A new analytical model for geometric size and forming force prediction in incremental flanging(IF)is presented in this work.The complex deformation characteristics of IF are considered in the modeling process,which ca...A new analytical model for geometric size and forming force prediction in incremental flanging(IF)is presented in this work.The complex deformation characteristics of IF are considered in the modeling process,which can accurately describe the strain and stress states in IF.Based on strain analysis,the model can predict the material thickness distribution and neck height after IF.By considering contact area,strain characteristics,material thickness changes,and friction,the model can predict specific moments and corresponding values of maximum axial forming force and maximum horizontal forming force during IF.In addition,an IF experiment involving different tool diameters,flanging diameters,and opening hole diameters is conducted.On the basis of the experimental strain paths,the strain characteristics of different deformation zones are studied,and the stable strain ratio is quantitatively described through two dimensionless parameters:relative tool diameter and relative hole diameter.Then,the changing of material thickness and forming force in IF,and the variation of minimum material thickness,neck height,maximum axial forming force,and maximum horizontal forming force with flanging parameters are studied,and the reliability of the analytical model is verified in this process.Finally,the influence of the horizontal forming force on the tool design and the fluctuation of the forming force are explained.展开更多
The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to indus...The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to industrial robots.Particle Swarm Optimization may frequently suffer from local optima and inaccuracies in identifying the geometric parameters,which are necessary for applications requiring high-accuracy performances.The proposed approach integrates pheromone-based learning of ACO with the D-H method of developing an error model;hence,the global search effectiveness together with the convergence accuracy is further improved.Comparison studies of the hybrid PSO-ACO algorithm show higher precision and effectiveness in the optimization of geometric error parameters compared to the traditional methods.This is a remarkable reduction of localization errors,thus yielding accuracy and reliability in industrial robotic systems,as the results show.This approach improves performance in those applications that demand high geometric calibration by reducing the geometric error.The paper provides an overview of input for developing robotics and automation,giving importance to precision in industrial engineering.The proposed hybrid methodology is a good way to enhance the working accuracy and effectiveness of industrial robots and shall enable their wide application to complex tasks that require a high degree of accuracy.展开更多
The influence of geometric configuration on the friction characteristics during incremental sheet forming of AA5052 was analyzed by integrating surface morphology and its characteristic parameters,along with plastic s...The influence of geometric configuration on the friction characteristics during incremental sheet forming of AA5052 was analyzed by integrating surface morphology and its characteristic parameters,along with plastic strain,contact pressure,and area.The interface promotes lubrication and support when wall angles were≤40°,a 0.5 mm-thin sheet was used,and a 10 mm-large tool radius was employed.This mainly results in micro-plowing and plastic extrusion flow,leading to lower friction coefficient.However,when wall angles exceed 40°,significant plastic strain roughening occurs,leading to inadequate lubrication on the newly formed surface.Increased sheet thickness and decreased tool radius elevate contact pressure.These actions trigger micro-cutting and adhesion,potentially leading to localized scuffing and dimple tears,and higher friction coefficient.The friction mechanisms remain unaffected by the part’s plane curve features.As the forming process progresses,abrasive wear intensifies,and surface morphology evolves unfavorably for lubrication and friction reduction.展开更多
Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address th...Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address this issue,we propose a geometric error cost sensitivity-based accuracy allocation method for five-axis machine tools.A geometric error model consisting of 4l error components is constructed based on homogeneous transformation matrices.Volumetric points with positional and tool direction deviations are randomly sampled to evaluate the accuracy of the machine tool.The sensitivity of each error component at these sampling points is analyzed using the Sobol method.To balance the needs of geometric precision and manufacturing cost,a geometric error cost sensitivity function is developed to estimate the required cost.By allocating error components affecting tool direction deviation first and the remaining components second,this allocation scheme ensures that both deviations meet the requirements.We also perform numerical simulation of a BC-type(B-axis and C-axis type)five-axis machine tool to validate the method.The results show that the new allocation scheme reduces the total geometric error cost by 27.8%compared to a uniform allocation scheme,and yields the same positional and tool direction machining accuracies.展开更多
The CNC machine tool is the fundamental equipment of the manufacturing industry,particularly in sectors where achieving high levels of accuracy is crucial.Geometric accuracy design is an important step in machine tool...The CNC machine tool is the fundamental equipment of the manufacturing industry,particularly in sectors where achieving high levels of accuracy is crucial.Geometric accuracy design is an important step in machine tool design and plays an essential role in determining the machining accuracy of the workpiece.Researchers have extensively studied methods to model,extract,optimize,and measure the geometric errors that affect the geometric accuracy of machine tools.This paper provides a comprehensive review of the state-of-the-art approaches and an overview of the latest research progress associated with geometric accuracy design in CNC machine tools.This paper explores the interrelated aspects of CNC machine tool accuracy design:modeling,analysis and optimization.Accuracy analysis,which includes geometric error modeling and sensitivity analysis,determines a machine tool’s output accuracy through its volumetric error model,given the known accuracy of its individual components.Conversely,accuracy allocation designs the accuracy of the machine tool components according to given output accuracy requirements to achieve optimization between the objectives of manufacturing cost,quality,reliability,and environmental impact.In addition to discussing design factors and evaluation methods,this paper outlines methods for verifying the accuracy of design results,aiming to provide a practical basis for ensuring that the designed accuracy is achieved.Finally,the challenges and future research directions in geometric accuracy design are highlighted.展开更多
