To examine the similarities and differences in the evolution of cavity,wetting and dynamics of a highspeed,oblique water-entry projectile with different positive angles of attack,a comparative analysis has been conduc...To examine the similarities and differences in the evolution of cavity,wetting and dynamics of a highspeed,oblique water-entry projectile with different positive angles of attack,a comparative analysis has been conducted based on the numerical results of two mathematical models,the rigid-body model and fluid-structure interaction model.In addition,the applicable scope of the above two methods,and the structural response characteristics of the projectile have also been investigated.Our results demonstrate that:(1) The impact loads and angular motion of the projectile of the rigid-body method are more likely to exhibit periodic variations due to the periodic tail slap,its range of positive angles of attack is about α<2°.(2) When the projectile undergone significant wetting,a strong coupling effect is observed among wetting,structural deformation,and projectile motion.With the applied projectile shape,it is observed that,when the projectile bends,the final wetting position is that of Part B(cylinder of body).With the occu rrence of this phenomenon,the projectile ballistics beco me completely unstable.(3) The force exerted on the lower surface of the projectile induced by wetting is the primary reason of the destabilization of the projectile traj ectory and structu ral deformation failure.Bending deformation is most likely to appear at the junction of Part C(cone of body) and Part D(tail).The safe angles of attack of the projectile stability are found to be about α≤2°.展开更多
The effects of temperature and Re content on the mechanical properties,dislocation morphology,and deformation mechanism of γ-γ′phases nickel-based single crystal superalloys are investigated by using the molecular ...The effects of temperature and Re content on the mechanical properties,dislocation morphology,and deformation mechanism of γ-γ′phases nickel-based single crystal superalloys are investigated by using the molecular dynamics method through the model of γ-γ′phases containing hole defect.The addition of Re makes the dislocation distribution tend towards the γ phase.The higher the Re content,the earlier theγphase yields,while the γ′phase yields later.Dislocation bends under the combined action of the applied force and the resistance of the Re atoms to form a bend point.The Re atoms are located at the bend points and strengthen the alloy by fixing the dislocation and preventing it from cutting the γ′phase.Dislocations nucleate first in the γ phase,causing theγphase to deform plastically before the γ′phase.As the strain increases,the dislocation length first remains unchanged,then increases rapidly,and finally fluctuates and changes.The dislocation lengths in the γ phase are larger than those in the γ′phase at different temperatures.The dislocation length shows a decreasing tendency with the increase of the temperature.Temperature can affect movement of the dislocation,and superalloys have different plastic deformation mechanisms at low,medium and high temperatures.展开更多
The shear pin of the friction pendulum bearing(FPB)can be made of 40Cr steel.In conceptual design,the optimal cut-off point of the shear pin is predetermined,guiding the design of bridges isolated by FPBs to maximize ...The shear pin of the friction pendulum bearing(FPB)can be made of 40Cr steel.In conceptual design,the optimal cut-off point of the shear pin is predetermined,guiding the design of bridges isolated by FPBs to maximize their isolation performance.Current researches on the shear pins are mainly based on linear elastic models,neglecting their plasticity,damage,and fracture mechanical properties.To accurately predict its cutoff behavior,the elastic-plastic degradationmodel of 40Cr steel is indeed calibrated.For this purpose,the Ramberg-Osgoodmodel,the Bao-Wierzbicki damage initiation criterion,and the linear damage evolution criterion were selected to develop the elastic-plastic degradation model of 40Cr.Subsequently,parameter calibration of this model was performed through uniaxial tensile tests on two sets of six smooth,round bars with different diameters.Following this,finite element simulations were conducted for the pure shear test of grade 10.9 high-strength bolts made of 40Cr steel,aiming to verify the elasticplastic degradation model.The results showed that the failure modes and force-displacement curves simulated by the finite element method were in good agreement with the test results.Moreover,the error between the primary characteristic parameters(initial stiffness,peak load,fracture displacement,and absorbed energy)obtained by finite element calculation and the test values was within 15%.These results demonstrated that the calibration elastic-plastic degradation model of 40Cr steel can predict the cutoff of the shear pin.展开更多
In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):104...In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):1045-1049]and Monrad and Rootzén[Probab.Theory Related Fields,1995,101(2):173-192].展开更多
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
This paper presents the design of an asymmetrically variable wingtip anhedral angles morphing aircraft,inspired by biomimetic mechanisms,to enhance lateral maneuver capability.Firstly,we establish a lateral dynamic mo...This paper presents the design of an asymmetrically variable wingtip anhedral angles morphing aircraft,inspired by biomimetic mechanisms,to enhance lateral maneuver capability.Firstly,we establish a lateral dynamic model considering additional forces and moments resulting during the morphing process,and convert it into a Multiple Input Multiple Output(MIMO)virtual control system by importing virtual inputs.Secondly,a classical dynamics inversion controller is designed for the outer-loop system.A new Global Fast Terminal Incremental Sliding Mode Controller(NDO-GFTISMC)is proposed for the inner-loop system,in which an adaptive law is implemented to weaken control surface chattering,and a Nonlinear Disturbance Observer(NDO)is integrated to compensate for unknown disturbances.The whole control system is proven semiglobally uniformly ultimately bounded based on the multi-Lyapunov function method.Furthermore,we consider tracking errors and self-characteristics of actuators,a quadratic programmingbased dynamic control allocation law is designed,which allocates virtual control inputs to the asymmetrically deformed wingtip and rudder.Actuator dynamic models are incorporated to ensure physical realizability of designed allocation law.Finally,comparative experimental results validate the effectiveness of the designed control system and control allocation law.The NDO-GFTISMC features faster convergence,stronger robustness,and 81.25%and 75.0%reduction in maximum state tracking error under uncertainty compared to the Incremental Nonlinear Dynamic Inversion Controller based on NDO(NDO-INDI)and Incremental Sliding Mode Controller based on NDO(NDO-ISMC),respectively.The design of the morphing aircraft significantly enhances lateral maneuver capability,maintaining a substantial control margin during lateral maneuvering,reducing the burden of the rudder surface,and effectively solving the actuator saturation problem of traditional aircraft during lateral maneuvering.展开更多
