bluuebunny/crossref_metadata_2025 huggingface dataset:
Magnetovolume effects in the weak itinerant helimagnet Fe0.5Co0.5Si
Authors: Kortov S. V. , Barmin S. M. , Sevast’yanov A. A. , Romasheva L. F. , Gel’d P. V.
Published: December 2024

The thermal expansion at low temperatures (4.2–280 K) and forced magnetostriction in fields of up to 200 kOe at different temperatures have been studied in the weak itinerant helimagnet Fe0.5Co0.5Si. Within the framework of the Stoner–Edwards–Wohlfarth and Moriya–Usami models we determined the magnetic contributions to the linear thermal expansion coefficient, calculated the magnetoelastic coupling constants, and demonstrated that the experimental results are in good agreement with the Moriya–Usami theory of spin-density fluctuations.
Stabilization of a magnetic soliton (bion) upon parametric excitation of a one-dimensional ferromagnet
Authors: Bogdan M. M. , Kosevich A. M. , Manzhos I. V.
Published: December 2024

It is shown that under the conditions of parallel parametric pumping (a microwave field parallel to a constant field in the easy plane) a magnetic soliton in a one-dimensional easy-plane ferromagnet is stabilized in a state that is uniquely determined by the parameters of the constant and microwave fields.
2D materials for infrared sensing and hyperspectral imaging
Authors: Kandegedara R. M. E. B. , Krishnamurthy Srini , Yu Zhi-Gang , Grein Christoph , Sivananthan Sivalingam
Published: December 2024

2D materials for sensing applications offer several advantages—high absorption in thin layers, the lack of surface dangling bonds or major defects, ease of materials synthesis and device fabrication, and relaxed substrate lattice-matching requirements. We theoretically explore two 2D materials, hexagonal boron phosphide and hexagonal boron arsenide, for possible infrared sensing and hyperspectral applications. Using first principles, we calculate the total energy of formation, band structures, and absorption coefficient of monolayer and bilayer materials. We evaluate the bandgap and absorption coefficient of bilayers as a function of layer stacking, number of layers, and applied field across the layers. We find that with a choice of stacking order, number of layers, and applied field, the material can be chosen appropriately for sensing of short-, mid-, or long-wavelength infrared radiation. Furthermore, the absorption is increased in these materials with applied electric fields. With the ability to dynamically change the bandgap with an external electric field, this class of materials is ideally suited for continuous hyperspectral sensing in the infrared.
Sub-ablation-threshold light-induced modification of thin ruthenium layers detected using optical reflectance
Authors: Abram Ester , Orlov Nikolai , Garnett Erik C. , Planken Paul
Published: December 2024

In semiconductor device manufacturing, wafer materials may be exposed to intense light sources by optical metrology tools. The desired light fluence often needs to be maximized to levels just below the optical damage threshold of materials deposited on the wafer, such as ruthenium. We, therefore, investigate light-induced permanent structural changes to thin Ru films after exposure to single 400nm wavelength femtosecond pulses in the fluence regime before catastrophic damage. For fluences below that where full-ablation occurs, small optical increases in the reflectivity of up to 4% are observed in the aftermath with a weak probe beam. In this fluence regime, dark-field, scanning electron, and atomic force microscopy images reveal morphological changes such as top-level ablation, where only the top part of the ruthenium layer is ablated whereas the lower part still remains on the substrate, and nanovolcano formation. However, neither top-level ablation nor nanovolcano formation is responsible for the reflection increase. Instead, Electron Backscatter Diffraction reveals that in this low fluence regime where reflectivity increases, Ru grains melt and resolidify into larger grains, which is likely responsible for the observed reflectivity increases. This result is reminiscent of our earlier work on aluminum layers and it suggests that there may be more metals that display this behavior.
Scale analysis of surface roughness impacted by airflow
Authors: Wei P. S. , Weng C. H.
Published: December 2024

This study scales the roughness, parallel to the scanning direction, on a solid surface solidified from thermocapillary surfaces under various working conditions as well as the gas inflow introduced from above. This roughness is commonly observed in autogenous and non-autogenous welding processes, additive manufacturing, and polishing techniques, leading to reduced yield, increased fatigue and fracture strength, and heightened stress concentration in the solidified area. The roughness of the solidified surface subjected to gas inflow from above is quantitatively scaled by applying the Young–Laplace equation, accounting for surface deformation due to differences in impact pressure across the free surface and dynamic pressure in the shear layer beneath the free surface. Surface velocity is scaled by balancing viscous stress with thermocapillary force and inertial force with viscous stress in the shear layer, while also considering mass conservation during melting and solidification. Results indicate that concave depth in the central region and bulge height at the edge increase as the impact pressure difference across the free surface, Weber number, Marangoni number, and Prandtl number increase, while the Peclet number decreases. The widths of the central and edge regions, which are independent of inflow velocity from above, increase with dimensionless beam power, solid-to-liquid thermal conductivity ratio, and other factors. COMSOL Multiphysics version 6.0 is used to compute surface deformation roughness influenced by unsteady two-dimensional fluid flow and heat transfer. The predicted roughness amplitude and pitch align well with scaling analysis data.
Design and investigation of a transparent and actively tunable broadband electromagnetic wave-absorbing metamaterial
Authors: Li Ruilong , Lin Weijiong , Leng Shaoyong , Xu Zhibiao , Wang Ying , Wang Tao
Published: December 2024

