The complex vibration directly affects the dynamic safety of drill string in ultra-deep wells and extra-deep wells.It is important to understand the dynamic characteristics of drill string to ensure the safety of dril...The complex vibration directly affects the dynamic safety of drill string in ultra-deep wells and extra-deep wells.It is important to understand the dynamic characteristics of drill string to ensure the safety of drill string.Due to the super slenderness ratio of drill string,strong nonlinearity implied in dynamic analysis and the complex load environment,dynamic simulation of drill string faces great challenges.At present,many simulation methods have been developed to analyze drill string dynamics,and node iteration method is one of them.The node iteration method has a unique advantage in dealing with the contact characteristics between drill string and borehole wall,but its drawback is that the calculation consumes a considerable amount of time.This paper presents a dynamic simulation method of drilling string in extra-deep well based on successive over-relaxation node iterative method(SOR node iteration method).Through theoretical analysis and numerical examples,the correctness and validity of this method were verified,and the dynamics characteristics of drill string in extra-deep wells were calculated and analyzed.The results demonstrate that,in contrast to the conventional node iteration method,the SOR node iteration method can increase the computational efficiency by 48.2%while achieving comparable results.And the whirl trajectory of the extra-deep well drill string is extremely complicated,the maximum rotational speed downhole is approximately twice the rotational speed on the ground.The dynamic torque increases rapidly at the position of the bottom stabilizer,and the lateral vibration in the middle and lower parts of drill string is relatively intense.展开更多
The high-speed winding spindle employs a flexible support system incorporating rubber O-rings.By precisely configuring the structural parameters and the number of the O-rings,the spindle can stably surpass its critica...The high-speed winding spindle employs a flexible support system incorporating rubber O-rings.By precisely configuring the structural parameters and the number of the O-rings,the spindle can stably surpass its critical speed points and maintain operational stability across the entire working speed range.However,the support stiffness and damping of rubber O-rings exhibit significant nonlinear frequency dependence.Conventional experimental methods for deriving equivalent stiffness and damping,based on the principle of the forced non-resonance method,require fabricating custom setups for each O-ring specification and conducting vibration tests at varying frequencies,resulting in low efficiency and high costs.This study proposes a hybrid simulation-experimental method for dynamic parameter identification.Firstly,the frequency-dependent dynamic parameters of a specific O-ring support system are experimentally obtained.Subsequently,a corresponding parametric finite element model is established to simulate and solve the equivalent elastic modulus and equivalent stiffness-damping coefficient of this O-ring support system.Ultimately,after iterative simulation,the simulated and experimental results achieve a 99.7%agreement.The parametric finite element model developed herein can directly simulate and inversely estimate frequency-dependent dynamic parameters for O-rings of different specifications but identical elastic modulus.展开更多
Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.Howev...Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.However,the widened hydraulic excitation frequency may satisfy the blade resonance due to the time variation in the velocity and angle of attack of the ocean current,even resulting in blade fatigue and destructively interfering with grid stability.A key parameter that determines the resonance amplitude of the blade is the hydrodynamic damping ratio(HDR).However,HDR is difficult to obtain due to the complex fluid-structure interaction(FSI).Therefore,a literature review was conducted on the hydrodynamic damping characteristics of blade-like structures.The experimental and simulation methods used to identify and obtain the HDR quantitatively were described,placing emphasis on the experimental processes and simulation setups.Moreover,the accuracy and efficiency of different simulation methods were compared,and the modal work approach was recommended.The effects of key typical parameters,including flow velocity,angle of attack,gap,rotational speed,and cavitation,on the HDR were then summarized,and the suggestions on operating conditions were presented from the perspective of increasing the HDR.Subsequently,considering multiple flow parameters,several theoretical derivations and semi-empirical prediction formulas for HDR were introduced,and the accuracy and application were discussed.Based on the shortcomings of the existing research,the direction of future research was finally determined.The current work offers a clear understanding of the HDR of blade-like structures,which could improve the evaluation accuracy of flow-induced vibration in the design stage.展开更多
The feasibility of using a problem-dependent method to solve systems of second order ODEs is corroborated by an eigen-based theory and a methodology to develop such a numerical method is constructed.The key steps of t...The feasibility of using a problem-dependent method to solve systems of second order ODEs is corroborated by an eigen-based theory and a methodology to develop such a numerical method is constructed.The key steps of this methodology are to decouple a system of ODEs of second order into a set of uncoupled ODEs of second order;next,an eigen-dependent method is proposed to approximate the solution of each uncoupled ODE of second order.It is vital to transform all eigen-dependent methods to a problem-dependent method to bypass an Eigen analysis.The development of an eigen-dependent method plays a key role in this methodology so that slow eigenmodes can be accurately integrated while there is no instability or excessive amplitude growth in fast eigenmodes.This can explain why a problem-dependent method can simultaneously combine the explicitness of each step and A-stability.Consequently,huge computational efforts can be saved for solving nonlinear stiff problems.A new family of problem-dependent methods is developed in this work so that the feasibility of the proposed methodology can be affirmed.It has almost the same performance as that of the HHT-αmethod.However,it can save more than 99.5%of CPU demand in approximating a solution for a system of 1000 nonlinear second order ODEs.展开更多
In recent years,scholars around the world have shown increasing interest in elastic support structures,leading to significant progress in dynamic modeling techniques for pipeline systems.Although multiple analytical a...In recent years,scholars around the world have shown increasing interest in elastic support structures,leading to significant progress in dynamic modeling techniques for pipeline systems.Although multiple analytical approaches exist,engineers increasingly prioritize computationally efficient,precise low-order models for practical implementation.In order to address this need,this study develops an innovative nonlinear dynamic formulation for pipelines accounting for both foundation and boundary nonlinearities.The proposed solution methodology initiates with global mode extraction using the global mode technique,followed by a detailed implementation procedure.Model validation is conducted through a cantilever pipeline case study featuring nonlinear support conditions,where strong agreement between the proposed model's predictions and finiteelement benchmark solutions demonstrates its reliability.Subsequently,a comprehensive parametric study investigates the combined effects of foundation stiffness,boundary constraints,excitation intensity,and nonlinear interaction terms on the vibrational response of the cantilever pipe.This systematic approach yields critical insights for practical engineering designs and applications.展开更多
