Search Results (135)

This study investigates the nonlinear aeroelastic behavior and energy harvesting performance of a two-degrees-of-freedom NACA 0012 airfoil under varying reduced velocities and electrical load resistances. The system exhibits a range of dynamic responses, including periodic and chaotic states, governed by strong fluid–structure interactions. Nonlinear oscillations first appear near the critical reduced velocity $U_r^{*}=6$, with large-amplitude limit-cycle oscillations emerging around $U_r^{*}=8$ in the absence of the electrical loading. As the load resistance increases, this transition shifts to higher $U_r^{*}$, reflecting the damping effect of the electrical load. Fourier spectra reveal the presence of odd and even superharmonics in the lift coefficient, indicating nonlinearities induced by fluid–structure coupling, which diminishes at higher resistances. Phase portraits and Poincaré maps capture transitions across dynamical regimes, from periodic to chaotic behavior, particularly at a low resistance. The voltage output correlates with variations in the lift force, reaching its maximum at an intermediate resistance before declining due to a suppressing nonlinearity. Flow visualizations identify various vortex shedding patterns, including single (S), paired (P), triplet (T), multiple-pair (mP) and pair with single (P + S) that weaken at higher resistances and reduced velocities. The results demonstrate that nonlinearity plays a critical role in efficient voltage generation but remains effective only within specific parameter ranges. Full article

Research at the intersection of quantum gravity and quantum information theory has seen significant success in describing the emergence of spacetime and gravity from quantum states whose entanglement entropy approximately obeys an area law. In a different direction, the Kaluza–Klein proposal aims to recover gauge symmetries by means of dimensional reduction in higher-dimensional gravitational theories. Integrating both of these, gravitational and gauge degrees of freedom in $3+1$ dimensions may be obtained upon dimensional reduction in higher-dimensional emergent gravity. To this end, we show that entangled systems of two and three qubits can be associated with $5+1$- and $9+1$-dimensional spacetimes, respectively, which are reduced to $3+1$ dimensions upon singling out a preferred complex direction. Depending on the interpretation of the residual symmetry, either the Standard Model gauge group, $SU\left(3\right)\times SU\left(2\right)\times U\left(1\right)/{\mathbb{Z}}_6$, or the symmetry of Minkowski spacetime together with the gauge symmetry of a right-handed ‘half-generation’ of fermions can be recovered. Thus, there seems to be a natural way to accommodate the chirality of the weak force in the given construction. This motivates a picture in which spacetime emerges from the area law contribution to the entanglement entropy, while gauge and matter degrees of freedom are obtained due to area-law-violating terms. Furthermore, we highlight the possibility of using this construction in quantum simulations of Standard Model fields. Full article

This paper presents a fault-tolerant thruster configuration scheme and a thrust control allocation strategy for an underwater vehicle. First, to accommodate the vehicle’s flexible spatial motion capabilities and address potential thruster failures, an 8-thruster vector arrangement is designed, and the impact of thruster failures on vehicle maneuverability is analyzed. Based on this configuration, a mathematical model of the vector propulsion system is then developed, establishing the relationship between the thrust generated by the individual thrusters and the virtual control forces applied to the vehicle’s 6 degrees of freedom (DOF). Subsequently, a thrust allocation strategy based on quadratic programming (QP) is proposed to optimize thrust allocation, enhancing energy efficiency while satisfying thrust saturation constraints. Finally, simulation results demonstrate that the proposed thruster configuration exhibits strong fault-tolerance. Moreover, compared to the least squares (LS) method based on the pseudo-inverse of the configuration matrix, the QP-based thrust allocation strategy achieves significantly better energy-saving performance. Full article