With the development of electronic information technology, the demand for electromagnetic wave-absorbing materials with special characteristics such as transparency and tunability has surged. Here, a transparent and actively tunable broadband electromagnetic wave-absorbing metamaterial combined with diodes and indium tin oxide is designed and experimentally realized, achieving a transmittance of 71.9% and an effective absorption (reflection loss (RL) < −10 dB) bandwidth of 10.1 GHz (7.9–18 GHz). The RL of the sample changes from −35.95 dB to −11.53 dB at 9.69 GHz and from −11.11 dB to −42.29 dB at 15.83 GHz when the applied voltage is varied from 10 V to 20 V. In addition, the modulatory mechanisms of the absorption performance are investigated. The tunable RL is attributed to variations in the reflection, transmission and absorption of the metasurface and to the presence of multiple reflection mechanisms, which are essentially related to the electromagnetic coupling effect on the metasurface. This work lays the foundation for the preparation of wave-absorbing materials applicable to special scenarios and provides guidance for the modulation of the absorptive properties of metamaterials.
Research on micro-arc oxidation discharge spark detection technology based on MO-DETR
Authors: Li Fangqiang , Lu Hailin , Zhi Shuangshuang , Zhao Ziyue , Zhou Li , Bai Xiutao , Xu Guangshen , Chen Yongdang
Published: December 2024

During microarc oxidation (MAO), the unique characteristics of the discharge spark have a profound effect on the morphology, structure and surface properties of the oxide film. However, due to the high-pressure environment and the complexity of the spark characteristics, it is difficult to accurately observe and analyze these features by conventional detection methods. To this end, we propose a novel target detection model, MO-DETR, which combines the improved CSPDarknet53 as a backbone and a new lightweight encoder, DEEDP (DASi-enhanced feature diffusion pyramid), to systematically process and fuse multiscale features, reduce model complexity and increase processing speed. MO-DETR uses DETR’s multilayer decoder architecture to achieve real-time detection in multiple scenarios and without retraining. On our homegrown MAO dataset MO-Dataset, MO-DETR achieves an average precision of 92.1% and 135.9 FPS on 1080ti GPUs, which outperforms the Yolo series detectors overall. Compared to RT-DETR, MO-DETR achieves a 1.2% improvement in accuracy (from 90.9% to 92.1%), an 82% reduction in parameter volume (from 31 987 850 to 5 728 600), a 91.6% reduction in arithmetic requirements (from 103.4 GFLOPs to 11.8 GFLOPs), and a 71% speedup on the same task (from 39.6 FPS to 135.9 FPS). These improvements significantly increase performance and reduce hardware requirements, making it more practical for real-world applications.
A meta transfer learning fault diagnosis method for gearbox with few-shot data
Authors: Yang Zhichao , Duan Yudan , She Daoming , Pecht Michael G
Published: December 2024

The gearbox of large-scale mechanical equipment operates under complex working conditions, and its operation and maintenance are crucial to ensure safe production. This paper proposes a fault diagnosis method for gearboxes under variable operating conditions with few-shot data to address the scarcity of data for specific fault types. Firstly, several fault diagnosis tasks are constructed under variable operating conditions. These deep features of different tasks are extracted by a deep convolutional neural network. In the training process, the model adaptively adjusts its parameters and inner loop learning rate, enabling it to acquire domain invariant features. The Batch Spectral Shrinkage is presented to reduce the impact of negative transfer and catastrophic forgetting on model optimization during knowledge transfer. The loss function is reconstructed using the weight balance strategy to mitigate the distribution discrepancy between the source and target domains. Consequently, the Meta-SGD transfer neural network framework enables a fault diagnosis model for gearboxes under variable operating conditions with few-shot data. The experimental datasets of the gearbox verify the effectiveness of the proposed fault diagnosis framework.
Advances in nanomaterials for radiation protection in the aerospace industry: a systematic review
Authors: Sales Antonio Said Webbe , Pereira Vinicius de Queiros , Dias Airton Natanael Coelho
Published: December 2024