This paper presents a framework for constructing surrogate models for sensitivity analysis of structural dynamics behavior.Physical models involving deformation,such as collisions,vibrations,and penetration,are devel-...This paper presents a framework for constructing surrogate models for sensitivity analysis of structural dynamics behavior.Physical models involving deformation,such as collisions,vibrations,and penetration,are devel-oped using the material point method.To reduce the computational cost of Monte Carlo simulations,response surface models are created as surrogate models for the material point system to approximate its dynamic behavior.An adaptive randomized greedy algorithm is employed to construct a sparse polynomial chaos expansion model with a fixed order,effectively balancing the accuracy and computational efficiency of the surrogate model.Based on the sparse polynomial chaos expansion,sensitivity analysis is conducted using the global finite difference and Sobol methods.Several examples of structural dynamics are provided to demonstrate the effectiveness of the proposed method in addressing structural dynamics problems.展开更多
0 INTRODUCTION In recent years,modern railways have been actively under construction in the complex mountainous area of Southwest China.However,rockfall poses a significant threat to both construction and operation ph...0 INTRODUCTION In recent years,modern railways have been actively under construction in the complex mountainous area of Southwest China.However,rockfall poses a significant threat to both construction and operation phases of railway projects(Yan et al.,2023;Chen et al.,2022;Fanos and Pradhan,2018).展开更多
The Fringe Projection Profilometry(FPP)system with a single exposure time or a single projection intensity is limited by the dynamic range of the camera,which can lead to overexposure and underexposure of the image,re...The Fringe Projection Profilometry(FPP)system with a single exposure time or a single projection intensity is limited by the dynamic range of the camera,which can lead to overexposure and underexposure of the image,resulting in point cloud loss or reduced accuracy.To address this issue,unlike the pixel modulation method of projectors,we utilize the characteristics of color projectors where the intensity of the three-channel LED can be controlled independently.We propose a method for separating the projector's three-channel light intensity,combined with a color camera,to achieve single exposure and multi-intensity image acquisition.Further,the crosstalk coefficient is applied to predict the three-channel reflectance of the measured object.By integrating clustering and channel mapping,we establish a pixel-level mapping model between the projector's three-channel current and the camera's three-channel image intensity,which realizes the optimal projection current prediction and the high dynamic range(HDR)image acquisition.The proposed method allows for high-precision three-dimensional(3D)data acquisition of HDR scenes with a single exposure.The effectiveness of this method has been validated through experiments with standard planes and standard steps,showing a significant reduction in mean absolute error(44.6%)compared to existing singleexposure HDR methods.Additionally,the number of images required for acquisition is significantly reduced(by 70.8%)compared to multi-exposure fusion methods.This proposed method has great potential in various FPP-related fields.展开更多
Ribonucleic acid(RNA)structures and dynamics play a crucial role in elucidating RNA functions and facilitating the design of drugs targeting RNA and RNA-protein complexes.However,obtaining RNA structures using convent...Ribonucleic acid(RNA)structures and dynamics play a crucial role in elucidating RNA functions and facilitating the design of drugs targeting RNA and RNA-protein complexes.However,obtaining RNA structures using conventional biophysical techniques,such as Xray crystallography and solution nuclear magnetic resonance(NMR),presents challenges due to the inherent flexibility and susceptibility to degradation of RNA.In recent years,solid-state NMR(SSNMR)has rapidly emerged as a promising alternative technique for characterizing RNA structure and dynamics.SSNMR has several distinct advantages,including flexibility in sample states,the ability to capture dynamic features of RNA in solid form,and suitability to character RNAs in various sizes.Recent decade witnessed the growth of ^(1)H-detected SSNMR methods on RNA,which targeted elucidating RNA topology and base pair dynamics in solid state.They have been applied to determine the topology of RNA segment in human immunodeficiency virus(HIV)genome and the base pair dynamics of riboswitch RNA.These advancements have expanded the utility of SSNMR techniques within the RNA research field.This review provides a comprehensive discussion of recent progress in ^(1)H-detected SSNMR investigations into RNA structure and dynamics.We focus on the established ^(1)H-detected SSNMR methods,sample preparation protocols,and the implementation of rapid data acquisition approaches.展开更多
Dynamic soaring,inspired by the wind-riding flight of birds such as albatrosses,is a biomimetic technique which leverages wind fields to enhance the endurance of unmanned aerial vehicles(UAVs).Achieving a precise soar...Dynamic soaring,inspired by the wind-riding flight of birds such as albatrosses,is a biomimetic technique which leverages wind fields to enhance the endurance of unmanned aerial vehicles(UAVs).Achieving a precise soaring trajectory is crucial for maximizing energy efficiency during flight.Existing nonlinear programming methods are heavily dependent on the choice of initial values which is hard to determine.Therefore,this paper introduces a deep reinforcement learning method based on a differentially flat model for dynamic soaring trajectory planning and optimization.Initially,the gliding trajectory is parameterized using Fourier basis functions,achieving a flexible trajectory representation with a minimal number of hyperparameters.Subsequently,the trajectory optimization problem is formulated as a dynamic interactive process of Markov decision-making.The hyperparameters of the trajectory are optimized using the Proximal Policy Optimization(PPO2)algorithm from deep reinforcement learning(DRL),reducing the strong reliance on initial value settings in the optimization process.Finally,a comparison between the proposed method and the nonlinear programming method reveals that the trajectory generated by the proposed approach is smoother while meeting the same performance requirements.Specifically,the proposed method achieves a 34%reduction in maximum thrust,a 39.4%decrease in maximum thrust difference,and a 33%reduction in maximum airspeed difference.展开更多
