Ceramic oxides,renowned for their exceptional combination of mechanical,thermal,and chemical properties,are indispensable in numerous crucial applications across diverse engineering fields.However,conventional manufac...Ceramic oxides,renowned for their exceptional combination of mechanical,thermal,and chemical properties,are indispensable in numerous crucial applications across diverse engineering fields.However,conventional manufacturing methods frequently grapple with limitations,such as challenges in shaping intricate geometries,extended processing durations,elevated porosity,and substantial shrinkage deformations.Direct additive manufacturing(dAM)technology stands out as a state-of-the-art solution for ceramic oxides production.It facilitates the one-step fabrication of high-performance,intricately designed components characterized by dense structures.Importantly,dAM eliminates the necessity for post-heat treatments,streamlining the manufacturing process and enhancing overall efficiency.This study undertakes a comprehensive review of recent developments in dAM for ceramic oxides,with a specific emphasis on the laser powder bed fusion and laser directed energy deposition techniques.A thorough investigation is conducted into the shaping quality,microstructure,and properties of diverse ceramic oxides produced through dAM.Critical examination is given to key aspects including feedstock preparation,laser-material coupling,formation and control of defects,in-situ monitoring and simulation.This paper concludes by outlining future trends and potential breakthrough directions,taking into account current gaps in this rapidly evolving field.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
To detect space gravitational waves in the extremely low-frequency band,the telescope and optic-al platform require high stability and reliability.However,the cantilevered design presents challenges,espe-cially in the...To detect space gravitational waves in the extremely low-frequency band,the telescope and optic-al platform require high stability and reliability.However,the cantilevered design presents challenges,espe-cially in the glass-metal hetero-bonding process.This study focuses on the analysis and experimental re-search of the bonding layer in the integrated structure.By optimizing the structural configuration and select-ing suitable bonding processes,the reliability of the telescope system is enhanced.The research indicates that using J-133 adhesive achieves the best performance,with a bonding layer thickness of 0.30 mm and a metal substrate surface roughness of Ra 0.8.These findings significantly enhance the reliability of the optical sys-tem while minimizing potential risks.展开更多
Permanent magnet synchronous motor(PMSM),known for their compact size and high-power density,is widely used in fields such as electric vehicles and servo drives.However,traditional PID control methods for PMSM cannot ...Permanent magnet synchronous motor(PMSM),known for their compact size and high-power density,is widely used in fields such as electric vehicles and servo drives.However,traditional PID control methods for PMSM cannot dynamically adjust parameters according to varying operating conditions.To address this issue,this paper proposes a PID control method based on a radial basis function(RBF)neural network,which adaptively tunes the PID controller parameters.First,an offline RBF neural network with optimal structural parameters is trained using the current and speed data of the PMSM,and then employed to construct the RBF-PID controller.During online training,the Jacobian information calculated via the RBF neural network is used to adaptively adjust the PID parameters.Simultaneously,the structural parameters of the RBF network are updated in reverse based on the error between the predicted and reference speed values.Finally,numerical simulations and experiments in the context of electric vehicle drive control show that the maximum speed errors of the SMC controller and the RBF-PID controller are 1.97 km/h and 0.17 km/h,respectively.Moreover,the RBF-PID controller outperforms both the SMC and traditional PID controllers in handling sudden speed changes.展开更多
Sodium-ion batteries(SIBs)have emerged as a promising alternative to commercial lithium-ion batteries be-cause of the similar properties of Li and Na as well as the abundance and accessibility of sodium resources.The ...Sodium-ion batteries(SIBs)have emerged as a promising alternative to commercial lithium-ion batteries be-cause of the similar properties of Li and Na as well as the abundance and accessibility of sodium resources.The devel-opment of anode materials with a high capacity,excellent rate performance,and long cycle life is the key to the indus-trialization of SIBs.Biomass-derived carbon(BDC)anode materials synthesized from resource-rich,low-cost,and re-newable biomass have been extensively researched and their excellent sodium storage performance has been proven,making them the most promising new low-cost and high-performance anode material for SIBs.This review first intro-duces the sources of BDCs,including waste biomass such as plants,animals,and microorganisms,and then describes sev-eral methods for preparing BDC anode materials,including carbonization,chemical activation,and template methods.The storage mechanism and kinetic process of Na^(+)in BDCs are then considered as well as their structure control.The electrochemical properties of sodium-ion storage in BDCs with different structures are examined,and suggestions for future re-search are made.展开更多
The semiconductor bridge(SCB)ignites through bridge film discharge,offering advantages such as low ignition energy,high safety,and compatibility with digital logic circuits.The study uses laser interferometry to inves...The semiconductor bridge(SCB)ignites through bridge film discharge,offering advantages such as low ignition energy,high safety,and compatibility with digital logic circuits.The study uses laser interferometry to investigate the gas dynamics of the bridge film after SCB plasma extinction.Interferometric images of the SCB film gas were obtained through a laser interferometry optical path.After the degradation model of digital image processing,clearer images were produced to facilitate analysis and calculation.The results show that the gas temperature at the center of the SCB film reaches a maximum of 1000 K,and the temperature rapidly decreases along the axial direction of the bridge surface to room temperature at 300 K.The maximum diffusion velocity of the plasma is 1.8 km/s.These findings provide critical insights for SCB design and ignition control.展开更多