The quantum geometric tensor(QGT)is a fundamental quantity for characterizing the geometric properties of quantum states and plays an essential role in elucidating various physical phenomena.The traditional QGT,defned...The quantum geometric tensor(QGT)is a fundamental quantity for characterizing the geometric properties of quantum states and plays an essential role in elucidating various physical phenomena.The traditional QGT,defned only for pure states,has limited applicability in realistic scenarios where mixed states are common.To address this limitation,we generalize the defnition of the QGT to mixed states using the purifcation bundle and the covariant derivative.Notably,our proposed defnition reduces to the traditional QGT when mixed states approach pure states.In our framework,the real and imaginary parts of this generalized QGT correspond to the Bures metric and the mean gauge curvature,respectively,endowing it with a broad range of potential applications.Additionally,using our proposed mixed-state QGT,we derive the geodesic equation applicable to mixed states.This work establishes a unifed framework for the geometric analysis of both pure and mixed states,thereby deepening our understanding of the geometric properties of quantum states.展开更多
In this paper,we study the geometric ergodicity of continuous time Markov pro-cesses in general state space.For the geometric ergodic continuous time Markov processes,the condition π(f^(p))<∞,p>1 is added.Usin...In this paper,we study the geometric ergodicity of continuous time Markov pro-cesses in general state space.For the geometric ergodic continuous time Markov processes,the condition π(f^(p))<∞,p>1 is added.Using the coupling method,we obtain the existence of a full absorbing set on which continuous time Markov processes are f-geometric ergodic.展开更多
Background As visual simultaneous localization and mapping(SLAM)is primarily based on the assumption of a static scene,the presence of dynamic objects in the frame causes problems such as a deterioration of system rob...Background As visual simultaneous localization and mapping(SLAM)is primarily based on the assumption of a static scene,the presence of dynamic objects in the frame causes problems such as a deterioration of system robustness and inaccurate position estimation.In this study,we propose a YGC-SLAM for indoor dynamic environments based on the ORB-SLAM2 framework combined with semantic and geometric constraints to improve the positioning accuracy and robustness of the system.Methods First,the recognition accuracy of YOLOv5 was improved by introducing the convolution block attention model and the improved EIOU loss function,whereby the prediction frame converges quickly for better detection.The improved YOLOv5 was then added to the tracking thread for dynamic target detection to eliminate dynamic points.Subsequently,multi-view geometric constraints were used for re-judging to further eliminate dynamic points while enabling more useful feature points to be retained and preventing the semantic approach from over-eliminating feature points,causing a failure of map building.The K-means clustering algorithm was used to accelerate this process and quickly calculate and determine the motion state of each cluster of pixel points.Finally,a strategy for drawing keyframes with de-redundancy was implemented to construct a clear 3D dense static point-cloud map.Results Through testing on TUM dataset and a real environment,the experimental results show that our algorithm reduces the absolute trajectory error by 98.22%and the relative trajectory error by 97.98%compared with the original ORBSLAM2,which is more accurate and has better real-time performance than similar algorithms,such as DynaSLAM and DS-SLAM.Conclusions The YGC-SLAM proposed in this study can effectively eliminate the adverse effects of dynamic objects,and the system can better complete positioning and map building tasks in complex environments.展开更多
Three-dimensional(3D)braided composites have significant potential for use in engineering structural materials.However,conventional 3D braiding machines are insufficient for designing composites with complex geometrie...Three-dimensional(3D)braided composites have significant potential for use in engineering structural materials.However,conventional 3D braiding machines are insufficient for designing composites with complex geometries.This paper proposes a programmable design methodology for 3D rotary braiding machines using circle-cutting and combination strategies.By introducing varying numbers of incisions on the circle,a diverse range of horn gears can be designed.Different combinations of these cut-circles allow the horn gears to be assembled into various 3D rotary braiders.The parametric equation for the braider plate is derived,showing that a combination strategy involving two cut-circles is feasible for braider design,whereas integrating three cut-circles simultaneously is impossible for a single machine.The construction of an automatic 6-3 type 3D braiding machine demonstrates the effectiveness of the proposed design strategy.This flexible braider design approach provides a practical solution for producing 3D braided composites with complex geometries.展开更多
The performance and price of copper-based micro linear products are determined by the diameter uniformity.How to accurately detect the wire diameter of long-length copper based micro linear products without cutting or...The performance and price of copper-based micro linear products are determined by the diameter uniformity.How to accurately detect the wire diameter of long-length copper based micro linear products without cutting or damage has always been a technical concern for production enterprises.Herein,a novel approach was developed for nondestructive detection of the average diameter at any given segment of a long copper wire by assessing the adsorption capacity of arginine on its surface.The amount of adsorbent on the surface of the copper wire exhibits a positive correlation with the area,which can be detected by extractive electrospray ionization mass spectrometry(EESI-MS)after online elution with ammonia.The experimental results demonstrated that the analysis can be completed within 15 min,with a good linear relationship between copper wires with different diameters and the adsorption capacity of arginine.The linear correlation coefficient R2was 0.995,the relative standard deviation was 1.10%-2.81%,and the detection limit reached 2.5μm(length of segment=4 cm),showing potential applications for facile measurement of the average diameter of various metal wires.展开更多
