Journal of Military Science and Technology

Analysis of deformation of thin-walled steel tubes under clamping force during threaded joint assembly and disassembly using the finite element method

2025-12-27T05:45:58+00:00

Threaded joints on thin-walled steel tubes are widely used in industrial applications, where repeated assembly and disassembly may lead to local deformation and strength degradation. This study employs the Finite Element Method (FEM) to analyze the stress–strain behavior of a thin-walled steel tube under combined clamping and torsional loads. Nonlinear contact with friction and material plasticity were considered to simulate realistic boundary conditions. The results indicate that stress concentration occurs mainly at the thread root and clamp–tube contact region. Plastic deformation begins when the clamping force exceeds 2 kN. Based on numerical results, a safe clamping limit and design recommendations are proposed to prevent yielding and ensure structural reliability.

Research on the stress and strain state of gun barrel during rapid firing

2025-12-27T05:44:34+00:00

This study investigates the stress–strain behavior of a gun barrel under rapid firing conditions using the finite element method implemented in ANSYS Workbench. The numerical model considers the coupled effects of internal pressure and transient thermal loading to simulate the thermo-mechanical response of the barrel during continuous firing. The results, presented through stress–strain curves, contour plots, and time-dependent visualizations, reveal the evolution of stress concentration, plastic deformation, and material degradation in the barrel structure. The analysis demonstrates that repeated thermal and pressure cycles significantly affect the strength, fatigue resistance, and service life of the barrel. The findings provide a scientific foundation and computational reference for design optimization, material selection, manufacturing processes, and strength verification of modern artillery barrels, contributing to enhanced reliability and durability in high-rate firing applications.

Dynamic stability analysis of a soft viscoelastic dielectric elastomer

2025-12-27T05:43:26+00:00

Dielectric elastomers (DEs) exhibit pronounced electromechanical deformation under high-voltage excitation, a response actuation by their intrinsic hyperelastic properties. When exposed to alternating electric fields, DEs exhibit complex nonlinear vibrational dynamics, demonstrating their potential for dynamic electromechanical actuation and soft robotics applications. As is well known, the dynamic characteristics of vibrational systems, including dielectric elastomer systems, exhibit significant frequency-dependent behavior. In this study, an effective generalized rheological model is employed to characterize the electromechanical response behavior of dielectric elastomers. The dynamic stability evolution process is systematically investigated under alternating excitation voltages with varying frequencies. Based on current applications of dielectric elastomers, this study contributes an effective modeling approach for analyzing the dynamic behavior of DEs, providing valuable guidance for the design and practical implementation of dielectric elastomer-based soft actuators and robotic systems.

Social-DeepWriter: An iterative retrieval-augmented framework for strategic social media content generation

2025-12-27T05:46:32+00:00

Social media has become a critical domain for strategic communication, influencing public perception and supporting both civil and military operations. In high-tempo information environments, traditional manual content creation is often too slow and resource-intensive to meet the demands of real-time engagement. While large language models (LLMs) such as GPT-4 offer the capability to generate human-like text at scale, their reliance on static training data limits their contextual relevance, factual accuracy, and responsiveness to evolving mission needs. To overcome these limitations, this paper introduces Social-DeepWriter, an AI-enabled framework for the automatic generation of mission-aligned social media content. Built upon the Deep Research paradigm, Social-DeepWriter enhances traditional Retrieval-Augmented Generation (RAG) by incorporating iterative query refinement, multi-hop retrieval, and content evaluation, mirroring the layered reasoning of human analysts. We evaluate how factors such as retrieval quality, prompt design, and generation constraints influence the informativeness, coherence, and strategic fit of generated posts. Our findings highlight the potential of Social-DeepWriter to support dual-use communication scenarios, including military public affairs, psychological operations, and rapid-response campaigns, where accuracy, adaptability, and scalability are essential.

On a solution for converting radio-controlled drones into fiber-optic-controlled drones: News & Views

2025-12-27T05:42:34+00:00

The paper presents a solution for converting the system of control channels, data channels, and status channels from the commonly used radio transmission channels in current drones to optical fiber transmission channels. Drones controlled via fiber-optic cables offer significant advantages, such as immunity to electronic warfare countermeasures from the adversary, the ability to transmit high-definition reconnaissance images with large bandwidth, real-time operation, low latency, and strong information security. Additionally, fiber-optic technology effectively supports the processing of control algorithms and complex recognition tasks due to its ability to transmit large amounts of data and provide high-speed processing back to the central control station.