Incremental search provides real-time suggestions as users type their queries.However,recent studies demonstrate that its encrypted search traffic can disclose privacy-sensitive data through side channels.Specifically...Incremental search provides real-time suggestions as users type their queries.However,recent studies demonstrate that its encrypted search traffic can disclose privacy-sensitive data through side channels.Specifically,attackers can derive information about user keystrokes from observable traffic features,like packet sizes,timings,and directions,thereby inferring the victim's entered search query.This vulnerability is known as a remote keystroke inference attack.While various attacks leveraging different traffic features have been developed,accompanied by obfuscation-based countermeasures,there is still a lack of overall and in-depth understanding regarding these attacks and defenses.To fill this gap,we conduct the first comprehensive evaluation of existing remote keystroke inference attacks and defenses.We carry out extensive experiments on five well-known incremental search websites.all listed in Alexa's top 50,to evaluate and compare their realworld performance.The results demonstrate that attacks utilizing multidimensional request features pose the greatest risk to user privacy,and random padding is currently considered the optimal defense balancing both efficacy and resource demands.Our work sheds light on the real-world implications of remote keystroke inference attacks and provides developers with guidelines to enhance privacy protection strategies.展开更多
A relationship was discovered between the amplification factor and the number of load increments that are needed to limit the relative error to one percent in second-order elastic analyses with a predictor-corrector s...A relationship was discovered between the amplification factor and the number of load increments that are needed to limit the relative error to one percent in second-order elastic analyses with a predictor-corrector solution scheme.Previous research by the authors proposed a design equation to determine the required minimum number of load increments based on an evaluation of the elastic critical buckling load ratio.Further research has shown that an approximate amplification factor equation that is based on the B2 multiplier equation produces similar results when the amplification factor is less than approximately four.Eleven moment frames are used to verify the use of the new approximate amplification factor in the proposed design equation.展开更多
Current machine learning models for predicting geological conditions during earth pressure balance(EPB)shield tunneling predominantly rely on accurate geological conditions as model label inputs.This study introduces ...Current machine learning models for predicting geological conditions during earth pressure balance(EPB)shield tunneling predominantly rely on accurate geological conditions as model label inputs.This study introduces an innovative approach for the real-time prediction of geological conditions in EPB shield tunneling by utilizing an unsupervised incremental learning model that integrates deep temporal clustering(DTC)with elastic weight consolidation(EWC).The model was trained and tested using data from an EPB shield tunneling project in Nanjing,China.Results demonstrate that the DTC model outperforms nine comparison models by clustering the entire dataset into four distinct groups representing various geological conditions without requiring labeled data.Additionally,integrating EWC into the DTC model significantly enhances its continuous learning capabilities,enabling automatic parameter updates with incoming data and facilitating the real-time recognition of geological conditions.Feature importance was evaluated using the feature elimination method and the Shapley additive explanations(SHAP)method,underscoring the critical roles of earth chamber pressure and cutterhead rotation speed in predicting geological conditions.The proposed EWC-DTC model demonstrates practical utility for EPB shield tunneling in complex environments.展开更多
In this paper,an incremental contact model is developed for the elastic self-affine fractal rough surfaces under plane strain condition.The contact between a rough surface and a rigid plane is simplified by the accumu...In this paper,an incremental contact model is developed for the elastic self-affine fractal rough surfaces under plane strain condition.The contact between a rough surface and a rigid plane is simplified by the accumulation of identical line contacts with half-width given by the truncated area divided by the contact patch number at varying heights.Based on the contact stiffness of two-dimensional flat punch,the total stiffness of rough surface is estimated,and then the normal load is calculated by an incremental method.For various rough surfaces,the approximately linear load-area relationships predicted by the proposed model agree well with the results of finite element simulations.It is found that the real average contact pressure depends significantly on profile properties.展开更多