ZIF-8 is widely applied in lubrication,adsorption,and catalysis owing to its unique physicochemical properties.Previous experimental studies have demonstrated its feasibility as a lubricant additive.In the present wor...ZIF-8 is widely applied in lubrication,adsorption,and catalysis owing to its unique physicochemical properties.Previous experimental studies have demonstrated its feasibility as a lubricant additive.In the present work,the lubricating performance of ZIF-8 as an additive to lithiumbased grease is quantitatively and dynamically analyzed at the atomic scale using molecular dynamics simulations.Friction wear experiments are also conducted to elucidate the lubrication mechanism of ZIF-8.The simulation and experimental results indicate that the incorporation of ZIF-8 effectively enhances the antifriction and antiwear characteristics of lithium grease.The most significant improvement in the lubrication performance of the grease is obtained at a mass fraction of 2.0 wt.%ZIF-8,which reduces the friction factorof the grease by about 17.0%and the wear by40.0%.Furthermore,the molecular dynamics simulations reveal that ZIF-8 primarily functions as a ball bearing under low-load conditions.However,under high-load conditions,ZIF-8 undergoes significant deformation and primarily acts as a filler.This explains the experimentally observed significant reduction in friction coefficient after the addition of ZIF-8.The results of this study provide a theoretical foundation for the development of new environmentally friendly grease additives.展开更多
During direct chilling(DC)casting of ZK61 alloys,the primary and secondary cooling causes strong thermal gradients,which leads to the uneven crystallization rate and thermal contraction in different positions of the i...During direct chilling(DC)casting of ZK61 alloys,the primary and secondary cooling causes strong thermal gradients,which leads to the uneven crystallization rate and thermal contraction in different positions of the ingot.The consequences manifested appearance of heterogeneous grains,huge casting stresses,and even hot cracking flaws.In this paper,chemical and physical methods were integrated to produce large-scale magnesium(Mg)alloy ingots.A φ525 mm ZK61-RE alloy ingot that was refined,homogeneous,and free from hot cracking was obtained via the DC process coupled with a differential low frequency pulsed magnetic field(DLPM).The effects of rare earth(RE)and DLPM on the hot cracking tendency were investigated,and the mechanism of hot cracking formation and modification in largescale ingots was revealed.The findings indicate that the addition of moderate amounts of RE lessens the tendency of hot cracking in large-scale ZK61 alloy ingots.This is mainly attributed to the addition of RE increases the content of the second phase,thus enhancing the ability of the eutectic liquid phase to feed the cracking.With the introduction of DLPM,the grain sizes are significantly refined and homogenized,and there is no obvious hot cracking observed in the ingot.This is because the coupling of the DLPM provides a more homogeneous temperature field,leading to the synchronization of the solidification process,and the consequent reduction of the casting stress,thus reducing the driving force for the formation of hot cracking.In addition,the casting conditions are modified to enhance the ability of solidification feeding and the resistance to hot cracking.This work provides theoretical and practical references for the preparation of large-scale high-quality Mg alloy ingots.展开更多
Workpiece rotational grinding is widely used in the ultra-precision machining of hard and brittle semiconductor materials,including single-crystal silicon,silicon carbide,and gallium arsenide.Surface roughness and sub...Workpiece rotational grinding is widely used in the ultra-precision machining of hard and brittle semiconductor materials,including single-crystal silicon,silicon carbide,and gallium arsenide.Surface roughness and subsurface damage depth(SDD)are crucial indicators for evaluating the surface quality of these materials after grinding.Existing prediction models lack general applicability and do not accurately account for the complex material behavior under grinding conditions.This paper introduces novel models for predicting both surface roughness and SDD in hard and brittle semiconductor materials.The surface roughness model uniquely incorporates the material’s elastic recovery properties,revealing the significant impact of these properties on prediction accuracy.The SDD model is distinguished by its analysis of the interactions between abrasive grits and the workpiece,as well as the mechanisms governing stress-induced damage evolution.The surface roughness model and SDD model both establish a stable relationship with the grit depth of cut(GDC).Additionally,we have developed an analytical relationship between the GDC and grinding process parameters.This,in turn,enables the establishment of an analytical framework for predicting surface roughness and SDD based on grinding process parameters,which cannot be achieved by previous models.The models were validated through systematic experiments on three different semiconductor materials,demonstrating excellent agreement with experimental data,with prediction errors of 6.3%for surface roughness and6.9%for SDD.Additionally,this study identifies variations in elastic recovery and material plasticity as critical factors influencing surface roughness and SDD across different materials.These findings significantly advance the accuracy of predictive models and broaden their applicability for grinding hard and brittle semiconductor materials.展开更多
BACKGROUND Obstructive sleep apnea-hypopnea syndrome(OSAHS)is a highly prevalent sleep-related respiratory disorder associated with serious health risks.Although polysomnography is the clinical gold standard for diagn...BACKGROUND Obstructive sleep apnea-hypopnea syndrome(OSAHS)is a highly prevalent sleep-related respiratory disorder associated with serious health risks.Although polysomnography is the clinical gold standard for diagnosis,it is expensive,in-convenient,and unsuitable for population-level screening due to the need for professional scoring and overnight monitoring.AIM To address these limitations,this review aims to systematically analyze recent ad-vances in deep learning–based OSAHS detection methods using snoring sounds,particularly focusing on graphical signal representations and network architec-tures.METHODS A comprehensive literature search was conducted following the PRISMA 2009 guidelines,covering publications from 2010 to 2025.Studies were included based on predefined criteria involving the use of deep learning models on snoring sounds transformed into graphical representations such as spectrograms and scalograms.A total of 14 studies were selected for in-depth analysis.RESULTS This review summarizes the types of signal modalities,datasets,feature extraction methods,and classification frameworks used in the current literatures.The strengths and limitations of different deep network architectures are evaluated.CONCLUSION Challenges such as dataset variability,generalizability,model interpretability,and deployment feasibility are also discussed.Future directions highlight the importance of explainable artificial intelligence and domain-adaptive learning for clinically viable OSAHS diagnostic tools.展开更多
