This paper introduces dynamic mode decomposition(DMD)as a novel approach to model the breakage kinetics of particulate systems.DMD provides a data-driven framework to identify a best-fit linear dynamics model from a s...This paper introduces dynamic mode decomposition(DMD)as a novel approach to model the breakage kinetics of particulate systems.DMD provides a data-driven framework to identify a best-fit linear dynamics model from a sequence of system measurement snapshots,bypassing the nontrivial task of determining appropriate mathemat-ical forms for the breakage kernel functions.A key innovation of our method is the instilling of physics-informed constraints into the DMD eigenmodes and eigenvalues,ensuring they adhere to the physical structure of particle breakage processes even under sparse measurement data.The integration of eigen-constraints is computationally aided by a zeroth-order global optimizer for solving the nonlinear,nonconvex optimization problem that elicits system dynamics from data.Our method is evaluated against the state-of-the-art optimized DMD algorithm using both generated data and real-world data of a batch grinding mill,showcasing over an order of magnitude lower prediction errors in data reconstruction and forecasting.展开更多
The precise characterization of hypersonic glide vehicle(HGV) maneuver laws in complex flight scenarios still faces challenges. Non-stationary changes in flight state due to abrupt changes in maneuver modes place high...The precise characterization of hypersonic glide vehicle(HGV) maneuver laws in complex flight scenarios still faces challenges. Non-stationary changes in flight state due to abrupt changes in maneuver modes place high demands on the accuracy of modeling methods. To address this issue, a novel maneuver laws modeling and analysis method based on higher order multi-resolution dynamic mode decomposition(HMDMD) is proposed in this work. A joint time-space-frequency decomposition of the vehicle's state sequence in the complex flight scenario is achieved with the higher order Koopman assumption and standard multi-resolution dynamic mode decomposition, and an approximate dynamic model is established. The maneuver laws can be reconstructed and analyzed with extracted multi-scale spatiotemporal modes with clear physical meaning. Based on the dynamic model of HGV, two flight scenarios are established with constant angle of attack and complex maneuver laws, respectively. Simulation results demonstrate that the maneuver laws obtained using the HMDMD method are highly consistent with those derived from the real dynamic model, the modeling accuracy is better than other common modeling methods, and the method has strong interpretability.展开更多
This article presents a novel approach for predicting transition locations over airfoils,which are used to activate turbulence model in a Reynolds-averaged Navier-Stokes flow solver.This approach combines Dynamic Mode...This article presents a novel approach for predicting transition locations over airfoils,which are used to activate turbulence model in a Reynolds-averaged Navier-Stokes flow solver.This approach combines Dynamic Mode Decomposition(DMD)with e^Ncriterion.The core idea is to use a spatial DMD analysis to extract the modes of unstable perturbations from a steady flowfield and substitute the local Linear Stability Theory(LST)analysis to quantify the spatial growth of Tollmien–Schlichting(TS)waves.Transition is assumed to take place at the stream-wise location where the most amplified mode’s N-factor reaches a prescribed threshold and a turbulence model is activated thereafter.To improve robustness,the high-order version of DMD technique(known as HODMD)is employed.A theoretical derivation is conducted to interpret how a spatial highorder DMD analysis can extract the growth rate of the unsteady perturbations.The new method is validated by transition predictions of flows over a low-speed Natural-Laminar-Flow(NLF)airfoil NLF0416 at various angles of attack and a transonic NLF airfoil NPU-LSC-72613.The transition locations predicted by our HODMD/e^Nmethod agree well with experimental data and compare favorably to those obtained by some existing methods■.It is shown that the proposed method is able to predict transition locations for flows over different types of airfoils and offers the potential for application to 3D wings as well as more complex configurations.展开更多
Unsteady flow in the hub endwall region has long been a hot topic in the turbomachinery community.However important it is to the performance of the whole engine,the coherent unsteady flow phenomena are still not well ...Unsteady flow in the hub endwall region has long been a hot topic in the turbomachinery community.However important it is to the performance of the whole engine,the coherent unsteady flow phenomena are still not well understood.In this paper,the complex flow field in the hub endwall of a cantilevered compressor cascade has been investigated through numerical approach.The predicted results were validated by experimental data.To highlight the dominant flow structures among irregular and chaotic motions of various vortices,a Dynamic Mode Decomposition(DMD)method was utilized.The results show that there exist three dominant periodic flow structures:the oscillation of the leakage vortex,a circumferential migration of a Breakdown Induced Vortex(BIV)and the fluctuation of the passage vortex.These three coherent structures all together form a self-sustained closed loop which accounts for the flow unsteadiness of the studied cascade.During this process,the BIV plays a key role in inducing the flow unsteadiness.Only if the BIV is strong enough to affect the passage vortex,the flow unsteadiness occurs.This study expands current knowledge base of flow unsteadiness in a compressor environment,and shows the efficacy of the DMD method for revealing the origin of flow unsteadiness.展开更多
A combination of the lattice Boltzmann method and the most recently developed dynamic mode decomposition is proposed for stability analysis. The simulations are performed on a graphical processing unit. Stability of t...A combination of the lattice Boltzmann method and the most recently developed dynamic mode decomposition is proposed for stability analysis. The simulations are performed on a graphical processing unit. Stability of the flow past a cylinder at supercritical state, Re = 50, is studied by the combination for both the exponential growing and the limit cycle regimes. The Ritz values, energy spectrum, and modes for both regimes are presented and compared with the Koopman eigenvalues. For harmonic-like periodic flow in the limit cycle, global analysis from the combination gives the same results as those from the Koopman analysis. For transient flow as in the exponential growth regime, the combination can provide more reasonable results. It is demonstrated that the combination of the lattice Boltzmann method and the dynamic mode decomposition is powerful and can be used for stability analysis for more complex flows.展开更多