The structure and electronic properties of Co_(2)Ge_(10)^(-)anion and its neutral counterpart were investigated by anion photoelectron spectroscopy and theoretical calculations.The experimental vertical detachment ene...The structure and electronic properties of Co_(2)Ge_(10)^(-)anion and its neutral counterpart were investigated by anion photoelectron spectroscopy and theoretical calculations.The experimental vertical detachment energy of Co_(2)Ge_(10)^(-)was measured to be 2.86±0.08 eV.The lowest-energy isomer of Co_(2)Ge_(10)^(-)is in a doublet state and has a cage-like structure with Cs symmetry,which can be constructed by a tetragonal bipyramid on top of a pentagonal bipyramid and these two bipyramid structures share a common Co atom.The most stable structure of neutral Co_(2)Ge_(10)resembles its anionic counterpart and it is in a triplet state.The natural population analysis showed that the inner Co atom of both the anionic and neutral Co_(2)Ge_(10)acquires negative charge from the neighboring Ge atoms.The outer Co atom has a larger spin moment than the inner Co atom,indicating that the magnetic moments of Co_(2)Ge_(10)^(-/0)are mainly contributed by the outer Co atom.Analyses of the density of states and molecular orbitals indicated that there are a few highly delocalized molecular orbitals in Co_(2)Ge_(10)^(-),which are mainly contributed by Ge 4s atomic orbitals.展开更多
In this paper,we introduce a new geometric constant R_(X)(κ)based on isosceles orthogonality.First,we explore some basic properties of this new constant and then provide several examples to estimate its exact values ...In this paper,we introduce a new geometric constant R_(X)(κ)based on isosceles orthogonality.First,we explore some basic properties of this new constant and then provide several examples to estimate its exact values in certain specific Banach spaces.Next,we investigate the relationships between this new constant and other classical constants.Specifically,we establish an inequality relationship between it and the J(X)constant,as well as an identity relationship between it and theρX(t)constant.Furthermore,we characterize some geometric properties of Banach spaces by means of this new constant.Finally,by restricting the above-mentioned constant to the unit sphere,we introduce another new constant,calculate its upper and lower bounds,and present a relevant example.展开更多
Thermal vibrational convection(TVC)refers to the time-averaged convection of a non-isothermal fluid subjected to oscillating force fields.It serves as an effective mechanism for heat transfer control,particularly unde...Thermal vibrational convection(TVC)refers to the time-averaged convection of a non-isothermal fluid subjected to oscillating force fields.It serves as an effective mechanism for heat transfer control,particularly under microgravity conditions.A key challenge in this field is understanding the effect of rotation on TVC,as fluid oscillations in rotating systems exhibit unique and specific characteristics.In this study,we examine TVC in a vertical flat layer with boundaries at different temperatures,rotating around a horizontal axis.The distinctive feature of this study is that the fluid oscillations within the cavity are not induced by vibrations of the cavity itself,but rather by the gravity field,giving them a tidal nature.Our findings reveal that inertial waves generated in the rotating layer qualitatively alter the TVC structure,producing time-averaged flows in the form of toroidal vortices.Experimental investigations of the structure of oscillatory and time-averaged flows,conducted using Particle Image Velocimetry(PIV)for flow velocity visualization,are complemented by theoretical calculations of inertial modes in a cavity with this geometry.To the best of our knowledge,this study represents the first of its kind.The agreement between experimental results and theoretical predictions confirms that the formation of convective structures in the form of toroidal vortices is driven by inertial waves induced by the gravity field.A decrease in the rotational velocity leads to a transformation of the convective structures,shifting from toroidal vortices of inertial-wave origin to classical cellular TVC.We present dimensionless parameters that define the excitation thresholds for both cellular convection and toroidal structures.展开更多
The dynamic average consensus(DAC)algorithm is to enable a group of networked agents to track the average of their time-varying reference signals.For most existing DAC algorithms,a necessary assumption is that the upp...The dynamic average consensus(DAC)algorithm is to enable a group of networked agents to track the average of their time-varying reference signals.For most existing DAC algorithms,a necessary assumption is that the upper bounds of the reference signals and their derivatives are known in advance,thereby posing significant challenges in practical scenarios.Introducing adaptive gains in DAC algorithms provides a remedy by relaxing this assumption.However,the current adaptive gains used in this type of DAC algorithms are non-decreasing and may increase to infinity if persist disturbance exists.In order to overcome this defect,this paper presents a novel DAC algorithm with modified adaptive gains.This approach obviates the necessity for prior knowledge concerning the upper bounds of the reference signals and their derivatives.Moreover,the adaptive gains are able to remain bounded even in the presence of external disturbances.Furthermore,the proposed adaptive DAC algorithm is employed to address the distributed secondary control problem of DC microgrids.Comparative case studies are provided to verify the superiority of the proposed DAC algorithm.展开更多
In machine vision,elliptical targets frequently appear within the camera's region of interest(ROI).Ellipse detection is essential for shape detection and geometric measurements in machine vision.However,existing e...In machine vision,elliptical targets frequently appear within the camera's region of interest(ROI).Ellipse detection is essential for shape detection and geometric measurements in machine vision.However,existing ellipse detection algorithms often face issues such as high computational complexity,strong dependence on initial conditions,sensitivity to noise,and lack of robustness to occlusions.In this paper,we propose a fast and robust ellipse detection method to address these challenges.This method first utilizes edge gradient and curvature information to segment the curve into circular arcs.Next,based on the convexity of the arcs,it divides them into different quadrants of the ellipse,groups and fits the arcs according to multiple geometric constraints at a low computational cost.Finally,it reduces the parameter space for hierarchical clustering and then segments the complete ellipse into several sectors for verification.We compare our method across seven datasets,including five public image datasets and two from industrial camera scenes.Experimental results show that our method achieves a precision ranging from 67.1%to 98.9%,a recall ranging from 48.1%to 92.9%,and an F-measure ranging from 58.0%to 95.8%.The average execution time per image ranges from 25 ms to 192 ms,demonstrating both high accuracy and efficiency.展开更多
