Search Results (206)

Oscillatory motions in stratified atmospheric fluid layers significantly influence weather and climate dynamics. Shallow-water equations effectively describe these motions. This study extends the shallow-water model to the time-fractional domain using the conformable fractional derivative. This derivative preserves the local differential structure while introducing tunable time scaling in the dynamics. Approximate analytical solutions were obtained using the conformable Laplace Adomian Decomposition Method (CLADM). This method combines the conformable Laplace transform with Adomian decomposition. Numerical results for fractional orders $\vartheta \in (0, 1]$ demonstrate that the fractional parameter systematically modulates the system dynamics. The solutions at $\vartheta =1$ align well with the established Elzaki Adomian Decomposition Method (EADM), Homotopy Analysis Method (HAM), Fractional Reduced Differential Transform Method (FRDTM), and reference numerical solutions (NUM). This fractional framework offers a flexible approach to modeling atmospheric fluid-layer dynamics. Full article

Energy harvesting has emerged as a promising solution for powering aircraft structural health monitoring (SHM) systems by exploiting ambient vibration energy. This work presents a novel clustered piezoelectric energy harvester (CPEH) designed to enable autonomous sensing and wireless data transmission in aircraft structures. Aircraft sections experience complex, multiple vibration modes during flight; however, the proposed harvester is specifically designed to exploit the oscillatory motion of the vertical tail unit (VTU) of a VUT-100 Cobra aircraft during the cruise phase. The energy harvester employs a clustered piezoelectric cantilever configuration incorporating magnetic stiffness nonlinearity, which enhances vibration-induced strain and enables effective frequency tuning. The nonlinear magnetic interaction broadens the operational bandwidth and improves energy conversion performance under low excitation amplitudes. The system is tuned to operate over a broadband frequency range of 110–130 Hz, with optimal performance achieved at acceleration amplitudes of less than 0.5 g, corresponding to the measured VTU vibration levels during the cruise phase of the flight. An experimental prototype was tested in the laboratory under aircraft cruise-phase vibration conditions, successfully achieving maximum power of 0.041 mW at optimum resistance of 390 KΩ and 5.45 mJ of stored energy in a 1000 µF capacitor within 10 min, confirming the feasibility of the proposed harvester for aircraft SHM applications. Full article

In order to evade interception, advanced aircraft often adopt jump-gliding trajectories to efficiently utilize aerodynamics and achieve complex maneuvers. Precise guidance of UAVs for intercepting such targets is critically challenged due to their high speed and uncertain maneuvers. For terminal guidance scenarios, the extremely short engagement window necessitates strict convergence within the predefined finite time. While PPC offers a promising framework to ensure such convergence with guaranteed transient performance, it suffers from singularity when target uncertainties drive tracking errors beyond performance bounds. To address these challenges, this paper proposes an adaptive prescribed-performance guidance law with predefined-time convergence for UAVs. Built upon the analysis that jump-gliding targets exhibit predominantly longitudinal oscillatory maneuvers, we first establish a velocity model to characterize their motion uncertainties. Using the derived uncertainty bounds and estimated parameters, a predefined-time performance function (PPF) is then developed and robustly modified to eliminate the singularity risk. By integrating this modified PPC with an adaptive law, the proposed framework achieves robust predefined-time convergence of the line-of-sight angle while simultaneously compensating for unknown target maneuvers. Theoretical analysis verifies the framework’s stability, and simulation results demonstrate its effectiveness in intercepting highly maneuverable targets. Full article