Earth’s magnetic field,which is generated in the liquid outer core through the dynamo action,undergoes changes on timescales of a few years to several million years,yet the underlying mechanisms responsible for the f...Earth’s magnetic field,which is generated in the liquid outer core through the dynamo action,undergoes changes on timescales of a few years to several million years,yet the underlying mechanisms responsible for the field variations remain to be elucidated.In this study,we apply a novel data analysis technique developed in fluid dynamics,namely the dynamic mode decomposition,to analyze the geomagnetic variations over the last two decades when continuous satellite observations are available.The dominant dynamic modes are extracted by solving an eigen-value problem,so one can identify modes with periods longer than the time span of data.Our analysis show that similar dynamic modes are extracted from the geomagnetic secular variation and secular acceleration,justifying the validity of applying the dynamic mode decomposition method to geomagnetic field.We reveal that the geomagnetic field variations are characterized by a global mode with period of 58 years,a localized mode with period of 16 years and an equatorially trapped mode with period of 8.5 years.These modes are possibly related to magnetohydrodynamic waves in the Earth’s outer core.展开更多
The transient cavitating flow around the Clark-Y hydrofoil is numerically investigated by the dynamic mode decomposition with criterion.Based on the ranking dominant modes,frequencies of the first four modes are in go...The transient cavitating flow around the Clark-Y hydrofoil is numerically investigated by the dynamic mode decomposition with criterion.Based on the ranking dominant modes,frequencies of the first four modes are in good accordance with those obtained by fast Fourier transform.Furthermore,the cavitating flow field is reconstructed by the first four modes,and the dominant flow features are well captured with the reconstructed error below 12%when compared to the simulated flow field.This paper offers a reference for observing and reconstructing the flow fields,and gives a novel insight into the transient cavitating flow features.展开更多
Gearbox is a key part in machinery,in which gear,shaft and bearing operate together to transmit motion and power.The wide usage and high failure rate of gearbox make it attract much attention on its health monitoring ...Gearbox is a key part in machinery,in which gear,shaft and bearing operate together to transmit motion and power.The wide usage and high failure rate of gearbox make it attract much attention on its health monitoring and fault diagnosis.Dynamic modelling can study the mechanism under different faults and provide theoretical foundation for fault detection.However,current commonly used gear dynamic model usually neglects the influence of bearing and shaft,resulting in incomplete understanding of gearbox fault diagnosis especially under the effect of local defects on gear and shaft.To address this problem,an improved gear-shaft-bearing-housing dynamic model is proposed to reveal the vibration mechanism and responses considering shaft whirling and gear local defects.Firstly,an eighteen degree-of-freedom gearbox dynamic model is proposed,taking into account the interaction among gear,bearing and shaft.Secondly,the dynamic model is iteratively solved.Then,vibration responses are expounded and analysed considering gear spalling and shaft crack.Numerical results show that the gear mesh frequency and its harmonics have higher amplitude through the spectrum.Vibration RMS and the shaft rotating frequency increase with the spalling size and shaft crack angle in general.An experiment is designed to verify the rationality of the proposed gearbox model.Lastly,comprehensive analysis under different spalling size and shaft crack angle are analysed.Results show that when spalling size and crack angle are larger,RMS and the amplitude of shaft rotating frequency will not increase linearly.The dynamic model can accurately simulate the vibration of gear transmission system,which is helpful for gearbox fault diagnosis.展开更多
Dynamic mode decomposition(DMD) aims at extracting intrinsic mechanisms in a time sequence via linear recurrence relation of its observables, thereby predicting later terms in the sequence. Stability is a major concer...Dynamic mode decomposition(DMD) aims at extracting intrinsic mechanisms in a time sequence via linear recurrence relation of its observables, thereby predicting later terms in the sequence. Stability is a major concern in DMD predictions. We adopt a regularized form and propose a Regularized DMD(Re DMD) algorithm to determine the regularization parameter. This leverages stability and accuracy. Numerical tests for Burgers' equation demonstrate that Re DMD effectively stabilizes the DMD prediction while maintaining accuracy. Comparisons are made with the truncated DMD algorithm.展开更多
In recent years,subsynchronous resonance(SSR)has frequently occurred in DFIG-connected series-compensated systems.For the analysis and prevention,it is of great importance to achieve wide area monitoring of the incide...In recent years,subsynchronous resonance(SSR)has frequently occurred in DFIG-connected series-compensated systems.For the analysis and prevention,it is of great importance to achieve wide area monitoring of the incident.This paper presents a Hankel dynamic mode decomposition(DMD)method to identify SSR parameters using synchrophasor data.The basic idea is to employ the DMD technique to explore the subspace of Hankel matrices constructed by synchrophasors.It is analytically demonstrated that the subspace of these Hankel matrices is a combination of fundamental and SSR modes.Therefore,the SSR parameters can be calculated once the modal parameter is extracted.Compared with the existing method,the presented work has better dynamic performances as it requires much less data.Thus,it is more suitable for practical cases in which the SSR characteristics are timevarying.The effectiveness and superiority of the proposed method have been verified by both simulations and field data.展开更多
