Search Results (77)

Molecular dynamics (MD) simulations have been performed on the energetics, mechanical properties, and irradiation response of seventy-three 3C-SiC symmetric tilt grain boundaries (STGBs) with three tilt axes (<100>, <110> and <111>). The effect of GB characteristics on the STGB properties has been investigated. The GB energy is positively and linearly correlated with the excess volume, but the linearity in SiC is not as good as in metals, which stems from the inhomogeneous structural relaxation near GBs induced by orientation-sensitive covalent bonding. For <110>STGBs, the shear strength exhibits symmetry with respect to the misorientation angle of 90°, which is consistent with ab initio calculations for Al in similar shear orientations. Cascades are performed with 8 keV silicon as the primary knock-on atom (PKA). No direct correlation is found between the sink efficiency of GBs for defects and GB characteristics, which comes from the complexity of the diatomic system during the recovery phase. For GBs with smaller values of Σ, the GBs exhibit a weaker blocking effect on the penetration of irradiated defects, resulting in a lower number of defects in GBs and a higher number of total surviving defects. In particular, it is seen that the percentage decrease in tensile strength after irradiation is positively correlated with the Σ value. Taken together, these results help to elucidate the impact of GB behavior on the mechanical properties of as well as the primary irradiation damage in SiC and provide a reference for creating improved materials through GB engineering. Full article

Aiming to enable intelligent vehicles to achieve autonomous charging under low-battery conditions, this paper presents a navigation system for autonomous charging that integrates an improved bidirectional A* algorithm for path planning and an optimized YOLOv11n model for visual recognition. The system utilizes the improved bidirectional A* algorithm to generate collision-free paths from the starting point to the charging area, dynamically adjusting the heuristic function by combining node–target distance and search iterations to optimize bidirectional search weights, pruning expanded nodes via a greedy strategy and smoothing paths into cubic Bézier curves for practical vehicle motion. For precise localization of charging areas and piles, the YOLOv11n model is enhanced with a CAFMFusion mechanism to bridge semantic gaps between shallow and deep features, enabling effective local–global feature fusion and improving detection accuracy. Experimental evaluations in long corridors and complex indoor environments showed that the improved bidirectional A* algorithm outperforms the traditional improved A* algorithm in all metrics, particularly in that it reduces computation time significantly while maintaining robustness in symmetric/non-symmetric and dynamic/non-dynamic scenarios. The optimized YOLOv11n model achieves state-of-the-art precision (P) and mAP@0.5 compared to YOLOv5, YOLOv8n, and the baseline model, with a minor 0.9% recall (R) deficit compared to YOLOv5 but more balanced overall performance and superior capability for small-object detection. By fusing the two improved modules, the proposed system successfully realizes autonomous charging navigation, providing an efficient solution for energy management in intelligent vehicles in real-world environments. Full article

Our work presents a laser fuze detector structure with a four-channel center-symmetrical emitting laser under the influence of the three-dimensional (3D) and spatial properties of smoke clouds, which was used to improve the laser fuze’s anti-smoke interference ability, as well as the target detection performance. A laser echo signal model under multiple frequency-modulated continuous-wave (FMCW) lasers was constructed by investigating the hybrid collision scattering process of photons and smoke particles. Using a virtual particle system implemented in Unity3D, the laser target characteristics were studied under the conditions of multiple smoke particle characteristic variations. The simulation results showed that false alarms in low-visibility and missed alarms in high-visibility smoke scenes could be effectively solved with four emitting lasers. With this structure of the laser fuze prototype, the smoke echo signal and the target echo signal could be separated, and the average amplitude growth rate of the target echo signal was improved. The conclusions are supported by the results of experiments. Therefore, this study not only reveals laser target properties for 3D and spatial properties of particles, but also provides design guidance and reasonable optimization of FMCW laser fuze multi-channel emission structures in combination with multi-particle collision types and target characteristics. Full article

