To develop a moisture-insensitive, high-performance, catalyst-free binder system for advanced solid propellants, a propargyl-terminated hyperbranched polyester (PTH) was synthesized. The crosslinking cure of branched glycidyl azide polymer (B-GAP) was achieved via the Huisgen azide-alkyne cycloaddition reaction. Non-isothermal DSC analysis indicated that the curing kinetics of the B-GAP/PTH system conformed to an autocatalytic model, with an optimal curing temperature determined at 50 °C. By systematically varying the PTH content from 2% to 10% under a low stoichiometric ratio, where the alkyne groups were significantly fewer than the azide groups, the performance evolution of the polytriazole (PTA) elastomer was investigated. A recommended minimum effective load was identified at a PTH content of 6%. Based on this formulation, a PTA-based composite solid propellant was prepared using ammonium perchlorate (AP) as the oxidizer. Through optimization of AP particle size and total solid content, a propellant formulation with superior mechanical properties was achieved: at a solid content of 85 wt% and an AP particle diameter of 220 μm, the tensile strength reached 1.1 MPa with an elongation at break of 14%. This study demonstrates that the B-GAP/PTH curing system exhibits excellent humidity tolerance under ambient conditions and enables efficient crosslinking at low stoichiometric ratios, thereby providing essential theoretical guidance and process parameters for its engineering application in solid propellants.
Continuous wave laser cleaning of steel structures is hindered by low energy efficiency and degraded surface quality due to excessive thermal input. This study systematically addresses these limitations through integrated experimental and multi-physics numerical investigations of conventional, magnetic field-assisted laser cleaning (MLC) and surfactant-assisted laser cleaning (SLC) of Q235B carbon steel. A validated finite element model coupling heat transfer, deformable geometry and magnetic-field-dependent absorption coefficient reveals the governing thermomechanical mechanisms. Complete rust removal is achieved at a threshold power density of 3821 W/mm2, where cleaning depth (≈33 μm) matches rust layer thickness and surface oxygen content drops to 4.12 wt%. Surface roughness exhibits a U-shaped dependence on power density, reaching a minimum of 0.7 μm at 4204 W/mm2, corresponding to a “cleaning–strengthening–damage” transition. MLC dramatically enhances performance: a 200 mT transverse magnetic field increases cleaning depth by 86.2% (from 29 to 54 μm) under sub-threshold conditions and reduces roughness from 2.236 to 1.623 μm. Two synergistic mechanisms—plasma confinement and Lorentz force damping—are identified. Surfactant (CaF2) exhibits an optimal thickness window (≈0.25 mm) that improves depth but slightly increases roughness, while ethanol mixing further improves surface quality at the expense of safety. The optimal processing window (3821–4204 W/mm2, 10 mm/s, 100–200 mT, LR orientation) yields a 60% hardness improvement (163 HV), 32.7% friction reduction, 50% wear depth reduction, and restored corrosion resistance. This work provides quantitative guidelines and mechanistic insights for industrial laser cleaning of steel components.
TC6 titanium alloy, a typical metal material for manufacturing high-performance equipment components, is nevertheless prone to fatigue failure under prolonged extreme service conditions. Laser shock peening (LSP) technique offers distinct advantages in the controllable strengthening of critical structural parts, yet the strength-plasticity mismatch of strengthened components remains a bottleneck restricting further enhancement of fatigue resistance. In this work, molecular dynamics simulations and experiments were integrated to investigate the regulation process and underlying mechanisms of electropulsing-assisted laser shock peening (EP-LSP) on the microstructures of TC6 titanium alloy. By leveraging the thermoelectric-mechanical coupling effects, dislocation motion and configuration rearrangement were promoted, while the nucleation rates of subgrains and mechanical twins were enhanced, leading to a higher volume fraction of fine grains. The results demonstrated that EP-LSP lead to significantly improved surface properties, mainly in terms of surface hardness, residual stress and full width at half maximum. Moreover, EP-LSP simultaneously enhanced both the tensile strength and plasticity, with a 4.3% increase in tensile strength and a 16.8% increase in strain compared to those treated by LSP. In addition, the synergistic regulation of microstructures and compressive residual stress induced by EP-LSP effectively suppressed the initiation and propagation of cracks, and the tensile fatigue life of the EP-LSP treated samples increased by 137.2% and 26.2% compared to untreated and LSP treated specimens. This study offers a practical new approach to address the strength-plasticity trade-off and further enhance the fatigue resistance of titanium alloys.
