Panel structures on supersonic vehicles experience severe thermal and aerodynamic loads, leading to nonlinear aerothermoelastic responses that can jeopardize structural safety. Analyzing these responses is particularly challenging because of strong nonlinearity and rich frequency content, especially in long-duration numerical simulations. This work introduces a novel Fourier time-sequential physics-informed neural network (FT-PINN) for aerothermoelastic analysis. By incorporating a primitive function, FT-PINN transforms integro-differential governing equations into partial differential equations. Solution accuracy over long-duration time periods for dynamic analysis is maintained through time-sequential training, normalization, and hard-constraint techniques, while random Fourier feature mapping enhances the model ability to capture complex nonlinear and multi-frequency behaviors. Numerical experiments demonstrate that FT-PINN accurately predicts aerothermoelastic responses under various loading conditions, including thermal buckling, limit cycle oscillations, and both quasi-periodic and chaotic motions. The proposed method reduces relative L2 error by two to three orders of magnitude compared to existing PINN approaches. It also effectively handles cases involving viscoelastic damping, non-uniform thickness and time-varying parameters, further highlighting its applicability and versatility.

Achieving tunable vibration suppression in aeronautical stiffened plates remains a challenging problem. This study proposes a reconfigurable inertial amplification metamaterial stiffened plate (RIAP), in which a reconfigurable curved-beam resonator is integrated with a chiral translational-rotational inertial amplification mechanism to enable tunable multi-bandgap vibration suppression. A theoretical model was established based on energy principles and equivalent stiffness to predict the bandgap range of the RIAP. The predictive capability of this model was validated through experimental measurements and simulations. The findings confirm that the RIAP exhibits dual bandgaps originating from local resonance and inertial amplification mechanisms. These bandgaps can be further tuned to overlap by adjusting the rotation angle φ, enabling broadband vibration attenuation over 100-250 Hz. Furthermore, transmission analysis demonstrates significant vibration attenuation within the predicted bandgap regions, accompanied by a peak-splitting phenomenon caused by resonator-plate coupling. The proposed design provides a compact strategy for low-frequency vibration suppression by combining structural reconfiguration and inertia amplification in stiffened structures.

Triply periodic minimal surface (TPMS) architectures have become a prominent class of mechanical metamaterials, largely due to their excellent lightweight load-bearing capability and energy-absorption performance enabled by smooth, continuous, and highly connected geometries. In contrast, their dynamic characteristics remain far less systematically understood. In this work, we present a comprehensive study of 3D elastic-wave dispersion relations and bandgaps for fourteen TPMS-based metamaterials constructed from seven minimal surfaces using two thickening strategies (solid- and sheet-based). Building on these baselines, we further introduce two practical bandgap- engineering routes, geometric flattening and smooth multi-morphology hybridization, and quantify their effects on flexural bandgaps. Our results show that among the fourteen structures, only solid-primitive and solid-neovius support complete bandgaps, whereas sheet-diamond design exhibits no bandgap; the remaining structures predominantly feature directional bandgaps. Geometric flattening leads to a consistent downshift of flexural bandgap frequencies and a reduction in bandgap bandwidth, while multi-morphology hybridization further enables bandgap frequency downshift without requiring a lower volume fraction. The predicted bandgaps are validated through harmonic-response simulations and transmission experiments. Overall, our work offers a quantitative basis for selecting TPMS structures and corresponding volume fractions for vibration suppression panels, and provides engineering methods for future TPMS-based elastic/acoustic metamaterial design.

Existing elastic meta-structures capable of mode conversion are typically limited to a single function, that is, converting one specific mode into another. However, the modal richness inherent in elastic waveguides presents a broader opportunity. Motivated by this, in this work, we present a gradient elastic metamaterial composed of a graded array of cylindrical pillars with varying heights, which is designed to convert flexural waves with different polarizations into distinct elastic wave modes at the same working frequency. Specifically, converting out-of-plane flexural waves (polarization along the thickness direction) into longitudinal waves, and in-plane flexural waves (polarization along the width direction) into torsional waves. Transient simulations and experiments are implemented to validate the multifunctional mode conversion of the gradient metamaterial. Notably, the frequency component of the converted waves is more concentrated than that of the incident waves, indicating an inherent filtering effect. Our work presents a clear and systematic design strategy for a gradient metamaterial capable of multiple mode conversions. This metamaterial not only can filter out non-target frequency components and convert out-of-plane vibrations that cause damage to the structure into in-plane vibrations that cause less damage to the structure. In particular, we envision extending this concept to the development of high-frequency acoustic filtering devices and to the suppression of low-frequency vibrations in bridge structures.