The turbine blades operate under high temperature and high pressure conditions,and when using radiation thermometry,the influence of radiation from surrounding blades leads to measurement errors.To address this issue,...The turbine blades operate under high temperature and high pressure conditions,and when using radiation thermometry,the influence of radiation from surrounding blades leads to measurement errors.To address this issue,this paper develops a three-dimensional discretized dynamic radiation transfer model based on the blade shape of the turbine.The relationship between the radiation angle coefficient of the surrounding blades and the rotation angle of the blade under test is analyzed.The radiation angle coefficient is calculated using the triangular element method,and temperature inversion is performed based on the effective emissivity to compute the measurement error.The results show that under dynamic high temperature conditions,the temperature measurement error caused by reflection at the selected 60%leaf height point varies with the rotation angle,and the maximum reaches 25.58K.The angular coefficient exhibits periodic fluctuations with changes in rotation angle,and the maximum effective emissivity increases as the rotation angle increases.As the blade height increases,the impact of reflected radiation on radiometric temperature measurement errors shows a decreasing trend.This study provides a reference for radiation thermometry in dynamic high-temperature environments.展开更多
Intelligent production is an important development direction in intelligent manufacturing,with intelligent factories playing a crucial role in promoting intelligent production.Flexible job shops,as the main form of in...Intelligent production is an important development direction in intelligent manufacturing,with intelligent factories playing a crucial role in promoting intelligent production.Flexible job shops,as the main form of intelligent factories,constantly face dynamic disturbances during the production process,including machine failures and urgent orders.This paper discusses the basic models and research methods of job shop scheduling,emphasizing the important role of dynamic job shop scheduling and its response schemes in future research.A multi-objective flexible job shop dynamic scheduling mathematical model is established,highlighting its complex and multi-constraint characteristics under different interferences.A classification discussion is conducted on the dynamic response methods and optimization objectives under machine failures,emergency orders,fuzzy completion times,and mixed dynamic events.The development process of traditional scheduling rules and intelligent methods in dynamic scheduling are also analyzed.Finally,based on the current development status of job shop scheduling and the requirements of intelligent manufacturing,the future development trends of dynamic scheduling in flexible job shops are proposed.展开更多
In this study,we construct a bi-level optimization model based on the Stackelberg game and propose a robust optimization algorithm for solving the bi-level model,assuming an actual situation with several participants ...In this study,we construct a bi-level optimization model based on the Stackelberg game and propose a robust optimization algorithm for solving the bi-level model,assuming an actual situation with several participants in energy trading.Firstly,the energy trading process is analyzed between each subject based on the establishment of the operation framework of multi-agent participation in energy trading.Secondly,the optimal operation model of each energy trading agent is established to develop a bi-level game model including each energy participant.Finally,a combination algorithm of improved robust optimization over time(ROOT)and CPLEX is proposed to solve the established game model.The experimental results indicate that under different fitness thresholds,the robust optimization results of the proposed algorithm are increased by 56.91%and 68.54%,respectively.The established bi-level game model effectively balances the benefits of different energy trading entities.The proposed algorithm proposed can increase the income of each participant in the game by an average of 8.59%.展开更多
Feedforward control is one of the most effective control techniques to increase the robot’s tracking accuracy.However,most of the dynamic models used in the feedforward controllers are linearly simplified such that t...Feedforward control is one of the most effective control techniques to increase the robot’s tracking accuracy.However,most of the dynamic models used in the feedforward controllers are linearly simplified such that the nonlinear and time-varying characteristics of dynamics in the workspace are ignored.In this paper,an iterative tuning method for feedforward control of parallel manipulators by taking nonlinear dynamics into account is proposed.Based on the robot rigid-body dynamic model,a feedforward controller considering the dynamic nonlinearity is presented.An iterative tuning method is given to iteratively update the feedforward controller by minimizing the root mean square(RMS)of the joint errors at each cycle.The effectiveness and extrapolation capability of the proposed method are validated through the experiments on a 2-DOF parallel manipulator.This research proposes an iterative tuning method for feedforward control of parallel manipulators considering nonlinear dynamics,which has better extrapolation capability in the whole workspace of manipulators.展开更多
The structural dynamic response reconstruction technology can extract unmeasured information from limited measured data,significantly impacting vibration control,load identification,parameter identification,fault diag...The structural dynamic response reconstruction technology can extract unmeasured information from limited measured data,significantly impacting vibration control,load identification,parameter identification,fault diagnosis,and related fields.This paper proposes a dynamic response reconstruction method based on the Kalman filter,which simultaneously identifies external excitation and reconstructs dynamic responses at unmeasured positions.The weighted least squares method determines the load weighting matrix for excitation identification,while the minimum variance unbiased estimation determines the Kalman filter gain.The excitation prediction Kalman filter is constructed through time,excitation,and measurement updates.Subsequently,the response at the target point is reconstructed using the state vector,observation matrix,and excitation influence matrix obtained through the excitation prediction Kalman filter algorithm.An algorithm for reconstructing responses in continuous system using the excitation prediction Kalman filtering algorithm in modal space is derived.The proposed structural dynamic response reconstruction method evaluates the response reconstruction and the load identification performance under various load types and errors through simulation examples.Results demonstrate the accurate excitation identification under different load conditions and simultaneous reconstruction of target point responses,verifying the feasibility and reliability of the proposed method.展开更多