This paper investigates the development and performance of a new higher-order geometric stiffness matrix that more closely approximates the theoretically derived stiffness coefficients.Factors that influence the accur...This paper investigates the development and performance of a new higher-order geometric stiffness matrix that more closely approximates the theoretically derived stiffness coefficients.Factors that influence the accuracy of the solution are studied using two columns,two braced frames,and one unbraced frame.Discussion is provided when the new geometric stiffness matrix can be used to improve the buckling load analysis results and when it may provide only nominal additional benefit.展开更多
This study aimed to identify and compensate for the geometric errors of the double swiveling axes in a five-axis computer numerical control(CNC)machining center.Hence,a three-dimensional coordinate calculation algorit...This study aimed to identify and compensate for the geometric errors of the double swiveling axes in a five-axis computer numerical control(CNC)machining center.Hence,a three-dimensional coordinate calculation algorithm for a measured point with additional rotational rigid body motion constraints is proposed.The motion constraints of the rotational rigid body were analyzed,and a mathematical model of the measured point algorithm in the swiveling axes was established.The Levenberg-Marquard method was used to solve the nonlinear superstatically determined equations.The spatial coordinate error was used to separate the spatial deviation of the measured point.An identification model of the position-independent and position-dependent geometric errors was established.The three-dimensional coordinate-solving algorithm of the measured point in the swiveling axis and geometric error identification method based on the Monte Carlo method were analyzed numerically.Geometric error measurement and cutting experiments were performed on a VMC25100U five-axis machining center,which integrated two swiveling axes.Geometric errors of the A-and B-axes were identified and measured experimentally.The angular positioning errors before and after compensation were measured using a laser interferometer,which verified the effectiveness of the proposed algorithm.A cutting experiment of a round table part was performed.The shape and position accuracy of the processed part before and after compensation were detected using a coordinate measuring machine.It verified that the geometric error of the swiveling axis was effectively compensated by the algorithm proposed herein.展开更多
We conduct optical-tweezers experiments to investigate the average potential energies of passive plates harmonically trapped in bacterial suspensions.Our results show that the mean potential energies along both the ma...We conduct optical-tweezers experiments to investigate the average potential energies of passive plates harmonically trapped in bacterial suspensions.Our results show that the mean potential energies along both the major and minor axes increase with bacterial concentration but decrease with trap stiffness.Notably,the average potential energy along the major axis consistently exceeds that along the minor axis.This discrepancy from equilibrium systems is primarily attributed to the distinct bacterial flow fields and direct bacterium–plate collisions near the major and minor axes,as evidenced by the higher orientational order around the plate along the major compared to the minor axis,despite identical bacterial densities in these regions.Our findings highlight the critical role of hydrodynamic interactions in determining the potential energy of passive objects immersed in an active bath.展开更多
Using quantum discord(QD)and geometric quantum discord(GQD),quantum correlation dynamics is investigated for two coupled qubits within a multiqubit interacting system in the zero-temperature bosonic reservoir,under bo...Using quantum discord(QD)and geometric quantum discord(GQD),quantum correlation dynamics is investigated for two coupled qubits within a multiqubit interacting system in the zero-temperature bosonic reservoir,under both weak and strong qubit-reservoir coupling regimes.The multiqubit system is connected with either a common bosonic reservoir(CBR)or multiple independent bosonic reservoirs(IBRs).In the CBR case,our findings indicate that both QD and GQD can be strengthened by increasing the number of qubits in the multiqubit system.Furthermore,we study the steady state QD and GQD in the strong coupling regime,and find that the stable value in the long-time limit is determined exclusively by the number of qubits.The evolution period of QD and GQD gets longer as the dipole–dipole interaction(DDI)strength increases,which helps prolong the correlation time and thus preserves the quantum correlation under the weak coupling regime.Further analysis reveals notable differences between the CBR and IBRs scenarios.In the IBRs case,the decay of QD and GQD becomes slower compared to the CBR case,with both measures tending to zero at a reduced rate.Moreover,GQD consistently exhibits lower values than QD in both scenarios.These findings provide valuable insights into the selection of appropriate correlation measurement techniques for quantifying quantum correlations.展开更多
In order to improve the reconstruction accuracy of magnetic resonance imaging(MRI),an accurate natural image compressed sensing(CS)reconstruction network is proposed,which combines the advantages of model-based and de...In order to improve the reconstruction accuracy of magnetic resonance imaging(MRI),an accurate natural image compressed sensing(CS)reconstruction network is proposed,which combines the advantages of model-based and deep learning-based CS-MRI methods.In theory,enhancing geometric texture details in linear reconstruction is possible.First,the optimization problem is decomposed into two problems:linear approximation and geometric compensation.Aimed at the problem of image linear approximation,the data consistency module is used to deal with it.Since the processing process will lose texture details,a neural network layer that explicitly combines image and frequency feature representation is proposed,which is named butterfly dilated geometric distillation network.The network introduces the idea of butterfly operation,skillfully integrates the features of image domain and frequency domain,and avoids the loss of texture details when extracting features in a single domain.Finally,a channel feature fusion module is designed by combining channel attention mechanism and dilated convolution.The attention of the channel makes the final output feature map focus on the more important part,thus improving the feature representation ability.The dilated convolution enlarges the receptive field,thereby obtaining more dense image feature data.The experimental results show that the peak signal-to-noise ratio of the network is 5.43 dB,5.24 dB and 3.89 dB higher than that of ISTA-Net+,FISTA and DGDN networks on the brain data set with a Cartesian sampling mask CS ratio of 10%.展开更多
基金supported in part by financial support from the National Key R&D Program of China(No.2023YFB3407003)the National Natural Science Foundation of China(No.52375378).