Graphene nanoplatelets(GNPs)reinforced A380 composites(GNPs/A380 composites)were prepared by ultrasonic vibration casting method.The microstructure,aging behavior and mechanical properties of the composites were inves...Graphene nanoplatelets(GNPs)reinforced A380 composites(GNPs/A380 composites)were prepared by ultrasonic vibration casting method.The microstructure,aging behavior and mechanical properties of the composites were investigated.It was found that the peak aging time of GNPs/A380 composites could be decreased by GNPs.The GNPs-Al interface could serve as a more stable nucleation site for the precipitated phases.With bridging GNPs,the coordinated deformation of the matrix is increased and larger dimples appear on the fracture surface of GNPs/A380 composites.The yield strength of the GNPs/A380 composites increased by 28.1%compared with that of the A380 alloy due to the fine grain strengthening,load transfer and precipitation strengthening mechanisms.展开更多
This paper introduces a novel numerical method based on an energy-minimizing normalized residual network(EMNorm Res Net)to compute the ground-state solution of Bose-Einstein condensates at zero or low temperatures.Sta...This paper introduces a novel numerical method based on an energy-minimizing normalized residual network(EMNorm Res Net)to compute the ground-state solution of Bose-Einstein condensates at zero or low temperatures.Starting from the three-dimensional Gross-Pitaevskii equation(GPE),we reduce it to the 1D and 2D GPEs because of the radial symmetry and cylindrical symmetry.The ground-state solution is formulated by minimizing the energy functional under constraints,which is directly solved using the EM-Norm Res Net approach.The paper provides detailed solutions for the ground states in 1D,2D(with radial symmetry),and 3D(with cylindrical symmetry).We use the Thomas-Fermi approximation as the target function to pre-train the neural network.Then,the formal network is trained using the energy minimization method.In contrast to traditional numerical methods,our neural network approach introduces two key innovations:(i)a novel normalization technique designed for high-dimensional systems within an energy-based loss function;(ii)improved training efficiency and model robustness by incorporating gradient stabilization techniques into residual networks.Extensive numerical experiments validate the method's accuracy across different spatial dimensions.展开更多
Based on the relationship between deformation microstructures and grain orientations,three characteristic Cu single crystals were used to investigate the opposite effects of ultrasonic superimposed high-strain-rate on...Based on the relationship between deformation microstructures and grain orientations,three characteristic Cu single crystals were used to investigate the opposite effects of ultrasonic superimposed high-strain-rate on the dislocation motion during ultrasonic welding(UW).The results revealed that equiaxed dislocation cells and discontinuous dynamic recrystallization(DRX)grains dominated in the joint microstructures.Three Cu single crystal joints exhibited an isotropic trend in grain orientation,welding quality,and microscopic mechanical properties.The preferred dislocation behaviors and DRX modes were further analyzed by modelling the stored energy difference,indicating that high mobility of intra-granular dislocations and homogeneous dislocation motion induced by the ultrasonic excitation were the intrinsic factors contributing to the formation of isotropic microstructures and welding quality.展开更多
This paper considers the swarm vigilance problem for multi-agent systems(MAS),where multiple agents are deployed within a rectangular region for perception-based vigilance.There are two main challenges,namely the task...This paper considers the swarm vigilance problem for multi-agent systems(MAS),where multiple agents are deployed within a rectangular region for perception-based vigilance.There are two main challenges,namely the task allocation for vigilance roles and the coverage planning of the perception ranges.Firstly,vigilance behavioral patterns and processes in animal populations within natural habitats are investigated.Inspired by these biological vigilance behaviors,an efficient vigilance task allocation model for MAS is proposed.Secondly,the subsequent optimization of task layouts can achieve efficient surveillance coverage with fewer agents,minimizing resource consumption.Thirdly,an improved particle swarm optimization(IPSO)algorithm is proposed,which incorporates fitness-driven adaptive inertia weight dynamics.According to simulation analysis and comparative studies,optimal parameter configurations for genetic algorithm(GA)and IPSO are determined.Finally,the results indicate the proposed IPSO's superior performance to both GA and standard particle swarm optimization(PSO)in vigilance task allocation optimization,with satisfying advantages in computational efficiency and solution quality.展开更多
For permanent magnet synchronous machines(PMSMs),accurate inductance is critical for control design and condition monitoring.Owing to magnetic saturation,existing methods require nonlinear saturation model and measure...For permanent magnet synchronous machines(PMSMs),accurate inductance is critical for control design and condition monitoring.Owing to magnetic saturation,existing methods require nonlinear saturation model and measurements from multiple load/current conditions,and the estimation is relying on the accuracy of saturation model and other machine parameters in the model.Speed harmonic produced by harmonic currents is inductance-dependent,and thus this paper explores the use of magnitude and phase angle of the speed harmonic for accurate inductance estimation.Two estimation models are built based on either the magnitude or phase angle,and the inductances can be from d-axis voltage and the magnitude or phase angle,in which the filter influence in harmonic extraction is considered to ensure the estimation performance.The inductances can be estimated from the measurements under one load condition,which is free of saturation model.Moreover,the inductance estimation is robust to the change of other machine parameters.The proposed approach can effectively improve estimation accuracy especially under the condition with low current magnitude.Experiments and comparisons are conducted on a test PMSM to validate the proposed approach.展开更多