Rapid population growth in recent decades has intensified both the global energy crisis and the challenges posed by climate change,including global warming.Currently,the increased frequency of extreme weather events a...Rapid population growth in recent decades has intensified both the global energy crisis and the challenges posed by climate change,including global warming.Currently,the increased frequency of extreme weather events and large fluctuations in ambient temperature disrupt thermal comfort and negatively impact health,driving a growing dependence on cooling and heating energy sources.Consequently,efficient thermal management has become a central focus of energy research.Traditional thermal management systems consume substantial energy,further contributing to greenhouse gas emissions.In contrast,emergent radiant thermal management technologies that rely on renewable energy have been proposed as sustainable alternatives.However,achieving year-round thermal management without additional energy input remains a formidable challenge.Recently,dynamic radiative thermal management technologies have emerged as the most promising solution,offering the potential for energy-efficient adaptation across seasonal variations.This review systematically presents recent advancements in dynamic radiative thermal management,covering fundamental principles,switching mechanisms,primary materials,and application areas.Additionally,the key challenges hindering the broader adoption of dynamic radiative thermal management technologies are discussed.By highlighting their transformative potential,this review provides insights into the design and industrial scalability of these innovations,with the ultimate aim of promoting renewable energy integration in thermal management applications.展开更多
This review provides a comprehensive and systematic examination of Computational Fluid Dynamics(CFD)techniques and methodologies applied to the development of Vertical Axis Wind Turbines(VAWTs).Although VAWTs offer si...This review provides a comprehensive and systematic examination of Computational Fluid Dynamics(CFD)techniques and methodologies applied to the development of Vertical Axis Wind Turbines(VAWTs).Although VAWTs offer significant advantages for urban wind applications,such as omnidirectional wind capture and a compact,ground-accessible design,they face substantial aerodynamic challenges,including dynamic stall,blade-wake interactions,and continuously varying angles of attack throughout their rotation.The review critically evaluates how CFD has been leveraged to address these challenges,detailing the modelling frameworks,simulation setups,mesh strategies,turbulence models,and boundary condition treatments adopted in the literature.Special attention is given to the comparative performance of 2-D vs.3-D simulations,static and dynamic meshing techniques(sliding,overset,morphing),and the impact of near-wall resolution on prediction fidelity.Moreover,this review maps the evolution of CFD tools in capturing key performance indicators including power coefficient,torque,flow separation,and wake dynamics,while highlighting both achievements and current limitations.The synthesis of studies reveals best practices,identifies gaps in simulation fidelity and validation strategies,and outlines critical directions for future research,particularly in high-fidelity modelling and cost-effective simulation of urban-scale VAWTs.By synthesizing insights from over a hundred referenced studies,this review serves as a consolidated resource to advance VAWT design and performance optimization through CFD.These include studies on various aspects such as blade geometry refinement,turbulence modeling,wake interaction mitigation,tip-loss reduction,dynamic stall control,and other aerodynamic and structural improvements.This,in turn,supports their broader integration into sustainable energy systems.展开更多
We present a hybrid smoothed particle magnetohydrodynamics(SPMHD)code integrating smoothed particle hydrodynamics(SPH)and finite element methods(FEM)to simulate coupled fluid-electromagnetic phenomena.The framework em...We present a hybrid smoothed particle magnetohydrodynamics(SPMHD)code integrating smoothed particle hydrodynamics(SPH)and finite element methods(FEM)to simulate coupled fluid-electromagnetic phenomena.The framework employs SPH for fluid dynamics,addressing large deformations,shocks,and plasma behavior,while FEM resolves electromagnetic fields via Maxwell's equations for magnetic vector and electric scalar potentials,ensuring divergence-free conditions and global current density calculations in conductive region.Operator splitting method couples these modules,enabling real-time integration of magnetic,electric,thermal,and fluid fields.Benchmark tests validate the code against analytical solutions and existing models,including blow-by instability simulations that demonstrate the method's accuracy in capturing fluid-magnetic interactions.Designed for 3D applications,SPMHD offers robust scalability across multiprocessor architectures,establishing it as a versatile tool for plasma physics research.展开更多
As a pyrometallurgical process,circulating fluidized bed(CFB) roasting has good potential for application in desulfurization of high-sulfur bauxite.The gas-solid distribution and reaction during CFB roasting of high-s...As a pyrometallurgical process,circulating fluidized bed(CFB) roasting has good potential for application in desulfurization of high-sulfur bauxite.The gas-solid distribution and reaction during CFB roasting of high-sulfur bauxite were simulated using the computational particle fluid dynamics(CPFD) method.The effect of primary air flow velocity on particle velocity,particle volume distribution,furnace temperature distribution and pressure distribution were investigated.Under the condition of the same total flow of natural gas,the impact of the number of inlets on the desulfurization efficiency,atmosphere mass fraction distribution and temperature distribution in the furnace was further investigated.展开更多
Accurate acquisition of the lithological composition of a tunnel face is crucial for efficient tunneling and hazard prevention in large-diameter slurry shield tunnels.While widely applied,current data-driven methods o...Accurate acquisition of the lithological composition of a tunnel face is crucial for efficient tunneling and hazard prevention in large-diameter slurry shield tunnels.While widely applied,current data-driven methods often face challenges such as indirect prediction,data sparsity,and data drift,which limit their accuracy and generalizability.This study develops an integrated method that combines a knowledge-driven method to directly compute distribution patterns of lithological components,which are used as a priori knowledge to guide the development of a data-driven method.Coupled Markov chain(CMC)and deep neural networks(DNNs)serve as the knowledge-driven and data-driven components,respectively.Additionally,a dynamic prediction strategy is proposed,where the model is continuously optimized as construction progresses and training samples accumulate,rather than being statically trained on post-construction data,as is common in data-driven methods.Finally,the proposed method is evaluated using a real-world project.The evaluation results show that the integrated method outperforms both individual data-and knowledge-driven methods,demonstrating higher predictive performance,greater stability,and greater robustness to data scarcity and data drift.Furthermore,the dynamic prediction strategy better captures the effects of gradual data accumulation and lithological spatial variability on prediction performance during construction,providing new insights for real-time prediction in practical tunneling applications.展开更多
基金supported by the National Natural Science Foundation of China(52174003,52374008).