In transonic wind tunnel tests, the model tail support system is highly susceptible to low-frequency, large-amplitude resonance due to aerodynamic loads, which seriously affects the quality of test data and restricts the design and improvement of the aircraft. A piezoelectric active vibration reduction system based on the error feedback filtered-x least mean square (EF-FxLMS) algorithm is proposed to efficiently and reliably suppress flow-induced vibrations in transonic wind tunnel models. Firstly, to address the limitation of the classical filtered-x least mean square (FxLMS) algorithm that requires prediction of the reference signal related to disturbance, the EF-FxLMS algorithm is proposed by directly using the error signal as the reference signal. This approach effectively solves the problem of real-time reference signal acquisition during wind tunnel tests. Subsequently, to meet the practical vibration reduction requirements of transonic wind tunnel models, a piezoelectric active vibration reduction structure with a driving displacement amplification mechanism is developed. Finally, a piezoelectric active vibration reduction system for transonic wind tunnel models is established using the proposed EF-FxLMS algorithm and the developed piezoelectric active vibration reduction structure, and ground test research and wind tunnel test verification are conducted. The experimental results demonstrate that the EF-FxLMS algorithm effectively suppresses flow-induced vibration responses of the aircraft model, with advantages such as strong noise immunity and adaptive variable step. Additionally, the system significantly extends the experimental attack angle range for the transonic wind tunnel model, ensuring accurate evaluation of its aerodynamic characteristics.

Dynamic load identification in the frequency domain is a typical ill-posed inverse problem. Existing studies usually attribute its instability to the ill-conditioning of the frequency response function matrix and the amplification of measurement noise. This study shows that spectral leakage caused by the finite-length discrete Fourier transform is another important source of identification error, especially in lightly damped structures with narrowband resonant responses. A theoretical model is first developed to describe how leakage-induced distortion in the measured response spectrum propagates into the identified load spectrum. On the basis of this analysis, a linear spectral compensation function is proposed to correct the distorted response spectrum. The method is further extended to multidegree-of-freedom systems through a modal response compensation strategy, which can be combined with both direct inversion and Tikhonov regularization. Numerical simulations on single-degree-of-freedom and eight-degree-of-freedom systems, together with experimental validation on an eight-story shear frame, demonstrate that the proposed method effectively reduces leakage-induced identification errors. The results indicate that spectral compensation and regularization play complementary roles: the former corrects systematic signal-domain distortion, whereas the latter suppresses noise amplification during inversion. This work provides a physically interpretable and easily implementable enhancement to classical frequency-domain dynamic load identification methods.

The demand for identifying modal parameters under random excitation is rapidly increasing, but improving the efficiency of automated operational modal analysis (AOMA) remains a significant challenge, particularly during the time-consuming system identification stage. We propose an efficient AOMA method based on the integration of the natural excitation technique (NExT) with dynamic mode decomposition (DMD), termed as NExT-DMD, coupled with the density-based spatial clustering of applications with noise (DBSCAN). This improved NExT-DMD overcomes the reliance of original DMD on free-decay responses and allows operational modal analysis, i.e. modal parameter identification from random excitations. A systematic hyperparameter optimization strategy for DBSCAN is developed based on rank stability, facilitating automated identification. A numerical composite wing model with closely spaced modes was used to validate the proposed method, demonstrating a maximum frequency difference of 3.43 % against the finite element method. With the responses captured by the non-contact three-dimensional optical technique, a physical wing model was tested to show the capability of the proposed method to deal with real-world complex structures. The results demonstrate that our method can improve the identification efficiency by 41.10 % compared with the NExT-eigensystem realization algorithm (ERA) and by 53.83 % compared with covariance-driven stochastic subspace identification (Cov-SSI). The efficient NExT-DMD AOMA method is promising for operational modal analysis with large datasets.