A structured method to generate conformal finite element(FE)mesh for realistic 3D woven textile reinforced composite is proposed.It is based on a voxel structure mesh reconstruction framework and aims to provide accur...A structured method to generate conformal finite element(FE)mesh for realistic 3D woven textile reinforced composite is proposed.It is based on a voxel structure mesh reconstruction framework and aims to provide accurate composite model at yarn level with material properties ready for use in commercial FE software.The textile representative volume element(RVE)is generated at filament level implementing the digital element method.Yarn structure is determined by filament bundle with variant cross-section shapes along its path.Yarn surface is then extracted using the Delaunay triangulation algorithm and a surface mesh is initiated.Then,the mesh domain is defined and constructed by voxel structure.Periodic boundary conditions,inter-yarn,and yarnmatrix interfaces are eliminated by re-mesh and mesh optimization.An element splitting rule is established to split the voxel unit into sub-elements to create smooth interface.A 3D orthogonal weave fabric reinforced composite is generated and simulated under compressive load.The composite structure and damage morphology are in good agreement with those of the experiment.展开更多
Atmospheric turbulence is an important parameter affecting laser atmospheric transmission.This paper reports on a self-developed atmospheric turbulence detection Li DAR system(scanning differential image motion Li DAR...Atmospheric turbulence is an important parameter affecting laser atmospheric transmission.This paper reports on a self-developed atmospheric turbulence detection Li DAR system(scanning differential image motion Li DAR(DIM-Li DAR)system).By designing and simulating the optical system of atmospheric turbulence detection Li DAR,the basic optical imaging accuracy has been determined.展开更多
In permanent magnet synchronous machine(PMSM) drives, temperature information is critical to achieve reliable and high-performance control. The popular model-based estimation methods are based on extracting temperatur...In permanent magnet synchronous machine(PMSM) drives, temperature information is critical to achieve reliable and high-performance control. The popular model-based estimation methods are based on extracting temperature dependent terms from the voltages using the machine model. The estimation accuracy under low speed or load can be greatly affected by the model uncertainty and noise due to low signal-tonoise ratio. This paper presents a high frequency(HF) position offset injection-based winding and permanent magnet(PM) temperature decoupled estimation approach for PMSMs to achieve accurate and robust temperature estimation among a wide speed range especially under low-speed conditions. In the proposed approach, a small HF position offset is injected into the machine to construct a decoupled winding and PM temperature estimation model, in which the winding and PM temperatures are independently estimated from HF excitations. The temperature estimation is independent from the fundamental model and parameter variation, and it achieves high signal-tonoise ratio under low-speed conditions. Moreover, the temperature estimation is also not affected by magnetic saturation and inverter distortion, which can improve the accuracy and robustness of temperature estimation. The proposed approach is validated with experiments and comparisons on a laboratory machine under various operating conditions.展开更多
This paper addresses the parallel control of autonomous surface vehicles subject to external disturbances,state constraints,and input constraints in complex ocean environments with multiple obstacles.A safety-certifie...This paper addresses the parallel control of autonomous surface vehicles subject to external disturbances,state constraints,and input constraints in complex ocean environments with multiple obstacles.A safety-certified parallel model predictive control scheme with collision-avoiding capability is proposed for autonomous surface vehicles in the framework of parallel control.Specifically,an extended state observer is designed by leveraging historical and real-time data for concurrent learning to map the motion of autonomous surface vehicles from its physical system to its artificial counterpart.A parallel model predictive control law is developed on the basis of the artificial system for both physical and artificial autonomous surface vehicles to realize virtual-physical tracking control of vehicles subject to state and input constraints.To ensure safety,highorder discrete control barrier functions are encoded in the parallel model predictive control law as safety constraints such that collision avoidance with obstacles can be achieved.A recedinghorizon constrained optimization problem is constructed with the safety constraints encoded by control barrier functions for parallel model predictive control of autonomous surface vehicles and solved via neurodynamic optimization with projection neural networks.The effectiveness and characteristics of the proposed method are demonstrated via simulations for the safe trajectory tracking and automatic berthing of autonomous surface vehicles.展开更多
Implants are inevitably subjected to stress corrosion,bringing serious challenges to the controlled degradation of biomedical Mg alloys.It is worth studying the stress corrosion cracking(SCC)behavior of Mg alloy and e...Implants are inevitably subjected to stress corrosion,bringing serious challenges to the controlled degradation of biomedical Mg alloys.It is worth studying the stress corrosion cracking(SCC)behavior of Mg alloy and exploring Mg alloy with good SCC resistance for wide biomedical applications.In this work,the as-cast and as-extruded Mg-3Gd-1Zn-0.4Zr(GZ31K)alloys with uniform corrosion were used to investigate SCC behavior.The as-extruded GZ31K alloy exhibited better corrosion resistance and mechanical properties than the as-cast one mainly owing to grain refinement and uniformly distributed fine precipitates,and possessed superior SCC resistance.To clarify the SCC mechanism,the slow strain rate tests were assisted with applied constant potentials via an electrochemical workstation.Accelerated anodic dissolution at anodic polarization deteriorated SCC resistance due to the initiation of corrosion pits and micro-cracks.However,cathodic polarization had no obvious effects on SCC resistance,along with both retarded corrosion and accelerated hydrogen evolution.Stacking faults in GZ31K alloy were hydrogen capture containers to reduce the effect of hydrogen on SCC resistance during cathodic polarization.These findings provide new insights into the evaluation of SCC mechanism,and offer more opportunities to explore Mg alloys with good SCC resistance by regulating anodic dissolution.展开更多
基金financially supported by the National Natural Science Foundation of China(Grant Nos:52305502,U23B6005,52293405)China Postdoctoral Science Foundation(Grant No:2023M732788)the Postdoctoral Research Project of Shaanxi Province.