This study presents the investigation of freezeout parameters, namely the kinetic freezeout temperature (T) and transverse flow velocity (${\beta }_T$), in different centrality intervals with fixed as well as with variable flow profile ($n_0$) in the blast-wave model (using Boltzmann Gibbs statistics). The model is used to fit the experimental data of transverse momentum spectra of ${\pi }^{+}$, $K^{+}$, and p in $Au$–$Au$ and $Pb$–$Pb$ collisions at 200 GeV and 2.76 TeV, respectively. In our observation, when the parameter $n_0$ is considered as a free parameter, the parameter T decreases from head-on to peripheral collisions, while it increases towards the periphery if $n_0$ is fixed. In addition, parameter ${\beta }_T$ decreases from central to peripheral collisions in both cases. These findings provide valuable insights into the dynamics of quark-gluon plasma formation and expansion in high-energy nuclear collisions. Moreover, the kinetic freezeout temperature T and the transverse flow velocity ${\beta }_T$ are mass-dependent; while the former becomes larger for massive particles, the latter becomes larger for light particles, showing the mass differential kinetic freezeout scenario. Full article

Under the framework of classical electrodynamics, this article investigates the nonlinear Thomson scattering generated by the cross-collision between a tightly focused linearly polarized Gaussian laser pulse and a relativistic electron through numerical simulation and emulation. The oscillation direction and emission angle of the electron’s trajectory are influenced by the beam waist radius and the delay time. The spatial radiation distribution of electrons exhibits a comet-shaped pattern, with the radiation being concentrated in the forward position. This is attributed to the high laser intensity at the focus, resulting in intense electron motion. As the beam waist radius keeps increasing continuously, the maximum radiation polar angle in the spatial distribution decreases. The time spectrum exhibits a symmetrical three-peak structure, with a high secondary peak. Meanwhile, the supercontinuum spectrum gradually transforms into a multi-peak distribution spectrum. In the multi-peak mode, the main peak and the secondary peak will interchange during the increase in the waist radius, generating rays with higher frequencies and energies. The aforementioned research findings reveal a portion of the mechanism of the nonlinear Thomson scattering theory and are beneficial for generating X-rays of higher quality. Full article

Within the framework of classical dynamics, the impact of laser amplitude on the cross-collision between a linearly polarized intense laser pulse and a relativistic electron under tight focusing conditions was investigated via numerical simulation. As the laser amplitude intensifies, the z-axis oscillation trajectory of the electron elongates. The spatial radiation angular distribution of the electron transforms from a “hill shape” to a “comet shape”, and the radiation peak shifts toward the direction of smaller polar angle, with the radiation concentrating in the forward position. The time spectrum is symmetrical; the number of peaks is reduced from multiple peaks to three peaks; and the relative height of the main peak and secondary peaks increases, with the time distribution gradually concentrating, which can be regarded as an ultrashort attosecond single pulse. The spectrum exhibits a multi-peak distribution trend. When the laser amplitude is relatively strong, radiation with a more concentrated frequency range and better quality can be output. The above research findings are beneficial for generating X-rays of higher quality and can be applied in fields such as biomedicine and atomic physics. Full article

There is evidence that the properties of hadrons are modified in a nuclear medium. Information about the medium modifications of the internal structure of hadrons is fundamental for the study of dense nuclear matter and high-energy processes, including heavy-ion and nucleus–nucleus collisions. At the moment, however, empirical information about medium modifications of hadrons is limited; therefore, theoretical studies are essential for progress in the field. In the present work, we review theoretical studies of the electromagnetic and axial form factors of octet baryons in symmetric nuclear matter. The calculations are based on a model that takes into account the degrees of freedom revealed in experimental studies of low and intermediate square transfer momentum $q^2=-Q^2$: valence quarks and meson cloud excitations of baryon cores. The formalism combines a covariant constituent quark model, developed for a free space (vacuum) with the quark–meson coupling model for extension to the nuclear medium. We conclude that the nuclear medium modifies the baryon properties differently according to the flavor content of the baryons and the medium density. The effects of the medium increase with density and are stronger (quenched or enhanced) for light baryons than for heavy baryons. In particular, the in-medium neutrino–nucleon and antineutrino–nucleon cross-sections are reduced compared to the values in free space. The proposed formalism can be extended to densities above the normal nuclear density and applied to neutrino–hyperon and antineutrino–hyperon scattering in dense nuclear matter. Full article