To identify the parameters of the extended Debye model of XLPE cables,and therefore evaluate the insulation performance of the samples,the sparsity-promoting dynamicmode decomposition(SPDMD)methodwas introduced,aswell...To identify the parameters of the extended Debye model of XLPE cables,and therefore evaluate the insulation performance of the samples,the sparsity-promoting dynamicmode decomposition(SPDMD)methodwas introduced,aswell the basics and processes of its applicationwere explained.The amplitude vector based on polarization current was first calculated.Based on the non-zero elements of the vector,the number of branches and parameters including the coefficients and time constants of each branch of the extended Debye model were derived.Further research on parameter identification of XLPE cables at different aging stages based on the SPDMD method was carried out to verify the practicability of the method.Compared with the traditional differential method,the simulation and experiment indicated that the SPDMD method can effectively avoid problems such as the relaxation peak being unobvious,and possessing more accuracy during the parameter identification.And due to the polarization current being less affected by the measurement noise than the depolarization current,the SPDMD identification results based on the polarization current spectral line proved to be better at reflecting the response characteristics of the dielectric.In addition,the time domain polarization current test results can be converted into the frequency domain,and then used to obtain the dielectric loss factor spectrum of the insulation.The integral of the dielectric loss factor on a frequency domain can effectively evaluate the insulation condition of the XLPE cable.展开更多
A rigid flexible coupling physical model which can represent a flexible spacecraft is investigated in this paper. By applying the mechanics theory in a non-inertial coordinate system,the rigid flexible coupling dynami...A rigid flexible coupling physical model which can represent a flexible spacecraft is investigated in this paper. By applying the mechanics theory in a non-inertial coordinate system,the rigid flexible coupling dynamic model with dynamic stiffening is established via the subsystemmodeling framework. It is clearly elucidated for the first time that,dynamic stiffening is produced by the coupling effect of the centrifugal inertial load distributed on the beamand the transverse vibration deformation of the beam. The modeling approach in this paper successfully avoids problems which are caused by other popular modeling methods nowadays： the derivation process is too complex by using only one dynamic principle; a clearly theoretical explanation for dynamic stiffening can＇t be provided. First,the continuous dynamic models of the flexible beamand the central rigid body are established via structural dynamics and angular momentumtheory respectively. Then,based on the conclusions of orthogonalization about the normal constrained modes,the finite dimensional dynamic model suitable for controller design is obtained. The numerical simulation validations showthat： dynamic stiffening is successfully incorporated into the dynamic characteristics of the first-order model established in this paper,which can indicate the dynamic responses of the rigid flexible coupling system with large overall motion accurately,and has a clear modeling mechanism,concise expressions and a good convergence.展开更多
The operation of pump-turbines in the S-shaped region is characterized by amplified pressure pulsations and grid synchronization challenges,which often lead to operational instability and reduced grid compatibility.Th...The operation of pump-turbines in the S-shaped region is characterized by amplified pressure pulsations and grid synchronization challenges,which often lead to operational instability and reduced grid compatibility.This study employs dynamic mode decomposition(DMD)method to extract coherent flow structures correlated with dominant pressure pulsation frequencies in the S-shaped region,while experiments have been conducted to validate numerical simulations.Results show that the DMD method can effectively identify the characteristic frequencies of complex flows in the S-shaped region:Low-frequency pressure pulsations in the vaneless space originate from the circumferential transmission component of the water ring over time,which is referred to as the water ring pulsation component.During operational condition transitions,this pulsation component first intensifies then attenuates as it propagates outward along the guide vanes.The dominant draft tube pressure pulsation frequency driven by vortex rope dynamics induces morphological vortex rope transformations via DMD mode shifts during operational transitions.Runner pressure pulsations within the S-shaped region predominantly originate from rotating stall propagating in the direction opposite to the runner's rotation.These findings advance the understanding of S-shaped region flow instabilities,linking component-specific flow structures to global pressure pulsation characteristics,and thereby providing critical insights for operational stability enhancement.展开更多
Dynamic mode decomposition(DMD),as a data-driven method,has been frequently used to construct reduced-order models(ROMs)due to its good performance in time extrapolation.However,existing DMD-based ROMs suffer from hig...Dynamic mode decomposition(DMD),as a data-driven method,has been frequently used to construct reduced-order models(ROMs)due to its good performance in time extrapolation.However,existing DMD-based ROMs suffer from high storage and computational costs for high-dimensional problems.To mitigate this problem,we develop a new DMD-based ROM,i.e.,TDMD-GPR,by combining tensor train decomposition(TTD)and Gaussian process regression(GPR),where TTD is used to decompose the high-dimensional tensor into multiple factors,including parameterdependent and time-dependent factors.Parameter-dependent factor is fed into GPR to build the map between parameter value and factor vector.For any parameter value,multiplying the corresponding parameter-dependent factor vector and the timedependent factor matrix,the result describes the temporal behavior of the spatial basis for this parameter value and is then used to train the DMD model.In addition,incremental singular value decomposition is adopted to acquire a collection of important instants,which can further reduce the computational and storage costs of TDMD-GPR.The comparison TDMD and standard DMD in terms of computational and storage complexities shows that TDMD is more advantageous.The performance of the TDMD and TDMD-GPR is assessed through several cases,and the numerical results confirm the effectiveness of them.展开更多
We present dynamic mode decomposition (DMD) for studying the hairpin vortices generated by hemisphere protuberance measured by two-dimensional (2D) time-resolved (TR) particle image velocimetry (PIV) in a water channe...We present dynamic mode decomposition (DMD) for studying the hairpin vortices generated by hemisphere protuberance measured by two-dimensional (2D) time-resolved (TR) particle image velocimetry (PIV) in a water channel. The hairpins dynamic information is extracted by identifying their dominant frequencies and associated spatial structures. For this quasi-periodic data system, the resulting main Dynamic modes illustrate the different spatial structures associated with the wake vortex region and the near-wall region. By comparisons with proper orthogonal decomposition (POD), it can be concluded that the dynamic mode concentrates on a certain frequency component more effectively than the mode determined by POD. During the analysis, DMD has proven itself a robust and reliable algorithm to extract spatial-temporal coherent structures.展开更多