Dynamic visual cryptography (DVC) can be formulated as a discrete-time reconstruction problem for time-averaged moiré fringes generated by oscillatory transformations of periodic gratings. When implemented on digital display hardware, the continuous oscillatory motion must be realized through discrete frames, which may prevent correct reconstruction of higher-order time-averaged fringes due to refresh-rate limitations. In this work, mathematical criteria are derived to ensure the reliable reconstruction of higher-order time-averaged moiré fringes under finite refresh rate constraints. Harmonic, stochastic, and rectangular temporal waveforms are examined within a unified framework based on the number of frames per oscillation period and the discrete structure of the resulting time-averaged intensity distribution. Stochastic waveforms are shown to not guaranty reproducible fringe formation. For harmonic modulation with a 240 Hz display refresh rate and a 50 Hz oscillation frequency, only four full frames per period are obtained, which is insufficient to reconstruct the third time-averaged moiré fringe requiring at least sixteen frames per period. Rectangular waveforms satisfy the derived reconstruction conditions when the pitch of the grating, the oscillation amplitude, and the resolution of the rendered grating meet explicit constraints. These results establish quantitative parameter bounds for a mathematically consistent software-based DVC implementation on digital displays. Full article

Ensuring efficient nutrient delivery and waste removal within the interior of three-dimensional (3D) cultures remains a major challenge in tissue engineering. Here, we demonstrate a proof-of-concept methodology that creates internally distributed driving sources to enhance diffusion and perfusion within 3D constructs. Iron microparticles or iron-containing microtubes were incorporated into collagen gels used for the 3D culture of dermal or cardiac fibroblasts, and cyclic dynamic magnetic fields were applied to the constructs. Oscillatory motion of the iron particles enhanced diffusion within the gels, as evidenced by increases in the fast diffusion coefficient of more than threefold and the slow diffusion coefficient of more than tenfold under conditions suitable for cell culture. In cardiac fibroblast cultures, this enhancement significantly increased proliferation by approximately twofold and reduced cytotoxicity by half compared with controls. In contrast, no significant effects were observed in dermal fibroblast cultures. Cyclic compression of microtubes within the collagen gels induced by dynamic magnetic fields primarily resulted in cellular morphological changes, including a reduction in cell area to approximately 0.8-fold of the control values, increased cell polarization with the cellular aspect ratio rising from 1.4 to 1.9, and preferred cell orientations either parallel or perpendicular to the microtube axis. Together, these results suggest that this methodology has the potential to be developed as an effective strategy for improving diffusivity in 3D metabolic environments and for promoting angiogenesis in hydrogel-based cultures. Full article

Linear integrators are traditionally used in motion control systems to compensate for static effects and suppress low-frequency disturbances. However, their use is inevitably accompanied by phase delays that limit the performance and robustness of control systems, especially in conditions of parametric uncertainty. In this regard, nonlinear integrators have been considered for several decades as a promising alternative that can weaken phase constraints and improve the quality of transients. In this paper, the concept of nonlinear integrators is reinterpreted in the context of self-organizing motion control of precision stages. In contrast to traditional approaches focused primarily on frequency analysis and the method of describing the function, a method is proposed for the synthesis of a self-organizing control system for nonlinear SISO objects based on catastrophe theory, namely in the class of elliptical dynamics with the property of structural stability. The control action is formed in such a way that transitions between stable modes occur due to bifurcation-conditioned self-organization, without using external switching logic. To ensure strict analytical guarantees of stability, the Lyapunov gradient-velocity vector function method is used, which guarantees aperiodic robust stability, suppression of oscillatory and chaotic modes, as well as monotonic convergence of trajectories under conditions of parameter uncertainty. The parameters of the nonlinear integrator are adapted using Self-Organizing Maps (SOM), while any parameter changes are allowed only within the regions that meet the conditions of Lyapunov stability. This approach ensures the alignment of analytical and data-oriented methods without violating the structural stability of the system. The results of numerical experiments demonstrate the superiority of the proposed method in comparison with classical linear and adaptive regulators in problems of controlling the movement of stages, especially near bifurcation boundaries and with significant parametric uncertainty. The results obtained confirm that the integration of nonlinear integrators with catastrophe theory and self-organization mechanisms forms a promising basis for the creation of robust and high-precision motion control systems of a new generation. Full article