To address the performance degradation in model predictive control (MPC) under vehicle state uncertainties caused by external disturbances (e.g., crosswinds and tire cornering stiffness variations) and rigid constraint conflicts, we propose a robust MPC framework with adaptive weight adjustment and dynamic constraint relaxation. Traditional MPC methods often suffer from infeasibility or deteriorated tracking accuracies when handling model mismatches and disturbances. To overcome these limitations, three key innovations are introduced: a three-degree-of-freedom vehicle dynamic model integrated with recursive least squares-based online estimation of tire slip stiffness for real-time lateral force compensation; an adaptive weight adjustment mechanism that dynamically balances control energy consumption and tracking accuracy by tuning cost function weights based on real-time state errors; and a dynamic constraint relaxation strategy using slack variables with variable penalty terms to resolve infeasibility while suppressing excessive constraint violations. The proposed method is validated via ROS (noetic)–MATLAB2023 co-simulations under crosswind disturbances (0–3 m/s) and varying road conditions. The results show that the improved algorithm achieves a 13% faster response time (5.2 s vs. 6 s control cycles), a 15% higher minimum speed during cornering (2.98 m/s vs. 2.51 m/s), a 32% narrower lateral velocity fluctuation range ([−0.11, 0.22] m/s vs. [−0.19, 0.22] m/s), and reduced yaw rate oscillations ([−1.8, 2.8] rad/s vs. [−2.8, 2.5] rad/s) compared with a traditional fixed-weight MPC algorithm. These improvements lead to significant enhancements in trajectory tracking accuracy, dynamic response, and disturbance rejection, ensuring both safety and efficiency in autonomous vehicle control under complex uncertainties. The framework provides a practical solution for real-time applications in intelligent transportation systems. Full article

Trajectory tracking control refers to the movement of an unmanned underwater vehicle (UUV) along a desired trajectory, which is a critical technology for the underwater tasks of UUVs. However, in actual scenarios, the reaction torque of propellers induces roll motion in UUVs, and the communication resource and computational resource of UUVs are limited, which affects the trajectory tracking performance of UUVs severely. Hence, this paper introduces an event triggering mechanism to design the double-loop integrated sliding mode control (EDLISMC), which is used for the trajectory tracking control of UUVs. This method designs the kinematic model and dynamic model of 6 degree of freedom (DoF) UUVs under the influence of reaction torque. Then, this method derives the dual loop integral sliding mode controller and designs the event triggering mechanism based on the relative threshold to reduce unnecessary control signals and improve the control efficiency of UUVs. In addition, this method uses a positive lower bound method to verify that the proposed event triggering mechanism does not have Zeno behavior and adopts the Lyapunov theorem to analyze the stability of EDLISMC. Finally, this paper conducts simulations on the simulink component of MATLAB. The relevant simulation proves that the proposed method can complete the trajectory tracking control of UUVs under the influence of reaction torque and it is superior to other methods in terms of resource consumption. Full article

With the increasing global emphasis on sustainable energy, wave energy has gained recognition as a significant renewable marine resource, drawing substantial research attention. However, the efficient conversion of low-frequency, random, and low-energy wave motion into electrical power remains a considerable challenge. In this study, an advanced hybrid generator design is introduced which enhances wave energy harvesting by optimizing wave–body coupling characteristics and incorporating both a triboelectric nanogenerator (TENG) and an electromagnetic generator (EMG) within the shell. The optimized asymmetric trapezoidal shell (ATS) improves output frequency and energy harvesting efficiency in marine environments. Experimental findings under simulated water wave excitation indicate that the accelerations in the x, y, and z directions for the ATS are 1.9 m·s⁻², 0.5 m·s⁻², and 1.4 m·s⁻², respectively, representing 1.2, 5.5, and 2.3 times those observed in the cubic shell. Under real ocean conditions, a single TENG unit embedded in the ATS achieves a maximum transferred charge of 1.54 μC, a short-circuit current of 103 μA, and an open-circuit voltage of 363 V, surpassing the cubic shell by factors of 1.21, 1.24, and 2.13, respectively. These performance metrics closely align with those obtained under six-degree-of-freedom platform oscillation (0.4 Hz, swing angle range of ±6°), exceeding the results observed in laboratory-simulated waves. Notably, the most probable output frequency of the ATS along the x-axis reaches 0.94 Hz in ocean trials, which is 1.94 times the significant wave frequency of ambient sea waves. The integrated hybrid generator efficiently captures low-quality wave energy to power water quality sensors in marine environments. This study highlights the potential of combining synergistic geometric shell design and generator integration to achieve high-performance wave energy harvesting through improved wave–body coupling. Full article