A dual-stage morphology engineering strategy that integrates solvent-antisolvent crystallisation with ultrasonic cavitation was developed for the controlled fabrication of micro-/nanometer-scale spherical 1,3,5,7-tetranitro-1,3,5,7-tetraazacyclooctane (HMX). Micro-/nanometer-scale crystals were first produced via solvent-antisolvent precipitation, followed by cavitation-induced selective dissolution-recrystallisation and surface reconstruction, yielding dense spherical crystals with a sphericity of 0.985. Ultrasonic treatment promoted transformation into thermodynamically stable β-HMX, highlighting the critical role of external-field energy in directing crystal evolution. The spherical HMX significantly enhanced thermal stability, with apparent activation energies increased by 15.4% relative to blocky HMX and 16.9% relative to the raw material. Mechanical safety is likewise improved: The critical impact energy rose by more than five-fold versus blocky HMX and by over seven-fold versus the raw sample, accompanied by gains in friction sensitivity and compressive strength. These findings elucidate the intrinsic mechanism underlying external-field-mediated morphology evolution and render an effective route for co-optimising energetic performance and insensitivity in advanced energetic materials.
To balance the blast resistance of polymer-based multilayer composite structures with the requirements for lightweight and thin-walled design, this study investigates the blast resistance of polyurethane/45# steel/ultra-high molecular weight polyethylene (UHMWPE) multilayer composite structures, the establishment of shock wave pressure prediction models, and the multi-objective optimal design of such structures. First, via numerical simulation, the optimal structural configuration of the multilayer composite structure was identified as the polyurethane-45# steel-UHMWPE layering scheme, and the pressure evolution characteristics of shock waves within the structure were analyzed. Subsequently, experimental validation was conducted, and the relative error between the numerical simulation results and the experimental data was found to be less than 10%. Then, to address the challenges of limited dataset size and a large variation range of output variables in predicting the shock wave pressure of multilayer composite media, a Bayesian-LightGBM hybrid model was developed. The model yielded an R2 of 0.9616 and an MAPE of 8.01%, and exhibited higher prediction accuracy than other comparative algorithms. Furthermore, combined with SHAP interpretability analysis, the key factors affecting the shock wave pressure were ranked in descending order as follows: charge radius R, charge height Le, polyurethane thickness L1, UHMWPE thickness L3, 45# steel thickness L2, and target plate side length a. Finally, the Bayesian-LightGBM prediction model was integrated into the NSGA-Ⅱ algorithm as a surrogate model to perform multi-objective optimization analysis. With the optimization objectives of minimizing the shock wave peak pressure, structural areal density and total structural thickness, a Pareto optimal solution set was obtained. Experimental validation was then conducted for the optimal design scheme screened from this solution set. The results show that the shock wave attenuation rate of the optimized structure is increased by 52.7% and its areal density is reduced by 20.7%, while the maximum deviation between the numerical simulation results and the experimental data is merely 6.12%. The findings of this study provide technical support for the optimal design of blast-resistant multilayer composite protective structures.
Multi-point simultaneous detonation typically involves the interaction of multiple shock waves, which leads to the formation of complex shock wave systems and presents significant risks to the safety of urban underground spaces. To investigate the dynamic response characteristics of underground tunnel structures under multi-point explosions, this study employs scaled model experiments, numerical simulations, and theoretical analysis to examine the pressure distribution and vibration deformation patterns of arched tunnel structures under various explosive configurations. The results show that as the spacing between explosives increases, both the pressure field and the structural dynamic response initially increase before decreasing. Compared to a single concentrated charge of equivalent mass, the pressure amplification effect in the medium and far field of a seven-point explosion can reach 3–6 times, while the peak displacement at the tunnel crown increases by 2–5 times, significantly intensifying the vibration deformation effects on the structure. Moreover, the interaction of multiple shock waves accelerates the transition from spherical waves to planar waves, with increasing explosive spacing further optimizing the wave system structure of the resulting shock waves. A dynamic calculation model for underground arched tunnel structures under seven-point explosive loading is also developed, capable of predicting the extreme displacement values at the tunnel crown for any given explosive spacing. The maximum deviation from experimental data is less than 17%, and a method for determining the optimal explosive spacing under the most adverse structural conditions is proposed. This study provides valuable insights for the protection of underground civil engineering structures.