The present work uses dynamic mode decomposition(DMD)to analyze wake flow of NACA0015 airfoil with Gurney flap.The physics of DMD is first introduced.Then the PIV-measured wake flow velocity field is decomposed into d...The present work uses dynamic mode decomposition(DMD)to analyze wake flow of NACA0015 airfoil with Gurney flap.The physics of DMD is first introduced.Then the PIV-measured wake flow velocity field is decomposed into dynamical modes.The vortex shedding pattern behind the trailing edge and its high-order harmonics have been captured with abundant information such as frequency,wavelength and convection speed.It is observed that high-order dynamic modes convect faster than low-order modes;moreover the wavelength of the dynamic modes scales with the corresponding frequency in power law.展开更多
The flow around a circular cylinder for Re=1000 is characterized by flow separation and Karman vortex street.The typical flow features can be captured to study the correlation between fluid fields and sound fields.In ...The flow around a circular cylinder for Re=1000 is characterized by flow separation and Karman vortex street.The typical flow features can be captured to study the correlation between fluid fields and sound fields.In this paper,the three-dimensional circular cylinder is taken as the research object,and the probes of surface fluctuating pressure and far field sound pressure are arranged every 10°.The directional diagram and the coherence of fluctuating pressure and sound pressure are analyzed.The relationship between the flow mode and hydrodynamic noise is studied by using dynamic mode decomposition(DMD).The characteristics of the dipole and quadrupole sound source term of a long span cylinder are studied.The results show that at the angles between 30°–120°and 190°–350°,the fluctuating pressure contributes more to the generation of dipole sounds.The quadrupole sound source shows three-dimensional effects,which is more obvious in a cylinder with large spanwise length.展开更多
Dynamic Mode Decomposition(DMD)is a data-driven and model-free decomposition technique.It is suitable for revealing spatio-temporal features of both numerically and experimentally acquired data.Conceptually,DMD perfor...Dynamic Mode Decomposition(DMD)is a data-driven and model-free decomposition technique.It is suitable for revealing spatio-temporal features of both numerically and experimentally acquired data.Conceptually,DMD performs a low-dimensional spectral decomposition of the data into the following components:the modes,called DMD modes,encode the spatial contribution of the decomposition,whereas the DMD amplitudes specify their impact.Each associated eigenvalue,referred to as DMD eigenvalue,characterizes the frequency and growth rate of the DMD mode.In this paper,we demonstrate how the components of DMD can be utilized to obtain temporal and spatial information from time-dependent flow fields.We begin with the theoretical background of DMD and its application to unsteady flow.Next,we examine the conventional process with DMD mathematically and put it in relationship to the discrete Fourier transform.Our analysis shows that the current use of DMD components has several drawbacks.To resolve these problems we adjust the components and provide new and meaningful insights into the decomposition:we show that our improved components capture the spatio-temporal patterns of the flow better.Moreover,we remove redundancies in the decomposition and clarify the interplay between components,allowing users to understand the impact of components.These new representations,which respect the spatio-temporal character of DMD,enable two clustering methods that segment the flow into physically relevant sections and can therefore be used for the selection of DMD components.With a number of typical examples,we demonstrate that the combination of these techniques allows new insights with DMD for unsteady flow.展开更多
Parametric dynamical systems are widely used to model physical systems,but their numerical simulation can be computationally demanding due to nonlinearity,long-time simulation,and multi-query requirements.Model reduct...Parametric dynamical systems are widely used to model physical systems,but their numerical simulation can be computationally demanding due to nonlinearity,long-time simulation,and multi-query requirements.Model reduction methods aim to reduce computation complexity and improve simulation efficiency.However,traditional model reduction methods are inefficient for parametric dynamical systems with nonlinear structures.To address this challenge,we propose an adaptive method based on local dynamic mode decomposition(DMD)to construct an efficient and reliable surrogate model.We propose an improved greedy algorithm to generate the atoms setΘbased on a sequence of relatively small training sets,which could reduce the effect of large training set.At each enrichment step,we construct a local sub-surrogate model using the Taylor expansion and DMD,resulting in the ability to predict the state at any time without solving the original dynamical system.Moreover,our method provides the best approximation almost everywhere over the parameter domain with certain smoothness assumptions,thanks to the gradient information.At last,three concrete examples are presented to illustrate the effectiveness of the proposed method.展开更多
This study presents the assumptions and strategies for the practical implementation of the dynamic mode decomposition approach in the wide-area monitoring system of the Italian transmission system operator,Terna.The p...This study presents the assumptions and strategies for the practical implementation of the dynamic mode decomposition approach in the wide-area monitoring system of the Italian transmission system operator,Terna.The procedure setup aims to detect poorly damped interarea oscillations of power systems.Dynamic mode decomposition is a data-driven technique that has gained increasing attention in different fields;the proposed implementation can both characterize the oscillatory modes and identify the most influenced areas.This study presents the results of its practical implementation and operational experience in power system monitoring.It focuses on the main characteristics and solutions identified to reliably monitor the interarea electromechanical modes of the interconnected European power system.Moreover,conditions to issue an appropriate alarm in case of critical operating conditions are described.The effectiveness of the proposed approach is validated by its application in three case studies:a critical oscillatory event and a short-circuit event that occurred in the Italian power system in the previous years,and a 15-min time interval of normal grid operation recorded in March 2021.展开更多
基金supported by the Ramanujan Fellowship from the Science and Engineering Research Board,Government of India(Grant No.RJF/2022/000115).
