This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,...This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,path following dynamics,and system input dynamics.The single-track vehicle model considers the vehicle’s coupled lateral and longitudinal dynamics,as well as nonlinear tire forces.The tracking error dynamics are derived based on the curvilinear coordinates.The cost function is designed to minimize path tracking errors and control effort while considering constraints such as actuator bounds and tire grip limits.An algorithm that utilizes the optimal preview distance vector to query the corresponding reference curvature and reference speed.The length of the preview path is adaptively adjusted based on the vehicle speed,heading error,and path curvature.We validate the controller performance in a simulation environment with the autonomous racing scenario.The simulation results show that the vehicle accurately follows the highly dynamic path with small tracking errors.The maximum preview distance can be prior estimated and guidance the selection of the prediction horizon for NMPC.展开更多
The cubic stiffness force model(CSFM)and Bouc-Wen model(BWM)are introduced and compared innovatively.The unknown coefficients of the nonlinear models are identified by the genetic algorithm combined with experiments.B...The cubic stiffness force model(CSFM)and Bouc-Wen model(BWM)are introduced and compared innovatively.The unknown coefficients of the nonlinear models are identified by the genetic algorithm combined with experiments.By fitting the identified nonlinear coefficients under different excitation amplitudes,the nonlinear vibration responses of the system are predicted.The results show that the accuracy of the BWM is higher than that of the CSFM,especially in the non-resonant region.However,the optimization time of the BWM is longer than that of the CSFM.展开更多
The main objective of this paper is to investigate the influence of inertia of nonlinear springs on the dispersion behavior of discrete monoatomic chains with lumped and distributed masses.The developed model can repr...The main objective of this paper is to investigate the influence of inertia of nonlinear springs on the dispersion behavior of discrete monoatomic chains with lumped and distributed masses.The developed model can represent the wave propagation problem in a non-homogeneous material consisting of heavy inclusions embedded in a matrix.The inclusions are idealized by lumped masses,and the matrix between adjacent inclusions is modeled by a nonlinear spring with distributed masses.Additionally,the model is capable of depicting the wave propagation in bi-material bars,wherein the first material is represented by a rigid particle and the second one is represented by a nonlinear spring with distributed masses.The discrete model of the nonlinear monoatomic chain with lumped and distributed masses is first considered,and a closed-form expression of the dispersion relation is obtained by the second-order Lindstedt-Poincare method(LPM).Next,a continuum model for the nonlinear monoatomic chain is derived directly from its discrete lattice model by a suitable continualization technique.The subsequent use of the second-order method of multiple scales(MMS)facilitates the derivation of the corresponding nonlinear dispersion relation in a closed form.The novelties of the present study consist of(i)considering the inertia of nonlinear springs on the dispersion behavior of the discrete mass-spring chains;(ii)developing the second-order LPM for the wave propagation in the discrete chains;and(iii)deriving a continuum model for the nonlinear monoatomic chains with lumped and distributed masses.Finally,a parametric study is conducted to examine the effects of the design parameters and the distributed spring mass on the nonlinear dispersion relations and phase velocities obtained from both the discrete and continuum models.These parameters include the ratio of the spring mass to the lumped mass,the nonlinear stiffness coefficient of the spring,and the wave amplitude.展开更多
This paper studies the strong convergence of the quantum lattice Boltzmann(QLB)scheme for the nonlinear Dirac equations for Gross-Neveu model in 1+1 dimensions.The initial data for the scheme are assumed to be converg...This paper studies the strong convergence of the quantum lattice Boltzmann(QLB)scheme for the nonlinear Dirac equations for Gross-Neveu model in 1+1 dimensions.The initial data for the scheme are assumed to be convergent in L^(2).Then for any T≥0 the corresponding solutions for the quantum lattice Boltzmann scheme are shown to be convergent in C([0,T];L^(2)(R^(1)))to the strong solution to the nonlinear Dirac equations as the mesh sizes converge to zero.In the proof,at first a Glimm type functional is introduced to establish the stability estimates for the difference between two solutions for the corresponding quantum lattice Boltzmann scheme,which leads to the compactness of the set of the solutions for the quantum lattice Boltzmann scheme.Finally the limit of any convergent subsequence of the solutions for the quantum lattice Boltzmann scheme is shown to coincide with the strong solution to a Cauchy problem for the nonlinear Dirac equations.展开更多
Due to the novel applications of flexible pipes conveying fluid in the field of soft robotics and biomedicine,the investigations on the mechanical responses of the pipes have attracted considerable attention.The fluid...Due to the novel applications of flexible pipes conveying fluid in the field of soft robotics and biomedicine,the investigations on the mechanical responses of the pipes have attracted considerable attention.The fluid-structure interaction(FSI)between the pipe with a curved shape and the time-varying internal fluid flow brings a great challenge to the revelation of the dynamical behaviors of flexible pipes,especially when the pipe is highly flexible and usually undergoes large deformations.In this work,the geometrically exact model(GEM)for a curved cantilevered pipe conveying pulsating fluid is developed based on the extended Hamilton's principle.The stability of the curved pipe with three different subtended angles is examined with the consideration of steady fluid flow.Specific attention is concentrated on the large-deformation resonance of circular pipes conveying pulsating fluid,which is often encountered in practical engineering.By constructing bifurcation diagrams,oscillating shapes,phase portraits,time traces,and Poincarémaps,the dynamic responses of the curved pipe under various system parameters are revealed.The mean flow velocity of the pulsating fluid is chosen to be either subcritical or supercritical.The numerical results show that the curved pipe conveying pulsating fluid can exhibit rich dynamical behaviors,including periodic and quasi-periodic motions.It is also found that the preferred instability type of a cantilevered curved pipe conveying steady fluid is mainly in the flutter of the second mode.For a moderate value of the mass ratio,however,a third-mode flutter may occur,which is quite different from that of a straight pipe system.展开更多