文摘The complex vibration directly affects the dynamic safety of drill string in ultra-deep wells and extra-deep wells.It is important to understand the dynamic characteristics of drill string to ensure the safety of drill string.Due to the super slenderness ratio of drill string,strong nonlinearity implied in dynamic analysis and the complex load environment,dynamic simulation of drill string faces great challenges.At present,many simulation methods have been developed to analyze drill string dynamics,and node iteration method is one of them.The node iteration method has a unique advantage in dealing with the contact characteristics between drill string and borehole wall,but its drawback is that the calculation consumes a considerable amount of time.This paper presents a dynamic simulation method of drilling string in extra-deep well based on successive over-relaxation node iterative method(SOR node iteration method).Through theoretical analysis and numerical examples,the correctness and validity of this method were verified,and the dynamics characteristics of drill string in extra-deep wells were calculated and analyzed.The results demonstrate that,in contrast to the conventional node iteration method,the SOR node iteration method can increase the computational efficiency by 48.2%while achieving comparable results.And the whirl trajectory of the extra-deep well drill string is extremely complicated,the maximum rotational speed downhole is approximately twice the rotational speed on the ground.The dynamic torque increases rapidly at the position of the bottom stabilizer,and the lateral vibration in the middle and lower parts of drill string is relatively intense.
基金National Key R&D Program of China(No.2017YFB1304000)Fundamental Research Funds for the Central Universities,China(No.2232023G-05-1)。
文摘The high-speed winding spindle employs a flexible support system incorporating rubber O-rings.By precisely configuring the structural parameters and the number of the O-rings,the spindle can stably surpass its critical speed points and maintain operational stability across the entire working speed range.However,the support stiffness and damping of rubber O-rings exhibit significant nonlinear frequency dependence.Conventional experimental methods for deriving equivalent stiffness and damping,based on the principle of the forced non-resonance method,require fabricating custom setups for each O-ring specification and conducting vibration tests at varying frequencies,resulting in low efficiency and high costs.This study proposes a hybrid simulation-experimental method for dynamic parameter identification.Firstly,the frequency-dependent dynamic parameters of a specific O-ring support system are experimentally obtained.Subsequently,a corresponding parametric finite element model is established to simulate and solve the equivalent elastic modulus and equivalent stiffness-damping coefficient of this O-ring support system.Ultimately,after iterative simulation,the simulated and experimental results achieve a 99.7%agreement.The parametric finite element model developed herein can directly simulate and inversely estimate frequency-dependent dynamic parameters for O-rings of different specifications but identical elastic modulus.
基金Supported by the National Natural Science Foundation of China(Nos.52222904 and 52309117)China Postdoctoral Science Foundation(Nos.2022TQ0168 and 2023M731895).
文摘Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.However,the widened hydraulic excitation frequency may satisfy the blade resonance due to the time variation in the velocity and angle of attack of the ocean current,even resulting in blade fatigue and destructively interfering with grid stability.A key parameter that determines the resonance amplitude of the blade is the hydrodynamic damping ratio(HDR).However,HDR is difficult to obtain due to the complex fluid-structure interaction(FSI).Therefore,a literature review was conducted on the hydrodynamic damping characteristics of blade-like structures.The experimental and simulation methods used to identify and obtain the HDR quantitatively were described,placing emphasis on the experimental processes and simulation setups.Moreover,the accuracy and efficiency of different simulation methods were compared,and the modal work approach was recommended.The effects of key typical parameters,including flow velocity,angle of attack,gap,rotational speed,and cavitation,on the HDR were then summarized,and the suggestions on operating conditions were presented from the perspective of increasing the HDR.Subsequently,considering multiple flow parameters,several theoretical derivations and semi-empirical prediction formulas for HDR were introduced,and the accuracy and application were discussed.Based on the shortcomings of the existing research,the direction of future research was finally determined.The current work offers a clear understanding of the HDR of blade-like structures,which could improve the evaluation accuracy of flow-induced vibration in the design stage.
文摘The feasibility of using a problem-dependent method to solve systems of second order ODEs is corroborated by an eigen-based theory and a methodology to develop such a numerical method is constructed.The key steps of this methodology are to decouple a system of ODEs of second order into a set of uncoupled ODEs of second order;next,an eigen-dependent method is proposed to approximate the solution of each uncoupled ODE of second order.It is vital to transform all eigen-dependent methods to a problem-dependent method to bypass an Eigen analysis.The development of an eigen-dependent method plays a key role in this methodology so that slow eigenmodes can be accurately integrated while there is no instability or excessive amplitude growth in fast eigenmodes.This can explain why a problem-dependent method can simultaneously combine the explicitness of each step and A-stability.Consequently,huge computational efforts can be saved for solving nonlinear stiff problems.A new family of problem-dependent methods is developed in this work so that the feasibility of the proposed methodology can be affirmed.It has almost the same performance as that of the HHT-αmethod.However,it can save more than 99.5%of CPU demand in approximating a solution for a system of 1000 nonlinear second order ODEs.
基金supported by the National Natural Science Foundation of China(Nos.52401342 and 12572025)the Fundamental Research Funds for the Central Universities of China(Nos.D5000240076 and G2025KY05171)+1 种基金the Natural Science Basic Research Program of Shaanxi Province(No.2025JCYBMS-026)the Basic Research Programs of Taicang(No.TC2024JC36)。
文摘In recent years,scholars around the world have shown increasing interest in elastic support structures,leading to significant progress in dynamic modeling techniques for pipeline systems.Although multiple analytical approaches exist,engineers increasingly prioritize computationally efficient,precise low-order models for practical implementation.In order to address this need,this study develops an innovative nonlinear dynamic formulation for pipelines accounting for both foundation and boundary nonlinearities.The proposed solution methodology initiates with global mode extraction using the global mode technique,followed by a detailed implementation procedure.Model validation is conducted through a cantilever pipeline case study featuring nonlinear support conditions,where strong agreement between the proposed model's predictions and finiteelement benchmark solutions demonstrates its reliability.Subsequently,a comprehensive parametric study investigates the combined effects of foundation stiffness,boundary constraints,excitation intensity,and nonlinear interaction terms on the vibrational response of the cantilever pipe.This systematic approach yields critical insights for practical engineering designs and applications.