The incremental capacity analysis(ICA)technique is notably limited by its sensitivity to variations in charging conditions,which constrains its practical applicability in real-world scenarios.This paper introduces an ...The incremental capacity analysis(ICA)technique is notably limited by its sensitivity to variations in charging conditions,which constrains its practical applicability in real-world scenarios.This paper introduces an ICA-compensation technique to address this limitation and propose a generalized framework for assessing the state of health(SOH)of batteries based on ICA that is applicable under differing charging conditions.This novel approach calculates the voltage profile under quasi-static conditions by subtracting the voltage increase attributable to the additional polarization effects at high currents from the measured voltage profile.This approach's efficacy is contingent upon precisely acquiring the equivalent impedance.To obtain the equivalent impedance throughout the batteries'lifespan while minimizing testing costs,this study employs a current interrupt technique in conjunction with a long short-term memory(LSTM)network to develop a predictive model for equivalent impedance.Following the derivation of ICA curves using voltage profiles under quasi-static conditions,the research explores two scenarios for SOH estimation:one utilizing only incremental capacity(IC)features and the other incorporating both IC features and IC sampling.A genetic algorithm-optimized backpropagation neural network(GABPNN)is employed for the SOH estimation.The proposed generalized framework is validated using independent training and test datasets.Variable test conditions are applied for the test set to rigorously evaluate the methodology under challenging conditions.These evaluation results demonstrate that the proposed framework achieves an estimation accuracy of 1.04%for RMSE and 0.90%for MAPE across a spectrum of charging rates ranging from 0.1 C to 1 C and starting SOCs between 0%and 70%,which constitutes a major advancement compared to established ICA methods.It also significantly enhances the applicability of conventional ICA techniques in varying charging conditions and negates the necessity for separate testing protocols for each charging scenario.展开更多
Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational,organizational,or regulatory factors.These changes,referred to as incremental con...Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational,organizational,or regulatory factors.These changes,referred to as incremental concept drift,gradually alter the behavior or structure of processes,making their detection and localization a challenging task.Traditional process mining techniques frequently assume process stationarity and are limited in their ability to detect such drift,particularly from a control-flow perspective.The objective of this research is to develop an interpretable and robust framework capable of detecting and localizing incremental concept drift in event logs,with a specific emphasis on the structural evolution of control-flow semantics in processes.We propose DriftXMiner,a control-flow-aware hybrid framework that combines statistical,machine learning,and process model analysis techniques.The approach comprises three key components:(1)Cumulative Drift Scanner that tracks directional statistical deviations to detect early drift signals;(2)a Temporal Clustering and Drift-Aware Forest Ensemble(DAFE)to capture distributional and classification-level changes in process behavior;and(3)Petri net-based process model reconstruction,which enables the precise localization of structural drift using transition deviation metrics and replay fitness scores.Experimental validation on the BPI Challenge 2017 event log demonstrates that DriftXMiner effectively identifies and localizes gradual and incremental process drift over time.The framework achieves a detection accuracy of 92.5%,a localization precision of 90.3%,and an F1-score of 0.91,outperforming competitive baselines such as CUSUM+Histograms and ADWIN+Alpha Miner.Visual analyses further confirm that identified drift points align with transitions in control-flow models and behavioral cluster structures.DriftXMiner offers a novel and interpretable solution for incremental concept drift detection and localization in dynamic,process-aware systems.By integrating statistical signal accumulation,temporal behavior profiling,and structural process mining,the framework enables finegrained drift explanation and supports adaptive process intelligence in evolving environments.Its modular architecture supports extension to streaming data and real-time monitoring contexts.展开更多
Ever since the research in machine learning gained traction in recent years,it has been employed to address challenges in a wide variety of domains,including mechanical devices.Most of the machine learning models are ...Ever since the research in machine learning gained traction in recent years,it has been employed to address challenges in a wide variety of domains,including mechanical devices.Most of the machine learning models are built on the assumption of a static learning environment,but in practical situations,the data generated by the process is dynamic.This evolution of the data is termed concept drift.This research paper presents an approach for predictingmechanical failure in real-time using incremental learning based on the statistically calculated parameters of mechanical equipment.The method proposed here is applicable to allmechanical devices that are susceptible to failure or operational degradation.The proposed method in this paper is equipped with the capacity to detect the drift in data generation and adaptation.The proposed approach evaluates the machine learning and deep learning models for their efficacy in handling the errors related to industrial machines due to their dynamic nature.It is observed that,in the settings without concept drift in the data,methods like SVM and Random Forest performed better compared to deep neural networks.However,this resulted in poor sensitivity for the smallest drift in the machine data reported as a drift.In this perspective,DNN generated the stable drift detection method;it reported an accuracy of 84%and an AUC of 0.87 while detecting only a single drift point,indicating the stability to performbetter in detecting and adapting to new data in the drifting environments under industrial measurement settings.展开更多
Semantic communication(SemCom)aims to achieve high-fidelity information delivery under low communication consumption by only guaranteeing semantic accuracy.Nevertheless,semantic communication still suffers from unexpe...Semantic communication(SemCom)aims to achieve high-fidelity information delivery under low communication consumption by only guaranteeing semantic accuracy.Nevertheless,semantic communication still suffers from unexpected channel volatility and thus developing a re-transmission mechanism(e.g.,hybrid automatic repeat request[HARQ])becomes indispensable.In that regard,instead of discarding previously transmitted information,the incremental knowledge-based HARQ(IK-HARQ)is deemed as a more effective mechanism that could sufficiently utilize the information semantics.However,considering the possible existence of semantic ambiguity in image transmission,a simple bit-level cyclic redundancy check(CRC)might compromise the performance of IK-HARQ.Therefore,there emerges a strong incentive to revolutionize the CRC mechanism,thus more effectively reaping the benefits of both SemCom and HARQ.In this paper,built on top of swin transformer-based joint source-channel coding(JSCC)and IK-HARQ,we propose a semantic image transmission framework SC-TDA-HARQ.In particular,different from the conventional CRC,we introduce a topological data analysis(TDA)-based error detection method,which capably digs out the inner topological and geometric information of images,to capture semantic information and determine the necessity for re-transmission.Extensive numerical results validate the effectiveness and efficiency of the proposed SC-TDA-HARQ framework,especially under the limited bandwidth condition,and manifest the superiority of TDA-based error detection method in image transmission.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