Inland waterway navigation involves complex traffic conditions with frequent multi-ship encounters. Benefiting from its straightforward structure and robust adaptability, reinforcement learning has found applications in navigation. This article proposes a deep actor–critic collision avoidance model which is based on the weighted summation of intrinsic reward and extrinsic reward, overcoming the sparsity of the reward function in navigation tasks. For the proposed algorithm, the extrinsic reward considers factors of collision risk, economic reward, and penalties for violating collision avoidance rules, while the intrinsic reward explores the novelty of agent states. The optimization of the own ship’s actions is achieved through the utilization of a weighted summation of these two types of rewards, providing valuable guidance for decision-making in a symmetrical interaction framework. To validate the performance of the proposed multi-ship collision avoidance model, simulations of both two-ship encounters and complex multi-ship scenarios involving dynamic and static obstacles are conducted. The following conclusions can be drawn: (1) The proposed model could provide effective decisions for ship navigation in inland waterways, maintaining symmetrical coordination between vessels. (2) The hybrid reward mechanism successfully guides ship behavior in collision avoidance scenarios. Full article

Drone swarms often need to fly cooperatively in complex spaces filled with multiple obstacles. In such scenarios, they must meet the requirements of both external obstacle avoidance and internal collision avoidance while maintaining a certain topological configuration among individuals. This easily leads to problems such as congestion, oscillation, and poor stability, including being out of control. Thus, it is essential to measure system-wide stability, regulate the autonomous cooperative evolution of swarms, and enhance their adaptation to environmental changes. To solve this problem, using the symmetric unmanned aerial vehicle (UAV) swarm as the research object, a group entropy measurement theory for the stability of drone swarms is proposed. We introduce an entropy-based metric for group motion consistency. This metric serves as a fitness index for individual collaboration, enabling adaptive adjustment of drone swarm coherence under multi-obstacle conditions. Finally, simulation experiments are conducted to verify the effectiveness of the established theory and algorithm. Full article

This study explores an innovative approach to integrating modern technology with traditional culture by replacing human performers with clusters of intelligent unmanned vehicles in the Chinese Lunar New Year bench dragon dance. The primary technical challenge lies in addressing the motion control issues of vehicle clusters moving along and out of an Archimedean spiral trajectory, where the forces and constraints acting on the vehicles during the spiral-in and spiral-out processes are symmetrically distributed. To this end, a geometric–analytical framework is developed to tackle kinematic coordination and collision prediction for connected autonomous vehicle fleets along such paths. A motion control model for the unmanned vehicle fleet, incorporating analytical geometry and recursive relationships, is established, accompanied by the proposal of iterative algorithms and intelligent optimization techniques. These methods are employed to compute the fleet’s positions and velocities, determine the interference moments between the lead and following vehicles, and optimize the minimum pitch for collision avoidance. The simulation results demonstrate that the vehicle fleet maintains a stable formation and trajectory along the Archimedean spiral path with minimal speed variations. The motion control problem of autonomous robots following an Archimedean spiral trajectory addressed in this study exhibits a degree of novelty as no related motion control studies have been identified to date, precluding comparative experiments. This work provides fundamental insights into multi-agent coordination along spiral trajectories, offers practical solutions for spatial optimization in autonomous robotic system operations, and presents a paradigmatic framework for the preservation of intangible cultural heritage through robotic systems equipped with motion planning algorithms. Furthermore, it serves as an inspiration for future research into controlling autonomous robots along complex predetermined trajectories, such as the Archimedean spiral. Full article

The investigation of the nuclear matter equation of state (EOS) beyond saturation density has been a fundamental goal of heavy ion collision experiments for more than 40 years. First constraints on the EOS of symmetric nuclear matter at high densities were extracted from heavy ion data measured at AGS and GSI. At GSI, symmetry energy has also been investigated in nuclear collisions. These results of laboratory measurements are complemented by the analysis of recent astrophysical observations regarding the mass and radius of neutron stars and gravitational waves from neutron star merger events. The research programs of upcoming laboratory experiments include the study of the EOS at neutron star core densities and will also shed light on the elementary degrees of freedom of dense QCD matter. The status of the CBM experiment at FAIR and the perspective regarding the studies of the EOS of symmetric and asymmetric dense nuclear matter will be presented. Full article