Traditional Bernoulli-based steady underwater penetration models exhibit limitations, particularly in their inability to describe velocity attenuation at low velocities accurately or to account for the observed resistance effect (the deceleration of penetrator elements under resistance) on the JPC (Jetting Projectile Charge) penetrator. To address these limitations, a novel attenuation mechanism of JPC underwater penetration is proposed and an unsteady penetration model is established in this study. According to the stress distribution, the JPC precursor penetrator is in a state of fluid and elastic-plastic coexistence. As underwater penetration progresses, the velocity attenuation mode shifts from the combined effects of resistance and hydrodynamic erosion to resistance alone. In this study, the solution for the penetration velocity U accounting for the dynamic strength and changes in the shock wave region is obtained, which characterizes the transition of the attenuation mode. The critical values for the attenuation mode transition of materials with different dynamic strengths are presented. In addition, an unsteady motion model that accounts for stress distribution is introduced to characterize penetration under resistance. The X-ray experiments on JPC formation and underwater penetration were carried out further. The penetrator morphology and penetration velocity at the typical time were obtained. The results show that, compared with the Bernoulli-based steady model in existing research, the proposed model can more accurately predict the penetration velocity U corresponding to the penetrator velocity Vp and more effectively describe the attenuation process under low-velocity conditions. An important theoretical basis can be provided by this study for the design of underwater shaped charges.
Space targets detection is critical for safeguarding space assets. However, accurate detection of such targets remains challenging, as they typically manifest as faint spots or streaks that lost inherent structural information in observational images. Deep-learning-based approaches face two major difficulties when detecting these targets: weak feature responses and the inherent dilemma between accurate discrimination and precise localization. To address these challenges, we propose the CF-FENet, which performs coarse-to-fine feature enhancement for space targets. The CF-FENet primarily consists of two core modules: the Spatial-Frequency Synergistic Attention (SFSA) and the Mask-Guided Semantic Refinement (MGSR). To tackle the issue of weak feature responses, the SFSA extracts multiple feature cues in both the spatial and frequency domains, which complementarily guide spatial attention to coarsely enhance the feature responses of potential targets. Building upon this, the MGSR addresses the dilemma between precise localization and accurate discrimination. It generates dedicated masks for both the highest-level features and lower-level features, thereby leveraging the semantic richness of the highest-level features and the spatial detail advantages of the lower-level features. Subsequently, each position in the masked lower-level features receives semantically fine-grained modulation from the masked highest-level features, achieving both accurate discrimination and precise localization. Through the synergistic operation of these modules, the CF-FENet effectively enhances feature representation for space targets, leading to more robust detection performance. Comprehensive experiments conducted on three space target detection datasets demonstrate the superior performance of the proposed CF-FENet. Furthermore, ablation studies and feature visualizations confirm the effectiveness of each module within the CF-FENet framework.
Ballistic protection in light vehicles has traditionally been implemented through add-on armor panels, which increases the areal density of the structural system and reduces mobility and maneuverability in operational environments. As an alternative, the development of structural components that integrate protective functions within the load-bearing element itself allows for maintaining structural integrity while providing impact resistance. In this context, stainless steel-based Fiber Metal Laminates (FMLs) represent a potential solution to combine load-bearing capacity and ballistic protection into a single integrated system and constitute a promising architecture for the preliminary assessment of lightweight structural protection concepts.This work addresses a comprehensive experimental and numerical study of the impact behavior of FMLs consisting of AISI 304 stainless steel as the metallic phase and UHMWPE composite material as reinforcement. The analysis is structured in two stages. First, the constituent materials are studied independently through small-caliber projectile ballistic impact tests to characterize their ballistic response and the damage induced by the energy absorption mechanisms inherent to each material. These results are used to calibrate and validate specific numerical models for each constituent. Damage assessment is performed using computed tomography (CT) and 3D scanning techniques, enabling both internal and external characterization.In the second stage, the validated constituent models are integrated into multilayer FML configurations. Two laminates of different thicknesses are subjected to ballistic impact and damage analysis, using experimental results to validate the predictive capability of the developed numerical model. The proposed procedure provides a validated modeling framework capable of predicting the impact behavior of stainless steel–UHMWPE FMLs in various configurations, aimed at the preliminary assessment of lightweight structural protection concepts and future vehicle-oriented applications.