Dynamic load identification, as one of the inverse problems in structural dynamics, often suffers from ill-posedness when directly inverting transfer function matrices in traditional dynamic load identification approaches. Although numerous solutions have been proposed, most existing dynamic load identification methods still rely on matrix inversion. This leads to computational complexity, low accuracy, and failure to achieve real-time identification. We propose a novel time-domain identification method for arbitrary dynamic loads in time-domain inspired by the disturbance observer (DOB) of control theory. We innovatively treat dynamic loads as external disturbances of the structural dynamic system, and develop the DOB based on the state-space equation parameters of the system. In this way, the dynamic load identification is transformed into the estimation of external disturbances by using the DOB transformed from the structural dynamical equations. The convergence of the proposed method has been rigorously proven and its feasibility is validated through numerical simulations and experiments on a cantilever frame structure. With known structural parameters and vibration responses, the method achieves accurate identification of both single-point and multi-point arbitrary dynamic loads with good noise tolerance. In the simulation example, the normalized root mean square error (NRMSE) of the single-point dynamic load time history identification result is 4.946%, and the average NRMSE of the multi-point dynamic load identification result is 2.676%. The experimental results show that the NRMSE results of single-point and multi-point arbitrary dynamic loads on the cantilever frame structure are less than 10%.

A tunable non-smooth nonlinear oscillator (NSNO), comprising a cantilever-beam resonator integrated with dual limiters, has been developed and implemented on a three-dimensional supersonic panel structure to achieve effective flutter suppression and aeroelastic response mitigation. The nonlinear characteristics of the NSNO with piecewise-linear stiffness properties have been analytically investigated through Harmonic Linearization methodology incorporating the Kelvin-Voigt impact model, with experimental validation. The governing equations for nonlinear aeroelastic behavior of the supersonic panel-NSNO coupled system have been formulated using Hamilton's principle and supersonic piston aerodynamic theory, employing the Rayleigh-Ritz approximation approach. Linear flutter analysis demonstrates that the NSNO configuration fundamentally alters the flutter coupling mechanism of the baseline aeroelastic system, resulting in a 33.3 % enhancement of the flutter boundary. Subsequent nonlinear aeroelastic analysis reveals substantial vibration suppression capabilities, with comparative bifurcation analysis indicating up to 92.56 % amplitude reduction across the entire post-flutter regime. Comprehensive parametric studies have identified nonlinear stiffness and collision damping as critical parameters governing suppression performance. An optimized NSNO parameter configuration is established, indicating superior aeroelastic vibration attenuation characteristics. This study demonstrates that NSNO-based structural configuration represents a novel and effective methodology for significant enhancement of aeroelastic stability and nonlinear flutter suppression performance.

Nonlinear mechanical metastructures have emerged as a promising approach for aeroelastic suppression in advanced aircraft. This study introduces a clearance-type nonlinear metastructure integrated into a supersonic low-aspect-ratio wing to suppress flutter and tailor its stability boundary. The proposed nonlinear resonators employ piecewise stiffness and clearance characteristics, overcoming limitations inherent in conventional nonlinear stiffness designs that require large deformation to activate strong nonlinear effects. Based on an equivalent wing-plate model of low-aspect-ratio wing, the aeroelastic formulation of nonlinear metastructure wing-plate is developed by incorporating supersonic piston theory aerodynamics, along with the concept of affine transformation and an improved global shape function method. The influences of key resonator parameters and spatial distributions on the flutter behavior are systematically examined. A correlation coefficient defined on aeroelastic mode shape vectors is proposed to quantitatively characterize inter-modal coupling. The flutter coupling mechanism between the wing and the metastructure is elucidated, thereby revealing the underlying tailoring mechanism governing the stability boundary. Furthermore, by exploiting structural modal characteristics, a multi-frequency combined nonlinear metastructure design strategy is developed, which enhances the aeroelastic stability boundary of the wing by 29.6% under low-added-mass condition. This work provides a theoretical foundation and a practical design methodology for the application of nonlinear metastructures in aeroelastic suppression of lightweight aerospace structures.