In this paper, the concept of symmetry is utilized to design the trajectory planning for parallel parking of autonomous ground vehicles—that is, the construction and the solution of the optimization-based trajectory planning approach are symmetrical. Parking is the main factor that troubles most drivers for their daily driving travel, and it can even lead to traffic congestion in severe cases. With the rise of new intelligent and autonomous vehicles, automatic parking seems to have become a trend. Traditional geometric planning methods are less adaptable to parking scenarios, while the parking paths planned by graph search methods may only achieve local optimality. Additionally, significant computational time is often required by numerical optimization methods to find a parking path when a good initial solution is not available. This paper presents a hierarchical trajectory planning approach for high-quality parallel parking of autonomous ground vehicles. The approach begins with a graph search layer to roughly generate an initial solution, which is refined by a numerical optimization layer to produce a high-quality parallel parking trajectory. Considering the high dimensionality and difficulty of finding an optimal solution for the path planning optimization problem, this paper proposes an improved safe travel corridor (I-STC) with the construction of collision constraints isolated from surrounding environmental obstacles. By constructing collision constraints of the I-STC based on the initial solution, the proposed method avoids the complexities and non-differentiability of traditional obstacle avoidance constraints, and simplifies the problem modeling the subsequent numerical optimization process. The simulation results demonstrate that the I-STC is capable of generating parallel parking trajectories with both comfort and safety. Full article

The input layer, hidden layer, and output layer are three models of neural processors that comprise feedforward neural networks. In this paper, an enhanced tunicate swarm algorithm based on a differential sequencing alteration operator (ETSA) with symmetric cooperative swarms is presented to train feedforward neural networks. The objective is to accomplish minimum classification errors and the most appropriate neural network layout by regulating the layers’ connection weights and neurons’ deviation thresholds according to the transmission error between the anticipated input and the authentic output. The TSA mimics jet motorization and swarm scavenging to mitigate directional collisions and to maintain the greatest solution that is customized and regional. However, the TSA exhibits the disadvantages of low computational accuracy, a slow convergence speed, and easy search stagnation. The differential sequencing alteration operator has adaptable localized extraction and search screening to broaden the identification scope, enrich population creativity, expedite computation productivity, and avoid search stagnation. The ETSA integrates exploration and exploitation to mitigate search stagnation, which has sufficient stability and flexibility to acquire the finest solution. The ETSA was distinguished from the ETTAO, EPSA, SABO, SAO, EWWPA, YDSE, and TSA by monitoring seventeen alternative datasets. The experimental results confirm that the ETSA maintains profound sustainability and durability to avoid exaggerated convergence, locate the acceptable transmission error, and equalize extraction and prospection to yield a faster convergence speed, superior calculation accuracy, and greater categorization accuracy. Full article

This article presents a vibration model of neighboring rolling parts that takes into account non-smooth symmetric collisions. This model was used to examine the motion state of the rolling element and the collision force between nearby rolling elements. It also determined the motion posture and overall collision form of the rolling element after setting the functional slot. Afterwards, the level of disorderly movement and the structure of the moving object were examined and confirmed through the use of a phase diagram of the motion system in relation to zero symmetry, the Lyapunov exponent, and a platform for measuring irregular vibrations in the bearing. This work aims to clarify the factors that contribute to the persistent chaotic state of rolling elements in bearing vibration. Full article

The thickness of the coating on the surface of a workpiece is an important factor in determining the quality of spraying. However, it is challenging to estimate the distribution of film thickness accurately before the actual spraying process. This lack of estimation hinders the optimization of spraying process parameters and trajectory. To overcome this, a numerical simulation of surface spray coating thickness was conducted to provide guidance for the actual coating process. The research consists of three main parts. Firstly, the spray trajectory of the spray gun is determined using the proposed Stereo Lithography (STL) model slicing algorithm. Secondly, a two-phase flow spray model and collision adhesion model are established to construct the spray film model. The surface mesh is determined, and the spraying process parameters are set. Finally, numerical simulation is conducted to analyze the dynamic spraying trajectory and the distribution of coating thickness. The results show that the coating thickness distribution on an arc surface is thicker in the middle and thinner on the edges. The distribution is symmetric with respect to both the transverse and longitudinal directions of the arc surface. The coating thickness distribution at both ends is not as uniform as in the middle section. The concave part of the free surface has the largest coating thickness, while the coating thickness distribution on the convex part is not as uniform as on the relatively flat part. This method of simulating the coating thickness distribution on complex surfaces provides a solid foundation for further optimization of spraying process parameters and trajectory, ultimately improving the qualification rate of workpiece spraying processing. Full article