Formaldehyde removal via peroxymonosulfate activated by transition metal-doped bagasse biochar

2025-12-27T05:45:08+00:00

This study introduces a process for formaldehyde (HCHO) treatment using peroxymonosulfate (PMS) activated by copper and cobalt metal-impregnated biochar derived from sugarcane bagasse. The bagasse was subjected to alkali pre-treatment before metal impregnation and subsequent pyrolysis at 700 °C to produce the Co-Cu/Biochar material. Modern analytical methods, including SEM, EDS, XRD, and nitrogen adsorption-desorption isotherms, were employed for structural characterization. The results showed that the Co-Cu/Biochar possesses a high specific surface area (SSA=419 m²/g), making it suitable for PMS activation to eliminate HCHO. The influence of material dosage, PMS concentration, and solution pH was investigated. The findings demonstrated that HCHO was completely removed after 5 minutes of reaction at an initial concentration of 20 mg/L.

Optimization of cooling slope casting parameters and reheating process for semi-solid ADC12 aluminum alloy feedstock

2025-12-27T05:42:00+00:00

This study investigates the optimization of cooling slope (CS) casting parameters and reheating conditions for semi-solid ADC12 aluminum alloy feedstock to achieve refined microstructures and improved formability. ADC12, a hypoeutectic Al–Si–Cu alloy widely used in automotive applications, was cast using a water-cooled SS400 steel CS at angles of 30°, 45°, and 60°, with pouring temperatures of 585 °C, 595 °C, 605 °C, and 615 °C. The as-cast billets were reheated at 580 °C for holding times between 40 and 80 min to promote spheroidization of primary α-Al grains. Microstructural characterization was conducted using optical microscopy, and grain size and sphericity were quantified via ImageJ and statistically analyzed using the Weibull distribution in OriginPro. Results showed that a slope angle of 45° with a pouring temperature of 595 °C, followed by reheating at 580 °C for 80 min, produced fine, highly spherical α-Al grains with uniform distribution and minimal porosity. Compared with other tested conditions, this combination demonstrated superior microstructural stability, which is expected to enhance rheological behavior and mechanical integrity during subsequent semi-solid forming. The optimized parameters have direct applicability in producing high-quality ADC12 components for the automotive industry, reducing defects, and improving dimensional precision.

Research on mixing and testing VG 22 hydraulic oil for use in military technical vehicles

2025-12-27T05:44:52+00:00

The paper presents the results of research on the formulation and performance evaluation of VKX.AU hydraulic oil with a viscosity grade of VG 22, developed based on an improved formulation aimed at enhancing transmission efficiency and equipment reliability under specific military operating conditions. The product was blended from high-quality refined base oils combined with a specialized additive package, including a pour point depressant, antioxidant, anti-wear agent, and rust inhibitor, ensuring physicochemical stability and long-term durability. Test results show that the formulated VKX.AU hydraulic oil meets the quality standards equivalent to the imported product specified in TU 38.1011232–89, with several superior properties such as enhanced anti-wear, anti-rust, and demulsifying performance. In addition, the blended oil demonstrated good compatibility with sealing materials used in the hydraulic system of the 105 mm artillery.

The study and analysis of chemical main materials in Li-ion polymer batteries for UAV

2025-12-27T05:47:06+00:00

For modern UAVs, the power source is usually a Li-ion polymer battery. Using modern physicochemical analysis methods such as scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), differential thermogravimetry (TGA), specific surface area (BET) and infrared spectroscopy (FT-IR), we determined the chemical composition of some of the main materials in Li-ion polymer batteries used for drones. We used the method of determining the corresponding size, voltage, and internal resistance to determine some of the main technical indicators of this type of battery. The analysis results show that the Li-ion polymer battery used for UAV has a cubic shape, dimensions of 281×72×5.2 mm (LxWxH), voltage of 3.78 V, internal resistance of 0.456 mΩ, positive electrode material is LiNi_0.6Co_0.2Mn_0.2O₂ coated on Al foil, negative electrode material is graphite coated on Cu foil, separator is polyethylene, binder is polyvinylidene fluoride (PVDF), positive electrode side leaf is Al, negative electrode side leaf is Cu. The analysis results also show that both negative and positive electrodes are made of fine, micrometer-sized, uniform powdered materials.