Nanomaterials stand out for their exceptional properties and innovative potential, especially in applications that protect against space radiation. They offer an innovative approach to this challenge, demonstrating notable properties of radiation absorption and scattering, as well as flexibility and lightness for the development of protective clothing and equipment. This review details the use of polymeric materials, such as polyimides (PIs), which are efficient at attenuating ultraviolet (UV) radiation and atomic oxygen. For example, PIs show a decrease in elongation at break by 10% after exposure to VUV radiation of 2000 equivalent solar hours. The thermal stability under vacuum UV (VUV) irradiation shows that colorless PIs like colorless aluminized polyimide (CPI)-T/Al exhibit an onset degradation temperature (Tonset) of 451 °C, while CPI-L/Al shows a degradation onset of 439 °C. Additionally, advancements in composite materials for gamma and neutron radiation shielding are covered. Materials such as fluorinated hyperbranched PIs display a decomposition temperature of approximately 450 °C, which ensures structural integrity during space missions involving radiation. Radiation absorption and scattering properties of these composites are assessed, with materials such as W-Bi2O3 demonstrating a high linear attenuation coefficient of 2.5 MeV, enhancing their efficiency in protecting against gamma radiation. Mechanical and optical changes, such as a 15% increase in solar absorbance after exposure to VUV, are critical for prolonged space missions. Moreover, the integration of nanoparticles like graphene and carbon nanotubes into polymers has proven to be an efficient strategy for improving the shielding properties and stability of materials. Nanocomposites like BNTT-Ti display a neutron transmission reduction of 20%, further validating their potential for space applications. Future investigations will focus on optimizing the functionality, manufacturing, and compatibility of composite materials, as well as validating their performance under actual space mission conditions. Collaboration among material scientists, aerospace engineers, and space agencies is vital to transforming laboratory discoveries into viable solutions for radiation protection in space.
Design and simulation of magnetic field sensor based on dual-core photonic crystal fiber filled ferrofluid at different ambient temperatures
Authors: Amiri Tayobeh , Kadivar Erfan , Ghajarpour-Nobandegani Sajad
Published: December 2024

Dual-core photonic crystal fiber (DC-PCF) based on ferrofluid-filled core holes is proposed to detect and measure magnetic field. The suggested magnetic field sensor contains two core holes. The two core holes of photonic crystal fiber are filled by nanoparticle ferrosoferric oxide (Fe
3
O
4) magnetic fluid. The magnetic sensor mode distribution and mode coupling under different values of magnetic field strength and ambient temperatures are studied. Finally, the transmission spectrum and magnetic field sensitivity of the DC-PCF magnetic field sensor are calculated at different ambient temperatures. Our numerical results depict that the present magnetic field sensor could detect magnetic field in the range of 89-271 (Oe), has a good FOM of 450.7 RIU
−1, and shows high sensitivity to 21.9 (μm/RIU) and 35.1 (μm/RIU) for x −  and y −  polarizations at the room temperature, respectively. It was also found that the magnetic field sensitivity decreases with increasing the ambient temperature.
Features of magnetically induced exceptional points in cholesteric liquid crystals
Authors: Gevorgyan A H , Bulanov A V , Oganesyan K B
Published: December 2024

In this work, the photonic properties of cholesteric liquid crystals (CLCs) in an external magnetic field parallel to the helix axis are investigated for the first time in the short-wavelength band of the spectrum, where exceptional points (EPs) are found. It was shown that at EP the real parts of two of four wave numbers touch each over, and their imaginary parts intersect. Here the reflection, transmission and absorption show the same values for two eigenmodes of CLC layer. At anisotropic absorption near the EP there appear points where the magnetically induced transmittance and absorption are observed. The light localization peculiarities as well as photonic density of states (PDOS) peculiarities near these points were also investigated. Near EPs, PDOS for two eigenmodes shows significant changes, especially with different magneto-optical activity parameters.
Research and Development on a 334 kJ Pulse Power Module for Electromagnetic Launch
Authors: Zhang Y Z , Gao Y , Shi Y L , Zou H B , Li Y M , Qiu X Y
Published: December 2024

As electromagnetic launch technology continues to evolve, the demands on pulse power supply are becoming increasingly stringent. Megajoule-level capacitive energy storage pulse power supply(PPS) are generally composed of several hundred-kilojoule pulse power modules (PPMs) connected in parallel, with the performance of these modules determining the capabilities of the entire PSS. PPMs need to have higher energy storage density, higher peak currents, and the ability to operate continuously to enhance compactness, launch efficiency, and launch frequency. Continuous operation requires improved cooling capabilities in the PPMs. This paper presents the design of an actively cooled pulse power module (PPM) with an energy storage capacity of 334 kJ, a rated operating voltage of 6.67 kV, and an output peak current of approximately 100 kA, achieving an energy density of 1.13 MJ/m3. The module utilizes water cooling, with designed structures for main power components and simulated cooling capabilities under continuous operation. The design discharge frequency can reach up to 10 shots per minute. Ultimately, the module underwent discharge performance tests using a simulated railgun load. The tests confirmed that this actively cooled PPM meets the design specifications, with a compact structure and reliable operation.
Fixed-Time Adaptive Neural Network Compensation Control for Electric Cylinder Erection Systems
Authors: Wang Yancheng , Ma Jiahua , Deng Wenxiang , Yu Xiaochuan
Published: December 2024

