Miao Yu

Traditional system dynamics analysis often exhibits noticeable discrepancies due to neglected damper nonlinearities and the limited capability to predict coupled vibrations at distributed measurement locations. To address these gaps, this study develops a nonlinear multibody dynamic (MBD) model for a cab–seat–magnetorheological (MR) hybrid mounting system formulated via the Lagrange approach. A pivotal innovation of this study lies in the high-fidelity characterization of the nonlinear characteristics of the hybrid mount (comprising an MR mount and an air spring) and its seamless integration within the MBD framework. An experimental data-driven neural network model is employed to capture the MR mount’s nonlinear current–force–velocity relationship, while a polynomial model describes the air spring’s force–displacement behavior. By incorporating these high-fidelity component models, the proposed framework accurately represents multi-source nonlinearities and complex coupling effects. Furthermore, unlike conventional center of gravity (CG)-based evaluations, this model specifically focuses on seat-level dynamics to enhance vibration assessment at the driver-seat interface. Validation via ISO Class D road simulations at various vehicle speeds and bench tests demonstrates that the relative error of the seat vertical-acceleration RMS remains below 10% across all tested conditions. confirming the model’s superior prediction accuracy at critical measurement locations.

Precision platforms subject to three-axis, broadband (1–500 Hz), low-amplitude random vibrations that critically affect their dynamic performance can be effectively addressed by a magnetically controllable variable-damping magnetorheological (MR) triaxial vibration absorber. However, achieving vibration suppression control for such a triaxial nonlinear MR system remains a challenge. To address this issue, this paper proposes a model-free rule-based triaxial fuzzy controller. Firstly, a triaxial dynamic model of the system is established, which integrates a conical rubber element and a magnetic fluid damping channel to achieve three-axis independent controllable variable damping within a single structure. Then, theoretical analysis of the swept-frequency characteristics of the MR triaxial vibration isolation system is conducted, and its controllable damping performance is analyzed. Experimental results demonstrate the damping increases by 31.5% ( Z -axis, 3 A) and 22.8% (X/ Y -axis, 3 A). Secondly, a model-free triaxial fuzzy controller with dual-velocity feedback (relative velocity and absolute velocity) is designed. The fuzzy rules are established based on the swept-frequency characteristics obtained under various current conditions. Finally, experimental validation under broadband random excitation demonstrates that the proposed fuzzy control strategy achieves improved overall vibration isolation efficiencies of 68.8% ( Z -axis) and 64.4% (X/ Y -axis), while significantly reducing power consumption by 33.2% ( Z -axis) and 51.3% (X/ Y -axis) compared to ON-OFF control.

Achieving broadband absorption, wide-angle stability, polarization insensitivity, and low-profile thickness simultaneously remains a long-standing challenge for microwave-absorbing metamaterials. Although gradient-impedance structures can effectively suppress interfacial reflection, their absorption performance often deteriorates under oblique incidence and becomes polarization dependent, which limits practical deployment. Herein, inspired by the self-similar logarithmic spiral geometry of nautilus shells, we develop a bioinspired nonlinear honeycomb metamaterial absorber with logarithmic-spiral-derived inner walls. This nonlinear topology is integrated with magnetic-field-induced alignment of flaky carbonyl iron powder (FCIP), which constructs continuous magnetic-loss pathways within a silicone rubber matrix. A machine-learning-assisted inverse-design framework, combining random forest regression and a genetic algorithm, is further established to efficiently optimize the nonlinear impedance gradient. The fabricated absorber, with a thickness of 11.89 mm, achieves a measured effective absorption bandwidth, defined by reflection loss ≤ −10 dB, covering 4.08–18 GHz under TE polarization at an incidence angle of 40°. Stable absorption is also maintained under TE polarization from 0° to 40° and TM polarization from 0° to 60°. The synergistic coupling between the nonlinear impedance gradient and the oriented magnetic-particle network enables broadband electromagnetic energy dissipation over a wide angular range. This work provides a general strategy for the machine-learning-assisted nonlinear optimization of gradient-impedance absorbers.

Phononic crystals (PnCs) have garnered substantial attention owing to their exceptional capability to manipulate elastic waves. However, the bandgaps and other key characteristics of traditional PnCs are fixed, as their material parameters lack dynamic adjustability. To address this limitation, this study proposes a two-dimensional magnet-magnetorheological elastomer (MRE) composite PnC structure. Comprising acrylonitrile-butadiene-styrene (ABS), MRE, and a magnet array (embedded in the MRE via the ABS framework), this PnC features a compact structural design and facilitates convenient, power-free bandgap tuning by rearranging the magnet arrangement. Firstly, the physical parameters of MRE were tested and the magnetic response model of MRE was established. Subsequently, COMSOL finite element simulation was employed to analyze the modulus distribution, dispersion curves, and simulated transmission properties of the MRE with various magnetic field configurations. Subsequently, samples of magnetically sensitive composite PnCs were fabricated and their transmission characteristics were tested by vibration experiments to evaluate their tunable bandgap capability. The simulation results are basically consistent with the experimental results, indicating that this PnC can generate a bandgap, effectively isolate the vibration propagation, and adjust the bandgap frequency by modifying the arrangement of the magnet array.