Self-sustained oscillatory systems enable autonomous motion through continuous interaction with ambient energy sources, positioning them as promising candidates for soft robotic actuation, energy conversion, and biomedical applications. However, their utility is often limited by inherent vibrations and frictional losses, which can lead to impaired efficiency and generate noise. To overcome these limitations, a continuously rotating disc mechanism is proposed, which exploits the photothermal response of liquid crystal elastomers (LCEs) under uniform illumination. The resulting temperature field within the material is obtained via photothermal modeling of the LCE. The rotational actuation torque is generated through mass displacement resulting from light-induced LCE contraction. Based on the above conditions, we establish the equilibrium conditions and critical thresholds for continuous motion and reveal a synergy between the thermal field and torque. Through the interplay of the temperature field and the actuating rotating moment, the system ultimately attains steady self-rotation. Therefore, the absorbed energy offsets damping losses. Numerical simulations reveal that the steady-state self-spinning and translational velocity are influenced by multiple parameters including incident heat flux, gravitational field strength, material contraction coefficient, LCE element dimensions, illumination geometry, and resistive torque. The proposed LCE disc configuration exhibits exceptional operational stability and minimal damping, which has potential for implementation in advanced soft robotic systems and mechanical energy conversion applications. Full article

To overcome the limitations of conventional control strategies in simultaneously suppressing external sway disturbances and internal parameter variations—induced by strong eddy current effects in marine canned magnetic bearings (MBs)—this paper introduces an improved model reference adaptive control (MRAC) method. First, electromagnetic force and dynamic models of the marine canned MBs are developed, taking into account eddy current effects and oscillatory motion. On this basis, a state observer is designed to estimate the system’s unknown dynamics. A predictive error term is formulated to capture the combined influence of model uncertainties and external disturbances. An adaptive law is then applied to compensate for these unknown dynamics and external disturbances. Moreover, the stability of the marine canned MBs system under the proposed improved MRAC scheme is rigorously analyzed using Lyapunov stability theory. Simulation results confirm the effectiveness of the algorithm, showing that, compared with conventional PID control, the improved MRAC approach reduces rotor vibration by more than 53%, significantly strengthening the disturbance rejection performance of marine canned MBs. Full article

This study develops an analytical description of the motion of dilute solid particles in the boundary layer of laminar horizontal flows subjected to weak transverse pulsations. The analysis is formulated for dilute spherical solid particles subjected to transverse velocity pulsations in a laminar boundary-layer flow. A coupled matrix representation of the governing equations is formulated, and closed-form solutions are obtained using Laplace transformation. The analytical expressions capture transient evolution, forced oscillations, resonance effects, and long-term behaviour for particles with different density ratios. Numerical evaluation shows that light particles migrate toward faster regions of the boundary layer and accelerate longitudinally, while heavy particles move toward slower layers and decelerate. Transverse pulsations generate oscillatory trajectories whose amplitude increases near resonance. Impulsive perturbations superimposed on the continuous motion lead to discontinuous transitions consistent with the linear matrix system. The results provide a unified physical interpretation of particle redistribution mechanisms in boundary layers and offer a compact analytical tool for dilute multiphase flow modelling. Full article

This paper presents a comprehensive framework for evaluating the robustness and adaptability of human–robot collaboration (HRC) controllers under a spectrum of dynamic and unpredictable human intentions. Building upon variable admittance controller (VAC) frameworks augmented with Radial Basis Function Neural Network (RBFNN) online adaptation, we introduce two key innovations: (1) an intent-aware human force generator capable of simulating aggressive, hesitant, oscillatory, conflicting, and nominal behaviors, through the modulation of force gains and the introduction of stochastic noise, and (2) the extension of VAC to incorporate variable stiffness as an adaptive control parameter alongside damping and inertia. The adaptive parameters are jointly tuned online using a self-supervised learning (SSL) mechanism driven by motion error metrics and interaction dynamics. The framework is simulated in a dual-arm collaborative manipulation scenario involving two 7-DoF Franka Emika Panda robots transporting a shared object in a high-fidelity simulation environment. Simulation results demonstrate the system’s capability to maintain stable behavior and minimize tracking error despite abrupt changes in human intent. This work provides a novel and systematic tool for stress-testing adaptive controllers in HRC, with implications for the design of resilient, safe, and reliable robotic systems in real-world collaborative environments. Full article