文摘A new analytical model for geometric size and forming force prediction in incremental flanging(IF)is presented in this work.The complex deformation characteristics of IF are considered in the modeling process,which can accurately describe the strain and stress states in IF.Based on strain analysis,the model can predict the material thickness distribution and neck height after IF.By considering contact area,strain characteristics,material thickness changes,and friction,the model can predict specific moments and corresponding values of maximum axial forming force and maximum horizontal forming force during IF.In addition,an IF experiment involving different tool diameters,flanging diameters,and opening hole diameters is conducted.On the basis of the experimental strain paths,the strain characteristics of different deformation zones are studied,and the stable strain ratio is quantitatively described through two dimensionless parameters:relative tool diameter and relative hole diameter.Then,the changing of material thickness and forming force in IF,and the variation of minimum material thickness,neck height,maximum axial forming force,and maximum horizontal forming force with flanging parameters are studied,and the reliability of the analytical model is verified in this process.Finally,the influence of the horizontal forming force on the tool design and the fluctuation of the forming force are explained.
文摘The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to industrial robots.Particle Swarm Optimization may frequently suffer from local optima and inaccuracies in identifying the geometric parameters,which are necessary for applications requiring high-accuracy performances.The proposed approach integrates pheromone-based learning of ACO with the D-H method of developing an error model;hence,the global search effectiveness together with the convergence accuracy is further improved.Comparison studies of the hybrid PSO-ACO algorithm show higher precision and effectiveness in the optimization of geometric error parameters compared to the traditional methods.This is a remarkable reduction of localization errors,thus yielding accuracy and reliability in industrial robotic systems,as the results show.This approach improves performance in those applications that demand high geometric calibration by reducing the geometric error.The paper provides an overview of input for developing robotics and automation,giving importance to precision in industrial engineering.The proposed hybrid methodology is a good way to enhance the working accuracy and effectiveness of industrial robots and shall enable their wide application to complex tasks that require a high degree of accuracy.
基金the support of the Key Research and Development Program of Shaanxi Province,China(No.2021GXLH-Z-049)。
文摘The influence of geometric configuration on the friction characteristics during incremental sheet forming of AA5052 was analyzed by integrating surface morphology and its characteristic parameters,along with plastic strain,contact pressure,and area.The interface promotes lubrication and support when wall angles were≤40°,a 0.5 mm-thin sheet was used,and a 10 mm-large tool radius was employed.This mainly results in micro-plowing and plastic extrusion flow,leading to lower friction coefficient.However,when wall angles exceed 40°,significant plastic strain roughening occurs,leading to inadequate lubrication on the newly formed surface.Increased sheet thickness and decreased tool radius elevate contact pressure.These actions trigger micro-cutting and adhesion,potentially leading to localized scuffing and dimple tears,and higher friction coefficient.The friction mechanisms remain unaffected by the part’s plane curve features.As the forming process progresses,abrasive wear intensifies,and surface morphology evolves unfavorably for lubrication and friction reduction.
基金supported by the Key R&D Program of Zhejiang Province(Nos.2023C01166 and 2024SJCZX0046)the Zhejiang Provincial Natural Science Foundation of China(Nos.LDT23E05013E05 and LD24E050009)the Natural Science Foundation of Ningbo(No.2021J150),China.
文摘Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address this issue,we propose a geometric error cost sensitivity-based accuracy allocation method for five-axis machine tools.A geometric error model consisting of 4l error components is constructed based on homogeneous transformation matrices.Volumetric points with positional and tool direction deviations are randomly sampled to evaluate the accuracy of the machine tool.The sensitivity of each error component at these sampling points is analyzed using the Sobol method.To balance the needs of geometric precision and manufacturing cost,a geometric error cost sensitivity function is developed to estimate the required cost.By allocating error components affecting tool direction deviation first and the remaining components second,this allocation scheme ensures that both deviations meet the requirements.We also perform numerical simulation of a BC-type(B-axis and C-axis type)five-axis machine tool to validate the method.The results show that the new allocation scheme reduces the total geometric error cost by 27.8%compared to a uniform allocation scheme,and yields the same positional and tool direction machining accuracies.
基金Supported by the National Natural Science Foundation of China(Grant Nos.52375448,52275440).
文摘The CNC machine tool is the fundamental equipment of the manufacturing industry,particularly in sectors where achieving high levels of accuracy is crucial.Geometric accuracy design is an important step in machine tool design and plays an essential role in determining the machining accuracy of the workpiece.Researchers have extensively studied methods to model,extract,optimize,and measure the geometric errors that affect the geometric accuracy of machine tools.This paper provides a comprehensive review of the state-of-the-art approaches and an overview of the latest research progress associated with geometric accuracy design in CNC machine tools.This paper explores the interrelated aspects of CNC machine tool accuracy design:modeling,analysis and optimization.Accuracy analysis,which includes geometric error modeling and sensitivity analysis,determines a machine tool’s output accuracy through its volumetric error model,given the known accuracy of its individual components.Conversely,accuracy allocation designs the accuracy of the machine tool components according to given output accuracy requirements to achieve optimization between the objectives of manufacturing cost,quality,reliability,and environmental impact.In addition to discussing design factors and evaluation methods,this paper outlines methods for verifying the accuracy of design results,aiming to provide a practical basis for ensuring that the designed accuracy is achieved.Finally,the challenges and future research directions in geometric accuracy design are highlighted.