This paper proposes a robust control scheme based on the sequential convex programming and learning-based model for nonlinear system subjected to additive uncertainties.For the problem of system nonlinearty and unknow...This paper proposes a robust control scheme based on the sequential convex programming and learning-based model for nonlinear system subjected to additive uncertainties.For the problem of system nonlinearty and unknown uncertainties,we study the tube-based model predictive control scheme that makes use of feedforward neural network.Based on the characteristics of the bounded limit of the average cost function while time approaching infinity,a min-max optimization problem(referred to as min-max OP)is formulated to design the controller.The feasibility of this optimization problem and the practical stability of the controlled system are ensured.To demonstrate the efficacy of the proposed approach,a numerical simulation on a double-tank system is conducted.The results of the simulation serve as verification of the effectualness of the proposed scheme.展开更多
How the state of living muscles modulates the features of nonlinear elastic waves generated by external dynamic loads remains unclear because of the challenge of directly observing and modeling nonlinear elastic waves...How the state of living muscles modulates the features of nonlinear elastic waves generated by external dynamic loads remains unclear because of the challenge of directly observing and modeling nonlinear elastic waves in skeletal muscles in vivo,considering their active deformation behavior.Here,this important issue is addressed by combining experiments performed with an ultrafast ultrasound imaging system to track nonlinear shear waves(shear shock waves)in muscles in vivo and finite element analysis relying on a physically motivated constitutive model to study the effect of muscle activation level.Skeletal muscle was loaded with a deep muscle stimulator to generate shear shock waves(SSWs).The particle velocities,second and third harmonics,and group velocities of the SSWs in living muscles under both passive and active states were measured in vivo.Our experimental results reveal,for the first time,that muscle states have a pronounced effect on wave features;a low level of activation may facilitate the occurrence of both the second and third harmonics,whereas a high level of activation may inhibit the third harmonic.Finite element analysis was further carried out to quantitatively explore the effect of active muscle deformation behavior on the generation and propagation of SSWs.The simulation results at different muscle activation levels confirmed the experimental findings.The ability to reveal the effects of muscle state on the features of SSWs may be helpful in elucidating the unique dynamic deformation mechanism of living skeletal muscles,quantitatively characterizing diverse shock wave-based therapy instruments,and guiding the design of muscle-mimicking soft materials.展开更多
In order to enhance the control performance of piezo-positioning system,the influence of hysteresis characteristics and its compensation method are studied.Hammerstein model is used to represent the dynamic hysteresis...In order to enhance the control performance of piezo-positioning system,the influence of hysteresis characteristics and its compensation method are studied.Hammerstein model is used to represent the dynamic hysteresis nonlinear characteristics of piezo-positioning actuator.The static nonlinear part and dynamic linear part of the Hammerstein model are represented by models obtained through the Prandtl-Ishlinskii(PI)model and Hankel matrix system identification method,respectively.This model demonstrates good generalization capability for typical input frequencies below 200 Hz.A sliding mode inverse compensation tracking control strategy based on P-I inverse model and integral augmentation is proposed.Experimental results show that compared with PID inverse compensation control and sliding mode control without inverse compensation,the sliding mode inverse compensation control has a more ideal step response and no overshoot,moreover,the settling time is only 6.2 ms.In the frequency domain,the system closed-loop tracking bandwidth reaches 119.9 Hz,and the disturbance rejection bandwidth reaches 86.2 Hz.The proposed control strategy can effectively compensate the hysteresis nonlinearity,and improve the tracking accuracy and antidisturbance capability of piezo-positioning system.展开更多
This paper develops a comprehensive computational modeling and simulation framework based on Complex Adaptive Systems(CAS)theory to unveil the underlying mechanisms of self-organization,nonlinear evolution,and emergen...This paper develops a comprehensive computational modeling and simulation framework based on Complex Adaptive Systems(CAS)theory to unveil the underlying mechanisms of self-organization,nonlinear evolution,and emergence in social systems.By integrating mathematical models,agent-based modeling,network dynamic analysis,and hybrid modeling approaches,the study applies CAS theory to case studies in economic markets,political decision-making,and social interactions.The experimental results demonstrate that local interactions among individual agents can give rise to complex global phenomena,such as market fluctuations,opinion polarization,and sudden outbreaks of social movements.This framework not only provides a more robust explanation for the nonlinear dynamics and abrupt transitions that traditional models often fail to capture,but also offers valuable decision-support tools for public policy formulation,social governance,and risk management.Emphasizing the importance of interdisciplinary approaches,this work outlines future research directions in high-performance computing,artificial intelligence,and real-time data integration to further advance the theoretical and practical applications of CAS in the social sciences.展开更多
