Search Results (88)

As critical air-dropped acoustic sensors for underwater target detection, sonobuoys are frequently compromised by severe hydrodynamic self-noise induced by sea-surface wave excitation, which masks target signals and degrades detection performance. While structural optimizations have traditionally been employed, effective signal-processing-based noise suppression remains challenging because the noise is non-stationary and physically coupled with buoy motion. To address the limited physical interpretability of conventional decomposition methods, this study proposes a physically guided self-noise suppression framework: VMD Constrained by DCCA Correlation (VMD-DCCA). The main contribution is the incorporation of the Detrended Cross-Correlation Analysis (DCCA) coefficient between the sonobuoy’s vertical velocity and the acoustic data as a correlation-dependent constraint within the Variational Mode Decomposition (VMD) optimization process. This motion prior allows more targeted isolation of motion-induced components than standard data-driven decomposition. Simulation and controlled water-tank results show that VMD-DCCA outperforms EEMD and standard VMD, achieving an SNR improvement of approximately 15 dB at an input SNR of −9 dB. The reconstructed signal also preserves visible narrowband spectral lines in the time-frequency representation. These results demonstrate the potential of the proposed method for controlled or post-processing sonobuoy self-noise reduction, while validation under irregular open-ocean conditions remains necessary. Full article

To support the seismic optimization of long-span bridges in regions of high seismicity, this study evaluates the seismic performance of continuous rigid-frame box-girder bridges with different web configurations. A continuous box-girder bridge with corrugated steel webs (CSWBGB) having a main span of 105 m was analyzed and compared with two control models: a continuous box-girder bridge with flat steel webs (FSWBGB) and a conventional prestressed concrete box-girder bridge (PCBGB). Finite element models of the three web types were developed using MIDAS/Civil, and seismic responses were evaluated using the response spectrum method with geometric nonlinearity incorporated; the analyses were conducted under E1 and E2 ground motion intensities (corresponding to a 63% probability of exceedance in 100 years and a 2% probability in 50 years, respectively, as specified in the Chinese seismic design code). Displacement, axial force, and shear force responses were systematically compared among the three configurations. The results show markedly different seismic responses despite the bridges having similar fundamental frequencies. In the longitudinal direction under seismic excitation, the CSWBGB exhibited larger axial displacement than the FSWBGB, yet its peak axial force and shear force decreased by 13% and 18%, respectively, indicating that the greater axial deformation helps relieve internal force demands. Under transverse E1 seismic action, the CSWBGB displayed smaller lateral displacements than both the FSWBGB and the PCBGB. Compared with the CSWBGB, the PCBGB experienced an 11% larger longitudinal displacement and a 43% higher peak axial force, reflecting its relatively limited seismic performance. These findings demonstrate that the CSWBGB not only provides lighter self-weight than the PCBGB but also offers enhanced transverse stiffness, which results in smaller lateral displacements and lower peak shear forces—thus achieving an optimal balance between lightweight design and structural strength. Although the CSWBGB shows strong potential for practical application, its longitudinal displacement response should be carefully controlled in design. Full article

Rotor imbalance and abnormal vibration are classical operating conditions in rotating machinery and can often be identified by conventional vibration analysis. However, the development of low-power, self-powered, and distributed sensing nodes remains important for long-term condition monitoring, particularly in scenarios where external power supply, wiring, and maintenance are constrained. Existing vibration sensors, including piezoelectric and capacitive types, are constrained by power consumption and degraded performance under low-frequency and weak excitation. To address this issue, a magnetically repulsive cushion triboelectric nanogenerator (MRCT) is proposed to enable self-powered vibration sensing. The magnetic-repulsion cushion allows the upper friction layer to undergo stable contact–separation motion under a non-contact restoring force, while the microstructured strip electrode array (MSEA) enhances the triboelectric output and signal stability. A hybrid convolutional neural network–gated recurrent unit (CNN-GRU) deep-learning model is employed to extract time-domain and frequency-domain features from the collected signals, enabling real-time identification of rotor vibration amplitude, frequency, and imbalance weight. Experimental results show that the MRCT provides stable output, a high signal-to-noise ratio, and an identification accuracy above 98% for predefined rotor imbalance-weight states under laboratory conditions. In addition, a shaft-misalignment-related abnormal vibration condition was examined on the motor platform. The corresponding time-domain and frequency-domain analyses show that the MRCT voltage signal exhibits distinguishable signal variations under normal and misalignment-related conditions, including spectral changes around the 2× rotational frequency. A laboratory-scale AIoT-oriented demonstration further verifies the feasibility of integrating MRCT signal acquisition, CNN-GRU inference, wireless transmission, and GUI-based visualization. It should be noted that the present work mainly focuses on imbalance-state recognition, while the misalignment-related experiment provides an additional sensor-response verification. Broader validation involving mechanical looseness, bearing defects, variable-speed operation, cross-machine testing, and long-term industrial conditions remains necessary. Full article