文摘This paper introduces dynamic mode decomposition(DMD)as a novel approach to model the breakage kinetics of particulate systems.DMD provides a data-driven framework to identify a best-fit linear dynamics model from a sequence of system measurement snapshots,bypassing the nontrivial task of determining appropriate mathemat-ical forms for the breakage kernel functions.A key innovation of our method is the instilling of physics-informed constraints into the DMD eigenmodes and eigenvalues,ensuring they adhere to the physical structure of particle breakage processes even under sparse measurement data.The integration of eigen-constraints is computationally aided by a zeroth-order global optimizer for solving the nonlinear,nonconvex optimization problem that elicits system dynamics from data.Our method is evaluated against the state-of-the-art optimized DMD algorithm using both generated data and real-world data of a batch grinding mill,showcasing over an order of magnitude lower prediction errors in data reconstruction and forecasting.
基金supported by the National Natural Science Foundation of China (Grant No. 12302056)the Postdoctoral Fellowship Program of CPSF:GZC20233445。
文摘The precise characterization of hypersonic glide vehicle(HGV) maneuver laws in complex flight scenarios still faces challenges. Non-stationary changes in flight state due to abrupt changes in maneuver modes place high demands on the accuracy of modeling methods. To address this issue, a novel maneuver laws modeling and analysis method based on higher order multi-resolution dynamic mode decomposition(HMDMD) is proposed in this work. A joint time-space-frequency decomposition of the vehicle's state sequence in the complex flight scenario is achieved with the higher order Koopman assumption and standard multi-resolution dynamic mode decomposition, and an approximate dynamic model is established. The maneuver laws can be reconstructed and analyzed with extracted multi-scale spatiotemporal modes with clear physical meaning. Based on the dynamic model of HGV, two flight scenarios are established with constant angle of attack and complex maneuver laws, respectively. Simulation results demonstrate that the maneuver laws obtained using the HMDMD method are highly consistent with those derived from the real dynamic model, the modeling accuracy is better than other common modeling methods, and the method has strong interpretability.
基金supported by the National Natural Science Foundation of China (No. 11772261)the Aeronautical Science Foundation of China (No. 2016ZA53011)+1 种基金the ATCFD Project (No. 2015-F-016)the 111 Project of China (No. B17037)
文摘This article presents a novel approach for predicting transition locations over airfoils,which are used to activate turbulence model in a Reynolds-averaged Navier-Stokes flow solver.This approach combines Dynamic Mode Decomposition(DMD)with e^Ncriterion.The core idea is to use a spatial DMD analysis to extract the modes of unstable perturbations from a steady flowfield and substitute the local Linear Stability Theory(LST)analysis to quantify the spatial growth of Tollmien–Schlichting(TS)waves.Transition is assumed to take place at the stream-wise location where the most amplified mode’s N-factor reaches a prescribed threshold and a turbulence model is activated thereafter.To improve robustness,the high-order version of DMD technique(known as HODMD)is employed.A theoretical derivation is conducted to interpret how a spatial highorder DMD analysis can extract the growth rate of the unsteady perturbations.The new method is validated by transition predictions of flows over a low-speed Natural-Laminar-Flow(NLF)airfoil NLF0416 at various angles of attack and a transonic NLF airfoil NPU-LSC-72613.The transition locations predicted by our HODMD/e^Nmethod agree well with experimental data and compare favorably to those obtained by some existing methods■.It is shown that the proposed method is able to predict transition locations for flows over different types of airfoils and offers the potential for application to 3D wings as well as more complex configurations.
基金supports of National Natural Science Foundation of China(Nos.51790512,52176045)the National Major Science and technology Project of China(No.J2017-Ⅱ-0010-0024)the Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University,China(No.CX201911)。
文摘Unsteady flow in the hub endwall region has long been a hot topic in the turbomachinery community.However important it is to the performance of the whole engine,the coherent unsteady flow phenomena are still not well understood.In this paper,the complex flow field in the hub endwall of a cantilevered compressor cascade has been investigated through numerical approach.The predicted results were validated by experimental data.To highlight the dominant flow structures among irregular and chaotic motions of various vortices,a Dynamic Mode Decomposition(DMD)method was utilized.The results show that there exist three dominant periodic flow structures:the oscillation of the leakage vortex,a circumferential migration of a Breakdown Induced Vortex(BIV)and the fluctuation of the passage vortex.These three coherent structures all together form a self-sustained closed loop which accounts for the flow unsteadiness of the studied cascade.During this process,the BIV plays a key role in inducing the flow unsteadiness.Only if the BIV is strong enough to affect the passage vortex,the flow unsteadiness occurs.This study expands current knowledge base of flow unsteadiness in a compressor environment,and shows the efficacy of the DMD method for revealing the origin of flow unsteadiness.