This paper proposed a fixed-time adaptive neural network compensation control (FTANN) strategy for electric cylinder erection systems with unknown system dynamics and external time-varying disturbances. This method fully leveraged the estimation capabilities of neural networks and the rapid convergence of fixed-time control. Compared to traditional adaptive fixed-time neural network control methods, the proposed controller exploited the neural network’s ability to approximate arbitrary nonlinear functions, maximizing the neural network’s potential while avoiding the high gain issues that traditional controllers might have encountered. The Lyapunov stability theory was used to prove that the closed-loop system was fixed-time stable, and simulations verified the effectiveness of the proposed method.
The Influence of Magnetic Fields on the Operational State and Velocity of Smart Projectiles
Authors: Guo Zhangxia , Chen Jiahao , Zou Libo
Published: December 2024

The electromagnetic railgun, as a novel launching technology, held great potential for development. However, due to the strong magnetic interference during the launch process, most of the electromagnetic railguns that were being researched at that time could only launch kinetic projectiles. By incorporating magnetic shielding materials within the projectile to mitigate the impact of external magnetic fields on the internal circuitry, it became feasible to launch guided missiles and range-determining projectiles. This advancement could have significantly enhanced the versatility of electromagnetic railguns. The paper established a multi-physical field coupling model between the projectile and the magnetic field using the COMSOL software. First, the shielding efficiency of the shielding body inside the projectile as it passed through a uniform magnetic field was calculated. At the same time, when the projectile moved in the magnetic field, it was subjected to an action force exerted by the magnetic field. The paper studied the force relationship between the projectile and the magnetic field and the deceleration of the projectile, and found that the magnetic field had a role of accelerating the projectile first and then decelerating it. The acceleration stage was much smaller than the deceleration stage. The projectile also generated eddy currents in the magnetic field, causing the temperature of the projectile to rise. The experimental results obtained were basically consistent with the numerical calculation results. Under the shielding effect, the internal circuits of the projectile were greatly reduced by the interference of the magnetic field, and the speed and temperature of the projectile remained within a reasonable range. This also provided certain reference for the design of electromagnetic coil gun muzzle velocity measurement devices and proximity fuse signal transmission devices.
Sensitivity analysis of key parameters of tank stabilization system actuators for muzzle stabilization accuracy
Authors: Lin Darui , Yang Guolai , Yuan Shusen , Wang Yimin
Published: December 2024

This paper proposes a novel global sensitivity analysis method that combines deep neural networks with saltelli estimation, significantly enhancing the efficiency and reliability of sensitivity analysis in complex mechanical systems. Given that sensitivity analysis often requires a large amount of sample data, and the high-precision multi-body dynamics simulation model of tanks inevitably leads to increased computational costs. To address this, based on electromechanical integrated dynamics model of tank stabilization system, a deep neural network surrogate model for muzzle stability accuracy was established. Subsequently, further integrating saltelli estimation, a global sensitivity analysis targeting muzzle stabilization accuracy was conducted by selecting 18 key parameters of the actuator electric cylinder as the object. Finally, a key parameter system of the actuator electric cylinder influencing muzzle stabilization accuracy was established, providing theoretical support for the design optimization of the next generation tank stabilization system.
Clamping and buffering mechanism for large-caliber rocket projectiles based on bistable shells
Authors: Li Zhuangzhuang , Li Xuelin , Guo Zhuoyu , Zhou Yue , Lin JiaHui , Han Shuo , Mo Zonglai , Li Jun
Published: December 2024

Long-range large-caliber rocket projectiles are prone to impact with the rail on the launch box due to overload during transportation. In order to hold the rocket tightly during transportation and quickly separate it during launch, this paper proposes a novel clamping mechanism based on the bistable shells, which can not only provide transportation protection for the rocket projectile but also quickly detach from the rocket projectile. Through numerical study, the force-displacement curve of a single clamping mechanism under instantaneous compression load and the opening process under pneumatic load were analyzed. Based on this, a finite element model simulating the overload during transportation was established to compare the effects with and without the clamping mechanism. The results show that the designed clamping mechanism meets the design expectations, providing excellent protection for the rocket projectile, and allowing for quick opening. This mechanism also has broad application prospects in other fields such as packaging Engineering and soft clamping mechanisms.
Analysis of interval uncertainty response for the ramming coordination mechanism of artillery automatic loading system
Authors: Luo Guiyuan , Chen Guangsong , Li Ang
Published: December 2024

The ramming coordination mechanism is a critical component of the artillery automatic loading system. Its primary function is to receive projectiles from the manipulator and align them parallel to the bore axis, facilitating subsequent chambering of the projectiles. The reliability of the ramming coordination mechanism directly influences the subsequent precision of chambering. Therefore, analysing the boundary response of this mechanism is crucial for subsequent reliability assessments. In response to the issue of interval uncertainty response for the ramming coordination mechanism, this paper proposes a method that combines sequential simulation strategy with rigid-flexible coupled dynamic analysis. First, a ramming coordination mechanism rigid-flexible coupled controlled dynamic model considering clearances is constructed based on its motion principle. Subsequently, the sequential method is employed to solve the boundary response, resulting in the boundary response curve of angular displacement for the ramming coordination mechanism. The results indicate that the method combining sequential simulation with rigid-flexible coupled dynamic analysis can more efficiently solve the boundary response of the mechanism. Moreover, the uncertainty factors present during the initial coordination and velocity mutation moments significantly impact the motion precision of the mechanism, potentially leading to motion failure in severe cases. This provides a reference for the subsequent reliability analysis of the mechanism.
Test on the linear induction launcher with energy storage capacitor and propulsion winding integrated construction
Authors: Wang H Sh , Wang J Ch , Ma B D , Zheng Ch , Bai J , Wen N J , Chen X R , Xue J D , Jin P Y
Published: December 2024