The combination of strong structural nonlinearity and flow-induced vibration can enhance energy harvesting efficiency while potentially triggering system instability; however, its specific mechanism remains obscure. Motivated by this, a sliding-type electromagnetic vortex-induced vibration harvester, designed for durable operation in flowing water by integrating nonlinear stiffness, frictional and fluid damping, and nonlinear electromechanical coupling, is investigated. A wake-oscillator model is used to capture the nonlinear features of the system and enable parametric studies; analyses based on coupled computational fluid dynamics/computational structural dynamics/electrical simulation elucidate the wake-mode reorganization and energy-transfer pathways, with water-tunnel tests with particle image velocimetry validating the simulations and revealing key flow features. Differences among linear, nonlinear hardening, and bistable configurations are observed and elucidated in terms of frequency lock-in, amplitude changes, and power output. The nonlinear hardening case exhibits widened bandwidth and increased overall output. In the bistable configuration, a barrier-crossing amplitude reset-and-build-up (BC-ARB) phenomenon is identified. The BC-ARB phenomenon features a delayed and stretched roll-up of shear layer, which reverses the lift-velocity phase relative to structural velocity, creating a negative-work interval that rapidly resets the vibration amplitude; the wake then shifts to a 2S (two single vortices per cycle) mode alongside a synchrony phase return and amplitude rebuilding within the potential well. The phenomenon is found to be sensitive to the mass ratio and, alongside chaos, reduces the harvested power in the bistable configuration. This work elucidates how structural nonlinearity reshapes wake modes and energy transfer, informing parameter optimization for hydrodynamic energy harvester design and vibration control.

This paper proposes a Y-shaped bifurcated beam magnetic self-coupled piezoelectric energy harvester (Y-MSPEH). By incorporating built-in permanent magnets, the harvester is capable of nonlinear stiffness adjustment and broadband energy harvesting, which in turn helps reduce its physical footprint. To this end, a dynamic model of the Y-MSPEH is developed based on Hamilton’s principle, with geometric nonlinearity and piezoelectric coupling effects taken into account. The study derives numerical solutions for the system response through theoretical analysis and validates them via experiments. For the Y-MSPEH, key parameters, including the magnet’s terminal length, branch angle, and magnetic field strength, are analyzed under both repulsive and attractive magnetically self-coupled states. The results show that adjusting the parameters of the Y-MSPEH can effectively tune the peak frequency of the output voltage response and broaden the response frequency band. Comparative studies indicate that the attractive and repulsive magnetically self-coupled states result in wider response bandwidth and higher response amplitude, respectively. Specifically, compared with the linear Y-shaped bifurcated beam harvester and the geometrically nonlinear Y-shaped bifurcated beam harvester, the Y-MSPEH achieves an approximately 8.26% increase in effective bandwidth in the magnetically self-coupled attractive state, thus demonstrating superior energy harvesting performance.

Novel biomimetic tortuous porous architectures, represented by triply periodic minimal surface (TPMS) structures, exhibit excellent thermal management potential. However, their geometric tortuosity complicates heat conduction paths, contradicting fundamental assumptions in many pre-existing models. In this paper, we established the correlation between geometric tortuosity and thermal tortuosity, demonstrating that thermal tortuosity prolongs conductive paths and impairs heat transfer efficiency. Accounting for thermal tortuosity effects, we propose the thermal tortuosity driven model for the effective thermal conductivities of porous structures and apply it to vacuum and water-filled TPMS structures. This is convenient for the study of heat transfer in porous structures and water-cooling devices. Both numerical studies and experiment reveal that the effective thermal conductivities of TPMS structures can be accurately predicted by the thermal tortuosity driven model. Comparative analysis shows that the overhangs in TPMS structures lead to more complex thermal tortuosity and reduce effective thermal conductivity. Consequently, the Gyroid structure exhibits the lowest effective thermal conductivities at the same porosity among TPMS structures. Graded porosity TPMS structures can achieve thermal insulation in high-porosity regions while enhance heat dissipation in low-porosity zones. This work provides a reliable effective thermal conductivities model for TPMS structures, which promotes their research and applications in thermal management of porous structures.

Existing studies rarely address rapid reconstruction of distributed sloshing pressure loads, despite their importance for tank structural safety. To address this issue, this study proposes an end-to-end method integrating reduced-order modeling and deep learning for full-field pressure reconstruction from wall pressure signals. First, training samples are constructed based on Latin Hypercube Sampling (LHS), and a sloshing state classification model is developed using the Froude number and numerical simulation results to automatically distinguish between linear and nonlinear sloshing. Then, a common modal basis is constructed, and a Weighted Proper Orthogonal Decomposition (WPOD) method is introduced to improve the reconstruction accuracy in impact-dominated regions under nonlinear sloshing. Finally, a bidirectional long short-term memory (Bi-LSTM) network is employed to establish the mapping relationship between pressure responses and modal coefficients, enabling distributed liquid sloshing pressure field reconstruction. The results show that the proposed method achieves high reconstruction accuracy under both linear and nonlinear sloshing conditions. For strongly nonlinear sloshing (Froude number approximately 0.23), the minimum coefficient of determination R2 reaches 0.946, while for linear sloshing, R2 exceeds 0.967. Meanwhile, the computational efficiency is significantly improved. This study provides a new approach for efficient reconstruction of liquid sloshing pressure loads.