文摘Ceramic oxides,renowned for their exceptional combination of mechanical,thermal,and chemical properties,are indispensable in numerous crucial applications across diverse engineering fields.However,conventional manufacturing methods frequently grapple with limitations,such as challenges in shaping intricate geometries,extended processing durations,elevated porosity,and substantial shrinkage deformations.Direct additive manufacturing(dAM)technology stands out as a state-of-the-art solution for ceramic oxides production.It facilitates the one-step fabrication of high-performance,intricately designed components characterized by dense structures.Importantly,dAM eliminates the necessity for post-heat treatments,streamlining the manufacturing process and enhancing overall efficiency.This study undertakes a comprehensive review of recent developments in dAM for ceramic oxides,with a specific emphasis on the laser powder bed fusion and laser directed energy deposition techniques.A thorough investigation is conducted into the shaping quality,microstructure,and properties of diverse ceramic oxides produced through dAM.Critical examination is given to key aspects including feedstock preparation,laser-material coupling,formation and control of defects,in-situ monitoring and simulation.This paper concludes by outlining future trends and potential breakthrough directions,taking into account current gaps in this rapidly evolving field.
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.
文摘To detect space gravitational waves in the extremely low-frequency band,the telescope and optic-al platform require high stability and reliability.However,the cantilevered design presents challenges,espe-cially in the glass-metal hetero-bonding process.This study focuses on the analysis and experimental re-search of the bonding layer in the integrated structure.By optimizing the structural configuration and select-ing suitable bonding processes,the reliability of the telescope system is enhanced.The research indicates that using J-133 adhesive achieves the best performance,with a bonding layer thickness of 0.30 mm and a metal substrate surface roughness of Ra 0.8.These findings significantly enhance the reliability of the optical sys-tem while minimizing potential risks.
文摘Permanent magnet synchronous motor(PMSM),known for their compact size and high-power density,is widely used in fields such as electric vehicles and servo drives.However,traditional PID control methods for PMSM cannot dynamically adjust parameters according to varying operating conditions.To address this issue,this paper proposes a PID control method based on a radial basis function(RBF)neural network,which adaptively tunes the PID controller parameters.First,an offline RBF neural network with optimal structural parameters is trained using the current and speed data of the PMSM,and then employed to construct the RBF-PID controller.During online training,the Jacobian information calculated via the RBF neural network is used to adaptively adjust the PID parameters.Simultaneously,the structural parameters of the RBF network are updated in reverse based on the error between the predicted and reference speed values.Finally,numerical simulations and experiments in the context of electric vehicle drive control show that the maximum speed errors of the SMC controller and the RBF-PID controller are 1.97 km/h and 0.17 km/h,respectively.Moreover,the RBF-PID controller outperforms both the SMC and traditional PID controllers in handling sudden speed changes.
文摘Sodium-ion batteries(SIBs)have emerged as a promising alternative to commercial lithium-ion batteries be-cause of the similar properties of Li and Na as well as the abundance and accessibility of sodium resources.The devel-opment of anode materials with a high capacity,excellent rate performance,and long cycle life is the key to the indus-trialization of SIBs.Biomass-derived carbon(BDC)anode materials synthesized from resource-rich,low-cost,and re-newable biomass have been extensively researched and their excellent sodium storage performance has been proven,making them the most promising new low-cost and high-performance anode material for SIBs.This review first intro-duces the sources of BDCs,including waste biomass such as plants,animals,and microorganisms,and then describes sev-eral methods for preparing BDC anode materials,including carbonization,chemical activation,and template methods.The storage mechanism and kinetic process of Na^(+)in BDCs are then considered as well as their structure control.The electrochemical properties of sodium-ion storage in BDCs with different structures are examined,and suggestions for future re-search are made.
基金supported by the Anhui Zhongchuang Energy New Energy Technology Co.,Ltd.,Entrusted Project.
文摘The semiconductor bridge(SCB)ignites through bridge film discharge,offering advantages such as low ignition energy,high safety,and compatibility with digital logic circuits.The study uses laser interferometry to investigate the gas dynamics of the bridge film after SCB plasma extinction.Interferometric images of the SCB film gas were obtained through a laser interferometry optical path.After the degradation model of digital image processing,clearer images were produced to facilitate analysis and calculation.The results show that the gas temperature at the center of the SCB film reaches a maximum of 1000 K,and the temperature rapidly decreases along the axial direction of the bridge surface to room temperature at 300 K.The maximum diffusion velocity of the plasma is 1.8 km/s.These findings provide critical insights for SCB design and ignition control.
基金supported by the National Natural Science Foundation of China(52275178)the Fujian Industry University Cooperation Project(2020H6025)。
文摘ZIF-8 is widely applied in lubrication,adsorption,and catalysis owing to its unique physicochemical properties.Previous experimental studies have demonstrated its feasibility as a lubricant additive.In the present work,the lubricating performance of ZIF-8 as an additive to lithiumbased grease is quantitatively and dynamically analyzed at the atomic scale using molecular dynamics simulations.Friction wear experiments are also conducted to elucidate the lubrication mechanism of ZIF-8.The simulation and experimental results indicate that the incorporation of ZIF-8 effectively enhances the antifriction and antiwear characteristics of lithium grease.The most significant improvement in the lubrication performance of the grease is obtained at a mass fraction of 2.0 wt.%ZIF-8,which reduces the friction factorof the grease by about 17.0%and the wear by40.0%.Furthermore,the molecular dynamics simulations reveal that ZIF-8 primarily functions as a ball bearing under low-load conditions.However,under high-load conditions,ZIF-8 undergoes significant deformation and primarily acts as a filler.This explains the experimentally observed significant reduction in friction coefficient after the addition of ZIF-8.The results of this study provide a theoretical foundation for the development of new environmentally friendly grease additives.