基金support from the National Natural Science Foundation of China(Grant Nos.52174123&52274222).
文摘This paper presents a framework for constructing surrogate models for sensitivity analysis of structural dynamics behavior.Physical models involving deformation,such as collisions,vibrations,and penetration,are devel-oped using the material point method.To reduce the computational cost of Monte Carlo simulations,response surface models are created as surrogate models for the material point system to approximate its dynamic behavior.An adaptive randomized greedy algorithm is employed to construct a sparse polynomial chaos expansion model with a fixed order,effectively balancing the accuracy and computational efficiency of the surrogate model.Based on the sparse polynomial chaos expansion,sensitivity analysis is conducted using the global finite difference and Sobol methods.Several examples of structural dynamics are provided to demonstrate the effectiveness of the proposed method in addressing structural dynamics problems.
基金supported by the Open Research Fund of Key Laboratory of Geological Hazards on Three Gorges Reservoir Area(China Three Gorges University),Ministry of Education(No.2022KDZ03)the Science and Technology Projects of Yunnan Provincial Science and Technology Department(No.202401AT070328)+1 种基金the Young talents project of“Xingdian Talent Support Program”in Yunnan Province(No.YNWR-QNBJ-2020-019)the Fund Project of China Academy of Railway Sciences Co.,Ltd.(No.2021YJ178)。
文摘0 INTRODUCTION In recent years,modern railways have been actively under construction in the complex mountainous area of Southwest China.However,rockfall poses a significant threat to both construction and operation phases of railway projects(Yan et al.,2023;Chen et al.,2022;Fanos and Pradhan,2018).
文摘The Fringe Projection Profilometry(FPP)system with a single exposure time or a single projection intensity is limited by the dynamic range of the camera,which can lead to overexposure and underexposure of the image,resulting in point cloud loss or reduced accuracy.To address this issue,unlike the pixel modulation method of projectors,we utilize the characteristics of color projectors where the intensity of the three-channel LED can be controlled independently.We propose a method for separating the projector's three-channel light intensity,combined with a color camera,to achieve single exposure and multi-intensity image acquisition.Further,the crosstalk coefficient is applied to predict the three-channel reflectance of the measured object.By integrating clustering and channel mapping,we establish a pixel-level mapping model between the projector's three-channel current and the camera's three-channel image intensity,which realizes the optimal projection current prediction and the high dynamic range(HDR)image acquisition.The proposed method allows for high-precision three-dimensional(3D)data acquisition of HDR scenes with a single exposure.The effectiveness of this method has been validated through experiments with standard planes and standard steps,showing a significant reduction in mean absolute error(44.6%)compared to existing singleexposure HDR methods.Additionally,the number of images required for acquisition is significantly reduced(by 70.8%)compared to multi-exposure fusion methods.This proposed method has great potential in various FPP-related fields.
基金supported by the National Natural Science Foundation of China(grant number:22274050)the Shanghai Science and Technology Commission(contract number:23J21900300)the Fundamental Research Funds for the Central Universities.
文摘Ribonucleic acid(RNA)structures and dynamics play a crucial role in elucidating RNA functions and facilitating the design of drugs targeting RNA and RNA-protein complexes.However,obtaining RNA structures using conventional biophysical techniques,such as Xray crystallography and solution nuclear magnetic resonance(NMR),presents challenges due to the inherent flexibility and susceptibility to degradation of RNA.In recent years,solid-state NMR(SSNMR)has rapidly emerged as a promising alternative technique for characterizing RNA structure and dynamics.SSNMR has several distinct advantages,including flexibility in sample states,the ability to capture dynamic features of RNA in solid form,and suitability to character RNAs in various sizes.Recent decade witnessed the growth of ^(1)H-detected SSNMR methods on RNA,which targeted elucidating RNA topology and base pair dynamics in solid state.They have been applied to determine the topology of RNA segment in human immunodeficiency virus(HIV)genome and the base pair dynamics of riboswitch RNA.These advancements have expanded the utility of SSNMR techniques within the RNA research field.This review provides a comprehensive discussion of recent progress in ^(1)H-detected SSNMR investigations into RNA structure and dynamics.We focus on the established ^(1)H-detected SSNMR methods,sample preparation protocols,and the implementation of rapid data acquisition approaches.
基金support received by the National Natural Science Foundation of China(Grant Nos.52372398&62003272).
文摘Dynamic soaring,inspired by the wind-riding flight of birds such as albatrosses,is a biomimetic technique which leverages wind fields to enhance the endurance of unmanned aerial vehicles(UAVs).Achieving a precise soaring trajectory is crucial for maximizing energy efficiency during flight.Existing nonlinear programming methods are heavily dependent on the choice of initial values which is hard to determine.Therefore,this paper introduces a deep reinforcement learning method based on a differentially flat model for dynamic soaring trajectory planning and optimization.Initially,the gliding trajectory is parameterized using Fourier basis functions,achieving a flexible trajectory representation with a minimal number of hyperparameters.Subsequently,the trajectory optimization problem is formulated as a dynamic interactive process of Markov decision-making.The hyperparameters of the trajectory are optimized using the Proximal Policy Optimization(PPO2)algorithm from deep reinforcement learning(DRL),reducing the strong reliance on initial value settings in the optimization process.Finally,a comparison between the proposed method and the nonlinear programming method reveals that the trajectory generated by the proposed approach is smoother while meeting the same performance requirements.Specifically,the proposed method achieves a 34%reduction in maximum thrust,a 39.4%decrease in maximum thrust difference,and a 33%reduction in maximum airspeed difference.