The field of biometric identification has seen significant advancements over the years,with research focusing on enhancing the accuracy and security of these systems.One of the key developments is the integration of d...The field of biometric identification has seen significant advancements over the years,with research focusing on enhancing the accuracy and security of these systems.One of the key developments is the integration of deep learning techniques in biometric systems.However,despite these advancements,certain challenges persist.One of the most significant challenges is scalability over growing complexity.Traditional methods either require maintaining and securing a growing database,introducing serious security challenges,or relying on retraining the entiremodelwhen new data is introduced-a process that can be computationally expensive and complex.This challenge underscores the need for more efficient methods to scale securely.To this end,we introduce a novel approach that addresses these challenges by integrating multimodal biometrics,cancelable biometrics,and incremental learning techniques.This work is among the first attempts to seamlessly incorporate deep cancelable biometrics with dynamic architectural updates,applied incrementally to the deep learning model as new users are enrolled,achieving high performance with minimal catastrophic forgetting.By leveraging a One-Dimensional Convolutional Neural Network(1D-CNN)architecture combined with a hybrid incremental learning approach,our system achieves high recognition accuracy,averaging 98.98% over incrementing datasets,while ensuring user privacy through cancelable templates generated via a pre-trained CNN model and random projection.The approach demonstrates remarkable adaptability,utilizing the least intrusive biometric traits like facial features and fingerprints,ensuring not only robust performance but also long-term serviceability.展开更多
Using the finite element code ANSYS/LS-DYNA, a dynamic finite element modelwith an elastic-linear-kinematic-hardening plastic material is established to analyzeelastic-plastic stresses in the railhead in the impact pr...Using the finite element code ANSYS/LS-DYNA, a dynamic finite element modelwith an elastic-linear-kinematic-hardening plastic material is established to analyzeelastic-plastic stresses in the railhead in the impact process of wheel and rail occurring at thegap of rail joint. The model is based on the discrete elastic support condition of the rails, whichis suitable for the actual situation of wheel/track rolling contact. In the analysis the influencesof axle load, yield stress and tangent modulus of rail material on the stresses and strains areinvestigated in detail. The distribution of stresses and strains in the jointed railhead are given.It is found that the axle load, yield stress and tangent modulus of rail material greatly affect thestresses and strains in the railhead during impacting. The study provides a reliable method anduseful datum for the further research on fatigue and wear of railhead and improving the rail jointmode.展开更多
Crack line field analysis method has become an independent method for crack elastic-plastic analysis, which greatly simplifies the complexity of crack elastic-plastic problems and overcomes the corresponding mathemati...Crack line field analysis method has become an independent method for crack elastic-plastic analysis, which greatly simplifies the complexity of crack elastic-plastic problems and overcomes the corresponding mathematical difficulty. With this method, the precise elastic-plastic solutions near crack lines for variety of crack problems can be obtained. But up to now all solutions obtained by this method were for different concrete problems, no general steps and no general form of matching equations near crack line are given out. With crack line analysis method, this paper proposes the general steps of elastic plastic analysis near crack line for mode I crack in elastic-perfectly plastic solids under plane stress condition, and in turn given out the solving process and result for a specific problem.展开更多
The reverse analysis provides a convenient method to determine four elastic-plastic parameters through an indentation curve such as Young s modulus E, hardness H, yield strength σy and strain hardening exponent n. In...The reverse analysis provides a convenient method to determine four elastic-plastic parameters through an indentation curve such as Young s modulus E, hardness H, yield strength σy and strain hardening exponent n. In this paper, mathematical analysis on a reverse algorithm from Dao model （Dao et al., Acta Mater., 2001, 49, 3899） was carried out, which thought that only when 20 ≤E＊/σ0.033≤ 26 and 0.3n≤ 0.5, the reverse algorithm would yield two solutions of n by dimensionless function Π2. It is shown that, however, there are also two solutions of n when 20≤E＊/σ0.033≤ 26 and 0≤n0.1. A unique n can be obtained by dimensionless function Π3 instead of Π2 in these two ranges. E and H can be uniquely determined by a full indentation curve, and σy can be determined if n is unique. Furthermore, sensitivity analysis on obtaining n from dimensionless function Π3 or Π2 has been made.展开更多
A new elastic-plastic impact-contact model is proposed in this paper. By adopting the principle of minimum acceleration for elastic-plastic continue at finite deformation, and with the aid of finite difference method,...A new elastic-plastic impact-contact model is proposed in this paper. By adopting the principle of minimum acceleration for elastic-plastic continue at finite deformation, and with the aid of finite difference method, the proposed model is applied in the problem of dynamic response of a clamped thin circular plate subjected to a projectile impact centrally. The impact force history and response characteristics of the target plate is studied in detail. The theoretical predictions of the impact force and plate deflection are in good agreements with those of LDA experimental data. Linear expressions of the maximum impact force/transverse deflection versus impact velocity are given on the basis of the theoretical results.展开更多
基金supported by the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX24_0714).