Fatigue failure caused by vibration is the most common type of pipeline failure.The core of this research is to obtain the nonlinear dynamic stress of a pipeline system accurately and efficiently,a topic that needs to...Fatigue failure caused by vibration is the most common type of pipeline failure.The core of this research is to obtain the nonlinear dynamic stress of a pipeline system accurately and efficiently,a topic that needs to be explored in the existing literature.The shell theory can better simulate the circumferential stress distribution,and thus the Mindlin-Reissner shell theory is used to model the pipeline.In this paper,the continuous pipeline system is combined with clamps through modal expansion for the first time,which realizes the coupling problem between a shell and a clamp.While the Bouc-Wen model is used to simulate the nonlinear external force generated by a clamp,the nonlinear coupling characteristics of the system are effectively captured.Then,the dynamic equation of the clamp-pipeline system is established according to the Lagrange energy equation.Based on the resonance frequency and stress amplitude obtained from the experiment,the nonlinear parameters of the clamp are identified with the semi-analytical method(SAM)and particle swarm optimization(PSO)algorithm.This study provides a theoretical basis for the clamp-pipeline system and an efficient and universal solution for stress prediction and analysis of pipelines in engineering.展开更多
As a common fault of the aero-engine,the blade-casing rubbing(BCR)has the potential to cause catastrophic accidents.In this paper,to investigate the dynamic responses and wear characteristics of the system,the laminat...As a common fault of the aero-engine,the blade-casing rubbing(BCR)has the potential to cause catastrophic accidents.In this paper,to investigate the dynamic responses and wear characteristics of the system,the laminated shell element is used to establish the finite element model(FEM)of a flexibly coated casing system.Using the shell element,the blade is modeled,and the surface stress of the blade is calculated.The stress-solving method of the blade is validated through comparisons with the measured time-domain waveform of the stress.Then,a dynamic model of a blade-flexibly coated casing system with rubbing is proposed,accounting for the time-varying mass and stiffness of the casing caused by coating wear.The effects of the proposed flexible casing model are compared with those of a rigid casing model,and the stress changes induced by rubbing are investigated.The results show that the natural characteristics of the coated casing decrease due to the coating wear.The flexibly coated casing model is found to be more suitable for studying casing vibration.Additionally,the stress changes caused by rubbing are slight,and the change in the stress maximum is approximately 5%under the influence of the abrasive coating.展开更多
Conducting predictability studies is essential for tracing the source of forecast errors,which not only leads to the improvement of observation and forecasting systems,but also enhances the understanding of weather an...Conducting predictability studies is essential for tracing the source of forecast errors,which not only leads to the improvement of observation and forecasting systems,but also enhances the understanding of weather and climate phenomena.In the past few decades,dynamical numerical models have been the primary tools for predictability studies,achieving significant progress.Nowadays,with the advances in artificial intelligence(AI)techniques and accumulations of vast meteorological data,modeling weather and climate events using modern data-driven approaches is becoming trendy,where FourCastNet,Pangu-Weather,and GraphCast are successful pioneers.In this perspective article,we suggest AI models should not be limited to forecasting but be expanded to predictability studies,leveraging AI's advantages of high efficiency and self-contained optimization modules.To this end,we first remark that AI models should possess high simulation capability with fine spatiotemporal resolution for two kinds of predictability studies.AI models with high simulation capabilities comparable to numerical models can be considered to provide solutions to partial differential equations in a data-driven way.Then,we highlight several specific predictability issues with well-determined nonlinear optimization formulizations,which can be well-studied using AI models,holding significant scientific value.In addition,we advocate for the incorporation of AI models into the synergistic cycle of the cognition–observation–model paradigm.Comprehensive predictability studies have the potential to transform“big data”to“big and better data”and shift the focus from“AI for forecasts”to“AI for science”,ultimately advancing the development of the atmospheric and oceanic sciences.展开更多
BACKGROUND The risk factors and prediction models for diabetic foot(DF)remain incompletely understood,with several potential factors still requiring in-depth investigations.AIM To identify risk factors for new-onset D...BACKGROUND The risk factors and prediction models for diabetic foot(DF)remain incompletely understood,with several potential factors still requiring in-depth investigations.AIM To identify risk factors for new-onset DF and develop a robust prediction model for hospitalized patients with type 2 diabetes.METHODS We included 6301 hospitalized patients with type 2 diabetes from January 2016 to December 2021.A univariate Cox model and least absolute shrinkage and selection operator analyses were applied to select the appropriate predictors.Nonlinear associations between continuous variables and the risk of DF were explored using restricted cubic spline functions.The Cox model was further employed to evaluate the impact of risk factors on DF.The area under the curve(AUC)was measured to evaluate the accuracy of the prediction model.RESULTS Seventy-five diabetic inpatients experienced DF.The incidence density of DF was 4.5/1000 person-years.A long duration of diabetes,lower extremity arterial disease,lower serum albumin,fasting plasma glucose(FPG),and diabetic nephropathy were independently associated with DF.Among these risk factors,the serum albumin concentration was inversely associated with DF,with a hazard ratio(HR)and 95%confidence interval(CI)of 0.91(0.88-0.95)(P<0.001).Additionally,a U-shaped nonlinear relationship was observed between the FPG level and DF.After adjusting for other variables,the HRs and 95%CI for FPG<4.4 mmol/L and≥7.0 mmol/L were 3.99(1.55-10.25)(P=0.004)and 3.12(1.66-5.87)(P<0.001),respectively,which was greater than the mid-range level(4.4-6.9 mmol/L).The AUC for predicting DF over 3 years was 0.797.CONCLUSION FPG demonstrated a U-shaped relationship with DF.Serum albumin levels were negatively associated with DF.The prediction nomogram model of DF showed good discrimination ability using diabetes duration,lower extremity arterial disease,serum albumin,FPG,and diabetic nephropathy(Clinicaltrial.gov NCT05519163).展开更多