Despite decades of studies on symmetric impinging-jet atomization, the combined role of controlled pre-impingement asymmetry and viscosity in setting the instability pathways and droplet statistics of laminar microjets remains insufficiently quantified. The effects of pre-impingement jet-length difference and liquid viscosity on the flow morphologies, instability dynamics, and atomization behavior of laminar impinging microjets are investigated experimentally using high-speed imaging. By systematically varying the jet-length asymmetry and viscosity over a range of Weber numbers, the evolution of liquid-sheet motion and breakup is resolved from synchronized front- and side-view observations. Specifically, the scientific objective of this work is to elucidate how pre-impingement jet-length asymmetry and liquid viscosity jointly regulate the dynamical behavior of laminar impinging microjets, with particular emphasis on regime transitions of liquid-sheet morphologies, the coupling between upper-sheet oscillations and rim instabilities revealed by synchronized multi-view imaging and POD-based frequency analysis and the resulting droplet-size statistics. These aspects address physical questions that have not been systematically resolved in classical impinging-jet studies, which predominantly focus on symmetric configurations or performance-oriented atomization. With increasing Weber number, the flow undergoes a sequence of regime transitions, including merged-jet, liquid-chain, wavy-rim, fishbone, closed-rim, open-rim, and arc-shaped atomization states. The presence and extent of the closed-rim regime depend sensitively on both jet-length asymmetry and liquid viscosity. Increasing jet-length difference accelerates transitions between these regimes, whereas increasing liquid viscosity stabilizes the liquid sheet and shifts the onset of unsteady breakup to higher Weber numbers. Proper orthogonal decomposition is applied to time-resolved image sequences to extract dominant oscillatory modes and their characteristic frequencies. Within the fishbone regime, the oscillation frequency of rim deformation either coincides with that of the upper region of the liquid sheet or appears as its subharmonic, indicating period-doubling behavior under specific combinations of Weber number and jet-length asymmetry. These frequency characteristics govern the spatiotemporal organization of ligament formation and detachment along the sheet rim. In the arc-shaped atomization regime, droplet-size distributions follow a log-normal form, and at sufficiently high Weber numbers, the mean droplet diameter shows only a weak dependence on jet-length asymmetry. These findings provide microscale-regime guidance for tunable droplet formation in open microfluidic jetting and related small-scale multiphase flows. The innovation of this study lies in the systematic use of synchronized multi-view imaging combined with POD-based frequency analysis and droplet statistics to directly connect liquid-sheet oscillations, rim instability dynamics, and breakup organization under controlled geometric asymmetry and viscosity variations. This approach enables a unified physical interpretation of regime transitions and instability mechanisms that cannot be resolved from single-view observations or morphology-based classification alone. Full article

Several nontrivial phenomena emerge when a quantum field is subjected to dynamical perturbations, with prominent examples including the Hawking and Unruh effects, as well as the dynamical Casimir effect. In this work, we compute the number of particles produced via the dynamical Casimir effect in an ideal cavity, where one of the mirrors is allowed to move under the influence of a gravitational wave. Assuming an oscillatory mirror motion and a plane gravitational wave, we identify the resonance conditions that lead to an exponential increase in the number of created particles through parametric amplification. Full article