基金Project supported by the Jiangxi Province Key Laboratory of Light Alloy(2024SSY05031)the National Natural Science Foundation of China(52061028)+1 种基金the National Key Research and Development Program of China(2021YFB3501001)the Major Research and Development Projects of Jiangxi Province(20223BBE51021,20213AAE02014)。
文摘During direct chilling(DC)casting of ZK61 alloys,the primary and secondary cooling causes strong thermal gradients,which leads to the uneven crystallization rate and thermal contraction in different positions of the ingot.The consequences manifested appearance of heterogeneous grains,huge casting stresses,and even hot cracking flaws.In this paper,chemical and physical methods were integrated to produce large-scale magnesium(Mg)alloy ingots.A φ525 mm ZK61-RE alloy ingot that was refined,homogeneous,and free from hot cracking was obtained via the DC process coupled with a differential low frequency pulsed magnetic field(DLPM).The effects of rare earth(RE)and DLPM on the hot cracking tendency were investigated,and the mechanism of hot cracking formation and modification in largescale ingots was revealed.The findings indicate that the addition of moderate amounts of RE lessens the tendency of hot cracking in large-scale ZK61 alloy ingots.This is mainly attributed to the addition of RE increases the content of the second phase,thus enhancing the ability of the eutectic liquid phase to feed the cracking.With the introduction of DLPM,the grain sizes are significantly refined and homogenized,and there is no obvious hot cracking observed in the ingot.This is because the coupling of the DLPM provides a more homogeneous temperature field,leading to the synchronization of the solidification process,and the consequent reduction of the casting stress,thus reducing the driving force for the formation of hot cracking.In addition,the casting conditions are modified to enhance the ability of solidification feeding and the resistance to hot cracking.This work provides theoretical and practical references for the preparation of large-scale high-quality Mg alloy ingots.
基金supported by the National Key Research and Development Program of China(2022YFB3605902)the National Natural Science Foundation of China(52375411,52293402)。
文摘Workpiece rotational grinding is widely used in the ultra-precision machining of hard and brittle semiconductor materials,including single-crystal silicon,silicon carbide,and gallium arsenide.Surface roughness and subsurface damage depth(SDD)are crucial indicators for evaluating the surface quality of these materials after grinding.Existing prediction models lack general applicability and do not accurately account for the complex material behavior under grinding conditions.This paper introduces novel models for predicting both surface roughness and SDD in hard and brittle semiconductor materials.The surface roughness model uniquely incorporates the material’s elastic recovery properties,revealing the significant impact of these properties on prediction accuracy.The SDD model is distinguished by its analysis of the interactions between abrasive grits and the workpiece,as well as the mechanisms governing stress-induced damage evolution.The surface roughness model and SDD model both establish a stable relationship with the grit depth of cut(GDC).Additionally,we have developed an analytical relationship between the GDC and grinding process parameters.This,in turn,enables the establishment of an analytical framework for predicting surface roughness and SDD based on grinding process parameters,which cannot be achieved by previous models.The models were validated through systematic experiments on three different semiconductor materials,demonstrating excellent agreement with experimental data,with prediction errors of 6.3%for surface roughness and6.9%for SDD.Additionally,this study identifies variations in elastic recovery and material plasticity as critical factors influencing surface roughness and SDD across different materials.These findings significantly advance the accuracy of predictive models and broaden their applicability for grinding hard and brittle semiconductor materials.
基金Supported by the National Natural Science Foundation of China,No.11974121Talent Research Fund of Hefei University,No.24RC08.
文摘BACKGROUND Obstructive sleep apnea-hypopnea syndrome(OSAHS)is a highly prevalent sleep-related respiratory disorder associated with serious health risks.Although polysomnography is the clinical gold standard for diagnosis,it is expensive,in-convenient,and unsuitable for population-level screening due to the need for professional scoring and overnight monitoring.AIM To address these limitations,this review aims to systematically analyze recent ad-vances in deep learning–based OSAHS detection methods using snoring sounds,particularly focusing on graphical signal representations and network architec-tures.METHODS A comprehensive literature search was conducted following the PRISMA 2009 guidelines,covering publications from 2010 to 2025.Studies were included based on predefined criteria involving the use of deep learning models on snoring sounds transformed into graphical representations such as spectrograms and scalograms.A total of 14 studies were selected for in-depth analysis.RESULTS This review summarizes the types of signal modalities,datasets,feature extraction methods,and classification frameworks used in the current literatures.The strengths and limitations of different deep network architectures are evaluated.CONCLUSION Challenges such as dataset variability,generalizability,model interpretability,and deployment feasibility are also discussed.Future directions highlight the importance of explainable artificial intelligence and domain-adaptive learning for clinically viable OSAHS diagnostic tools.
基金supported by the National Natural Science Foundation of China(No.51965040)。
文摘Graphene nanoplatelets(GNPs)reinforced A380 composites(GNPs/A380 composites)were prepared by ultrasonic vibration casting method.The microstructure,aging behavior and mechanical properties of the composites were investigated.It was found that the peak aging time of GNPs/A380 composites could be decreased by GNPs.The GNPs-Al interface could serve as a more stable nucleation site for the precipitated phases.With bridging GNPs,the coordinated deformation of the matrix is increased and larger dimples appear on the fracture surface of GNPs/A380 composites.The yield strength of the GNPs/A380 composites increased by 28.1%compared with that of the A380 alloy due to the fine grain strengthening,load transfer and precipitation strengthening mechanisms.