[Objective] The aim was to develop a nonlinear model of quantitative analysis of melamine content by infrared spectroscopy and provide theoretical basis for the nondestructive detection of melamine. [Method] According...[Objective] The aim was to develop a nonlinear model of quantitative analysis of melamine content by infrared spectroscopy and provide theoretical basis for the nondestructive detection of melamine. [Method] According to dynamics,mathematical modeling and optimization theory,linear and nonlinear models were respectively set up by taking an absorption peak of 1 550 cm-1 as characteristic absorption peak. [Result] The correlation coefficient of nonlinear model was 0.922 7 and the recovery was 96%,which showed that the nonlinear model was more accurate than linearity model with correlation coefficient of 0.904 9 and recovery of 557%. [Conclusion] It is feasible to determine melamine content by using the nonlinear model quantitatively.展开更多
A wavelet collocation method with nonlinear auto companding is proposed for behavioral modeling of switched current circuits.The companding function is automatically constructed according to the initial error distri...A wavelet collocation method with nonlinear auto companding is proposed for behavioral modeling of switched current circuits.The companding function is automatically constructed according to the initial error distribution obtained through approximating the input output function of the SI circuit by conventional wavelet collocation method.In practical applications,the proposed method is a general purpose approach,by which both the small signal effect and the large signal effect are modeled in a unified formulation to ease the process of modeling and simulation.Compared with the published modeling approaches,the proposed nonlinear auto companding method works more efficiently not only in controlling the error distribution but also in reducing the modeling errors.To demonstrate the promising features of the proposed method,several SI circuits are employed as examples to be modeled and simulated.展开更多
A classic hysteretic model, Preisach-Mayergoyz model （P-M model）, was used to calculate the nonlinear elastic deformation of magnesium （Mg） and cobalt （Co）. Mg and Co samples in cylinder shape were compressively...A classic hysteretic model, Preisach-Mayergoyz model （P-M model）, was used to calculate the nonlinear elastic deformation of magnesium （Mg） and cobalt （Co）. Mg and Co samples in cylinder shape were compressively tested by uniaxial test machine to obtain their stress—strain curves with hysteretic loops. The hysteretic loops do have two properties of P-M hysteretic systems： wiping out and congruency. It is proved that P-M model is applicable for the analysis of these two metals’ hysteresis. This model was applied on Mg at room temperature and Co at 300 ℃. By the P-M model, Co and Mg nonlinear elastic deformation can be calculated based on the stress history. The simulated stress—strain curves agree well with the experimental results. Therefore, the mechanical hysteresis of these two metals can be easily predicted by the classic P-M hysteretic model.展开更多
A class of nonlinear and continuous type Leontief model and its corresponding conditional input-output equation are introduced, and two basic problems under the so called positive or negative boundary assumption are p...A class of nonlinear and continuous type Leontief model and its corresponding conditional input-output equation are introduced, and two basic problems under the so called positive or negative boundary assumption are presented. By approaches of nonlinear analysis some solvability results of this equation and continuous perturbation properties of the relative solution sets are obtained, and some economic significance are illustrated by the remark.展开更多
In order to detect whether the data conforms to the given model, it is necessary to diagnose the data in the statistical way. The diagnostic problem in generalized nonlinear models based on the maximum Lq-likelihood e...In order to detect whether the data conforms to the given model, it is necessary to diagnose the data in the statistical way. The diagnostic problem in generalized nonlinear models based on the maximum Lq-likelihood estimation is considered. Three diagnostic statistics are used to detect whether the outliers exist in the data set. Simulation results show that when the sample size is small, the values of diagnostic statistics based on the maximum Lq-likelihood estimation are greater than the values based on the maximum likelihood estimation. As the sample size increases, the difference between the values of the diagnostic statistics based on two estimation methods diminishes gradually. It means that the outliers can be distinguished easier through the maximum Lq-likelihood method than those through the maximum likelihood estimation method.展开更多
Solving the nonlinear model of an aeroengine is converted to an optimization problem, and thus some optimization search methods can be used. An approach to solving the nonlinear model of an aeroengine by use of the g...Solving the nonlinear model of an aeroengine is converted to an optimization problem, and thus some optimization search methods can be used. An approach to solving the nonlinear model of an aeroengine by use of the genetic algorithm (GA) is developed. By comparison with N R algorithm, the accuracy of the values of initial guesses is not required for GA. Especially, the approach developed can be used when no priori knowledges of the values of initial guesses are availabe, and the convergence is improved significantly. GA properly combined with N R algorithm can increase the convergence speed.展开更多
基金“National Science and Technology Council”(NSTC 111-2221-E-027-088)。
文摘This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,path following dynamics,and system input dynamics.The single-track vehicle model considers the vehicle’s coupled lateral and longitudinal dynamics,as well as nonlinear tire forces.The tracking error dynamics are derived based on the curvilinear coordinates.The cost function is designed to minimize path tracking errors and control effort while considering constraints such as actuator bounds and tire grip limits.An algorithm that utilizes the optimal preview distance vector to query the corresponding reference curvature and reference speed.The length of the preview path is adaptively adjusted based on the vehicle speed,heading error,and path curvature.We validate the controller performance in a simulation environment with the autonomous racing scenario.The simulation results show that the vehicle accurately follows the highly dynamic path with small tracking errors.The maximum preview distance can be prior estimated and guidance the selection of the prediction horizon for NMPC.