Different from traditional EM coil launcher, a new type of primary construction was brought forward in this paper. The energy storage capacitor and primary winding were integrated into one component. The relevant basic equations of mathematical physics were deduced, the finite element simulation was carried out, and the experimental principle prototype was set up for experimental verification, which proves that the new structure is expected to enable the development of more compact and more efficiency EM coil launcher.
Research on present situation and development of fire strike equipment for mountain operations
Authors: Li Yuxi , Feng Zhanbo , Li Zhengyu , Song Zhenhua
Published: December 2024

Mountainous areas account for a large proportion in China’s border regions. In view of the special terrain and complex meteorological conditions of mountain warfare, mountain firepower strike equipment has become the core key for our military to deal with border conflicts. In order to adapt to the changes in future mountain warfare and lead its development, this paper summarizes and analyzes the performance characteristics and development history of mountain warfare equipment at home and abroad. Combined with the influence of future mountain warfare forms and battlefield environments, characteristics of active equipment and the application of high and new technologies on mountain warfare, the future development goals of mountain firepower strike equipment are prospected, and the technical research directions of mountain firepower strike equipment are proposed in stages according to the strike equipment system structure.
Research on automatic shotgun recoil reduction method and recoil force test
Authors: Zhang Zhenhui , Zhang Huihui , Wang Yong
Published: December 2024

Aiming at the requirement of a 30% reduction in the recoil of the automatic shotgun, the researchers investigated the various thicknesses of the stock rubber, the different hardness of the stock rubber, and the floating buffer mechanism of the gun body. Researchers also conducted the recoil test and comparison to determine the structural scheme for recoil reduction. The test results indicate that the recoil force of the automatic shotgun is reduced by 51.9% compared with that of a fixed shotgun when using NBR (nitrile rubber buna) with a thickness of 20 mm and a hardness of 20 Shore hardness. The technical measures adopted are effective and can meet the requirements of the specified technical indicators.
Research on Motion Coupling Interior Ballistics of Cased Telescoped Ammunition Artillery
Authors: Shi Junfei , Xu Kai , Xie Yao , Liu Aifeng
Published: December 2024

In this paper, the motion-coupled interior Ballistics of cased telescoped ammunition artillery is studied, and the physical process of the real interior ballistic process is analysed, on the basis of which, the gunpowder-gas energy conversion law at different stages and the combustion characteristics of the combustible guide cylinder are analysed, and the charge form function of the combustible guide cylinder material is established. Based on the classical interior ballistics theory, the motion-coupled interior ballistic theoretical model of cased telescoped ammunition artillery is established, taking into account the matching characteristics of the actual projectile and artillery movement. Combined with the energy conversion characteristics of the three phases, the set of internal ballistic control equations of cased telescoped ammunition artillery is numerically solved by the thermodynamic coupling and the fourth-order Lungkuta method, and the correctness of the theoretical model of the interior ballistics theory is verified by the firing test, and the results of the study can provide theoretical guidance for the related research and engineering application of the launching and controlling of cased telescoped ammunition artillery.
Research on flight intention recognition of UAVs-swarm
Authors: Zhang Genyuan , Qi Wanlong , Yu Xueyuan , Zhang Zhipeng , Lin Zhiwei
Published: December 2024

Most existing threat level assessments for aerial targets rely on numerical analysis and typically address only single or a few incoming targets without incorporating intention recognition. Such methods are inadequate for anti-UAV(Unmanned aerial vehicle) tasks involving large numbers of flight targets. To accurately and efficiently identify the flight intentions of UAVs-swarm, this paper proposes a method based on formation recognition and trajectory prediction. Initially, the trajectories of UAVs are obtained and clustered using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm. For each cluster, a Bayesian classifier is employed to recognize its flight formation. Subsequently, a minimum enclosing sphere is established for each cluster, and trajectory fusion and prediction are conducted based on the sphere’s center. Finally, a flight intention recognition model is constructed. The results demonstrate that this method effectively infers the flight intentions of each UAVs-cluster, providing a robust basis for the threat level assessment in anti-UAVs-swarm tasks.
Embedded deep learning video stabilization based on multiprocessing
Authors: Wang Fangyi , Zhong Bihua , Liu Tao , Lin Jiajun , Bai Hongyang , Wan Gang
Published: December 2024