The extensive utilization of high-speed aircraft has motivated considerable research on supersonic panel flutter, while research on the nonlinear aeroelastic behavior of panels subjected to non-classical boundary constraints remains limited, and an effective ground simulation test system for supersonic panel flutter is lacking. To elucidate the nonlinear flutter mechanism and parameter influences in supersonic rectangular panels under non-classical boundary conditions, a nonlinear aeroelastic model is developed employing the von-Karman plate theory, first-order piston theory, and the assumed-mode method. The accuracy of the model is validated through comparison with finite element method (FEM) results. Numerical integration reveals that reducing the length-width ratio slightly delays the onset of flutter while significantly lowering the threshold for complex dynamic responses. Phase diagrams, Poincare maps and spectral diagrams are employed to trace the system’s transition from ordered to chaotic motion. Furthermore, a second-order reduction and reconstruction method for distributed aerodynamics is proposed, tailored for the ground flutter simulation test of supersonic panels. A multi-input multi-output (MIMO) excitation force controller is designed, resulting in a comprehensive ground flutter simulation test system. Experimental results show good agreement with theoretical predictions, and the controller demonstrates effective real-time tracking of excitation forces, confirming the feasibility of the proposed test approach and its substantial value for engineering applications. This work addresses the challenge of performing aeroelastic tests under coupled multi-physical ground conditions, thereby overcoming a key bottleneck in evaluating the dynamic strength of supersonic/hypersonic panels, providing a novel methodology for the design and assessment of advanced thin-walled structures in next-generation high-speed aircraft.

To enhance aeroelastic stability in aircraft lifting surfaces, this study proposes a novel nonlinear metastructure wing (NMW) integratedwith clearance-type nonlinear resonators (CNRs) for passive flutter suppression, addressing limitations inherent in conventionalnonlinear stiffness designs. Each CNR comprises a cantilever-beam resonator and two pairs of symmetrically distributed cantilever beams, generatingtunable non-smooth nonlinear stiffness enabled by adjusting the piecewise stiffness ratio and clearance size. An aeroelastic model of a long-straight wing coupled with clearance-type nonlinear metastructure in subsonic flow is developed, employing unsteady aerodynamic model based on subsonic lifting surface theory with minimum state approximation. The influence mechanisms of CNR structural parameters and distributions on linear flutter stability and post-flutter response behaviors are elucidated. Results demonstratethat tuning the CNR fundamental frequency inducesdistinct flutter coupling patterns, with an optimal design frequency maximizing the stability boundary of limit cycle oscillations for the NMW. A multi-frequency resonator design strategy of CNRs is further developed to simultaneously suppress multiple flutter instability modes, substantially improving the aeroelastic stability margin. Notably, the NMW with low-added-mass CNRs (adding approximately 8% mass) achieves significant post-flutter vibration reduction and a 49.4% enhancement in aeroelastic stability. Furthermore, wind tunnel testsfurther validatean approximate 40% increase in aeroelastic stability boundary compared to the baseline wing, demonstrating good agreement with theoretical predictions. This work establishes clearance-type nonlinear metastructure as an effective approach for passive flutter suppressionin aircraft wings.

With the growing complexity of engineering systems, the demand for effective vibration isolation, particularly in low-frequency and specific frequency bands under high loads, continues to rise. Traditional isolation techniques often fail to meet these requirements due to their limited performance in such conditions. In response, researchers have explored innovative approaches involving nonlinear stiffness design and mechanical metastructures with bandgap regulation. Nonlinear stiffness is achieved through mechanisms such as negative stiffness elements, gradient beams, and biomimetic hinges, enabling “high-static-low-dynamic” behavior to reconcile static load support with dynamic isolation. Meanwhile, mechanical metastructures utilizes subwavelength local resonance to generate bandgaps, overcoming size constraints in low-frequency isolation. By integrating photonic crystal theory and Bloch wave analysis, the underlying mechanisms of bandgap formation are revealed, and nonlinear designs are employed to broaden isolation bandwidths. The advances systematically review the design strategies of locally resonant metastructures incorporating nonlinear stiffness, and highlights recent advances in broadband, low-frequency isolation. The findings provide theoretical guidance and technical references for both academic studies and practical applications in vibration isolation using locally resonant mechanical metastructures.