The aim of this research is to investigate and use a variety of immersive multisensory media techniques in order to create convincing digital models of fossilised tree trunks for use in XR (Extended Reality). This is made possible through the use of geospatial data derived from aerial imaging using UASs, terrestrial material captured using cameras and the incorporation of both the visual and audio elements for better immersion, accessed and explored in 6 Degrees of Freedom (6DoF). Immersiveness is a key factor of output that is especially engaging to the user. Both conventional and alternative methods are explored and compared, emphasising the advantages made possible with the help of Machine Learning Computational Photography. The material is collected using both UAS and terrestrial camera devices, including a multi-sensor 3D-360° camera, using stitched panoramas as sources for photogrammetry processing. Difficulties such as capturing large free-standing objects using terrestrial means are overcome using practical solutions involving mounts and remote streaming solutions. The key research contributions are comparisons between different imaging techniques and photogrammetry processes, resulting in significantly higher fidelity outputs. Conclusions indicate that superior fidelity can be achieved through the help of Machine Learning Computational Photography processes, and higher resolutions and technical specs of equipment do not necessarily translate into superior outputs. Full article

This study introduces a pose estimation algorithm integrating an Inertial Navigation System (INS) with an Alternating Current (AC) magnetic field-based navigation system, referred to as the Magnetic Positioning System (MPS), evaluated using a 6 Degrees of Freedom (DoF) drone. The study addresses significant challenges such as the magnetic vector distortions and model uncertainties caused by motor noise, which degrade attitude estimation and limit the effectiveness of traditional Extended Kalman Filter (EKF)-based fusion methods. To mitigate these issues, a Tightly Coupled Unscented Kalman Filter (TC UKF) was developed to enhance robustness and navigation accuracy in dynamic environments. The proposed Unscented Kalman Filter (UKF) demonstrated a superior attitude estimation performance within a 6 m coil spacing area, outperforming both the MPS 3D LS (Least Squares) and EKF-based approaches. Furthermore, hyperparameters such as alpha, beta, and kappa were optimized using the Sequential Importance Resampling (SIR) process of the Particle Filter. This adaptive hyperparameter adjustment achieved improved navigation results compared to the default UKF settings, particularly in environments with high model uncertainty. Full article

A fault-tolerant collaborative control strategy for four-wheel-drive electric vehicles is proposed to address hidden safety issues caused by one or more in-wheel motor faults; the basic design scheme is that the control system is divided into two layers of motion tracking and torque distribution, and three systems, including driving, braking, and front-wheel steering are controlled collaboratively for four-wheel torque distribution. In the layer of motion tracking, a vehicle model with two-degree-of-freedom is employed to predict the control reference values of the longitudinal force and additional yaw moment required; four types of sensors, such as wheel speed, acceleration, gyroscope, and steering wheel angle, are used to calculate the actual values. At the torque distribution layer, SSOD and MSCD distribution schemes are designed to cope with two operating conditions, namely sufficient and insufficient output capacity after local hub motor failure, respectively, focusing on the objective function, constraints, and control variables of the MSCD control strategy. Finally, two operating environments, a straight-line track, and a DLC track, are set up to verify the effectiveness of the proposed control method. The results indicate that, compared with traditional methods, the average errors of the center of mass sideslip angle and yaw rate are reduced by at least 12.9% and 5.88%, respectively, in the straight-line track environment. In the DLC track environment, the average errors of the center of mass sideslip angle and yaw rate are reduced by at least 6% and 4.5%, respectively. The proposed fault-tolerant controller ensures that the four-wheel-drive electric vehicle meets the requirements of handling stability and safety under one or more hub motor failure conditions. Full article