With the gradual development of modern war in the direction of informationization and intelligentization, image guidance has established a prominent position in precision guidance technology with its high guidance accuracy, strong anti-jamming ability and precise hit probability, so the image seeker has become the focus of competitive development. However, missile jitter during flight, influenced by external disturbances and projectile rigidity, seriously affects the video quality captured by the camera in the image seeker, thereby reducing the detection accuracy of target recognition and tracking. In addition, the computational resources of the missile-mounted embedded platform are limited, and algorithms based on deep learning compute slowly. To address these issues, we have proposed a lightweight video stabilization framework and harnessed the potential of multi-core embedded devices through multiprocessing to achieve higher operating speeds. We tested our algorithm on an NVIDIA Jetson Orin Nano device and achieved a speed improvement of nearly 30% compared to an algorithm for serial computation.
Adaptive robust control of tank gun pitching stabilization system considering uncertainty
Authors: Zhou Ruohan , Yao Jianyong , Deng Wenxiang , Yuan Shusen
Published: December 2024

Aiming at the complex nonlinearity, uncertainty and coupling of the tank gun pitching stabilization system, an adaptive robust control strategy for the tank gun pitching stabilization system is proposed by combining adaptive control and deterministic robust control. Considering that the tank gun pitching stabilization system is a kind of uncertainty as well as nonlinear coupled dynamics system, a mechanical dynamics model and an electrical control model under the high mobility environment are established. Based on the backstepping concept fusion adaptive robust idea, the parameter adaptive law is constructed to eliminate the effect of unknown system parameter, and the adaptive robust function is designed to inhibit the interference for unmodeled disturbance of the system control precision. The designed controller synthesizes the advantages of adaptive control methods as well as robust control methods to improve the practical value in engineering. Based on Lyapunov theory, the analysis indicates that the tank gun pitching stabilization system can be controlled asymptotically only by unknown parameter effects, and the ideal stabilization accuracy of the system can be ensured when both parameter uncertainty and uncertain nonlinearity exist in the system. A large number of comparative co-simulations based on Recurdyn-Simulink demonstrate the superiority of the presented technique in this study.
A-star Ant Colony Fusion Optimisation for Unmanned Ground Vehicle Route Planning
Authors: Hou Rong , Zhang Pengfei
Published: December 2024

Route planning technology of Unmanned Ground Vehicle (UGV) is a key issue in robotics, with the goal of avoiding obstacles and moving quickly to the target point. Aiming at the problem of easy collision with obstacles when utilizing the conventional A-star algorithm for global route planning, an improved turning mechanism is proposed to avoid collision. Aiming at the problems of longer routes and insufficiently smooth routes introduced by it, an improved A-star ant colony fusion algorithm for UGV route planning is proposed by combining the local planning capability of the ant colony algorithm. The A-star algorithm with an improved turning mechanism is fused with an ant colony algorithm to iteratively optimize the route length and route smoothness progressively. Simulation results show that the improved A-star ant colony fusion algorithm is able to avoid obstacles, reduce the length of the planned route by at least 2.34%, and improve the route smoothness by at least 5.62% compared to the A-star algorithm. It is beneficial for UGV to accomplish the corresponding tasks quickly on the basis of ensuring its obstacle avoidance.
Research on the game confrontation technology of UAV cluster
Authors: Zhuo Cao , Jian Shen , Qichen Yan , Ziwang Zhang , Fan Liu , Binna He
Published: December 2024

A reinforcement learning model is proposed for the problem of UAV cluster autonomy in air combat environment. A theoretical motion model was established for the quadcopter unmanned aerial vehicle to describe its motion states, and a framework for adversarial algorithms based on reinforcement learning was proposed. A series of simulation experiments are carried out to verify the influence of quadcopter UAV parameters change on the cluster game performance of both quadcopter UAV by constantly adjusting the parameter setting of quadcopter UAV.
Research on Adaptive Kalman Filtering Adjustment Based on Support Vector Regression and Bayesian Optimization
Authors: Zhang Chen , Guan Xueyuan , Cai Xiu , Wang Yanyi
Published: December 2024

This study addresses the performance optimization of Kalman filters in combined navigation systems, particularly the dynamic adjustment of the measurement noise covariance matrix R. An innovative adaptive method that incorporates Support Vector Regression (SVR) and Bayesian optimization techniques is proposed to achieve real-time optimization of the R value. This study initially utilizes the Support Vector Regression model, with innovation data as input, to predict the most suitable R values. Subsequently, the Bayesian optimization algorithm is applied to optimize the key parameters of the SVR model, thus enhancing the accuracy and response speed of the predictions. Comparative experiments with traditional methods demonstrate that the proposed adaptive adjustment method significantly improves the filtering accuracy and stability of the combined navigation system, especially under dynamically changing environmental conditions. This research not only provides a new approach to parameter optimization for Kalman filters but also offers an effective solution for similar real-time system dynamic adjustment issues.
A Research on Recommendation Method of Kill Chain Based on Graph Theory Algorithm
Authors: Wang Di , Wu Kun , Li Jun , Guo Zhiming , Sun Yong , Bai Zilong , Song Yixuan
Published: December 2024