基金supported by the National Natural Science Foundation of China(Grant Nos.12347104,U24A2017,12461160276,and 12175075)the National Key Research and Development Program of China(Grant No.2023YFC2205802)+1 种基金the Natural Science Foundation of Jiangsu Province(Grant Nos.BK20243060 and BK20233001)in part by the State Key Laboratory of Advanced Optical Communication Systems and Networks,China。
文摘The quantum geometric tensor(QGT)is a fundamental quantity for characterizing the geometric properties of quantum states and plays an essential role in elucidating various physical phenomena.The traditional QGT,defned only for pure states,has limited applicability in realistic scenarios where mixed states are common.To address this limitation,we generalize the defnition of the QGT to mixed states using the purifcation bundle and the covariant derivative.Notably,our proposed defnition reduces to the traditional QGT when mixed states approach pure states.In our framework,the real and imaginary parts of this generalized QGT correspond to the Bures metric and the mean gauge curvature,respectively,endowing it with a broad range of potential applications.Additionally,using our proposed mixed-state QGT,we derive the geodesic equation applicable to mixed states.This work establishes a unifed framework for the geometric analysis of both pure and mixed states,thereby deepening our understanding of the geometric properties of quantum states.
基金Supported by the Natural Science Foundation of Hubei Province(2021CFB275)National Natural Science Foundation of China(12301667).
文摘In this paper,we study the geometric ergodicity of continuous time Markov pro-cesses in general state space.For the geometric ergodic continuous time Markov processes,the condition π(f^(p))<∞,p>1 is added.Using the coupling method,we obtain the existence of a full absorbing set on which continuous time Markov processes are f-geometric ergodic.
基金Supported by Jiangsu Key R&D Program(BE2021622)Jiangsu Postgraduate Practice and Innovation Program(SJCX23_0395).
文摘Background As visual simultaneous localization and mapping(SLAM)is primarily based on the assumption of a static scene,the presence of dynamic objects in the frame causes problems such as a deterioration of system robustness and inaccurate position estimation.In this study,we propose a YGC-SLAM for indoor dynamic environments based on the ORB-SLAM2 framework combined with semantic and geometric constraints to improve the positioning accuracy and robustness of the system.Methods First,the recognition accuracy of YOLOv5 was improved by introducing the convolution block attention model and the improved EIOU loss function,whereby the prediction frame converges quickly for better detection.The improved YOLOv5 was then added to the tracking thread for dynamic target detection to eliminate dynamic points.Subsequently,multi-view geometric constraints were used for re-judging to further eliminate dynamic points while enabling more useful feature points to be retained and preventing the semantic approach from over-eliminating feature points,causing a failure of map building.The K-means clustering algorithm was used to accelerate this process and quickly calculate and determine the motion state of each cluster of pixel points.Finally,a strategy for drawing keyframes with de-redundancy was implemented to construct a clear 3D dense static point-cloud map.Results Through testing on TUM dataset and a real environment,the experimental results show that our algorithm reduces the absolute trajectory error by 98.22%and the relative trajectory error by 97.98%compared with the original ORBSLAM2,which is more accurate and has better real-time performance than similar algorithms,such as DynaSLAM and DS-SLAM.Conclusions The YGC-SLAM proposed in this study can effectively eliminate the adverse effects of dynamic objects,and the system can better complete positioning and map building tasks in complex environments.
基金funded by the Shanghai Natural Science Foundation of Shanghai Municipal Science and Technology Commission(20ZR1400600)the Fundamental Research Funds for the Central Universities(2232023G-06)through collaborative research with the Advanced Fibrous Materials Lab(AFML)at the University of British Columbia.
文摘Three-dimensional(3D)braided composites have significant potential for use in engineering structural materials.However,conventional 3D braiding machines are insufficient for designing composites with complex geometries.This paper proposes a programmable design methodology for 3D rotary braiding machines using circle-cutting and combination strategies.By introducing varying numbers of incisions on the circle,a diverse range of horn gears can be designed.Different combinations of these cut-circles allow the horn gears to be assembled into various 3D rotary braiders.The parametric equation for the braider plate is derived,showing that a combination strategy involving two cut-circles is feasible for braider design,whereas integrating three cut-circles simultaneously is impossible for a single machine.The construction of an automatic 6-3 type 3D braiding machine demonstrates the effectiveness of the proposed design strategy.This flexible braider design approach provides a practical solution for producing 3D braided composites with complex geometries.
基金supported by the National Natural Science Foundation of China(No.22422402)National Key Research and Development Program of China(No.2022YFF0705300)Key Research and Development Program of Jiangxi Province(No.20232BBG70004)。
文摘The performance and price of copper-based micro linear products are determined by the diameter uniformity.How to accurately detect the wire diameter of long-length copper based micro linear products without cutting or damage has always been a technical concern for production enterprises.Herein,a novel approach was developed for nondestructive detection of the average diameter at any given segment of a long copper wire by assessing the adsorption capacity of arginine on its surface.The amount of adsorbent on the surface of the copper wire exhibits a positive correlation with the area,which can be detected by extractive electrospray ionization mass spectrometry(EESI-MS)after online elution with ammonia.The experimental results demonstrated that the analysis can be completed within 15 min,with a good linear relationship between copper wires with different diameters and the adsorption capacity of arginine.The linear correlation coefficient R2was 0.995,the relative standard deviation was 1.10%-2.81%,and the detection limit reached 2.5μm(length of segment=4 cm),showing potential applications for facile measurement of the average diameter of various metal wires.
基金supported by the National Natural Science Foundation of China(Nos.92461313,12074387,and 92161114)the Innovation Capability Support Program of Shaanxi Province(No.2023-CX-TD-49).