Seismic isolation systems are widely adopted in bridge engineering to reduce earthquake-induced force transfer and improve structural resilience. Conventional lead rubber bearings (LRBs) provide effective energy dissipation and period elongation; however, their limited recentering capability may result in significant residual displacement after strong ground motions. This study investigates the seismic performance of a two-level shape memory alloy–lead rubber bearing (TL-LRB-SMA) hybrid isolation system for multi-span bridges considering structural flexibility, support compliance, and geometric irregularity. A nonlinear analytical model of the hybrid isolator was developed and validated under cyclic loading using benchmark hysteretic behavior from the literature. Subsequently, a multi-degree-of-freedom numerical model of an eleven-span benchmark bridge was established and verified through modal analysis, equivalent static analysis, and comparison with MSBridge software (MSBridge Beta 1.0.1). Nonlinear time-history analyses were performed using multiple excitation scenarios, including the 1940 El-Centro record, Kobe ground motion, oblique seismic incidence, and combined loading cases. Flexible foundation conditions were represented using equivalent translational soil springs. The results indicate that the TL-LRB-SMA system consistently improves self-centering performance and significantly reduces residual displacement relative to conventional LRBs. For the regular bridge with 48 ft piers, residual displacement decreased from 0.786 inches to 0.268 inches under El-Centro excitation, while under combined excitation it reduced from 0.264 inches to 0.087 inches. For irregular bridge configurations, substantial residual displacement reductions were also observed under both longitudinal and oblique loading. Although moderate increases in peak displacement occurred in some cases due to staged SMA activation, the overall recentering performance improved markedly. Overall, the proposed TL-LRB-SMA system demonstrates strong potential for enhancing seismic resilience and post-earthquake serviceability of bridge structures, particularly in flexible and irregular configurations. Full article

This study investigates the reliable numerical analysis of chaotic dynamics in the Glukhovsky–Dolzhansky system, which models convective fluid motion in a rotating ellipsoidal cavity. Hidden and self-excited attractors are localized using the numerical continuation method (NCM), Pyragas time-delayed feedback control, and Leonov’s analytical dimension formula following global stability loss. A critical assessment of Lyapunov exponents and Lyapunov dimensions in a finite-time setting shows that positive values over long but finite intervals may incorrectly indicate sustained chaos due to transient effects and shadowing breakdown. Furthermore, we demonstrate that the fractional order $\gamma$ plays a bidirectional control role: it induces chaotic behavior at $\rho =5$ for $\gamma <0.94$ and suppresses chaos at $\rho =15$ for $\gamma <0.93$. The multifractal spectrum and correlation dimension are used to quantify attractor complexity, where transient chaos exhibits a broader spectrum ($\Delta \alpha \approx 0.67$) compared to sustained chaos ($\Delta \alpha \approx 0.48$). Monte Carlo simulations, Sobol sensitivity analysis, Kaplan–Meier survival analysis, and bootstrap-based hypothesis testing confirm the robustness of the results. Overall, the findings provide a unified framework for analyzing hidden attractors, transient chaos, and fractional-order effects in nonlinear fluid dynamical systems. Full article