The application of lower-limb exoskeleton robots in rehabilitation is becoming more prevalent, where the precision of control and the speed of response are essential for effective movement tracking. This study tackles the challenge of optimizing both control accuracy and response speed in trajectory tracking for lower-limb exoskeleton hip robots. We introduce an optimization strategy that integrates the Sparrow Search Algorithm (SSA) with fuzzy Proportional-Integral-Derivative (PID) control. This approach addresses the inefficiencies and time-consuming process of manual parameter tuning, thereby improving trajectory tracking performance. First, recognizing the complexity of hip joint motion, which involves multiple degrees of freedom and intricate dynamics, we employed the Lagrangian method. This method is particularly effective for handling nonlinear systems and simplifying the modeling process, allowing for the development of a dynamic model for the hip joint. The SSA is subsequently utilized for the online self-tuning optimization of both the proportional and quantization factors within the fuzzy PID controller. Simulation experiments confirm the efficacy of this strategy in tracking hip joint trajectories during flat walking and standing hip flexion rehabilitation exercises. Experimental results from diverse test populations demonstrate that SSA-fuzzy PID control improves response times by 27.8% (for flat walking) and 30% (for standing hip flexion) when compared to traditional PID control, and by 6% and 2%, respectively, relative to fuzzy PID control. Regarding tracking accuracy, the SSA-fuzzy PID approach increases accuracy by 81.4% (for flat walking) and 80% (for standing hip flexion) when compared to PID control, and by 57.5% and 56.8% relative to fuzzy PID control. The proposed strategy significantly improves both control accuracy and response speed, offering substantial theoretical support for rehabilitation training in individuals with lower-limb impairments. Moreover, in comparison to existing methods, this approach uniquely tackles the challenges of parameter tuning and optimization, presenting a more efficient solution for trajectory tracking in exoskeleton systems. Full article

This research proposes a method for reducing the dimension of the coefficient vector for Crank–Nicolson mixed finite element (CNMFE) solutions to solve the fourth-order variable coefficient parabolic equation. Initially, the CNMFE schemes and corresponding matrix schemes for the equation are established, followed by a thorough discussion of the uniqueness, stability, and error estimates for the CNMFE solutions. Next, a matrix-form reduced-dimension CNMFE (RDCNMFE) method is developed utilizing proper orthogonal decomposition (POD) technology, with an in-depth discussion of the uniqueness, stability, and error estimates of the RDCNMFE solutions. The reduced-dimension method employs identical basis functions, unlike standard CNMFE methods. It significantly reduces the number of unknowns in the computations, thereby effectively decreasing computational time, while there is no loss of accuracy. Finally, numerical experiments are performed for both fourth-order and time-fractional fourth-order parabolic equations. The proposed method demonstrates its effectiveness not only for the fourth-order parabolic equations but also for time-fractional fourth-order parabolic equations, which further validate the universal applicability of the POD-based RDCNMFE method. Under a spatial discretization grid $40\times 40$, the traditional CNMFE method requires $2\times {41}^2$ degrees of freedom at each time step, while the RDCNMFE method reduces the degrees of freedom to $2\times 6$ through POD technology. The numerical results show that the RDCNMFE method is nearly 10 times faster than the traditional method. This clearly demonstrates the significant advantage of the RDCNMFE method in saving computational resources. Full article

Background: Different lateral and postero-lateral cranial approaches to the petroclival region and to the mid-upper brain stem have been described so far, some of which require extensive osseous demolition and possible damage of neurovascular structures. Neuronavigational systems are now extensively available for preoperative planning and intraoperative navigation to assist the surgeons in choosing the optimally invasive approach for each pathology. Herein, we describe a detailed navigation-augmented morphometric analysis to bring insight into the usefulness of an anterior petrosectomy (AP) to handle lesions in the petroclival region. Methods: Eight cadaveric, silicone injected heads were used. A total of 14 approaches (AP, n = 8; retrosigmoid, RS, n = 6) using a standard microsurgical dissection technique were performed. All specimens had preoperative CT and MRI scans, as well as a post-dissection CT. The neuronavigational system was used for distance measurements, craniotomy sizes and surgical corridor volumes, for each approach. Results: The distance from the skull surface to the petrous apex was significantly shorter in the AP approach when compared with the RS (46.0 ± 1.9 mm versus 71.3 ± 1.8 mm, respectively, p < 0.001). Although the craniotomy size was not different, the volume of the surgical corridor was significantly larger with the AP approach (21.31 ± 1.91 cm³ vs. 13.39 ± 1.8 cm³). The AP approach increased the length of the basilar artery exposure from 6.9 ± 1.5 mm (obtained with a standard subtemporal approach) to 22.1 ± 1.7 mm (p < 0.0001). Conclusions: The surgical corridor to the petroclival region achieved by virtue of an AP was significantly larger and featured shorter working distances, resulting in a higher degree of surgical freedom. Although significant individual anatomical variations of fundamental neurovascular and bony structures were found, these difficulties were overcome by careful pre- and intraoperative use of neuronavigation. Full article