文摘The structure and electronic properties of Co_(2)Ge_(10)^(-)anion and its neutral counterpart were investigated by anion photoelectron spectroscopy and theoretical calculations.The experimental vertical detachment energy of Co_(2)Ge_(10)^(-)was measured to be 2.86±0.08 eV.The lowest-energy isomer of Co_(2)Ge_(10)^(-)is in a doublet state and has a cage-like structure with Cs symmetry,which can be constructed by a tetragonal bipyramid on top of a pentagonal bipyramid and these two bipyramid structures share a common Co atom.The most stable structure of neutral Co_(2)Ge_(10)resembles its anionic counterpart and it is in a triplet state.The natural population analysis showed that the inner Co atom of both the anionic and neutral Co_(2)Ge_(10)acquires negative charge from the neighboring Ge atoms.The outer Co atom has a larger spin moment than the inner Co atom,indicating that the magnetic moments of Co_(2)Ge_(10)^(-/0)are mainly contributed by the outer Co atom.Analyses of the density of states and molecular orbitals indicated that there are a few highly delocalized molecular orbitals in Co_(2)Ge_(10)^(-),which are mainly contributed by Ge 4s atomic orbitals.
基金Supported by the Higher Education Science Research Project(Natural Science)of Anhui Province(Grant No.2023AH050487)。
文摘In this paper,we introduce a new geometric constant R_(X)(κ)based on isosceles orthogonality.First,we explore some basic properties of this new constant and then provide several examples to estimate its exact values in certain specific Banach spaces.Next,we investigate the relationships between this new constant and other classical constants.Specifically,we establish an inequality relationship between it and the J(X)constant,as well as an identity relationship between it and theρX(t)constant.Furthermore,we characterize some geometric properties of Banach spaces by means of this new constant.Finally,by restricting the above-mentioned constant to the unit sphere,we introduce another new constant,calculate its upper and lower bounds,and present a relevant example.
基金funded by the Ministry of Education of the Russian Federation within the framework of a state assignment,number 1023032300071-6-2.3.1.
文摘Thermal vibrational convection(TVC)refers to the time-averaged convection of a non-isothermal fluid subjected to oscillating force fields.It serves as an effective mechanism for heat transfer control,particularly under microgravity conditions.A key challenge in this field is understanding the effect of rotation on TVC,as fluid oscillations in rotating systems exhibit unique and specific characteristics.In this study,we examine TVC in a vertical flat layer with boundaries at different temperatures,rotating around a horizontal axis.The distinctive feature of this study is that the fluid oscillations within the cavity are not induced by vibrations of the cavity itself,but rather by the gravity field,giving them a tidal nature.Our findings reveal that inertial waves generated in the rotating layer qualitatively alter the TVC structure,producing time-averaged flows in the form of toroidal vortices.Experimental investigations of the structure of oscillatory and time-averaged flows,conducted using Particle Image Velocimetry(PIV)for flow velocity visualization,are complemented by theoretical calculations of inertial modes in a cavity with this geometry.To the best of our knowledge,this study represents the first of its kind.The agreement between experimental results and theoretical predictions confirms that the formation of convective structures in the form of toroidal vortices is driven by inertial waves induced by the gravity field.A decrease in the rotational velocity leads to a transformation of the convective structures,shifting from toroidal vortices of inertial-wave origin to classical cellular TVC.We present dimensionless parameters that define the excitation thresholds for both cellular convection and toroidal structures.
基金supported in part by the National Natural Science Foundation of China(20221017-10,62573258,62188101)the National Natural Science Foundation of Shandong Province(ZR2024 JQ018,ZR2022MF227).
文摘The dynamic average consensus(DAC)algorithm is to enable a group of networked agents to track the average of their time-varying reference signals.For most existing DAC algorithms,a necessary assumption is that the upper bounds of the reference signals and their derivatives are known in advance,thereby posing significant challenges in practical scenarios.Introducing adaptive gains in DAC algorithms provides a remedy by relaxing this assumption.However,the current adaptive gains used in this type of DAC algorithms are non-decreasing and may increase to infinity if persist disturbance exists.In order to overcome this defect,this paper presents a novel DAC algorithm with modified adaptive gains.This approach obviates the necessity for prior knowledge concerning the upper bounds of the reference signals and their derivatives.Moreover,the adaptive gains are able to remain bounded even in the presence of external disturbances.Furthermore,the proposed adaptive DAC algorithm is employed to address the distributed secondary control problem of DC microgrids.Comparative case studies are provided to verify the superiority of the proposed DAC algorithm.
基金supported by National Major Scientific Research Instrument Development Project of China(No.51927804)Science Fund for Shaanxi Provincial Department of Education's Youth Innovation Team Research Plan under Grant(No.23JP169).
文摘In machine vision,elliptical targets frequently appear within the camera's region of interest(ROI).Ellipse detection is essential for shape detection and geometric measurements in machine vision.However,existing ellipse detection algorithms often face issues such as high computational complexity,strong dependence on initial conditions,sensitivity to noise,and lack of robustness to occlusions.In this paper,we propose a fast and robust ellipse detection method to address these challenges.This method first utilizes edge gradient and curvature information to segment the curve into circular arcs.Next,based on the convexity of the arcs,it divides them into different quadrants of the ellipse,groups and fits the arcs according to multiple geometric constraints at a low computational cost.Finally,it reduces the parameter space for hierarchical clustering and then segments the complete ellipse into several sectors for verification.We compare our method across seven datasets,including five public image datasets and two from industrial camera scenes.Experimental results show that our method achieves a precision ranging from 67.1%to 98.9%,a recall ranging from 48.1%to 92.9%,and an F-measure ranging from 58.0%to 95.8%.The average execution time per image ranges from 25 ms to 192 ms,demonstrating both high accuracy and efficiency.
文摘This paper investigates the development and performance of a new higher-order geometric stiffness matrix that more closely approximates the theoretically derived stiffness coefficients.Factors that influence the accuracy of the solution are studied using two columns,two braced frames,and one unbraced frame.Discussion is provided when the new geometric stiffness matrix can be used to improve the buckling load analysis results and when it may provide only nominal additional benefit.