Uncertain factors generally exist in aeroelasticity systems, and ignoring their impacts can potentially result in unexpected flutter failures. Additionally, the computational cost of integrating flutter reliability with optimization is significant, as it requires a large number of expensive model evaluations to estimate the failure probability for each distribution parameter. In this paper, a new decoupled flutter reliability optimization method based on adaptive ensemble model is proposed, which fully leverages the advantages of each surrogate model and no additional original model evaluation is required. Firstly, flutter modelling is presented for supersonic composite plate embedded in Shape Memory Alloys (SMA). Secondly, an ensemble model is proposed to estimate the Failure Probability Function (FPF) with enhancing accuracy and efficiency by assigning specific weights to each individual model. The flutter reliability optimization is then decoupled using the FPF. Finally, a highly nonlinear function is employed to demonstrate the validity and computational efficiency of the proposed method compared to DLMCRO, DROAK and DROAPCK method. Two numerical applications including composite plate with SMA and wing model with engine considering the reliability and deterministic optimization are discussed.

In this paper, we propose an adaptive non-Hermitian elastic metasurface (ANEM) composed of symmetrical piezoelectric pillars, whose stiffness and loss are modulated by shunted tunable circuits, to examine its perfect absorption of flexural waves for beam and plate models. The tunable perfect absorption and corresponding mechanisms are theoretically and numerically studied by cooperating with the inductance-resistance (LR) and negative capacitance-resistance (NCR) circuits. Especially, the broadband perfect absorption is realized by a hybrid circuit composed of LR and NC connected in parallel without tuning the circuit parameters, achieved through the simultaneous radiation-dissipation balance at electrical and mechanical resonances. The broadband and wide-angle perfect absorption of flexural waves in plate is numerically and analytically demonstrated. Besides, the high-efficiency asymmetric absorption in plate is achieved by ANEMs with the multiple reflection effect, and the perfect asymmetric absorption is further realized at the exceptional point. The broadband or asymmetrical perfect absorption only rely on the resistance in shunting circuits without needing additional damping material. Our design opens a new route for wave absorption by ultra-compact configuration, which may have potential applications in low-frequency vibration and noise suppression.

Nonlinear metastructures with unique mechanical properties provide potential application in broadband suppression of aeroelastic vibration; however, it is challenging to reveal the intrinsic correlation mechanism between nonlinear bandgap and aeroelastic vibration. In this study, a nonlinear metastructure with net-type nonlinear resonators (NNR) is proposed for both vibration suppression and aeroelastic performance enhancement of the wing-plate in the supersonic flow. The net-type nonlinear metastructure wing-plate is composed of a cantilever stiffened plate and multiple net-type mass-spring systems. The nonlinear stiffness of NNRs can be designed by tuning four pre-tension springs for realizing significant nonlinear effect. The cantilevered wing-like plate with various arrangements of stiffeners is modeled based on the first-order shear deformation theory. The governing equations of the nonlinear metastructure wing-plate in the supersonic flow are derived through Hamilton’s principle, and the aerodynamic model are obtained by using supersonic piston aerodynamic theory. The energy transfer mechanism is firstly explored by a simplified 2-DOF nonlinear system and contributes to the design of three-dimensional (3D) nonlinear metastructure. Numerical simulations show that the present nonlinear metastructure wing-plate can be effectively used for low-frequency broadband vibration attenuation by recurrent transient resonance capture. The prototype is fabricated and the experiments are carried out to show excellent broadband vibration suppression. The supersonic aeroelastic analysis shows that the designed nonlinear metastructure wing-plate with low-additional-mass NNRs can significantly enhance the flutter boundary and suppress the post-flutter aeroelastic vibration, with an improvement of over 14% in aeroelastic stability. Especially, the flutter coupling mechanism of nonlinear metastructure and the suppression mechanism of post-flutter aeroelastic response caused by nonlinear effect of NNRs are clarified in detail. The present work demonstrates that the net-type nonlinear metastructure can provide a novel and effective approach for aeroelastic vibration suppression of supersonic wing.