Synthesis and characterization of selenium nanoparticles stabilized by pumpkin polysaccharide

2025-12-27T05:42:16+00:00

This study presents a green synthesis of selenium nanoparticles from Na₂SeO₃ using ascorbic acid as the reducing agent in the presence of pumpkin polysaccharide (PP). PP was employed as a stabilizing and dispersing agent for selenium nanoparticles (SeNPs), which has not been reported in previous studies. The obtained material was characterized using UV-Vis spectrophotometry, XRD, FTIR, SEM, TEM, EDX, and zeta potential analyses. FTIR profiles revealed that PP capped the SeNPs surface through hydrogen bonding and electrostatic interactions involving hydroxyl and carboxylate groups. Microscopic observations further showed that PP markedly improved the particle morphology of PP-SeNPs, producing nanoparticles with enhanced dispersion, reduced aggregation and a dominant size range of 70 - 120 nm, compared with 75 - 160 nm for uncapped SeNPs. The enhanced colloidal stability was supported by a significantly more negative zeta potential (-22.9 mV versus -8.7 mV for pure SeNPs). Acute toxicity testing demonstrated that PP-SeNPs exhibited low toxicity, with an LD₅₀ value of 945.83 mg/kg. These results suggest that PP offers a promising platform for SeNPs and may support their future biomedical applications.

Composting process of Dipterocarpus alatus and kitchen waste (vegetables and fruits) at isolated military units

2025-12-27T05:44:16+00:00

Dipterocarpus alatus is widely planted in military units due to its strong adaptability to various soil types, high drought tolerance, and deep root system, which enhances stability and minimizes wind damage, thereby ensuring the safety of military infrastructures. At present, the fallen leaves of this species are mostly collected and burned, causing environmental pollution because they contain 50 - 70% essential oils and 30 - 40% resin, which release toxic compounds during combustion. This study aimed to develop and evaluate a composting process utilizing Dipterocarpus leaves combined with kitchen waste. The composting mixture consisted of 60% dried D. alatus leaves, 15% rice husk, and 25% kitchen waste (vegetables, tubers, and fruits) by weight. The application of the Bima bio-agent effectively accelerated the decomposition process. The resulting compost product met the Vietnamese industry standard 10TCN 526:2002 for microbial organic fertilizer derived from household waste, with the following characteristics: 97.1% of particles passing through a 5 mm sieve, moisture content of 32.26%, pH of 7.58, total organic matter content of 34.16%, total nitrogen content of 2.61%, and absence of Salmonella spp.

Evaluation of parameters affecting recombinant PETase and MHETase activity in PET degradation

2025-12-27T05:41:43+00:00

PETase and MHETase are two enzymes catalyzing the degradation of polyethylene terephthalate (PET) into terephthalic acid (TPA) and ethylene glycol (EG), which are environmentally friendly and non-toxic. The application of these enzymes holds significant potential for treating plastic waste and advancing green technologies in environmental protection. In this study, several factors affecting enzyme activity, including buffer composition, temperature, and pH, were investigated. The optimal conditions for PETase and MHETase activity were identified as a temperature range of 30–40 °C, pH 8–9, and 100 mM sodium phosphate buffer. Under these conditions, the recombinant enzymes hydrolyzed commercial PET film within 7 days of treatment, resulting in a significant change in the PET surface morphology and thereby demonstrating the effectiveness of PETase and MHETase in PET film cleavage. These results highlight the potential of two recombinant enzymes for plastic waste treatment.

Enhanced VOCs gas mixture recognition with sensor array and SSA-BP neural network

2025-12-27T05:45:41+00:00

Accurate identification of VOCs in mixtures is essential for monitoring toxic and explosive gases, serving industrial, environmental, as well as military and defense applications. In this study, a Salp Swarm Algorithm-Back Propagation (SSA-BP) neural network was proposed in combination with a MEMS-based nano-SnO₂ sensor array to enhance mixed-gas detection. The nano SnO2 sensors offer high sensitivity, while the SSA-BP neural network optimizes data processing based on noise filtering, feature extraction, and a robust nonlinear learning model, thus improving recognition accuracy, thereby improving recognition accuracy. This combination achieved excellent classification results for mixed gases, with a classification accuracy of up to 99% for various indoor toxic gas mixtures, including acetone, ethanol, and methanol. Additionally, it attained an R-squared score of 0.95 for accurately predicting gas concentrations. Based on the experimental results, we also propose reducing the number of sensors required while maintaining system performance. This integration shows great potential for real-time gas monitoring, as well as for portable VOCs detection systems and safety applications.