文摘The cubic stiffness force model(CSFM)and Bouc-Wen model(BWM)are introduced and compared innovatively.The unknown coefficients of the nonlinear models are identified by the genetic algorithm combined with experiments.By fitting the identified nonlinear coefficients under different excitation amplitudes,the nonlinear vibration responses of the system are predicted.The results show that the accuracy of the BWM is higher than that of the CSFM,especially in the non-resonant region.However,the optimization time of the BWM is longer than that of the CSFM.
基金the support of Texas A&M University at Qatar for the 2022 Sixth Cycle Seed Grant Project。
文摘The main objective of this paper is to investigate the influence of inertia of nonlinear springs on the dispersion behavior of discrete monoatomic chains with lumped and distributed masses.The developed model can represent the wave propagation problem in a non-homogeneous material consisting of heavy inclusions embedded in a matrix.The inclusions are idealized by lumped masses,and the matrix between adjacent inclusions is modeled by a nonlinear spring with distributed masses.Additionally,the model is capable of depicting the wave propagation in bi-material bars,wherein the first material is represented by a rigid particle and the second one is represented by a nonlinear spring with distributed masses.The discrete model of the nonlinear monoatomic chain with lumped and distributed masses is first considered,and a closed-form expression of the dispersion relation is obtained by the second-order Lindstedt-Poincare method(LPM).Next,a continuum model for the nonlinear monoatomic chain is derived directly from its discrete lattice model by a suitable continualization technique.The subsequent use of the second-order method of multiple scales(MMS)facilitates the derivation of the corresponding nonlinear dispersion relation in a closed form.The novelties of the present study consist of(i)considering the inertia of nonlinear springs on the dispersion behavior of the discrete mass-spring chains;(ii)developing the second-order LPM for the wave propagation in the discrete chains;and(iii)deriving a continuum model for the nonlinear monoatomic chains with lumped and distributed masses.Finally,a parametric study is conducted to examine the effects of the design parameters and the distributed spring mass on the nonlinear dispersion relations and phase velocities obtained from both the discrete and continuum models.These parameters include the ratio of the spring mass to the lumped mass,the nonlinear stiffness coefficient of the spring,and the wave amplitude.
基金partially supported by the NSFC(11421061,12271507)the Natural Science Foundation of Shanghai(15ZR1403900)。
文摘This paper studies the strong convergence of the quantum lattice Boltzmann(QLB)scheme for the nonlinear Dirac equations for Gross-Neveu model in 1+1 dimensions.The initial data for the scheme are assumed to be convergent in L^(2).Then for any T≥0 the corresponding solutions for the quantum lattice Boltzmann scheme are shown to be convergent in C([0,T];L^(2)(R^(1)))to the strong solution to the nonlinear Dirac equations as the mesh sizes converge to zero.In the proof,at first a Glimm type functional is introduced to establish the stability estimates for the difference between two solutions for the corresponding quantum lattice Boltzmann scheme,which leads to the compactness of the set of the solutions for the quantum lattice Boltzmann scheme.Finally the limit of any convergent subsequence of the solutions for the quantum lattice Boltzmann scheme is shown to coincide with the strong solution to a Cauchy problem for the nonlinear Dirac equations.