文摘The turbine blades operate under high temperature and high pressure conditions,and when using radiation thermometry,the influence of radiation from surrounding blades leads to measurement errors.To address this issue,this paper develops a three-dimensional discretized dynamic radiation transfer model based on the blade shape of the turbine.The relationship between the radiation angle coefficient of the surrounding blades and the rotation angle of the blade under test is analyzed.The radiation angle coefficient is calculated using the triangular element method,and temperature inversion is performed based on the effective emissivity to compute the measurement error.The results show that under dynamic high temperature conditions,the temperature measurement error caused by reflection at the selected 60%leaf height point varies with the rotation angle,and the maximum reaches 25.58K.The angular coefficient exhibits periodic fluctuations with changes in rotation angle,and the maximum effective emissivity increases as the rotation angle increases.As the blade height increases,the impact of reflected radiation on radiometric temperature measurement errors shows a decreasing trend.This study provides a reference for radiation thermometry in dynamic high-temperature environments.
基金supported by the National Key Research and Development Program Project(No.2021YFB3301300).
文摘Intelligent production is an important development direction in intelligent manufacturing,with intelligent factories playing a crucial role in promoting intelligent production.Flexible job shops,as the main form of intelligent factories,constantly face dynamic disturbances during the production process,including machine failures and urgent orders.This paper discusses the basic models and research methods of job shop scheduling,emphasizing the important role of dynamic job shop scheduling and its response schemes in future research.A multi-objective flexible job shop dynamic scheduling mathematical model is established,highlighting its complex and multi-constraint characteristics under different interferences.A classification discussion is conducted on the dynamic response methods and optimization objectives under machine failures,emergency orders,fuzzy completion times,and mixed dynamic events.The development process of traditional scheduling rules and intelligent methods in dynamic scheduling are also analyzed.Finally,based on the current development status of job shop scheduling and the requirements of intelligent manufacturing,the future development trends of dynamic scheduling in flexible job shops are proposed.
基金supported by the National Nature Science Foundation of China(Nos.62063019)Natural Science Foundation of Gansu Province(22JR5RA241,2023CXZX-465).
文摘In this study,we construct a bi-level optimization model based on the Stackelberg game and propose a robust optimization algorithm for solving the bi-level model,assuming an actual situation with several participants in energy trading.Firstly,the energy trading process is analyzed between each subject based on the establishment of the operation framework of multi-agent participation in energy trading.Secondly,the optimal operation model of each energy trading agent is established to develop a bi-level game model including each energy participant.Finally,a combination algorithm of improved robust optimization over time(ROOT)and CPLEX is proposed to solve the established game model.The experimental results indicate that under different fitness thresholds,the robust optimization results of the proposed algorithm are increased by 56.91%and 68.54%,respectively.The established bi-level game model effectively balances the benefits of different energy trading entities.The proposed algorithm proposed can increase the income of each participant in the game by an average of 8.59%.
基金Supported by National Natural Science Foundation of China(Grant No.52375502)EU H2020 MSCA R&I Programme(Grant No.101022696).
文摘Feedforward control is one of the most effective control techniques to increase the robot’s tracking accuracy.However,most of the dynamic models used in the feedforward controllers are linearly simplified such that the nonlinear and time-varying characteristics of dynamics in the workspace are ignored.In this paper,an iterative tuning method for feedforward control of parallel manipulators by taking nonlinear dynamics into account is proposed.Based on the robot rigid-body dynamic model,a feedforward controller considering the dynamic nonlinearity is presented.An iterative tuning method is given to iteratively update the feedforward controller by minimizing the root mean square(RMS)of the joint errors at each cycle.The effectiveness and extrapolation capability of the proposed method are validated through the experiments on a 2-DOF parallel manipulator.This research proposes an iterative tuning method for feedforward control of parallel manipulators considering nonlinear dynamics,which has better extrapolation capability in the whole workspace of manipulators.
基金supported by the National Natural Science Foundation of China(Nos.12372066,U23B6009,52171261)the Aeronautical Science Fund(No.20240013052002)the Qing Lan Project。
文摘The structural dynamic response reconstruction technology can extract unmeasured information from limited measured data,significantly impacting vibration control,load identification,parameter identification,fault diagnosis,and related fields.This paper proposes a dynamic response reconstruction method based on the Kalman filter,which simultaneously identifies external excitation and reconstructs dynamic responses at unmeasured positions.The weighted least squares method determines the load weighting matrix for excitation identification,while the minimum variance unbiased estimation determines the Kalman filter gain.The excitation prediction Kalman filter is constructed through time,excitation,and measurement updates.Subsequently,the response at the target point is reconstructed using the state vector,observation matrix,and excitation influence matrix obtained through the excitation prediction Kalman filter algorithm.An algorithm for reconstructing responses in continuous system using the excitation prediction Kalman filtering algorithm in modal space is derived.The proposed structural dynamic response reconstruction method evaluates the response reconstruction and the load identification performance under various load types and errors through simulation examples.Results demonstrate the accurate excitation identification under different load conditions and simultaneous reconstruction of target point responses,verifying the feasibility and reliability of the proposed method.