文摘To examine the similarities and differences in the evolution of cavity,wetting and dynamics of a highspeed,oblique water-entry projectile with different positive angles of attack,a comparative analysis has been conducted based on the numerical results of two mathematical models,the rigid-body model and fluid-structure interaction model.In addition,the applicable scope of the above two methods,and the structural response characteristics of the projectile have also been investigated.Our results demonstrate that:(1) The impact loads and angular motion of the projectile of the rigid-body method are more likely to exhibit periodic variations due to the periodic tail slap,its range of positive angles of attack is about α<2°.(2) When the projectile undergone significant wetting,a strong coupling effect is observed among wetting,structural deformation,and projectile motion.With the applied projectile shape,it is observed that,when the projectile bends,the final wetting position is that of Part B(cylinder of body).With the occu rrence of this phenomenon,the projectile ballistics beco me completely unstable.(3) The force exerted on the lower surface of the projectile induced by wetting is the primary reason of the destabilization of the projectile traj ectory and structu ral deformation failure.Bending deformation is most likely to appear at the junction of Part C(cone of body) and Part D(tail).The safe angles of attack of the projectile stability are found to be about α≤2°.
基金Project supported by the Xi’an Science and Technology Plan Project of Shaanxi Province of China(Grant No.23GXFW0086).
文摘The effects of temperature and Re content on the mechanical properties,dislocation morphology,and deformation mechanism of γ-γ′phases nickel-based single crystal superalloys are investigated by using the molecular dynamics method through the model of γ-γ′phases containing hole defect.The addition of Re makes the dislocation distribution tend towards the γ phase.The higher the Re content,the earlier theγphase yields,while the γ′phase yields later.Dislocation bends under the combined action of the applied force and the resistance of the Re atoms to form a bend point.The Re atoms are located at the bend points and strengthen the alloy by fixing the dislocation and preventing it from cutting the γ′phase.Dislocations nucleate first in the γ phase,causing theγphase to deform plastically before the γ′phase.As the strain increases,the dislocation length first remains unchanged,then increases rapidly,and finally fluctuates and changes.The dislocation lengths in the γ phase are larger than those in the γ′phase at different temperatures.The dislocation length shows a decreasing tendency with the increase of the temperature.Temperature can affect movement of the dislocation,and superalloys have different plastic deformation mechanisms at low,medium and high temperatures.
基金The Research Start-up Fund for Talents Introduction of Huaiyin Institute of Technology(Grant No.Z301B23517).
文摘The shear pin of the friction pendulum bearing(FPB)can be made of 40Cr steel.In conceptual design,the optimal cut-off point of the shear pin is predetermined,guiding the design of bridges isolated by FPBs to maximize their isolation performance.Current researches on the shear pins are mainly based on linear elastic models,neglecting their plasticity,damage,and fracture mechanical properties.To accurately predict its cutoff behavior,the elastic-plastic degradationmodel of 40Cr steel is indeed calibrated.For this purpose,the Ramberg-Osgoodmodel,the Bao-Wierzbicki damage initiation criterion,and the linear damage evolution criterion were selected to develop the elastic-plastic degradation model of 40Cr.Subsequently,parameter calibration of this model was performed through uniaxial tensile tests on two sets of six smooth,round bars with different diameters.Following this,finite element simulations were conducted for the pure shear test of grade 10.9 high-strength bolts made of 40Cr steel,aiming to verify the elasticplastic degradation model.The results showed that the failure modes and force-displacement curves simulated by the finite element method were in good agreement with the test results.Moreover,the error between the primary characteristic parameters(initial stiffness,peak load,fracture displacement,and absorbed energy)obtained by finite element calculation and the test values was within 15%.These results demonstrated that the calibration elastic-plastic degradation model of 40Cr steel can predict the cutoff of the shear pin.
基金Supported by NSFC(Nos.11661025,12161024)Natural Science Foundation of Guangxi(Nos.2020GXNSFAA159118,2021GXNSFAA196045)+2 种基金Guangxi Science and Technology Project(No.Guike AD20297006)Training Program for 1000 Young and Middle-aged Cadre Teachers in Universities of GuangxiNational College Student's Innovation and Entrepreneurship Training Program(No.202110595049)。
文摘In this paper,we present local functional law of the iterated logarithm for Cs?rg?-Révész type increments of fractional Brownian motion.The results obtained extend works of Gantert[Ann.Probab.,1993,21(2):1045-1049]and Monrad and Rootzén[Probab.Theory Related Fields,1995,101(2):173-192].
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.