With the increasing threat of soft-kill laser weapons to military optoelectronic systems, there is an urgent need for nonlinear laser protection technologies that combine high performance, long-term stability, environmental robustness, and operational sustainability. Conventional laser protection materials, whether liquid-based or solid-state, suffer from critical shortcomings including poor stability, low damage thresholds, limited environmental adaptability, and lack of recyclability. Here, we report a colloidal suspension based nonlinear laser protection system that overcomes these limitations. Using magnetic graphene oxide (MGO) dispersed in a high-viscosity, water-soluble polyethyleneimine medium, the system achieves exceptional stability (no sedimentation for over two months), a high laser damage threshold (>1.2 J/cm2), and green recyclability via magnetic recovery. At a concentration of 0.0219 mg/mL, the MGO colloidal suspension exhibits a minimum transmittance of 22.7% and an NOL capacity coefficient of 0.385 at 1064 nm. Its protective performance exceeded that of many existing NOL materials. The nonlinear absorption coefficients measured by Z-scan experiments reach up to 1.69×10−9 m/W. Furthermore, the material maintains stable performance at elevated temperatures (up to 75 °C) and after extended storage. This work demonstrates that colloidal suspensions represent a new class of practical laser protection media, offering a promising solution for defending military platforms against soft-kill laser threats.
Thermoplastic composite solid propellants, a new type of solid propellant that do not require chemical curing, have attracted increasing attention due to their unique R3 (Recover, Reuse, and Recycle) characteristics. However, the absence of a chemically crosslinked three-dimensional macromolecular network results in relatively poor mechanical properties, particularly low elongation, which significantly limits their practical applications. In this work, a mechanochemically mediated small-molecule modification strategy was proposed. Three functionalized small molecules (MAH, MAN, and MABE) were synthesized, and subsequently grafted onto EVA (ethylene vinyl acetate) thermoplastic elastomers under amine-borane mediated mechanochemical conditions to achieve functional modification. The results showed that compared with unmodified EVA, the mechanical properties of EVA-based thermoplastic adhesives and propellants are significantly improved after mechanochemical modification, and the AP dewetting phenomenon in the propellant is markedly reduced. Among them, MABE, containing boronate ester groups, demonstrates the most pronounced improvement. While maintaining the processing performance and thermal behavior, the mechanical properties of the propellants could achieve 0.63 MPa/22.3% (25 °C) and 4.55 MPa/13.5% (−40 °C), respectively. Further study suggested that mechanochemistry-engineered EVA featured a pronounced decrease in γSL accompanied by a significant increase in Wa, indicating enhanced wetting and strengthened interfacial interactions with AP.
Conventional active control approaches in underwater environments primarily focus on one- or two-dimensional suppression along the incident direction. It often generates pronounced echo highlights in non-controlled regions and can hardly meet the practical requirements under bistatic/multistatic detection scenarios. A thin, lightweight, and high-pressure-resistant integrated active-passive acoustic coating was designed for omnidirectional stealth of acoustic scattering from three-dimensional surfaces of underwater vehicles. Based on the bare-hull Benchmark submarine model, acoustic modulation was implemented through a combined active noise control and phased-array acoustic beamforming strategy. The design for omnidirectional active echo suppression was validated through numerical simulations and experiments. Full spatial coverage in both circumferential and radial directions was considered, with special emphasis on solving the difficult-to-suppress scattering from the bow region. Within the 300–1200 Hz low-frequency band, the target strength reduction exceeds 20 dB in the incident direction, while the spatially averaged enhancement of the new echo highlights remains below 0.7 dB. All these effects can be achieved within a 12° incident angle bandwidth at low frequencies. The proposed framework provides a feasible modular-layout design and control methodology for omnidirectional active acoustic control of underwater vehicles in the broadband, multi-azimuth detection environments.
Nano-thermite (Al/CuO) exhibits high reactivity and energy density, but its application is often limited by issues such as nanoparticle agglomeration and inhomogeneous mixing. This study presents an innovative strategy that employs microfluidic technology to overcome these challenges. Molecular dynamics simulations identified F2603 as an optimal binder for improving interfacial stability. By precise regulation of multiphase flow within microchannels, Al/CuO@F2603 composite microspheres were successfully fabricated, featuring excellent dispersibility, high sphericity, and strong hydrophobicity. Among formulations with varying aluminum content (30%, 40%, and 50%), the Al/CuO@F2603-2 sample (containing 40% Al) demonstrated superior performance. Specifically, its initial exothermic peak occurred approximately 200 °C lower than that of raw Al powder, achieving a maximum heat release of 1929.8 J/g and a unique deflagration phenomenon. Constant-volume combustion tests further confirmed its exceptional reactivity, showing an ignition delay of 0.157 s, a 43 ms combustion duration, a peak pressurization rate of 5.633 MPa/s, and an ignition energy of 4.472 J. This enhanced performance is attributed to the near-stoichiometric Al/CuO thermite reaction combined with a pre-ignition reaction (PIR) between the binder and aluminum. Overall, this work provides valuable theoretical guidance for designing advanced energetic composites with high reactivity, hydrophobicity, and sphericity.
