity and granule structural fidelity.This work provides a novel approach for multi-source solar data synergy,with future potential to incorporate physics-driven evaluation metrics to further improve the model generalization.
文摘The dual challenges of critical speed prediction inaccuracies and ambiguous vibration behaviors are present in high-speed flexible rotors,particularly in free turbine rotors in turboshaft engine systems.The study begins with an examination of the rotor-bearing bidirectional coupling mechanism,with a primary focus on the nonlinear characteristics of the bearing.An investigation is carried out on the mechanical modeling methodologies for four-point contact ball bearings(FPCBBs)and cylindrical roller bearings(CRBs).To address the issue of excessive computational time in traditional bearing calculation methods,the sled dog optimization(SDO)algorithm is substituted for the conventional Newton-Raphson method.A rotor-bearing coupling dynamics model is developed by the finite element and lumped mass methods,with experimental validation achieved through a simulator test rig.The effects of three internal bearing parameters in FPCBBs(arching width and raceway groove curvature coefficient)and CRBs(initial radial clearance)on the critical speed characteristics and vibrational behavior of rotorbearing coupled systems are examined.The numerical simulation results show some interesting conclusions.