The Soft Yoke Mooring (SYM) system is a critical single-point mooring method for Floating Production Storage and Offloading systems (FPSOs) in shallow waters. Its articulated thrust roller bearing operates long-term in harsh marine environments, making it prone to failure and difficult to diagnose. To address the issues of non-stationary signals and fault features submerged in strong noise caused by the bearing’s non-rotational oscillatory motion, this paper proposes an adaptive improved diagnosis scheme based on Minimum Entropy Deconvolution (MED). By optimizing Finite Impulse Response (FIR) filter parameters to adapt to the oscillatory operating conditions and combining joint analysis of time-domain indicators and envelope spectra, precise identification of bearing faults is achieved. Research shows that this method effectively enhances fault impact components. After MED processing, the kurtosis value of the fault signal can be significantly increased from approximately 2.6 to over 8.6. Its effectiveness in noisy environments was verified through simulation. Experiments conducted on a 1:10 scale soft yoke model demonstrated that the MED denoising and filtering signal analysis method can effectively identify damage in the thrust roller bearing of the SYM system under marine conditions characterized by high noise and complex frequencies. This study provides an efficient and reliable method for fault diagnosis of non-rotational oscillatory bearings in complex marine environments, holding significant engineering application value. Full article

With the rapid development of mobile robotics, wheeled bipedal robots, which combine the terrain adaptability of legged robots with the high mobility of wheeled systems, have attracted increasing research attention. To address the balance control problem during both standing and locomotion while reducing the influence of noise on control performance, this paper proposes a balance control framework based on a Linear Quadratic Regulator integrated with an Extended Kalman Filter (KLQR). Specifically, a baseline LQR controller is designed using the robot’s dynamic model, where the control input is generated in the form of wheel-hub motor torques. To mitigate measurement noise and suppress oscillatory behavior, an Extended Kalman Filter is applied to smooth the LQR torque output, which is then used as the final control command. Filtering experiments demonstrate that, compared with median filtering and other baseline methods, the proposed EKF-based approach significantly reduces high-frequency torque fluctuations. In particular, the peak-to-peak torque variation is reduced by more than 60%, and large-amplitude torque spikes observed in the baseline LQR controller are effectively eliminated, resulting in continuous and smooth torque output. Static balance experiments show that the proposed KLQR algorithm reduces the pitch-angle oscillation amplitude from approximately ±0.03 rad to ±0.01 rad, corresponding to an oscillation reduction of about threefold. The estimated RMS value of the pitch angle is reduced from approximately 0.010 rad to 0.003 rad, indicating improved convergence and steady-state stability. Furthermore, experiments involving constant-speed straight-line locomotion and turning indicate that the KLQR algorithm maintains stable motion with velocity fluctuations limited to within ±0.05 m/s. The lateral displacement deviation during locomotion remains below 0.02 m, and no abrupt acceleration or deceleration is observed throughout the experiments. Overall, the results demonstrate that applying Extended Kalman filtering to smooth the control torque effectively improves the smoothness and stability of LQR-based balance control for wheeled bipedal robots. Full article

The flow structure and unsteady evolution characteristics of dual impinging jets represent a flow problem of significant engineering importance in the aerospace field. Currently, there is a lack of systematic research on the unsteady characteristics and the underlying mechanisms of flow structure evolution in dual impinging jets across different velocity regimes. This study investigates a dual impinging jet configuration with a nozzle pressure ratio ranging from 1.52 to 2.77, an impingement spacing of 5d (where d is the nozzle exit diameter), and an inter-nozzle spacing of 10.42d. By employing Particle Image Velocimetry and Proper Orthogonal Decomposition, the evolution of the flow field structure from subsonic to supersonic conditions is systematically analyzed. The results demonstrate that the fountain motion is composed of an anti-symmetric oscillatory mode, a symmetric breathing mode, and an intermittent transport mode. The upper confinement plate obstructs the fountain motion to some extent, inducing unsteady oscillation modes. An increase in jet velocity enhances the upwash momentum of the fountain and raises the characteristic frequencies of its dynamic structures. This research elucidates the influence of jet velocity variation on the flow field structure, providing a theoretical basis for formulating flow control strategies in related engineering applications. Full article