基金Project supported by the National Natural Science Foundation of China (Nos.12072119,12325201,and 52205594)the China National Postdoctoral Program for Innovative Talents (No.BX20220118)。
文摘Due to the novel applications of flexible pipes conveying fluid in the field of soft robotics and biomedicine,the investigations on the mechanical responses of the pipes have attracted considerable attention.The fluid-structure interaction(FSI)between the pipe with a curved shape and the time-varying internal fluid flow brings a great challenge to the revelation of the dynamical behaviors of flexible pipes,especially when the pipe is highly flexible and usually undergoes large deformations.In this work,the geometrically exact model(GEM)for a curved cantilevered pipe conveying pulsating fluid is developed based on the extended Hamilton's principle.The stability of the curved pipe with three different subtended angles is examined with the consideration of steady fluid flow.Specific attention is concentrated on the large-deformation resonance of circular pipes conveying pulsating fluid,which is often encountered in practical engineering.By constructing bifurcation diagrams,oscillating shapes,phase portraits,time traces,and Poincarémaps,the dynamic responses of the curved pipe under various system parameters are revealed.The mean flow velocity of the pulsating fluid is chosen to be either subcritical or supercritical.The numerical results show that the curved pipe conveying pulsating fluid can exhibit rich dynamical behaviors,including periodic and quasi-periodic motions.It is also found that the preferred instability type of a cantilevered curved pipe conveying steady fluid is mainly in the flutter of the second mode.For a moderate value of the mass ratio,however,a third-mode flutter may occur,which is quite different from that of a straight pipe system.
文摘This paper proposes a robust control scheme based on the sequential convex programming and learning-based model for nonlinear system subjected to additive uncertainties.For the problem of system nonlinearty and unknown uncertainties,we study the tube-based model predictive control scheme that makes use of feedforward neural network.Based on the characteristics of the bounded limit of the average cost function while time approaching infinity,a min-max optimization problem(referred to as min-max OP)is formulated to design the controller.The feasibility of this optimization problem and the practical stability of the controlled system are ensured.To demonstrate the efficacy of the proposed approach,a numerical simulation on a double-tank system is conducted.The results of the simulation serve as verification of the effectualness of the proposed scheme.
基金supported by the National Students Training Program for Innovation(Grant No.202210007029)。
文摘How the state of living muscles modulates the features of nonlinear elastic waves generated by external dynamic loads remains unclear because of the challenge of directly observing and modeling nonlinear elastic waves in skeletal muscles in vivo,considering their active deformation behavior.Here,this important issue is addressed by combining experiments performed with an ultrafast ultrasound imaging system to track nonlinear shear waves(shear shock waves)in muscles in vivo and finite element analysis relying on a physically motivated constitutive model to study the effect of muscle activation level.Skeletal muscle was loaded with a deep muscle stimulator to generate shear shock waves(SSWs).The particle velocities,second and third harmonics,and group velocities of the SSWs in living muscles under both passive and active states were measured in vivo.Our experimental results reveal,for the first time,that muscle states have a pronounced effect on wave features;a low level of activation may facilitate the occurrence of both the second and third harmonics,whereas a high level of activation may inhibit the third harmonic.Finite element analysis was further carried out to quantitatively explore the effect of active muscle deformation behavior on the generation and propagation of SSWs.The simulation results at different muscle activation levels confirmed the experimental findings.The ability to reveal the effects of muscle state on the features of SSWs may be helpful in elucidating the unique dynamic deformation mechanism of living skeletal muscles,quantitatively characterizing diverse shock wave-based therapy instruments,and guiding the design of muscle-mimicking soft materials.
文摘In order to enhance the control performance of piezo-positioning system,the influence of hysteresis characteristics and its compensation method are studied.Hammerstein model is used to represent the dynamic hysteresis nonlinear characteristics of piezo-positioning actuator.The static nonlinear part and dynamic linear part of the Hammerstein model are represented by models obtained through the Prandtl-Ishlinskii(PI)model and Hankel matrix system identification method,respectively.This model demonstrates good generalization capability for typical input frequencies below 200 Hz.A sliding mode inverse compensation tracking control strategy based on P-I inverse model and integral augmentation is proposed.Experimental results show that compared with PID inverse compensation control and sliding mode control without inverse compensation,the sliding mode inverse compensation control has a more ideal step response and no overshoot,moreover,the settling time is only 6.2 ms.In the frequency domain,the system closed-loop tracking bandwidth reaches 119.9 Hz,and the disturbance rejection bandwidth reaches 86.2 Hz.The proposed control strategy can effectively compensate the hysteresis nonlinearity,and improve the tracking accuracy and antidisturbance capability of piezo-positioning system.
文摘This paper develops a comprehensive computational modeling and simulation framework based on Complex Adaptive Systems(CAS)theory to unveil the underlying mechanisms of self-organization,nonlinear evolution,and emergence in social systems.By integrating mathematical models,agent-based modeling,network dynamic analysis,and hybrid modeling approaches,the study applies CAS theory to case studies in economic markets,political decision-making,and social interactions.The experimental results demonstrate that local interactions among individual agents can give rise to complex global phenomena,such as market fluctuations,opinion polarization,and sudden outbreaks of social movements.This framework not only provides a more robust explanation for the nonlinear dynamics and abrupt transitions that traditional models often fail to capture,but also offers valuable decision-support tools for public policy formulation,social governance,and risk management.Emphasizing the importance of interdisciplinary approaches,this work outlines future research directions in high-performance computing,artificial intelligence,and real-time data integration to further advance the theoretical and practical applications of CAS in the social sciences.