文摘A combination of the lattice Boltzmann method and the most recently developed dynamic mode decomposition is proposed for stability analysis. The simulations are performed on a graphical processing unit. Stability of the flow past a cylinder at supercritical state, Re = 50, is studied by the combination for both the exponential growing and the limit cycle regimes. The Ritz values, energy spectrum, and modes for both regimes are presented and compared with the Koopman eigenvalues. For harmonic-like periodic flow in the limit cycle, global analysis from the combination gives the same results as those from the Koopman analysis. For transient flow as in the exponential growth regime, the combination can provide more reasonable results. It is demonstrated that the combination of the lattice Boltzmann method and the dynamic mode decomposition is powerful and can be used for stability analysis for more complex flows.
基金supported by Macao Science and Technology Development Fund grant 0001/2019/A1Macao Foundation+1 种基金the preresearch Project on Civil Aerospace Technologies of CNSA(Grants No.D020303 and D020308)the National Natural Science Foundation of China(41904066,42142034)。
文摘Earth’s magnetic field,which is generated in the liquid outer core through the dynamo action,undergoes changes on timescales of a few years to several million years,yet the underlying mechanisms responsible for the field variations remain to be elucidated.In this study,we apply a novel data analysis technique developed in fluid dynamics,namely the dynamic mode decomposition,to analyze the geomagnetic variations over the last two decades when continuous satellite observations are available.The dominant dynamic modes are extracted by solving an eigen-value problem,so one can identify modes with periods longer than the time span of data.Our analysis show that similar dynamic modes are extracted from the geomagnetic secular variation and secular acceleration,justifying the validity of applying the dynamic mode decomposition method to geomagnetic field.We reveal that the geomagnetic field variations are characterized by a global mode with period of 58 years,a localized mode with period of 16 years and an equatorially trapped mode with period of 8.5 years.These modes are possibly related to magnetohydrodynamic waves in the Earth’s outer core.
基金the National Key R&D Program of China(Grants 2016YFC0300800 and 2016YFC0300802)the National Natural Science Foundation of China(Grants 11772340 and 11672315)the Science and Technology on Water Jet Propulsion Laboratory(Grant 6142223190101).
文摘The transient cavitating flow around the Clark-Y hydrofoil is numerically investigated by the dynamic mode decomposition with criterion.Based on the ranking dominant modes,frequencies of the first four modes are in good accordance with those obtained by fast Fourier transform.Furthermore,the cavitating flow field is reconstructed by the first four modes,and the dominant flow features are well captured with the reconstructed error below 12%when compared to the simulated flow field.This paper offers a reference for observing and reconstructing the flow fields,and gives a novel insight into the transient cavitating flow features.
基金supported by National Key R&D Program of China (No.2022YFB3303600)the Fundamental Research Funds for the Central Universities (No.2022CDJKYJH048).
文摘Gearbox is a key part in machinery,in which gear,shaft and bearing operate together to transmit motion and power.The wide usage and high failure rate of gearbox make it attract much attention on its health monitoring and fault diagnosis.Dynamic modelling can study the mechanism under different faults and provide theoretical foundation for fault detection.However,current commonly used gear dynamic model usually neglects the influence of bearing and shaft,resulting in incomplete understanding of gearbox fault diagnosis especially under the effect of local defects on gear and shaft.To address this problem,an improved gear-shaft-bearing-housing dynamic model is proposed to reveal the vibration mechanism and responses considering shaft whirling and gear local defects.Firstly,an eighteen degree-of-freedom gearbox dynamic model is proposed,taking into account the interaction among gear,bearing and shaft.Secondly,the dynamic model is iteratively solved.Then,vibration responses are expounded and analysed considering gear spalling and shaft crack.Numerical results show that the gear mesh frequency and its harmonics have higher amplitude through the spectrum.Vibration RMS and the shaft rotating frequency increase with the spalling size and shaft crack angle in general.An experiment is designed to verify the rationality of the proposed gearbox model.Lastly,comprehensive analysis under different spalling size and shaft crack angle are analysed.Results show that when spalling size and crack angle are larger,RMS and the amplitude of shaft rotating frequency will not increase linearly.The dynamic model can accurately simulate the vibration of gear transmission system,which is helpful for gearbox fault diagnosis.
基金supported by the National Nature Science Foundation of China (Grant No.11988102)National Undergraduate Training Program for Innovation and Entrepreneurship。
文摘Dynamic mode decomposition(DMD) aims at extracting intrinsic mechanisms in a time sequence via linear recurrence relation of its observables, thereby predicting later terms in the sequence. Stability is a major concern in DMD predictions. We adopt a regularized form and propose a Regularized DMD(Re DMD) algorithm to determine the regularization parameter. This leverages stability and accuracy. Numerical tests for Burgers' equation demonstrate that Re DMD effectively stabilizes the DMD prediction while maintaining accuracy. Comparisons are made with the truncated DMD algorithm.
基金supported by the China Key Technology Research on Risk Perception of Sub-Synchronous Oscillation of Grid with Large-Scale New Energy Access SGTYHT/21-JS-223.
文摘In recent years,subsynchronous resonance(SSR)has frequently occurred in DFIG-connected series-compensated systems.For the analysis and prevention,it is of great importance to achieve wide area monitoring of the incident.This paper presents a Hankel dynamic mode decomposition(DMD)method to identify SSR parameters using synchrophasor data.The basic idea is to employ the DMD technique to explore the subspace of Hankel matrices constructed by synchrophasors.It is analytically demonstrated that the subspace of these Hankel matrices is a combination of fundamental and SSR modes.Therefore,the SSR parameters can be calculated once the modal parameter is extracted.Compared with the existing method,the presented work has better dynamic performances as it requires much less data.Thus,it is more suitable for practical cases in which the SSR characteristics are timevarying.The effectiveness and superiority of the proposed method have been verified by both simulations and field data.