In response to the urgent requirement for sustainable power supply for deep-sea or offshore underwater sensing equipment, this work investigates autonomous power generation aboard marine vessels. The vertical vibrations induced by wave excitation at the bottom of the vessel are utilized to drive the vibration energy harvesters on the deck for power generation. In a scenario involving automatic steering, a multiplicity of magnetoelectric harvesters mounted on the deck would move vertically in response to surface wave motion, enabling continuous conversion of wave energy into electrical power. The key feature of this study is that the ship-based self-power generation system is simple to install and safe, with the vibration energy harvesters mounted above the sea surface to avoid the unpredictable underwater sea conditions. This study presents a numerical case analysis of a three-magnet energy harvester designed to generate induced electrical power under wave conditions characterized by a speed of V = 3.0 m/s, amplitude of Z_o = 0.4 m, and wavelength of λ = 2.0 m. Prior to optimizing the ship-based energy harvester, the mathematical model of a three-magnet vibration system was validated against experimental data to ensure accuracy. Subsequently, a sensitivity study was performed to evaluate the influence of wave parameters (e.g., amplitude and wavelength) and the harvester’s geometric parameters on the electrical power output. To maximize power generation, the flower pollination algorithm—an efficient bio-inspired optimization method known for its robustness in global search—was integrated with the objective function defined as the root-mean-square electrical power. Simulation results indicate that the optimized harvester is capable of producing up to 0.1943 W. These findings highlight the potential of ship-based energy harvesters as a sustainable and reliable source of electrical power. Full article

Ultrasonic motors have attracted considerable attention in precision actuation applications because of their advantages over conventional electromagnetic motors, such as compact structure, high positioning accuracy, immunity to electromagnetic interference, noise-free operation, and suitability for low-temperature environments. However, conventional traveling-wave linear ultrasonic motors usually rely on boundary constraints to establish stable traveling waves, which may limit their structural flexibility and self-propelled capability. To address this issue, this paper proposes a free-boundary traveling-wave linear ultrasonic motor capable of realizing self-propelled motion. The motor features a projection structure at each end of the stator. Two piezoelectric ceramics are placed at one end for excitation, while a damping material is arranged at the other end for energy absorption. This design enables the motor to generate traveling waves without requiring fixed boundary conditions. The motor operates in the B(3,1) out-of-plane vibration mode to enhance the energy absorption capacity of the non-excited end and reduce its standing wave ratio (SWR). A finite element model of the motor is established to investigate its vibration characteristics. In addition, a novel method for estimating the standing wave ratio is proposed by using piezoelectric ceramics attached to the motor surface, replacing the traditional calculation approach. A prototype is fabricated to verify the feasibility of the proposed design. Experimental results show that the prototype achieves a minimum SWR of 1.81, a no-load speed of 42.1 mm/s, and a maximum output force of 0.465 N. These results confirm the feasibility of the proposed scheme and provide a new approach for the design of free-boundary traveling-wave linear ultrasonic motors. Full article

Nonlinear energy harvesting systems based on multibody structures constitute a promising solution for autonomous devices powered by ambient vibrations. This paper presents the modeling and control of a nonlinear energy harvester employing a double pendulum configuration and BLDC motors operating as generators. The primary objective of the study was to develop a control strategy that enables the maximization of harvested power while simultaneously improving the energy conversion efficiency during the charging of the battery supplying the target system. The developed model incorporates the mechanical equations of motion of the double pendulum, an electrical model of the BLDC motors, and two independently controlled buck–boost converters, each connected to one joint of the pendulum. In addition, a perturb-and-observe (P&O) maximum power point tracking (MPPT) algorithm was implemented, which utilizes a portion of the computational resources of the target system’s microcontroller and allows for dynamic adjustment of the electrical loads seen by the generators. Simulation results obtained in the Simulink environment confirm that the application of independent power converters combined with local MPPT control leads to an increase in the total harvested power and ensures more stable battery charging under conditions of variable mechanical excitation. The obtained results demonstrate the effectiveness of the proposed approach and indicate its potential applicability in self-powered systems operating in environments characterized by irregular and stochastic vibrations. Full article