The present study introduces an optimization method based on graph theory to address the kill chain recommendation problem in rapidly changing modern battlefield environments. This method transforms the kill chain selection problem into a shortest path problem with time constraints and designs an efficient optimization process using branch-and-bound algorithm. This study constructs an evaluation model for kill chain efficacy and time utility to ensure that the recommended kill chain achieves optimal efficacy within the target’s active strike time. The efficacy and efficiency of the proposed algorithm in handling multi-target scenarios have been substantiated through the analysis of data procured from the “2020 Joint Operations Smart Game Challenge”, reducing the optimization time when compared to traditional methods. This study provides a new perspective and technical assistance to enhance the intelligence and automation of operational command decision-making processes.
Path optimization of unmanned vehicle based on ant colony algorithm
Authors: Qi Li , Haotian Zheng , Jian Wang , Xincheng Zhang , Zezhong Chong
Published: December 2024

In this paper, we use the ant colony algorithm(ACO) and the river formation dynamics(RFD) algorithm to solve the path optimisation problem of unmanned vehicle in grid models. The traditional ACO algorithm only considers the relationship between the current point and the next point in the probability selection, but the optimised ACO algorithm takes the relative relationship between the next point and the target point into account, which effectively avoids local stagnation and improves the search speed. Aiming at the problems of mutual interference of paths and slow reinforcement of new paths that may occur in the routing process of ACO algorithm, we introduced the river formation dynamics algorithm. The RFD algorithm achieves gradient-directed optimisation of ACO algorithm by adding height attributes to the nodes in the graph and deciding the selection probability according to the gradient between two points. Experimental results show that the hybrid algorithm combining the ACO and RFD algorithms exhibits stronger optimisation finding ability in path optimisation problems. We applied the ACO, RFD algorithm, and the hybrid algorithm to these complex path optimisation problems and achieved significant results.
Aerodynamic Angle Estimation in Rotating Projectiles: A NBCA Fusion Approach
Authors: Huai-Wei A , Fu Jian , Wang Liang-Ming
Published: December 2024

The angle of attack (AOA) is a crucial parameter for describing the flight state of a projectile and is one of the key elements in external ballistic testing. In light of the inherent difficulty and substantial cost associated with the direct detection of the AOA during the flight of guided projectiles, this study introduces an estimation method for the AOA that is predicated on a neuro-behavioural cognitive architecture (NBCA) neural network fusion model. This approach leverages data from geomagnetic sensors to calculate the geomagnetic azimuth angle related to the AOA. Subsequently, by fitting the geomagnetic azimuth angle and angle of attack-related quantities into the fusion model and training the neural network, the angle of attack is estimated. Research results indicate that the root mean square error of the angle of attack estimation is 0.0149°. This method achieves optimal estimation of the projectile’s angle of attack without the need for extensive detection equipment, providing a novel perspective for the practical engineering application of projectile angle of attack detection.
Design of a Software-Defined Artillery System Architecture
Authors: Hao Bai , Tegang Lu , Zhengzheng Yang , Sheng Zhao , Wufan Sun
Published: December 2024

The rapid development of software-defined technology aligns closely with future trends in artillery system architectures. This paper analyzes these trends and the technical requirements for future artillery development, proposing a software-defined artillery system architecture to meet the need for flexibility and rapid advancement. The proposed architecture features a layered design, standardized interfaces, generalized hardware, software-defined functions, and resource virtualization. By employing a service-oriented software architecture, this system facilitates dynamic adjustment and expansion of artillery functions, thereby shortening the equipment development cycle and improving system flexibility and scalability. Consequently, this architecture can significantly enhance the operational effectiveness and adaptability of artillery systems in complex battlefield environments.
Research on the Power Line Carrier Communication Network System for Vehicle-mounted Weapons
Authors: Chi Zhang , Shaohui Xue , Yongliang Yang , Xiangang Sun , Fengge Wang
Published: December 2024

Power line carrier communication is a unique communication method in the power system, which utilizes existing power lines to transmit analog or digital signals at high speed through carrier communication. Power line communication is widely used due to its advantages of low investment, no need for rewiring, wide application range, and low maintenance cost. This article combines the extensive user needs of power line communication in various application fields, and designs a power line carrier communication network system with wide universality, strong scalability, fast communication speed, and high security. It has a strong supporting role in promoting the intelligent information perception of vehicle mounted weapons, advanced firepower control of manned/unmanned equipment, intelligent human-machine interaction, multi platform collaboration, and group intelligent collaborative air defense combat.
CBISP-AIS: Component-Based Intelligent Software Platform for Artillery Integrated Systems
Authors: Qi Zhiqiang , Zhang Cheng , Wang Binyi , Liao Rui , Yao Tong
Published: December 2024