基金Project supported by the National Science and Technology Major Project(No.J2019-I-0008-0008)the National Natural Science Foundation of China(No.52305096)the Chinese Postdoctoral Science Foundation(No.GZB20230117)。
文摘Fatigue failure caused by vibration is the most common type of pipeline failure.The core of this research is to obtain the nonlinear dynamic stress of a pipeline system accurately and efficiently,a topic that needs to be explored in the existing literature.The shell theory can better simulate the circumferential stress distribution,and thus the Mindlin-Reissner shell theory is used to model the pipeline.In this paper,the continuous pipeline system is combined with clamps through modal expansion for the first time,which realizes the coupling problem between a shell and a clamp.While the Bouc-Wen model is used to simulate the nonlinear external force generated by a clamp,the nonlinear coupling characteristics of the system are effectively captured.Then,the dynamic equation of the clamp-pipeline system is established according to the Lagrange energy equation.Based on the resonance frequency and stress amplitude obtained from the experiment,the nonlinear parameters of the clamp are identified with the semi-analytical method(SAM)and particle swarm optimization(PSO)algorithm.This study provides a theoretical basis for the clamp-pipeline system and an efficient and universal solution for stress prediction and analysis of pipelines in engineering.
基金Project supported by the National Science and Technology Major Project(No.J2022-IV-0005-0022)the Aero Science Foundation of China(No.20230015050001)the Shenyang Science and Technology Plan Project of China(No.24-202-6-01)。
文摘As a common fault of the aero-engine,the blade-casing rubbing(BCR)has the potential to cause catastrophic accidents.In this paper,to investigate the dynamic responses and wear characteristics of the system,the laminated shell element is used to establish the finite element model(FEM)of a flexibly coated casing system.Using the shell element,the blade is modeled,and the surface stress of the blade is calculated.The stress-solving method of the blade is validated through comparisons with the measured time-domain waveform of the stress.Then,a dynamic model of a blade-flexibly coated casing system with rubbing is proposed,accounting for the time-varying mass and stiffness of the casing caused by coating wear.The effects of the proposed flexible casing model are compared with those of a rigid casing model,and the stress changes induced by rubbing are investigated.The results show that the natural characteristics of the coated casing decrease due to the coating wear.The flexibly coated casing model is found to be more suitable for studying casing vibration.Additionally,the stress changes caused by rubbing are slight,and the change in the stress maximum is approximately 5%under the influence of the abrasive coating.
基金in part supported by the National Natural Science Foundation of China(Grant Nos.42288101,42405147 and 42475054)in part by the China National Postdoctoral Program for Innovative Talents(Grant No.BX20230071)。
文摘Conducting predictability studies is essential for tracing the source of forecast errors,which not only leads to the improvement of observation and forecasting systems,but also enhances the understanding of weather and climate phenomena.In the past few decades,dynamical numerical models have been the primary tools for predictability studies,achieving significant progress.Nowadays,with the advances in artificial intelligence(AI)techniques and accumulations of vast meteorological data,modeling weather and climate events using modern data-driven approaches is becoming trendy,where FourCastNet,Pangu-Weather,and GraphCast are successful pioneers.In this perspective article,we suggest AI models should not be limited to forecasting but be expanded to predictability studies,leveraging AI's advantages of high efficiency and self-contained optimization modules.To this end,we first remark that AI models should possess high simulation capability with fine spatiotemporal resolution for two kinds of predictability studies.AI models with high simulation capabilities comparable to numerical models can be considered to provide solutions to partial differential equations in a data-driven way.Then,we highlight several specific predictability issues with well-determined nonlinear optimization formulizations,which can be well-studied using AI models,holding significant scientific value.In addition,we advocate for the incorporation of AI models into the synergistic cycle of the cognition–observation–model paradigm.Comprehensive predictability studies have the potential to transform“big data”to“big and better data”and shift the focus from“AI for forecasts”to“AI for science”,ultimately advancing the development of the atmospheric and oceanic sciences.
基金Supported by National Natural Science Foundation of China,No.81972947Academic Promotion Programme of Shandong First Medical University,No.2019LJ005.
文摘BACKGROUND The risk factors and prediction models for diabetic foot(DF)remain incompletely understood,with several potential factors still requiring in-depth investigations.AIM To identify risk factors for new-onset DF and develop a robust prediction model for hospitalized patients with type 2 diabetes.METHODS We included 6301 hospitalized patients with type 2 diabetes from January 2016 to December 2021.A univariate Cox model and least absolute shrinkage and selection operator analyses were applied to select the appropriate predictors.Nonlinear associations between continuous variables and the risk of DF were explored using restricted cubic spline functions.The Cox model was further employed to evaluate the impact of risk factors on DF.The area under the curve(AUC)was measured to evaluate the accuracy of the prediction model.RESULTS Seventy-five diabetic inpatients experienced DF.The incidence density of DF was 4.5/1000 person-years.A long duration of diabetes,lower extremity arterial disease,lower serum albumin,fasting plasma glucose(FPG),and diabetic nephropathy were independently associated with DF.Among these risk factors,the serum albumin concentration was inversely associated with DF,with a hazard ratio(HR)and 95%confidence interval(CI)of 0.91(0.88-0.95)(P<0.001).Additionally,a U-shaped nonlinear relationship was observed between the FPG level and DF.After adjusting for other variables,the HRs and 95%CI for FPG<4.4 mmol/L and≥7.0 mmol/L were 3.99(1.55-10.25)(P=0.004)and 3.12(1.66-5.87)(P<0.001),respectively,which was greater than the mid-range level(4.4-6.9 mmol/L).The AUC for predicting DF over 3 years was 0.797.CONCLUSION FPG demonstrated a U-shaped relationship with DF.Serum albumin levels were negatively associated with DF.The prediction nomogram model of DF showed good discrimination ability using diabetes duration,lower extremity arterial disease,serum albumin,FPG,and diabetic nephropathy(Clinicaltrial.gov NCT05519163).