基金supported by the National Natural Science Foundation of China(Grant No.11971411)。
文摘This paper introduces a novel numerical method based on an energy-minimizing normalized residual network(EMNorm Res Net)to compute the ground-state solution of Bose-Einstein condensates at zero or low temperatures.Starting from the three-dimensional Gross-Pitaevskii equation(GPE),we reduce it to the 1D and 2D GPEs because of the radial symmetry and cylindrical symmetry.The ground-state solution is formulated by minimizing the energy functional under constraints,which is directly solved using the EM-Norm Res Net approach.The paper provides detailed solutions for the ground states in 1D,2D(with radial symmetry),and 3D(with cylindrical symmetry).We use the Thomas-Fermi approximation as the target function to pre-train the neural network.Then,the formal network is trained using the energy minimization method.In contrast to traditional numerical methods,our neural network approach introduces two key innovations:(i)a novel normalization technique designed for high-dimensional systems within an energy-based loss function;(ii)improved training efficiency and model robustness by incorporating gradient stabilization techniques into residual networks.Extensive numerical experiments validate the method's accuracy across different spatial dimensions.
基金supported by the National Natural Science Foundation of China(Nos.52175310,52232004)the Launch Research Program of Fuzhou University,China(No.XRC-23083)+1 种基金the Education&Research Project of Fujian Province,China(No.JAT231003)the Open Test Fund for Valuable Instruments and Equipment of Fuzhou University,China(No.2024T036).
文摘Based on the relationship between deformation microstructures and grain orientations,three characteristic Cu single crystals were used to investigate the opposite effects of ultrasonic superimposed high-strain-rate on the dislocation motion during ultrasonic welding(UW).The results revealed that equiaxed dislocation cells and discontinuous dynamic recrystallization(DRX)grains dominated in the joint microstructures.Three Cu single crystal joints exhibited an isotropic trend in grain orientation,welding quality,and microscopic mechanical properties.The preferred dislocation behaviors and DRX modes were further analyzed by modelling the stored energy difference,indicating that high mobility of intra-granular dislocations and homogeneous dislocation motion induced by the ultrasonic excitation were the intrinsic factors contributing to the formation of isotropic microstructures and welding quality.
基金The National Natural Science Foundation of China(62203015,62233001,62273351)The Beijing Natural Science Foundation(4242038)。
文摘This paper considers the swarm vigilance problem for multi-agent systems(MAS),where multiple agents are deployed within a rectangular region for perception-based vigilance.There are two main challenges,namely the task allocation for vigilance roles and the coverage planning of the perception ranges.Firstly,vigilance behavioral patterns and processes in animal populations within natural habitats are investigated.Inspired by these biological vigilance behaviors,an efficient vigilance task allocation model for MAS is proposed.Secondly,the subsequent optimization of task layouts can achieve efficient surveillance coverage with fewer agents,minimizing resource consumption.Thirdly,an improved particle swarm optimization(IPSO)algorithm is proposed,which incorporates fitness-driven adaptive inertia weight dynamics.According to simulation analysis and comparative studies,optimal parameter configurations for genetic algorithm(GA)and IPSO are determined.Finally,the results indicate the proposed IPSO's superior performance to both GA and standard particle swarm optimization(PSO)in vigilance task allocation optimization,with satisfying advantages in computational efficiency and solution quality.
基金supported in part by the National Natural Science Foundation of China(62473387)the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(SML2023SP241)the Department of Science and Technology of Guangdong Province(2021QN020085)。
文摘For permanent magnet synchronous machines(PMSMs),accurate inductance is critical for control design and condition monitoring.Owing to magnetic saturation,existing methods require nonlinear saturation model and measurements from multiple load/current conditions,and the estimation is relying on the accuracy of saturation model and other machine parameters in the model.Speed harmonic produced by harmonic currents is inductance-dependent,and thus this paper explores the use of magnitude and phase angle of the speed harmonic for accurate inductance estimation.Two estimation models are built based on either the magnitude or phase angle,and the inductances can be from d-axis voltage and the magnitude or phase angle,in which the filter influence in harmonic extraction is considered to ensure the estimation performance.The inductances can be estimated from the measurements under one load condition,which is free of saturation model.Moreover,the inductance estimation is robust to the change of other machine parameters.The proposed approach can effectively improve estimation accuracy especially under the condition with low current magnitude.Experiments and comparisons are conducted on a test PMSM to validate the proposed approach.
基金co-supported by the Chongqing Natural Science Foundation General Project,China(No.CSTB2022NSCQ-MSX1115)。
文摘A structured method to generate conformal finite element(FE)mesh for realistic 3D woven textile reinforced composite is proposed.It is based on a voxel structure mesh reconstruction framework and aims to provide accurate composite model at yarn level with material properties ready for use in commercial FE software.The textile representative volume element(RVE)is generated at filament level implementing the digital element method.Yarn structure is determined by filament bundle with variant cross-section shapes along its path.Yarn surface is then extracted using the Delaunay triangulation algorithm and a surface mesh is initiated.Then,the mesh domain is defined and constructed by voxel structure.Periodic boundary conditions,inter-yarn,and yarnmatrix interfaces are eliminated by re-mesh and mesh optimization.An element splitting rule is established to split the voxel unit into sub-elements to create smooth interface.A 3D orthogonal weave fabric reinforced composite is generated and simulated under compressive load.The composite structure and damage morphology are in good agreement with those of the experiment.