Airborne electro-optical systems, essential for reconnaissance, target tracking, and environmental monitoring, are highly susceptible to performance degradation and failure due to multi-axis broadband vibrations caused by engine operation, aerodynamic disturbances, and varying flight attitudes. To tackle the challenging problem of suppressing such complex vibrations, this study designed a magnetorheological (MR) multi-dimensional vibration absorber (MMDVA) featuring a decoupled multidimensional motion design. Firstly, the absorber is designed with a dual-cylinder configuration to decouple motion, allowing independent coils and fluid passages to achieve adaptable stiffness and damping characteristics. A triaxial mechanical model of MMDVA based on the magnetorheological fluid’s Bingham model was established, revealing the magnetically controllable characteristics of its three-axis output force. Secondly, to maximize the magnetically controllable range, the dimensions of mechanical units were optimized with correlation analysis and the genetic algorithm in COMSOL, thereby alleviating the computational burden and risk of local optima caused by multiple parameters. Finally, experimental results demonstrate outstanding magnetically controllable damping and stiffness properties in both vertical ( Z ) and lateral ( X, Y ) directions. The vertical and lateral damping increased by up to 131.55% and 223.98%, respectively, while the stiffness exhibited increases of 83.30% and 77.21%, respectively. These findings affirm the absorber’s effectiveness in mitigating multi-dimensional vibrations under realistic operating conditions.

Rotating machinery with complex vibrations is widely utilized in engineering applications. Variable damping provides an effective solution to adapt to dynamic conditions, mitigating resonance while enhancing stability and longevity. Electrorheological fluid (ERF) is a smart material that can be powered by the high voltage generated from a Triboelectric Nanogenerator (TENG), an emerging technology that converts mechanical energy into electricity. Here, we present a TENG-driven ERF damper capable of self-powered and variable-damping functions for rotational vibration mitigation. The electrorheological properties of the ERF were thoroughly characterized, revealing excellent electro-active mechanical properties, including yield stress and dynamic modulus. A disc-type TENG with a gridded structure was designed based on the principle of converting rotational motion into relative sliding between interdigitated electrodes and the triboelectric layer, generating a high-voltage output of up to 4 kV. By integrating the rotational ERF damper with this disc-type TENG, we achieved self-powered and tunable damping performance. Vibration reduction testing on a constructed rotating system demonstrated that the damper effectively attenuated resonance peaks, reducing vibration levels by 18.29% horizontally and 29.20% vertically compared to the original system. Furthermore, the damper’s output self-adapts to rotational speed, enabling effective vibration mitigation across a broader rotational speed range.

Magnetorheological dampers (MRDs) have become widely utilized for shock resistance and vibration mitigation due to their exceptional damping adjustability by magnetic control. However, researchers show that wide temperature range variations significantly affect their mechanical properties. As a typical system of coupled thermal–magnetic-fluid–solid multi-physical fields, the temperature factor complicates the coupling, making it hard to reveal its influence mechanism. Consequently, this study proposed a full-size, multi-physics field coupling simulation method considering the temperature effect for a single-outlet rod MRD with gas compensation to accurately characterize and predict its nonlinear mechanical properties at different temperatures. Firstly, the temperature and magneto-sensitive properties of magnetorheological fluids are described based on the Bingham model. A thermo–magnetic-fluid–solid multi-physics coupling mathematical model is established by integrating theories with thermodynamics, electromagnetism, and fluid mechanics. Then, based on the above theoretical model, a multi-physics field finite element simulation model is approved by the COMSOL platform to simulate the mechanical properties under different currents, velocities, and temperature conditions. Finally, tests are executed at temperatures ranging from −40 °C to 100 °C to verify mechanical performance under different working situations. The model’s accuracy is validated, with an average F _PRE of 5.4%, an average F _RRMSE of 10.3%. This research provides an effective method for revealing the mechanism and predicting the damping force of MRD at different temperatures.

To suppress vibrations on a precision measurement platform challenged by random vibration, a semi-active fuzzy control method utilizing magnetorheological elastomer (MRE) vibration isolator is proposed in this article. Firstly, based on stochastic process theory, Adams software is employed to establish an accurate model and analyze the random vibration response of the isolation platform. Secondly, based on the relative speed and displacement signal feedback, a robust fuzzy control algorithm which is independent of the system model is designed to suppress multiple spectral peaks. Finally, the results of Adams and Simulink co-simulation and semi-physical experiment based on dSPACE show that the designed fuzzy controller can effectively suppress the wide-frequency random vibrations of 15–2000 Hz. Compared with the passive system, the acceleration RMS, displacement RMS and peak acceleration power spectral density of the system are attenuated by 5.56%, 34.86%, and 48.42%, respectively. Especially, the two response peaks in the acceleration power spectral density attenuated by 48.42% and 73.74% compared with the natural resonance peak of the passive system and the excitation peak respectively, indicating the effectiveness of the designed control algorithm for vibration reduction of complex excitation spectrum.

The design and optimization of magnetorheological elastomer (MRE) isolators fundamentally dictate their ultimate performance and application potential. Current methods are limited by over-reliance on designer’s personal experience or inability to concurrently optimize structural configuration and performance parameters. To address these limitations, this study proposes a synergistic design method for MRE isolator, combining extended-variable tri-phase topology optimization and multi-objective parameter optimization. The tri-phase method expands design variables from [0, 1] to [−1, 1], enabling simultaneous optimization of the excitation coil, magnetic circuit and air region without increasing dimensionality, thus yielding a lightweight configuration of MRE isolator. It overcomes the drawback of traditional optimization methods that require predefined of structural configurations. Based on the topological results, a parametric model is constructed, and a multi-objective optimization method (coupling NSGA-II genetic algorithm with finite element simulation) is developed to derive the Pareto frontier. This frontier resolves design trade-offs among the ‘magnetic field–energy consumption–lightweighting’ of MRE isolator. An optimal design is selected from the feasible solution space, achieving minimal mass while maintaining an 89th-percentile magnetic energy ratio. Experimental validation confirms the design’s adaptive vibration mitigation performance and manufacturability. This work establishes a systematic and scalable methodology that bridges empirical design and data-driven optimization, applicable to MRE isolators and other electromagnetic smart devices.