基金supported by the Science and Technology Project of Guizhou Power Grid Co.,Ltd. (No.GZKJXM20210405).
文摘To identify the parameters of the extended Debye model of XLPE cables,and therefore evaluate the insulation performance of the samples,the sparsity-promoting dynamicmode decomposition(SPDMD)methodwas introduced,aswell the basics and processes of its applicationwere explained.The amplitude vector based on polarization current was first calculated.Based on the non-zero elements of the vector,the number of branches and parameters including the coefficients and time constants of each branch of the extended Debye model were derived.Further research on parameter identification of XLPE cables at different aging stages based on the SPDMD method was carried out to verify the practicability of the method.Compared with the traditional differential method,the simulation and experiment indicated that the SPDMD method can effectively avoid problems such as the relaxation peak being unobvious,and possessing more accuracy during the parameter identification.And due to the polarization current being less affected by the measurement noise than the depolarization current,the SPDMD identification results based on the polarization current spectral line proved to be better at reflecting the response characteristics of the dielectric.In addition,the time domain polarization current test results can be converted into the frequency domain,and then used to obtain the dielectric loss factor spectrum of the insulation.The integral of the dielectric loss factor on a frequency domain can effectively evaluate the insulation condition of the XLPE cable.
文摘A rigid flexible coupling physical model which can represent a flexible spacecraft is investigated in this paper. By applying the mechanics theory in a non-inertial coordinate system,the rigid flexible coupling dynamic model with dynamic stiffening is established via the subsystemmodeling framework. It is clearly elucidated for the first time that,dynamic stiffening is produced by the coupling effect of the centrifugal inertial load distributed on the beamand the transverse vibration deformation of the beam. The modeling approach in this paper successfully avoids problems which are caused by other popular modeling methods nowadays： the derivation process is too complex by using only one dynamic principle; a clearly theoretical explanation for dynamic stiffening can＇t be provided. First,the continuous dynamic models of the flexible beamand the central rigid body are established via structural dynamics and angular momentumtheory respectively. Then,based on the conclusions of orthogonalization about the normal constrained modes,the finite dimensional dynamic model suitable for controller design is obtained. The numerical simulation validations showthat： dynamic stiffening is successfully incorporated into the dynamic characteristics of the first-order model established in this paper,which can indicate the dynamic responses of the rigid flexible coupling system with large overall motion accurately,and has a clear modeling mechanism,concise expressions and a good convergence.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.52439006,U24B20107)supported by the Natural Science Basic Research Program of Shaanxi(Grant No.2025JC-QYXQ-023)the Doctoral Dissertation Innovation Fund of Xi’an University of Technology(Grant No.25207231).
文摘The operation of pump-turbines in the S-shaped region is characterized by amplified pressure pulsations and grid synchronization challenges,which often lead to operational instability and reduced grid compatibility.This study employs dynamic mode decomposition(DMD)method to extract coherent flow structures correlated with dominant pressure pulsation frequencies in the S-shaped region,while experiments have been conducted to validate numerical simulations.Results show that the DMD method can effectively identify the characteristic frequencies of complex flows in the S-shaped region:Low-frequency pressure pulsations in the vaneless space originate from the circumferential transmission component of the water ring over time,which is referred to as the water ring pulsation component.During operational condition transitions,this pulsation component first intensifies then attenuates as it propagates outward along the guide vanes.The dominant draft tube pressure pulsation frequency driven by vortex rope dynamics induces morphological vortex rope transformations via DMD mode shifts during operational transitions.Runner pressure pulsations within the S-shaped region predominantly originate from rotating stall propagating in the direction opposite to the runner's rotation.These findings advance the understanding of S-shaped region flow instabilities,linking component-specific flow structures to global pressure pulsation characteristics,and thereby providing critical insights for operational stability enhancement.
基金supported by the Taishan Scholars Program(tsqn202211059)the National Natural Science Foundation of China(12201592)+1 种基金the Shandong Provincial Natural Science Foundation(ZR2022QA006)Laoshan Laboratory(LSKJ202202302)。
文摘Dynamic mode decomposition(DMD),as a data-driven method,has been frequently used to construct reduced-order models(ROMs)due to its good performance in time extrapolation.However,existing DMD-based ROMs suffer from high storage and computational costs for high-dimensional problems.To mitigate this problem,we develop a new DMD-based ROM,i.e.,TDMD-GPR,by combining tensor train decomposition(TTD)and Gaussian process regression(GPR),where TTD is used to decompose the high-dimensional tensor into multiple factors,including parameterdependent and time-dependent factors.Parameter-dependent factor is fed into GPR to build the map between parameter value and factor vector.For any parameter value,multiplying the corresponding parameter-dependent factor vector and the timedependent factor matrix,the result describes the temporal behavior of the spatial basis for this parameter value and is then used to train the DMD model.In addition,incremental singular value decomposition is adopted to acquire a collection of important instants,which can further reduce the computational and storage costs of TDMD-GPR.The comparison TDMD and standard DMD in terms of computational and storage complexities shows that TDMD is more advantageous.The performance of the TDMD and TDMD-GPR is assessed through several cases,and the numerical results confirm the effectiveness of them.