Research on high-precision processing techniques of Nd-phosphate glass laser rods

2025-12-27T05:42:51+00:00

This research presents techniques for fabricating cylindrical laser rods from raw glass using specialized glass cutting, grinding, and polishing machines. A square-cross-section glass rod, cut from a raw glass, is first transformed into an octagonal cross-section by grinding off its four corners. The octagonal rod is then processed into a circular cross-section using a precision cylindrical glass grinder. To polish the end faces of the glass rods, a dedicated holder was designed to securely hold the rods during processing. The fabricated laser rods were then inspected using specialized optical measurement instruments to ensure the highest machining accuracy. The inspection results show that the proposed fabrication method can produce laser rods with a perpendicularity deviation to the cylindrical axis of up to 3 arcminutes, an end-face parallelism deviation of 7.5 arcseconds, and a surface figure error as low as 0.042λ. These parameters are 3–4 times smaller than the standard quality requirements for laser rods, demonstrating that this method can achieve superior quality suitable for high-precision or specialized laser applications.

Synthesis of MIL-88(Fe) and NH₂-MIL-88(Fe) using PEG under ambient pressure for methylene blue adsorption

2025-12-27T05:47:23+00:00

The MIL-88(Fe) and NH₂-MIL-88(Fe) materials were successfully synthesized using a solvothermal method using polyethylene glycol (PEG) as the solvent at ambient pressure conditions. The synthesized materials were characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), and Brunauer-Emmett-Teller (BET) techniques. The materials exhibited a needle-like crystal morphology with lengths ranging from 0.5 μm to 2 μm and widths from 0.3 μm to 0.5 μm. XRD patterns of both materials revealed similar diffraction peaks, with major peaks at 9° and 10°, and additional peaks at 16°, 18°, and 20°. The BET-specific surface areas were determined to be 257 m²/g for MIL-88(Fe) and 105 m²/g for NH₂-MIL-88(Fe). Both materials demonstrated the ability to remove over 70% of a 10 ppm methylene blue (MB) solution after 120 minutes of adsorption.

Splitting nucleation and growth potentials for controlling electrochemical deposition of Cu nanoparticles

2025-12-27T05:43:43+00:00

Uniformity in the size distribution of Cu nanoparticles plays an important role in enhancing the outstanding properties of Cu for diverse applications. This study proposes a simple method to control the size of Cu nanoparticles in an electrochemical deposition system using copper sulfate CuSO₄ as the copper source in a LiClO₄ electrolyte solution. The electrochemical kinetics of copper nucleation and growth on the ITO electrode were carefully analyzed using the LSV and CA processes combined with AFM characterization. Subsequently, the influence of pH conditions on the splitting factor of the nucleation and growth potentials was investigated, revealing that a pH value of 2.7 provides the optimal separation of potential for these two processes. The size of the deposited copper nanoparticles can be controlled by conducting two consecutive CA processes at distinct nucleation and growth potentials. Electrochemical deposition with an optimized pH approach provides a simple and straightforward method to synthesize copper nanoparticles with monodispersity and minimizes the risk of contamination by stabilizers.

Reducing the output torque ripple of switching reluctance motors using a fuzzy logic system

2025-12-27T05:46:14+00:00

Torque control for the Switched Reluctance Motor (SRM) is always a complex problem because continuous switching between phases is required during operation. This inherent characteristic often causes the SRM's torque profile to fluctuate significantly [1]. In recent years, researchers have endeavored to investigate control methods aimed at improving the torque characteristics of the SRM. These methods have relied on experimental approaches to select appropriate switching times (or switching angles) [2-4]. In a previous paper, we proposed a data table for selecting the switching time based on the reference speed [14]. To enhance the effectiveness of the proposed solution, in this paper, a Fuzzy Logic System (FLS) is constructed to automate the process of selecting the switching time for the SRM. The FLS is built upon the Takagi-Sugeno (TS) fuzzy model. The fuzzy inference system is implemented using the SUMPROD principle, and defuzzification is performed using the Center of Gravity (CoG) method. The TS fuzzy system is trained using the Steepest Gradient method. The research results will be analyzed through digital simulation.