基金supported by the National Natural Science Foundation of China(Nos.62103052 and No.52175214)。
文摘This paper presents the design of an asymmetrically variable wingtip anhedral angles morphing aircraft,inspired by biomimetic mechanisms,to enhance lateral maneuver capability.Firstly,we establish a lateral dynamic model considering additional forces and moments resulting during the morphing process,and convert it into a Multiple Input Multiple Output(MIMO)virtual control system by importing virtual inputs.Secondly,a classical dynamics inversion controller is designed for the outer-loop system.A new Global Fast Terminal Incremental Sliding Mode Controller(NDO-GFTISMC)is proposed for the inner-loop system,in which an adaptive law is implemented to weaken control surface chattering,and a Nonlinear Disturbance Observer(NDO)is integrated to compensate for unknown disturbances.The whole control system is proven semiglobally uniformly ultimately bounded based on the multi-Lyapunov function method.Furthermore,we consider tracking errors and self-characteristics of actuators,a quadratic programmingbased dynamic control allocation law is designed,which allocates virtual control inputs to the asymmetrically deformed wingtip and rudder.Actuator dynamic models are incorporated to ensure physical realizability of designed allocation law.Finally,comparative experimental results validate the effectiveness of the designed control system and control allocation law.The NDO-GFTISMC features faster convergence,stronger robustness,and 81.25%and 75.0%reduction in maximum state tracking error under uncertainty compared to the Incremental Nonlinear Dynamic Inversion Controller based on NDO(NDO-INDI)and Incremental Sliding Mode Controller based on NDO(NDO-ISMC),respectively.The design of the morphing aircraft significantly enhances lateral maneuver capability,maintaining a substantial control margin during lateral maneuvering,reducing the burden of the rudder surface,and effectively solving the actuator saturation problem of traditional aircraft during lateral maneuvering.
基金supported by the National Natural Science Foundation of China(Nos.62172027 and U24B20117)the Zhejiang Provincial Natural Science Foundation of China(No.LZ23F020013)the National Key R&D Program of China(No.2020YFB1005601).
文摘Incremental search provides real-time suggestions as users type their queries.However,recent studies demonstrate that its encrypted search traffic can disclose privacy-sensitive data through side channels.Specifically,attackers can derive information about user keystrokes from observable traffic features,like packet sizes,timings,and directions,thereby inferring the victim's entered search query.This vulnerability is known as a remote keystroke inference attack.While various attacks leveraging different traffic features have been developed,accompanied by obfuscation-based countermeasures,there is still a lack of overall and in-depth understanding regarding these attacks and defenses.To fill this gap,we conduct the first comprehensive evaluation of existing remote keystroke inference attacks and defenses.We carry out extensive experiments on five well-known incremental search websites.all listed in Alexa's top 50,to evaluate and compare their realworld performance.The results demonstrate that attacks utilizing multidimensional request features pose the greatest risk to user privacy,and random padding is currently considered the optimal defense balancing both efficacy and resource demands.Our work sheds light on the real-world implications of remote keystroke inference attacks and provides developers with guidelines to enhance privacy protection strategies.
文摘A relationship was discovered between the amplification factor and the number of load increments that are needed to limit the relative error to one percent in second-order elastic analyses with a predictor-corrector solution scheme.Previous research by the authors proposed a design equation to determine the required minimum number of load increments based on an evaluation of the elastic critical buckling load ratio.Further research has shown that an approximate amplification factor equation that is based on the B2 multiplier equation produces similar results when the amplification factor is less than approximately four.Eleven moment frames are used to verify the use of the new approximate amplification factor in the proposed design equation.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.52378392,52408356)Foal Eagle Program Youth Top-notch Talent Project of Fujian Province,China(Grant No.00387088).
文摘Current machine learning models for predicting geological conditions during earth pressure balance(EPB)shield tunneling predominantly rely on accurate geological conditions as model label inputs.This study introduces an innovative approach for the real-time prediction of geological conditions in EPB shield tunneling by utilizing an unsupervised incremental learning model that integrates deep temporal clustering(DTC)with elastic weight consolidation(EWC).The model was trained and tested using data from an EPB shield tunneling project in Nanjing,China.Results demonstrate that the DTC model outperforms nine comparison models by clustering the entire dataset into four distinct groups representing various geological conditions without requiring labeled data.Additionally,integrating EWC into the DTC model significantly enhances its continuous learning capabilities,enabling automatic parameter updates with incoming data and facilitating the real-time recognition of geological conditions.Feature importance was evaluated using the feature elimination method and the Shapley additive explanations(SHAP)method,underscoring the critical roles of earth chamber pressure and cutterhead rotation speed in predicting geological conditions.The proposed EWC-DTC model demonstrates practical utility for EPB shield tunneling in complex environments.
基金supported by the National Natural Science Foundation of China(Grant Nos.12372100,12302126,and 12302141)the China Postdoctoral Science Foundation(Grant No.2023M732799)+1 种基金the Fundamental Research Funds for the Central Universities(Grant No.xzy012024020)Sihe Wang also thanks the support from the China Scholarship Council(CSC).
文摘In this paper,an incremental contact model is developed for the elastic self-affine fractal rough surfaces under plane strain condition.The contact between a rough surface and a rigid plane is simplified by the accumulation of identical line contacts with half-width given by the truncated area divided by the contact patch number at varying heights.Based on the contact stiffness of two-dimensional flat punch,the total stiffness of rough surface is estimated,and then the normal load is calculated by an incremental method.For various rough surfaces,the approximately linear load-area relationships predicted by the proposed model agree well with the results of finite element simulations.It is found that the real average contact pressure depends significantly on profile properties.