Fretting wear due to flow-induced vibration (FIV) remains a primary cause of fuel failure in light water nuclear reactors. In the study of axial FIV, i.e., FIV caused by axial flows, three vibration characteristics, namely natural frequency, damping ratio, and root-mean-square (RMS) amplitude, are critical for mitigating fretting wear by avoiding resonance, maximising overdamping, and preventing large-amplitude instability motion, respectively. This paper presents a set of best practices for simulating axial FIV with a focus on predicting these parameters based on a URANS-FSI numerical framework, utilising high-Reynolds-number Unsteady Reynolds-Averaged Navier–Stokes (URANS) turbulence modelling and two-way fluid–structure interaction (FSI) coupling. This strategy enables accurate and efficient prediction of vibration parameters and offers promising scalability for full-scale nuclear fuel assembly applications. Validation is performed against a semi-empirical model to predict RMS amplitude and experimental benchmarking. The validation experiments involve two setups: vibration of a square beam with fixed and roller-supported ends in annular flow tested at Vattenfall AB, and self-excited vibration of a cantilever beam in annular flow tested at the University of Manchester. The study recommends best practices for numerical schemes, mesh strategies, and convergence criteria, tailored to improve the accuracy and efficiency for each validated parameter. Full article

In this study, a nonlinear dynamic model is developed to examine the stability and vibration behavior of a self-balancing electric Segway operating over irregular stochastic terrains. The Segway is treated as a three-degrees-of-freedom cart–inverted pendulum system, incorporating elastic and damping effects at the wheel–ground interface. Road irregularities are generated in accordance with international standard using high-order filtered noise, allowing for representation of surface classes from smooth to highly degraded. The governing equations, formulated via Lagrange’s method, are transformed into a Lorenz-like state-space form for nonlinear analysis. Numerical simulations employ the fourth-order Runge–Kutta scheme to compute translational and angular responses under varying speeds and terrain conditions. Frequency-domain analysis using Fast Fourier Transform (FFT) identifies resonant excitation bands linked to road spectral content, while Kernel Density Estimation (KDE) maps the probability distribution of displacement states to distinguish stable from variable regimes. The Lyapunov stability assessment and bifurcation analysis reveal critical velocity thresholds and parameter regions marking transitions from stable operation to chaotic motion. The study quantifies the influence of the gravity–damping ratio, mass–damping coupling, control torque ratio, and vertical excitation on dynamic stability. The results provide a methodology for designing stability control systems that ensure safe and comfortable Segway operation across diverse terrains. Full article

Based on the research of the directional self-adaptive piezoelectric energy harvester (DSPEH), a structural design scheme of a multi-directional hybrid energy harvester (MHEH) is put forward. The working principle of the MHEH is experimentally studied. A prototype is designed and manufactured, and the output characteristics of the MHEH in vibrational degree of freedom (DOF) and rotational DOF are experimentally studied. Compared with the DSPEH, after adding the electromagnetic energy harvesting module, the MHEH effectively uses the rotational energy in the rotational DOF, achieves simultaneous energy harvesting from one excitation through two mechanisms, and the output power of the electromagnetic module reaches 61 μW. The total power of the system is increased by 10 times, the power density is increased by 500%, and the MHEH has high voltage output characteristics in multiple directions. Compared with traditional multi-directional and self-adaptive energy harvesters, the MHEH utilizes a reverse-thinking method to generate continuous rotational motion of the cantilever beam, thus eliminating the influence of external excitation direction on the normal vibration of the cantilever beam. In addition, the MHEH has achieved hybrid energy harvesting with a single cantilever beam and multiple mechanisms, providing new ideas for multi-directional energy harvesting. Full article

Conventional machines often face limitations due to complex controllers and bulky power supplies, which can hinder their reliability and operability. In contrast, self-excited movements can harness energy from a stable environment for self-regulation. In this study, we present a novel model of a self-rowing boat inspired by paddle boats. This boat is powered by a liquid crystal elastomer (LCE) turntable that acts as a motor and operates under consistent illumination. We investigated the dynamic behavior of the self-rowing boat under uniform illumination by integrating the photothermal reaction theory of LCEs with a nonlinear dynamic framework. The primary equations were solved using the fourth-order Runge–Kutta method. Our findings reveal that the model exhibits two modes of motion under steady illumination: a static pattern and a self-rowing pattern. The transition between these modes is influenced by the interaction of the driving and friction torques generated by photothermal energy. This study quantitatively analyzes the fundamental conditions necessary for initiating a self-rowing motion and examines how various dimensionless parameters affect the speed of the self-rowing system. The proposed system offers several unique advantages, including a simple structure, easy control, and independence from electronic components. Furthermore, it has the potential for miniaturization and integration, enhancing its applicability in miniature machines and systems. Full article