基金jointly funded by the National Science Foundation of China(No.42405069)the University Natural Sciences Research Project of Anhui Province(Nos.2023AH052201 and 2023AH052184)+1 种基金the 2023 Talent Research Fund Project of Hefei University(No.23RC01)the Technical Development Project of Hefei University(Nos.902/22050124128,902/22050124148 and 902/22050124250)。
文摘Atmospheric turbulence is an important parameter affecting laser atmospheric transmission.This paper reports on a self-developed atmospheric turbulence detection Li DAR system(scanning differential image motion Li DAR(DIM-Li DAR)system).By designing and simulating the optical system of atmospheric turbulence detection Li DAR,the basic optical imaging accuracy has been determined.
基金supported by Shenzhen Science and Technology Program under Grant JCYJ20250604175412017the National Natural Science Foundation of China under Grant 62473387+1 种基金the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) under Grant SML2024SP007in part by the Department of Science and Technology of Guangdong Province under Grant. 2021QN020085。
文摘In permanent magnet synchronous machine(PMSM) drives, temperature information is critical to achieve reliable and high-performance control. The popular model-based estimation methods are based on extracting temperature dependent terms from the voltages using the machine model. The estimation accuracy under low speed or load can be greatly affected by the model uncertainty and noise due to low signal-tonoise ratio. This paper presents a high frequency(HF) position offset injection-based winding and permanent magnet(PM) temperature decoupled estimation approach for PMSMs to achieve accurate and robust temperature estimation among a wide speed range especially under low-speed conditions. In the proposed approach, a small HF position offset is injected into the machine to construct a decoupled winding and PM temperature estimation model, in which the winding and PM temperatures are independently estimated from HF excitations. The temperature estimation is independent from the fundamental model and parameter variation, and it achieves high signal-tonoise ratio under low-speed conditions. Moreover, the temperature estimation is also not affected by magnetic saturation and inverter distortion, which can improve the accuracy and robustness of temperature estimation. The proposed approach is validated with experiments and comparisons on a laboratory machine under various operating conditions.
基金supported in part by the National Science and Technology Major Project(2022ZD0119902)the National Natural Science Foundation of China(52471372,623B2018,62203015,62233001)+4 种基金the Liaoning Revitalization Leading Talents Program(XLYC2402054)the Key Basic Research of Dalian(2023JJ11CG008)the Fundamental Research Funds for the Central Universities(3132023508)the Collaborative Research Fund of Hong Kong Research Grants Council(C1013-24G)the Cultivation Program for the Excellent Doctoral Dissertation of Dalian Maritime University(2023YBPY005).
文摘This paper addresses the parallel control of autonomous surface vehicles subject to external disturbances,state constraints,and input constraints in complex ocean environments with multiple obstacles.A safety-certified parallel model predictive control scheme with collision-avoiding capability is proposed for autonomous surface vehicles in the framework of parallel control.Specifically,an extended state observer is designed by leveraging historical and real-time data for concurrent learning to map the motion of autonomous surface vehicles from its physical system to its artificial counterpart.A parallel model predictive control law is developed on the basis of the artificial system for both physical and artificial autonomous surface vehicles to realize virtual-physical tracking control of vehicles subject to state and input constraints.To ensure safety,highorder discrete control barrier functions are encoded in the parallel model predictive control law as safety constraints such that collision avoidance with obstacles can be achieved.A recedinghorizon constrained optimization problem is constructed with the safety constraints encoded by control barrier functions for parallel model predictive control of autonomous surface vehicles and solved via neurodynamic optimization with projection neural networks.The effectiveness and characteristics of the proposed method are demonstrated via simulations for the safe trajectory tracking and automatic berthing of autonomous surface vehicles.
基金supported by the National Natural Science Foundation of China(52071175,52301304)the Natural Science Foundation of Jiangsu Province(BK20230704)+3 种基金the China Postdoctoral Science Foundation Funded Project(2023M731742)the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province(23KJB430019)the Research Fund of Nanjing Institute of Technology(YKJ202402)the Open Research Fund of Jiangsu Key Laboratory for Light Metal Alloys(LMA202401).
文摘Implants are inevitably subjected to stress corrosion,bringing serious challenges to the controlled degradation of biomedical Mg alloys.It is worth studying the stress corrosion cracking(SCC)behavior of Mg alloy and exploring Mg alloy with good SCC resistance for wide biomedical applications.In this work,the as-cast and as-extruded Mg-3Gd-1Zn-0.4Zr(GZ31K)alloys with uniform corrosion were used to investigate SCC behavior.The as-extruded GZ31K alloy exhibited better corrosion resistance and mechanical properties than the as-cast one mainly owing to grain refinement and uniformly distributed fine precipitates,and possessed superior SCC resistance.To clarify the SCC mechanism,the slow strain rate tests were assisted with applied constant potentials via an electrochemical workstation.Accelerated anodic dissolution at anodic polarization deteriorated SCC resistance due to the initiation of corrosion pits and micro-cracks.However,cathodic polarization had no obvious effects on SCC resistance,along with both retarded corrosion and accelerated hydrogen evolution.Stacking faults in GZ31K alloy were hydrogen capture containers to reduce the effect of hydrogen on SCC resistance during cathodic polarization.These findings provide new insights into the evaluation of SCC mechanism,and offer more opportunities to explore Mg alloys with good SCC resistance by regulating anodic dissolution.