Due to the variety of hardware types in integrated artillery systems, the information processing software faces challenges such as redundant low-level development, poor inheritance between systems, and difficulties in reusing software modules during iterative hardware and software upgrades. This paper presents the construction of a component-based intelligent software platform for integrated artillery systems (CBISP-AIS). CBISP-AIS modularizes and generalizes the integrated artillery information system, breaking down its development into corresponding functional components. CBISP-AIS enables an integrated design process encompassing simulation, design, coding, and verification of system application functions, facilitating faster function implementation and module deployment. Finally, CBISP-AIS is applied to weapon system development, with its effectiveness and reusability validated through case studies.
Gun Position Servo System Auto Tuning Control Based on Correlation Identification Method
Authors: Li Changhong , Han Chongwei , Zhu Chao
Published: December 2024

Position servo systems are used in kinds of gun weapons widely. It plays an important role for aiming to ground target or tracking to moving target. In this paper, a gun position servo system auto tuning control based on correlation identification method is presented. The M-sequence generator is constructed which is as a stimulus signal of the plant. Through signals acquisition of input and output of the plant speed loop, the cross-correlation function of the speed loop input and output can be calculated. Then the impulse response function of the position servo system plant speed loop can be identified. According to the identification results, position controller parameters are tuned based on the given width mid-frequency interval of the open loop position servo system. Last, simulations are carried out to a gun position servo system. The simulation results show that the identified impulse response function has high accuracy. Through the parameters tuning, the stable margin can be maintained which is determined by the width of mid-frequency interval for different speed loop time constant.
LSTM-GA-SVR based launch time window prediction algorithm
Authors: Zhang Quan , Zhao Zi-jie , Xu Li-wen
Published: December 2024

The strike-type unmanned underwater vehicle (UUV) is susceptible to external factors such as ocean currents during attack missions, resulting in unavoidable non-linear attitude fluctuations that have an adverse impact on the weapon hit rate of the UUV. To meet the requisite accuracy for target hits of strike-type UUVs in the presence of attitude fluctuations, this paper proposes an LSTM-GA-SVR launch time window prediction algorithm for short-term attitude prediction of UUVs. This algorithm combines a Long Short-Term Memory (LSTM) neural network, a Genetic Algorithm (GA) and Support Vector Regression (SVR) to address the non-linear motion characteristics of the UUV and enhance the generalization ability of the prediction. The Genetic Algorithm (GA) is employed to optimize the Support Vector Regression (SVR) model parameters, thereby enhancing the accuracy of the fitted data. The LSTM prediction model is introduced to capture long-term dependencies in the data and extract complex features, thus further optimizing short-term attitude prediction. The loss function is optimized using the least squares method, thereby achieving optimal weighting of the model, and improving prediction accuracy. The efficacy of the algorithm is then corroborated through simulation and experimentation. The results demonstrate that, under specific circumstances, the algorithm can achieve the predetermined target of deep displacement error <0.1m and yaw angle error <0.05rad. The model prediction time window reaches 88% of the actual window, thereby providing a relatively accurate launch time window based on measured data.
Path Planning for Unmanned Systems Based on Integrated Sampling Strategies and Improved PSO
Authors: Gao Wenjie , Wang Qiang , Hu Shengrong
Published: December 2024

B-splines and Particle Swarm Optimization algorithms are integrated for unmanned system path planning in mountainous terrains. In the early stages of the optimization search, the traditional Particle Swarm Optimization (PSO) algorithm achieves rapid convergence. However, as the process continues, it often struggles with local optima in later stages. To address this limitation, this research proposes an improved PSO algorithm that combines the Immune Algorithm (IMA) and Latin Hypercube Sampling Method. This enhancement bolsters the optimization capabilities of particles at different phases of the search by implementing an evaluation mechanism and dynamic weight adjustments. Experimental results demonstrate that, when confronting optimization challenges within complex mountainous terrains, the improved PSO algorithm (SIPSO) which is combined with IMA and Sampling Method significantly outperforms conventional PSO and Genetic Algorithm (GA) in both iteration counts and computational efficiency, showcasing a notable advancement in performance.
Research on safety technology of intelligent aviation ammunition system
Authors: Yongzhi Shan , Xianglei Meng , Long Zhang , Bangqi He , Liangchen Xu , Li-Feng Hu
Published: December 2024

With the continuous development of military technology, intelligent aviation ammunition has become an important part of modern military operations. However, the safety of intelligent aviation munitions systems has always been a matter of concern. This study aims to explore the safety technology of intelligent aviation ammunition systems to ensure their reliability and stability in combat. First, this study reviews the current development status and application fields of intelligent aviation ammunition systems. Subsequently, it focused on analyzing the security threats and risks that intelligent aviation ammunition systems may face, including perception security, planning security, communication security, and evaluation and testing security. In response to these security challenges, a series of technologies and strategies have been proposed, and comprehensive security measures have been adopted to effectively reduce the security risks of intelligent aviation ammunition systems and improve their credibility and availability in actual combat. This research provides theoretical support and practical guidance for the safety technology of intelligent aviation ammunition systems, and provides a reference for its future development and application.