基金supported by the National Natural Science Foundation of China (Grant Nos. 10832001 and 10872145)the State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences
文摘We present dynamic mode decomposition (DMD) for studying the hairpin vortices generated by hemisphere protuberance measured by two-dimensional (2D) time-resolved (TR) particle image velocimetry (PIV) in a water channel. The hairpins dynamic information is extracted by identifying their dominant frequencies and associated spatial structures. For this quasi-periodic data system, the resulting main Dynamic modes illustrate the different spatial structures associated with the wake vortex region and the near-wall region. By comparisons with proper orthogonal decomposition (POD), it can be concluded that the dynamic mode concentrates on a certain frequency component more effectively than the mode determined by POD. During the analysis, DMD has proven itself a robust and reliable algorithm to extract spatial-temporal coherent structures.
基金supported by National Natural Science Foundation of China(Grant No.10832001)Vision Foundation of Beijing University of Aeronautics and Astronautics(Grant No.YWF-10-20-003)
文摘The present work uses dynamic mode decomposition(DMD)to analyze wake flow of NACA0015 airfoil with Gurney flap.The physics of DMD is first introduced.Then the PIV-measured wake flow velocity field is decomposed into dynamical modes.The vortex shedding pattern behind the trailing edge and its high-order harmonics have been captured with abundant information such as frequency,wavelength and convection speed.It is observed that high-order dynamic modes convect faster than low-order modes;moreover the wavelength of the dynamic modes scales with the corresponding frequency in power law.
基金supported by the National Natural Science Foundation of China(Grant Nos.52201372,52131102).
文摘The flow around a circular cylinder for Re=1000 is characterized by flow separation and Karman vortex street.The typical flow features can be captured to study the correlation between fluid fields and sound fields.In this paper,the three-dimensional circular cylinder is taken as the research object,and the probes of surface fluctuating pressure and far field sound pressure are arranged every 10°.The directional diagram and the coherence of fluctuating pressure and sound pressure are analyzed.The relationship between the flow mode and hydrodynamic noise is studied by using dynamic mode decomposition(DMD).The characteristics of the dipole and quadrupole sound source term of a long span cylinder are studied.The results show that at the angles between 30°–120°and 190°–350°,the fluctuating pressure contributes more to the generation of dipole sounds.The quadrupole sound source shows three-dimensional effects,which is more obvious in a cylinder with large spanwise length.
文摘Dynamic Mode Decomposition(DMD)is a data-driven and model-free decomposition technique.It is suitable for revealing spatio-temporal features of both numerically and experimentally acquired data.Conceptually,DMD performs a low-dimensional spectral decomposition of the data into the following components:the modes,called DMD modes,encode the spatial contribution of the decomposition,whereas the DMD amplitudes specify their impact.Each associated eigenvalue,referred to as DMD eigenvalue,characterizes the frequency and growth rate of the DMD mode.In this paper,we demonstrate how the components of DMD can be utilized to obtain temporal and spatial information from time-dependent flow fields.We begin with the theoretical background of DMD and its application to unsteady flow.Next,we examine the conventional process with DMD mathematically and put it in relationship to the discrete Fourier transform.Our analysis shows that the current use of DMD components has several drawbacks.To resolve these problems we adjust the components and provide new and meaningful insights into the decomposition:we show that our improved components capture the spatio-temporal patterns of the flow better.Moreover,we remove redundancies in the decomposition and clarify the interplay between components,allowing users to understand the impact of components.These new representations,which respect the spatio-temporal character of DMD,enable two clustering methods that segment the flow into physically relevant sections and can therefore be used for the selection of DMD components.With a number of typical examples,we demonstrate that the combination of these techniques allows new insights with DMD for unsteady flow.
基金support by National Key R&D Program of China(No.2021YFA1001300)National Natural Science Foundation of China(Nos.12288101,12271150,12101216)+2 种基金the Hunan Provincial Natural Science Foundation of China(No.2022JJ40030)the Jiangsu Provincial Natural Science Foundation of China(No.BK20230346)Natural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications(No.NY222063).
文摘Parametric dynamical systems are widely used to model physical systems,but their numerical simulation can be computationally demanding due to nonlinearity,long-time simulation,and multi-query requirements.Model reduction methods aim to reduce computation complexity and improve simulation efficiency.However,traditional model reduction methods are inefficient for parametric dynamical systems with nonlinear structures.To address this challenge,we propose an adaptive method based on local dynamic mode decomposition(DMD)to construct an efficient and reliable surrogate model.We propose an improved greedy algorithm to generate the atoms setΘbased on a sequence of relatively small training sets,which could reduce the effect of large training set.At each enrichment step,we construct a local sub-surrogate model using the Taylor expansion and DMD,resulting in the ability to predict the state at any time without solving the original dynamical system.Moreover,our method provides the best approximation almost everywhere over the parameter domain with certain smoothness assumptions,thanks to the gradient information.At last,three concrete examples are presented to illustrate the effectiveness of the proposed method.
文摘This study presents the assumptions and strategies for the practical implementation of the dynamic mode decomposition approach in the wide-area monitoring system of the Italian transmission system operator,Terna.The procedure setup aims to detect poorly damped interarea oscillations of power systems.Dynamic mode decomposition is a data-driven technique that has gained increasing attention in different fields;the proposed implementation can both characterize the oscillatory modes and identify the most influenced areas.This study presents the results of its practical implementation and operational experience in power system monitoring.It focuses on the main characteristics and solutions identified to reliably monitor the interarea electromechanical modes of the interconnected European power system.Moreover,conditions to issue an appropriate alarm in case of critical operating conditions are described.The effectiveness of the proposed approach is validated by its application in three case studies:a critical oscillatory event and a short-circuit event that occurred in the Italian power system in the previous years,and a 15-min time interval of normal grid operation recorded in March 2021.