Optimal trajectory tracking control for USVs under dynamic uncertainties and time-varying disturbances via PI and IRL algorithms

2025-12-27T05:43:59+00:00

This paper presents a model-free optimal control framework for trajectory tracking of Unmanned Surface Vehicles operating under unknown dynamics and time-varying disturbances via Policy Iteration (PI) and Integral Reinforcement Learning (IRL) algorithms. The IRL-PI controller is developed based on an order reduction technique and an off-policy Actor-Critic neural network structure, allowing real-time approximation of the Hamilton-Jacobi-Bellman solution without requiring model knowledge. Simulation results on a three three-degree-of-freedom (3-DOF) USV model demonstrate that the proposed method outperforms conventional controllers in both tracking accuracy and robustness. These results highlight the potential of the IRL-PI controller to develop robust control solutions for complex marine systems operating in uncertain and dynamic environments.

Robust sliding mode control based on a new Quasi-sliding mode and adaptive artificial neural networks observer for robot

2025-12-27T05:46:49+00:00

This study designs and evaluates the simulation results of a robust sliding mode control based on a new Quasi–sliding mode and adaptive radial basis function neural network (RBFNN) observer applied to single-link robot control. An industrial robot (robot manipulator) is a multifunctional manipulator that can be programmed to perform dangerous and/or repetitive tasks with high precision. The robust adaptive RBFNN neural network observer is used to estimate the states and nonlinear functions in the mathematical description of the robot. The sliding mode controller based on a new Quasi–sliding mode combines with the robust adaptive RBFNN observer for the robot trajectory tracking control with appropriate quality indicators. The weights of the RBFNN are updated online. The stability of the proposed control methods is proven by Lyapunov stability theory. The simulation results in MATLAB/Simulink have shown the effectiveness and sustainability of the proposed method without the steady state error, the rising time achieves 0.4656(s), the settling time is 0.7690(s), the overshoot is 0(%), the values of RMSE (Root Mean Squared Error), IAE (Integral Absolute Error) and ISE (Integral Square Error) are 1.7549e-06, 0.0222 và 0.001124, respectively.

Design of frequency-domain beamforming solution for passive sonar systems in shallow-water environments

2025-12-27T05:43:09+00:00

This paper develops the frequency-domain beamforming solution for passive sonar systems operating in shallow-water environments, where acoustic signals are significantly affected by multipath propagation and spatially varying attenuation. The study focuses on optimizing the beamforming configuration by analyzing the influence of key processing parameters, namely FFT length, window type, and overlap ratio, on system performance, including half-power beamwidth (HPBW), peak-to-sidelobe ratio (PSLR), and output signal-to-noise ratio (SNR_out). Simulation experiments were conducted using three narrowband sources at 800, 900, and 1200 Hz, representing the typical operational frequency range of passive sonar systems in shallow-water conditions. Based on the obtained results, the optimal Short-Time Fourier Transform (STFT) configuration is proposed to balance performance and computational cost within the 800–1200 Hz frequency band, offering practical applicability for passive sonar systems operating in the shallow water environment of Vietnam.

Synthesis of parameter adaptive PSO-PIDA controller with swarm optimization algorithm for hydraulic jack drive system

2025-12-27T05:45:25+00:00

This paper presents a PSO-PIDA controller design for an electro-hydraulic actuation system driven by a proportional valve and supplied by an independent constant-pressure hydraulic source. The mathematical model of the actuator is derived from physical principles, incorporating valve flow dynamics, fluid compressibility, and piston motion to obtain a third-order transfer function. The Particle Swarm Optimization (PSO) algorithm is employed to determine the optimal parameters of the PIDA controller, aiming to minimize a composite time-domain performance index. Simulation results demonstrate that the proposed PSO-PIDA controller significantly improves transient response, reduces overshoot, and enhances pressure stability compared with Ziegler-Nichols-PID and PSO-PID controllers. The large parameter values obtained from PSO tuning are interpreted in terms of acceleration compensation, which increases control effort but yields faster settling and higher precision. The study confirms that PSO-PIDA control offers a practical and effective approach for high-performance electro-hydraulic systems and provides a clear foundation for future experimental validation.