基金the Institute of Biomass & Functional Materials of Shaanxi University of Science and Technology for funding this research workfinancially supported by the National Natural Science Foundation of China (2207081675, 22278257, 22308209)+1 种基金the Key R&D Program of Shaanxi Province (2024SF-YBXM-586)the Project of Innovation Capability Support Program in Shaanxi Province (2024ZC-KJXX-005)
文摘Rapid population growth in recent decades has intensified both the global energy crisis and the challenges posed by climate change,including global warming.Currently,the increased frequency of extreme weather events and large fluctuations in ambient temperature disrupt thermal comfort and negatively impact health,driving a growing dependence on cooling and heating energy sources.Consequently,efficient thermal management has become a central focus of energy research.Traditional thermal management systems consume substantial energy,further contributing to greenhouse gas emissions.In contrast,emergent radiant thermal management technologies that rely on renewable energy have been proposed as sustainable alternatives.However,achieving year-round thermal management without additional energy input remains a formidable challenge.Recently,dynamic radiative thermal management technologies have emerged as the most promising solution,offering the potential for energy-efficient adaptation across seasonal variations.This review systematically presents recent advancements in dynamic radiative thermal management,covering fundamental principles,switching mechanisms,primary materials,and application areas.Additionally,the key challenges hindering the broader adoption of dynamic radiative thermal management technologies are discussed.By highlighting their transformative potential,this review provides insights into the design and industrial scalability of these innovations,with the ultimate aim of promoting renewable energy integration in thermal management applications.
基金funded by Ministry of Higher Education Malaysia under the Fundamental Research Grant Scheme(FRGS/1/2024/TK10/UKM/02/7).
文摘This review provides a comprehensive and systematic examination of Computational Fluid Dynamics(CFD)techniques and methodologies applied to the development of Vertical Axis Wind Turbines(VAWTs).Although VAWTs offer significant advantages for urban wind applications,such as omnidirectional wind capture and a compact,ground-accessible design,they face substantial aerodynamic challenges,including dynamic stall,blade-wake interactions,and continuously varying angles of attack throughout their rotation.The review critically evaluates how CFD has been leveraged to address these challenges,detailing the modelling frameworks,simulation setups,mesh strategies,turbulence models,and boundary condition treatments adopted in the literature.Special attention is given to the comparative performance of 2-D vs.3-D simulations,static and dynamic meshing techniques(sliding,overset,morphing),and the impact of near-wall resolution on prediction fidelity.Moreover,this review maps the evolution of CFD tools in capturing key performance indicators including power coefficient,torque,flow separation,and wake dynamics,while highlighting both achievements and current limitations.The synthesis of studies reveals best practices,identifies gaps in simulation fidelity and validation strategies,and outlines critical directions for future research,particularly in high-fidelity modelling and cost-effective simulation of urban-scale VAWTs.By synthesizing insights from over a hundred referenced studies,this review serves as a consolidated resource to advance VAWT design and performance optimization through CFD.These include studies on various aspects such as blade geometry refinement,turbulence modeling,wake interaction mitigation,tip-loss reduction,dynamic stall control,and other aerodynamic and structural improvements.This,in turn,supports their broader integration into sustainable energy systems.
基金supported by the Major National Science and Technology Infrastructure(No.2208-000000-04-01249628)the Shanghai Science and Technology Commission(No.21DZ1206500)。
文摘We present a hybrid smoothed particle magnetohydrodynamics(SPMHD)code integrating smoothed particle hydrodynamics(SPH)and finite element methods(FEM)to simulate coupled fluid-electromagnetic phenomena.The framework employs SPH for fluid dynamics,addressing large deformations,shocks,and plasma behavior,while FEM resolves electromagnetic fields via Maxwell's equations for magnetic vector and electric scalar potentials,ensuring divergence-free conditions and global current density calculations in conductive region.Operator splitting method couples these modules,enabling real-time integration of magnetic,electric,thermal,and fluid fields.Benchmark tests validate the code against analytical solutions and existing models,including blow-by instability simulations that demonstrate the method's accuracy in capturing fluid-magnetic interactions.Designed for 3D applications,SPMHD offers robust scalability across multiprocessor architectures,establishing it as a versatile tool for plasma physics research.
基金supported by the National Key Research and Development Program of China(2022YFC2904400)Guangxi Science and Technology Major Project(Gui Ke AA23023033)。
文摘As a pyrometallurgical process,circulating fluidized bed(CFB) roasting has good potential for application in desulfurization of high-sulfur bauxite.The gas-solid distribution and reaction during CFB roasting of high-sulfur bauxite were simulated using the computational particle fluid dynamics(CPFD) method.The effect of primary air flow velocity on particle velocity,particle volume distribution,furnace temperature distribution and pressure distribution were investigated.Under the condition of the same total flow of natural gas,the impact of the number of inlets on the desulfurization efficiency,atmosphere mass fraction distribution and temperature distribution in the furnace was further investigated.
基金supported by the Beijing Natural Science Foundation(Grant No.8252012)the National Natural Science Foundation of China(Grant No.52378475).
文摘Accurate acquisition of the lithological composition of a tunnel face is crucial for efficient tunneling and hazard prevention in large-diameter slurry shield tunnels.While widely applied,current data-driven methods often face challenges such as indirect prediction,data sparsity,and data drift,which limit their accuracy and generalizability.This study develops an integrated method that combines a knowledge-driven method to directly compute distribution patterns of lithological components,which are used as a priori knowledge to guide the development of a data-driven method.Coupled Markov chain(CMC)and deep neural networks(DNNs)serve as the knowledge-driven and data-driven components,respectively.Additionally,a dynamic prediction strategy is proposed,where the model is continuously optimized as construction progresses and training samples accumulate,rather than being statically trained on post-construction data,as is common in data-driven methods.Finally,the proposed method is evaluated using a real-world project.The evaluation results show that the integrated method outperforms both individual data-and knowledge-driven methods,demonstrating higher predictive performance,greater stability,and greater robustness to data scarcity and data drift.Furthermore,the dynamic prediction strategy better captures the effects of gradual data accumulation and lithological spatial variability on prediction performance during construction,providing new insights for real-time prediction in practical tunneling applications.