Macroseismic intensity data are the only source of information for historical earthquakes; it is therefore necessary to devise methods that allow us to retrieve as many source parameters as possible on the basis of these data. We present the inversion of macroseismic data as a first validation of an improved version of the kinematic function, KF. Following the previous results of some earthquakes on Italian territory and several validations by Californian events provided with instrumental solutions, we have now simplified the KF by reducing some degrees of freedom of the parameters and rearranging the code for parallel calculation. This approach will allow for a more extensive application of the KF technique. We present the inversion of the macroseismic intensity pattern of the M_wp6 earthquake of 27 March 1928 (8:32 GMT), which occurred in Northeastern Italy (Carnia), and we retrieved source parameters that are compatible with the solutions of other authors who independently treat instrumental data. The 1928 event is located a few tens of kilometers west of the more destructive M_w6.5 of 6 May 1976 and northeast of the subsequent earthquake M_wp6.1 of 18 October 1936. The inversion was performed as a blind test, without prior knowledge for fault plane solutions and tectonic information; it resulted in a minimum variance model with a strike of 62°, a dip of 10°, and a rake of 101°. This solution is not consistent with the entire tectonic framework of the eastern Southalpine chain, but it is in agreement with the But-Chiarsò line. This result encourages us to test further improvements to the KF method and to treat other cases from the Italian macroseismic catalog. Full article

The safety of Jettisoned FDRS in the process of separation from an aircraft is a key factor in designing Jettisoned FDRs and enabling them to pass airworthiness certification and be widely used in civil aircraft. The separation process of Jettisoned FDR installed on NASA Common Research Model is studied by the simulation method based on anisotropic unstructured hybrid grid and overset grid technology coupled with the rigid body 6-DOF equation. First, the numerical simulation accuracy of software under same simulation method is verified by WPFS standard model. Then, according to the three main aerodynamic parameters, including incoming Mach number, angle of attack α and sideslip angle β, 10 conditions including standard condition are designed and the separation process of recorder is simulated numerically. The simulation obtained the movement of Jettisoned FDRs in 6 degrees of freedom relative to the body coordinate system in different operating conditions during the separation process and confirmed that Jettisoned FDRs can be safely separated under these operating conditions. Finally, combined with the standard operating condition, the impact of three parameters’ changes on recorder’s 6 degrees of freedom motion and the time required to complete separation are analyzed, and conditions to ensure the safe separation of Jettisoned FDRs are summarized according to the requirements of airworthiness terms. Full article

Worms are organisms characterized by simple structures, low energy consumption, and stable movement. Inspired by these characteristics, worm-like soft robots demonstrate exceptional adaptability to unstructured environments, attracting considerable interest in the field of biomimetic engineering. The primary challenge currently involves improving the motion performance of worm-like robots from the perspectives of actuation and anchoring. In this study, a single segment worm-like soft robot driven by electrohydraulic actuators is proposed. The robot consists of a soft actuation module and two symmetrical anchoring modules. The actuation modules enable multi-degree-of-freedom motion of the robot using symmetric dual-electrode electrohydraulic actuators, while the anchoring modules provide active friction control through bistable electrohydraulic actuators. A hierarchical microstructure design is used for the biomimetic adhesive surface, enabling rapid, reversible, and stable attachment to and detachment from different surfaces, thereby improving the robot’s surface anchoring performance. Experimental results show that the designed robot can perform peristaltic and bending motions similar to a worm. It achieves rapid bidirectional propulsion on both dry and wet surfaces, with a maximum speed of 10.36 mm/s (over 6 velocity/length ratio (min⁻¹)). Full article