基金funded by the Bavarian State Ministry of ScienceResearch and Art(Grant number:H.2-F1116.WE/52/2)。
文摘The incremental capacity analysis(ICA)technique is notably limited by its sensitivity to variations in charging conditions,which constrains its practical applicability in real-world scenarios.This paper introduces an ICA-compensation technique to address this limitation and propose a generalized framework for assessing the state of health(SOH)of batteries based on ICA that is applicable under differing charging conditions.This novel approach calculates the voltage profile under quasi-static conditions by subtracting the voltage increase attributable to the additional polarization effects at high currents from the measured voltage profile.This approach's efficacy is contingent upon precisely acquiring the equivalent impedance.To obtain the equivalent impedance throughout the batteries'lifespan while minimizing testing costs,this study employs a current interrupt technique in conjunction with a long short-term memory(LSTM)network to develop a predictive model for equivalent impedance.Following the derivation of ICA curves using voltage profiles under quasi-static conditions,the research explores two scenarios for SOH estimation:one utilizing only incremental capacity(IC)features and the other incorporating both IC features and IC sampling.A genetic algorithm-optimized backpropagation neural network(GABPNN)is employed for the SOH estimation.The proposed generalized framework is validated using independent training and test datasets.Variable test conditions are applied for the test set to rigorously evaluate the methodology under challenging conditions.These evaluation results demonstrate that the proposed framework achieves an estimation accuracy of 1.04%for RMSE and 0.90%for MAPE across a spectrum of charging rates ranging from 0.1 C to 1 C and starting SOCs between 0%and 70%,which constitutes a major advancement compared to established ICA methods.It also significantly enhances the applicability of conventional ICA techniques in varying charging conditions and negates the necessity for separate testing protocols for each charging scenario.
文摘Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational,organizational,or regulatory factors.These changes,referred to as incremental concept drift,gradually alter the behavior or structure of processes,making their detection and localization a challenging task.Traditional process mining techniques frequently assume process stationarity and are limited in their ability to detect such drift,particularly from a control-flow perspective.The objective of this research is to develop an interpretable and robust framework capable of detecting and localizing incremental concept drift in event logs,with a specific emphasis on the structural evolution of control-flow semantics in processes.We propose DriftXMiner,a control-flow-aware hybrid framework that combines statistical,machine learning,and process model analysis techniques.The approach comprises three key components:(1)Cumulative Drift Scanner that tracks directional statistical deviations to detect early drift signals;(2)a Temporal Clustering and Drift-Aware Forest Ensemble(DAFE)to capture distributional and classification-level changes in process behavior;and(3)Petri net-based process model reconstruction,which enables the precise localization of structural drift using transition deviation metrics and replay fitness scores.Experimental validation on the BPI Challenge 2017 event log demonstrates that DriftXMiner effectively identifies and localizes gradual and incremental process drift over time.The framework achieves a detection accuracy of 92.5%,a localization precision of 90.3%,and an F1-score of 0.91,outperforming competitive baselines such as CUSUM+Histograms and ADWIN+Alpha Miner.Visual analyses further confirm that identified drift points align with transitions in control-flow models and behavioral cluster structures.DriftXMiner offers a novel and interpretable solution for incremental concept drift detection and localization in dynamic,process-aware systems.By integrating statistical signal accumulation,temporal behavior profiling,and structural process mining,the framework enables finegrained drift explanation and supports adaptive process intelligence in evolving environments.Its modular architecture supports extension to streaming data and real-time monitoring contexts.
文摘Ever since the research in machine learning gained traction in recent years,it has been employed to address challenges in a wide variety of domains,including mechanical devices.Most of the machine learning models are built on the assumption of a static learning environment,but in practical situations,the data generated by the process is dynamic.This evolution of the data is termed concept drift.This research paper presents an approach for predictingmechanical failure in real-time using incremental learning based on the statistically calculated parameters of mechanical equipment.The method proposed here is applicable to allmechanical devices that are susceptible to failure or operational degradation.The proposed method in this paper is equipped with the capacity to detect the drift in data generation and adaptation.The proposed approach evaluates the machine learning and deep learning models for their efficacy in handling the errors related to industrial machines due to their dynamic nature.It is observed that,in the settings without concept drift in the data,methods like SVM and Random Forest performed better compared to deep neural networks.However,this resulted in poor sensitivity for the smallest drift in the machine data reported as a drift.In this perspective,DNN generated the stable drift detection method;it reported an accuracy of 84%and an AUC of 0.87 while detecting only a single drift point,indicating the stability to performbetter in detecting and adapting to new data in the drifting environments under industrial measurement settings.
基金supported in part by the National Key Research and Development Program of China under Grant 2024YFE0200600in part by the National Natural Science Foundation of China under Grant 62071425+3 种基金in part by the Zhejiang Key Research and Development Plan under Grant 2022C01093in part by the Zhejiang Provincial Natural Science Foundation of China under Grant LR23F010005in part by the National Key Laboratory of Wireless Communications Foundation under Grant 2023KP01601in part by the Big Data and Intelligent Computing Key Lab of CQUPT under Grant BDIC-2023-B-001.
文摘Semantic communication(SemCom)aims to achieve high-fidelity information delivery under low communication consumption by only guaranteeing semantic accuracy.Nevertheless,semantic communication still suffers from unexpected channel volatility and thus developing a re-transmission mechanism(e.g.,hybrid automatic repeat request[HARQ])becomes indispensable.In that regard,instead of discarding previously transmitted information,the incremental knowledge-based HARQ(IK-HARQ)is deemed as a more effective mechanism that could sufficiently utilize the information semantics.However,considering the possible existence of semantic ambiguity in image transmission,a simple bit-level cyclic redundancy check(CRC)might compromise the performance of IK-HARQ.Therefore,there emerges a strong incentive to revolutionize the CRC mechanism,thus more effectively reaping the benefits of both SemCom and HARQ.In this paper,built on top of swin transformer-based joint source-channel coding(JSCC)and IK-HARQ,we propose a semantic image transmission framework SC-TDA-HARQ.In particular,different from the conventional CRC,we introduce a topological data analysis(TDA)-based error detection method,which capably digs out the inner topological and geometric information of images,to capture semantic information and determine the necessity for re-transmission.Extensive numerical results validate the effectiveness and efficiency of the proposed SC-TDA-HARQ framework,especially under the limited bandwidth condition,and manifest the superiority of TDA-based error detection method in image transmission.