Numerical simulations of an 80-degree delta wing in free-to-roll motion are performed by applying the dynamic fluid–body interaction (DFBI) model and the overlap/chimera method using the URANS equations. The capabilities of modern computational fluid dynamics methods for predicting wing-rock phenomena over a wide range of angles of attack at low Mach numbers and strong wing–vortex interaction, including the vortex breakdown phenomenon, were investigated by comparing simulation results with wind tunnel test data. At low angles of attack, delays in the strength and position of the leading-edge vortices above the wing have a destabilizing effect on it, leading to the emergence of self-sustained limit-cycle oscillations. At high angles of attack, where vortex breakdown occurs, the available wind tunnel data show that there are two modes of wing self-oscillations in free-to-roll motion, namely, regular large-amplitude oscillations and irregular small-amplitude oscillations, where the excitation of the latter mode depends on the angle of attack and the initial roll angle of the wing motion. The performed numerical simulation also shows the existence of these two self-oscillatory modes in roll, qualitatively and quantitatively matching the experimental data. Full article

This study presents the results of an experimental investigation conducted on a 2:3 scale model of a two-story stone masonry building. We tested the model on the UniKORE L.E.D.A. lab shake table, simulating the Mw 6.3 earthquake ground motion that struck L’Aquila, Italy, on 6 April 2009, with progressively increasing peak acceleration levels. We installed a network of accelerometric sensors on the model to capture its structural behaviour under seismic excitation. Medium-to lower-cost MEMS accelerometers (classes A and B) were compared with traditional piezoelectric sensors commonly used in Structural Health Monitoring (SHM). The experiment assessed the structural performance and damage progression of masonry buildings subjected to realistic earthquake inputs. Additionally, the collected data provided valuable insights into the effectiveness of different sensor types and configurations in detecting key vibrational and failure patterns. All the sensors were able to accurately measure the dynamic response during seismic excitation. However, not all of them were suitable for Operational Modal Analysis (OMA) in noisy environments, where their self-noise represents a crucial factor. This suggests that the self-noise of MEMS accelerometers must be less than 1 µg/√Hz, or preferably below 0.5 µg/√Hz, to obtain good results from the OMA. Therefore, we recommend ultra-low-noise sensors for detecting differences in the structural behaviour before and after seismic events. Our findings provide valuable insights into the seismic vulnerability of masonry structures and the effectiveness of sensors in detecting damage. The management of buildings in earthquake-prone areas can benefit from these specifications. Full article

Self-excited systems rely on stable external stimuli to initiate and sustain oscillations via internal processes. However, these oscillations can compromise system stability and increase friction, limiting their practical applications. To overcome this issue, we propose the light-fueled stable self-rolling of a liquid crystal elastomer (LCE)-based wheel. A photothermal response model based on an LCE was used to analyze the temperature distribution within the LCE rods. The driving torque for self-rolling is generated by the contraction resulting from the LCE’s photothermal response, which displaces the wheel’s center of mass. We then derived the equilibrium equations and identified the critical conditions for achieving stable self-rolling motion. Through the interaction between the temperature field and driving torque, the wheel achieves continuous and stable self-rolling by absorbing thermal energy to counteract damping dissipation. Numerical simulations revealed that the stable self-rolling velocity is influenced by several key parameters, including heat flux, the contraction coefficient, gravitational acceleration, the initial damping torque, and the rolling damping coefficient. The proposed LCE-based wheel enhances system stability and significantly reduces frictional losses. These characteristics make it a promising candidate for applications in autonomous drive systems, micro-transportation devices, and photothermal energy conversion technologies. Full article