基金Supported by Promoting Projects of the Industrialization of University Research of Jiangsu Province (JHZD09-35)Natural Science Research Project of Universities in Jiangsu Province (09KJD210001)Research Foundation of Huaiyin Institute of Technology(HGA0908)~~
文摘[Objective] The aim was to develop a nonlinear model of quantitative analysis of melamine content by infrared spectroscopy and provide theoretical basis for the nondestructive detection of melamine. [Method] According to dynamics,mathematical modeling and optimization theory,linear and nonlinear models were respectively set up by taking an absorption peak of 1 550 cm-1 as characteristic absorption peak. [Result] The correlation coefficient of nonlinear model was 0.922 7 and the recovery was 96%,which showed that the nonlinear model was more accurate than linearity model with correlation coefficient of 0.904 9 and recovery of 557%. [Conclusion] It is feasible to determine melamine content by using the nonlinear model quantitatively.
文摘A wavelet collocation method with nonlinear auto companding is proposed for behavioral modeling of switched current circuits.The companding function is automatically constructed according to the initial error distribution obtained through approximating the input output function of the SI circuit by conventional wavelet collocation method.In practical applications,the proposed method is a general purpose approach,by which both the small signal effect and the large signal effect are modeled in a unified formulation to ease the process of modeling and simulation.Compared with the published modeling approaches,the proposed nonlinear auto companding method works more efficiently not only in controlling the error distribution but also in reducing the modeling errors.To demonstrate the promising features of the proposed method,several SI circuits are employed as examples to be modeled and simulated.
基金Projects (51002045, 10947105) supported by the National Natural Science Foundation of ChinaProject (2010B430016) supported by the Nature Science Research Project of Education Department of Henan Province, ChinaProject (2012IRTSTHN007) supported by Program for Innovative Research Team (in Science and Technology) in the University of Henan Province, China
文摘A classic hysteretic model, Preisach-Mayergoyz model （P-M model）, was used to calculate the nonlinear elastic deformation of magnesium （Mg） and cobalt （Co）. Mg and Co samples in cylinder shape were compressively tested by uniaxial test machine to obtain their stress—strain curves with hysteretic loops. The hysteretic loops do have two properties of P-M hysteretic systems： wiping out and congruency. It is proved that P-M model is applicable for the analysis of these two metals’ hysteresis. This model was applied on Mg at room temperature and Co at 300 ℃. By the P-M model, Co and Mg nonlinear elastic deformation can be calculated based on the stress history. The simulated stress—strain curves agree well with the experimental results. Therefore, the mechanical hysteresis of these two metals can be easily predicted by the classic P-M hysteretic model.
文摘A class of nonlinear and continuous type Leontief model and its corresponding conditional input-output equation are introduced, and two basic problems under the so called positive or negative boundary assumption are presented. By approaches of nonlinear analysis some solvability results of this equation and continuous perturbation properties of the relative solution sets are obtained, and some economic significance are illustrated by the remark.
基金The National Natural Science Foundation of China(No.11171065)the Natural Science Foundation of Jiangsu Province(No.BK2011058)
文摘In order to detect whether the data conforms to the given model, it is necessary to diagnose the data in the statistical way. The diagnostic problem in generalized nonlinear models based on the maximum Lq-likelihood estimation is considered. Three diagnostic statistics are used to detect whether the outliers exist in the data set. Simulation results show that when the sample size is small, the values of diagnostic statistics based on the maximum Lq-likelihood estimation are greater than the values based on the maximum likelihood estimation. As the sample size increases, the difference between the values of the diagnostic statistics based on two estimation methods diminishes gradually. It means that the outliers can be distinguished easier through the maximum Lq-likelihood method than those through the maximum likelihood estimation method.
基金Aeronautic Science Foundation of China ( 0 0 C5 2 0 3 0 ) and National Doctoral Education Foundation ( 2 0 0 0 0 2 870 1)
文摘Solving the nonlinear model of an aeroengine is converted to an optimization problem, and thus some optimization search methods can be used. An approach to solving the nonlinear model of an aeroengine by use of the genetic algorithm (GA) is developed. By comparison with N R algorithm, the accuracy of the values of initial guesses is not required for GA. Especially, the approach developed can be used when no priori knowledges of the values of initial guesses are availabe, and the convergence is improved significantly. GA properly combined with N R algorithm can increase the convergence speed.