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the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through project number RI-44-0833.
文摘The field of biometric identification has seen significant advancements over the years,with research focusing on enhancing the accuracy and security of these systems.One of the key developments is the integration of deep learning techniques in biometric systems.However,despite these advancements,certain challenges persist.One of the most significant challenges is scalability over growing complexity.Traditional methods either require maintaining and securing a growing database,introducing serious security challenges,or relying on retraining the entiremodelwhen new data is introduced-a process that can be computationally expensive and complex.This challenge underscores the need for more efficient methods to scale securely.To this end,we introduce a novel approach that addresses these challenges by integrating multimodal biometrics,cancelable biometrics,and incremental learning techniques.This work is among the first attempts to seamlessly incorporate deep cancelable biometrics with dynamic architectural updates,applied incrementally to the deep learning model as new users are enrolled,achieving high performance with minimal catastrophic forgetting.By leveraging a One-Dimensional Convolutional Neural Network(1D-CNN)architecture combined with a hybrid incremental learning approach,our system achieves high recognition accuracy,averaging 98.98% over incrementing datasets,while ensuring user privacy through cancelable templates generated via a pre-trained CNN model and random projection.The approach demonstrates remarkable adaptability,utilizing the least intrusive biometric traits like facial features and fingerprints,ensuring not only robust performance but also long-term serviceability.
基金National Natural Science Foundation of China(No.599355100)Foundation for Excellent PhD Thesis of University of Ministry of Education of China (No.200048)
文摘Using the finite element code ANSYS/LS-DYNA, a dynamic finite element modelwith an elastic-linear-kinematic-hardening plastic material is established to analyzeelastic-plastic stresses in the railhead in the impact process of wheel and rail occurring at thegap of rail joint. The model is based on the discrete elastic support condition of the rails, whichis suitable for the actual situation of wheel/track rolling contact. In the analysis the influencesof axle load, yield stress and tangent modulus of rail material on the stresses and strains areinvestigated in detail. The distribution of stresses and strains in the jointed railhead are given.It is found that the axle load, yield stress and tangent modulus of rail material greatly affect thestresses and strains in the railhead during impacting. The study provides a reliable method anduseful datum for the further research on fatigue and wear of railhead and improving the rail jointmode.
文摘Crack line field analysis method has become an independent method for crack elastic-plastic analysis, which greatly simplifies the complexity of crack elastic-plastic problems and overcomes the corresponding mathematical difficulty. With this method, the precise elastic-plastic solutions near crack lines for variety of crack problems can be obtained. But up to now all solutions obtained by this method were for different concrete problems, no general steps and no general form of matching equations near crack line are given out. With crack line analysis method, this paper proposes the general steps of elastic plastic analysis near crack line for mode I crack in elastic-perfectly plastic solids under plane stress condition, and in turn given out the solving process and result for a specific problem.
基金supported by the National Natural Science Foundation of China (Nos. 11002121, 11002122,and 10828205)the Natural Science Foundation of Hu-nan Province for Innovation Group (No. 09JJ7004)+2 种基金the Key Special Program for Science and Technology of Hu-nan Province (No. 2009FJ1002)and the Natural Science Foundation of Xiangtan University (No. 09XZX04)One of the authors (C. Lu) is also grateful to the support from the Australian Research Council (No. DP0985450)
文摘The reverse analysis provides a convenient method to determine four elastic-plastic parameters through an indentation curve such as Young s modulus E, hardness H, yield strength σy and strain hardening exponent n. In this paper, mathematical analysis on a reverse algorithm from Dao model （Dao et al., Acta Mater., 2001, 49, 3899） was carried out, which thought that only when 20 ≤E＊/σ0.033≤ 26 and 0.3n≤ 0.5, the reverse algorithm would yield two solutions of n by dimensionless function Π2. It is shown that, however, there are also two solutions of n when 20≤E＊/σ0.033≤ 26 and 0≤n0.1. A unique n can be obtained by dimensionless function Π3 instead of Π2 in these two ranges. E and H can be uniquely determined by a full indentation curve, and σy can be determined if n is unique. Furthermore, sensitivity analysis on obtaining n from dimensionless function Π3 or Π2 has been made.
基金The project supported by the National Natural Science Foundation of China(10532020)
文摘A new elastic-plastic impact-contact model is proposed in this paper. By adopting the principle of minimum acceleration for elastic-plastic continue at finite deformation, and with the aid of finite difference method, the proposed model is applied in the problem of dynamic response of a clamped thin circular plate subjected to a projectile impact centrally. The impact force history and response characteristics of the target plate is studied in detail. The theoretical predictions of the impact force and plate deflection are in good agreements with those of LDA experimental data. Linear expressions of the maximum impact force/transverse deflection versus impact velocity are given on the basis of the theoretical results.