基金Supported by Shanxi Provincial Natural Science Foundation(Grant No.2021JM010)The Youth Innovation Team of Shaanxi Universities.
文摘This study aimed to identify and compensate for the geometric errors of the double swiveling axes in a five-axis computer numerical control(CNC)machining center.Hence,a three-dimensional coordinate calculation algorithm for a measured point with additional rotational rigid body motion constraints is proposed.The motion constraints of the rotational rigid body were analyzed,and a mathematical model of the measured point algorithm in the swiveling axes was established.The Levenberg-Marquard method was used to solve the nonlinear superstatically determined equations.The spatial coordinate error was used to separate the spatial deviation of the measured point.An identification model of the position-independent and position-dependent geometric errors was established.The three-dimensional coordinate-solving algorithm of the measured point in the swiveling axis and geometric error identification method based on the Monte Carlo method were analyzed numerically.Geometric error measurement and cutting experiments were performed on a VMC25100U five-axis machining center,which integrated two swiveling axes.Geometric errors of the A-and B-axes were identified and measured experimentally.The angular positioning errors before and after compensation were measured using a laser interferometer,which verified the effectiveness of the proposed algorithm.A cutting experiment of a round table part was performed.The shape and position accuracy of the processed part before and after compensation were detected using a coordinate measuring machine.It verified that the geometric error of the swiveling axis was effectively compensated by the algorithm proposed herein.
基金supports of the National Natural Science Foundation of China(Grant Nos.12304245,12374205,12475031,and 12364029)the Science Foundation of China University of Petroleum,Beijing(Grant Nos.2462023YJRC031 and 2462024BJRC010)+4 种基金the National Key Laboratory of Petroleum Resources and Engineering(Grant No.PRE/DX-2407)the Natural Science Foundation of Shandong Province(Grant No.ZR2024YQ017)the Young Elite Scientist Sponsorship Program by BAST(Grant No.BYESS2023300)the Beijing Institute of Technology Research Fund Program for Young ScholarsThis work was also supported by Beijing National Laboratory for Condensed Matter Physics(Grant Nos.2023BNLCMPKF014 and 2024BNLCMPKF009).
文摘We conduct optical-tweezers experiments to investigate the average potential energies of passive plates harmonically trapped in bacterial suspensions.Our results show that the mean potential energies along both the major and minor axes increase with bacterial concentration but decrease with trap stiffness.Notably,the average potential energy along the major axis consistently exceeds that along the minor axis.This discrepancy from equilibrium systems is primarily attributed to the distinct bacterial flow fields and direct bacterium–plate collisions near the major and minor axes,as evidenced by the higher orientational order around the plate along the major compared to the minor axis,despite identical bacterial densities in these regions.Our findings highlight the critical role of hydrodynamic interactions in determining the potential energy of passive objects immersed in an active bath.
基金supported by the National Natural Science Foundation of China(Grant Nos.11564013 and 11964010)the Natural Science Foundation of Hunan Province(Grant No.2020JJ4495)the Scientific Research Fund of Hunan Provincial Education Department,China(Grant Nos.22A0377 and 21A0333).
文摘Using quantum discord(QD)and geometric quantum discord(GQD),quantum correlation dynamics is investigated for two coupled qubits within a multiqubit interacting system in the zero-temperature bosonic reservoir,under both weak and strong qubit-reservoir coupling regimes.The multiqubit system is connected with either a common bosonic reservoir(CBR)or multiple independent bosonic reservoirs(IBRs).In the CBR case,our findings indicate that both QD and GQD can be strengthened by increasing the number of qubits in the multiqubit system.Furthermore,we study the steady state QD and GQD in the strong coupling regime,and find that the stable value in the long-time limit is determined exclusively by the number of qubits.The evolution period of QD and GQD gets longer as the dipole–dipole interaction(DDI)strength increases,which helps prolong the correlation time and thus preserves the quantum correlation under the weak coupling regime.Further analysis reveals notable differences between the CBR and IBRs scenarios.In the IBRs case,the decay of QD and GQD becomes slower compared to the CBR case,with both measures tending to zero at a reduced rate.Moreover,GQD consistently exhibits lower values than QD in both scenarios.These findings provide valuable insights into the selection of appropriate correlation measurement techniques for quantifying quantum correlations.
基金the National Natural Science Foundation of China(No.61962032)。
文摘In order to improve the reconstruction accuracy of magnetic resonance imaging(MRI),an accurate natural image compressed sensing(CS)reconstruction network is proposed,which combines the advantages of model-based and deep learning-based CS-MRI methods.In theory,enhancing geometric texture details in linear reconstruction is possible.First,the optimization problem is decomposed into two problems:linear approximation and geometric compensation.Aimed at the problem of image linear approximation,the data consistency module is used to deal with it.Since the processing process will lose texture details,a neural network layer that explicitly combines image and frequency feature representation is proposed,which is named butterfly dilated geometric distillation network.The network introduces the idea of butterfly operation,skillfully integrates the features of image domain and frequency domain,and avoids the loss of texture details when extracting features in a single domain.Finally,a channel feature fusion module is designed by combining channel attention mechanism and dilated convolution.The attention of the channel makes the final output feature map focus on the more important part,thus improving the feature representation ability.The dilated convolution enlarges the receptive field,thereby obtaining more dense image feature data.The experimental results show that the peak signal-to-noise ratio of the network is 5.43 dB,5.24 dB and 3.89 dB higher than that of ISTA-Net+,FISTA and DGDN networks on the brain data set with a Cartesian sampling mask CS ratio of 10%.