Vibration isolation systems for precision instruments and aerospace equipment face growing demands, requiring the integration of broadband isolation, transient impact dissipation, and structural health monitoring. Herein, we present a stiffness-complementary magnetic-bistable beam vibration isolator with a designable target load capacity. By coupling repulsive permanent magnet assemblies with bistable beams, the system regulates its force-displacement characteristics, simultaneously improving broadband isolation and impact absorption. Through integrated theoretical, numerical, and experimental analyses, the effects of magnet surface flux density, bistable beam geometry, and array configuration on load-bearing characteristics were systematically investigated. Multi-objective optimization was performed with vibration isolation performance and energy absorption efficiency as the design objectives, leading to the determination of the optimal geometric parameters for the bistable beams. The resulting isolator achieves a peak transmissibility of 3.6 dB within 0–100 Hz, with an initial isolation frequency of 11.3 Hz and effective broadband performance above 36.8 Hz. By integrating an electromagnetic coil into the isolator, a vibration sensor was implemented, enabling real-time vibration monitoring and safety alerts. Under simulated transport vibration conditions (1.0 kg payload, peak acceleration of 33.9 m/s2), the system reduced the vibration amplitude across the entire frequency range of 0–100 Hz by an average of 75.5%. In simulated transient impact scenarios (0–50 g), it attenuated the average impact acceleration by 55.4% and generated warning signals when the sensor output voltage exceeded a predefined warning threshold. This study proposes a compact, target-load-designable vibration isolator, providing an integrated solution for the reliable operation of precision equipment under complex dynamic environments.
Achieving simultaneous improvement in safety and energy performance remains a major challenge in energetic materials. In this study, RDX/FATPE composite energetic microspheres were fabricated by using the dispersed-phase transient self-assembly method. By introducing a novel fluorine-containing azide thermoplastic elastomer (FATPE) as a surface binder, the crystal-polymer interface structure was regulated at the molecular scale, thereby realizing the synergistic control of particle size refinement and morphology regularization. Morphological characterizations show that the as-prepared microspheres exhibit a regular spherical structure, with the particle sizes reduced by approximately 87.5%–95.0% and surface defects significantly decreased. Molecular dynamics simulations reveal that FATPE molecular chains possess high interfacial binding energy with the dominant crystal facets of RDX. Structural characterizations confirm that FATPE and RDX exhibit favorable interfacial compatibility and stable physical adsorption. Based on this, thermal properties, mechanical sensitivity, and mechanical properties were tested and compared with those of refined RDX and composite samples prepared by the solvent evaporation method. Compared with raw RDX, the apparent activation energy of thermal decomposition decreased and the critical temperature of thermal explosion (Tb) increased. Safety performance tests demonstrate that both impact sensitivity and friction sensitivity of the composite microspheres are significantly reduced, while ignition performance is remarkably improved and tensile strength is substantially enhanced. These results demonstrate that the dispersive phase transient self-assembly granulation method exhibits significant advantages in structural control and performance synergistic optimization of composite energetic materials, and further verify the application potential of FATPE as a novel fluorinated energetic binder in high-performance explosive formulations and composite energetic materials.
Underwater Acoustic Monitoring Networks (UAMNs) are vital for maritime situational awareness but pose significant security risks when deployed by non-cooperative entities for covert reconnaissance. Current detection methods focus primarily on signal-level analysis of individual targets, failing to account for the tactical coordination within "swarmed and networked" underwater threats. This paper proposes a detection framework based on spatiotemporal graph representation and sequential reasoning (ST-GRSR) to identify network existence from a structural perspective. By introducing connectivity and scale constraints, the detection task is formulated as a blind inference problem of unknown topologies. A multi-dimensional feature space integrating physical, protocol, spatial, and behavioral attributes is constructed to characterize the sparse and heterogeneous nature of non-cooperative targets. We then develop an inductive spatiotemporal graph neural network that combines Graph Sample and Aggregate (GraphSAGE) for spatial neighborhood aggregation with Gated Recurrent Units for capturing long-term dependencies in uncertain observation sequences. This architecture enables feature-to-link mapping to determine network existence. Experimental results using a Network Simulator-3 (NS-3, AquaSim) simulated dataset demonstrate that the proposed method achieves over 90% accuracy in dynamic adversarial scenarios. The framework significantly outperforms benchmark models in precision and robustness, providing a theoretical foundation for identifying non-cooperative entities in complex maritime environments.
HMX is a representative nitramine energetic material whose decomposition mechanisms under various ignition stimuli have been extensively investigated, primarily for electronically neutral molecules. However, under practical conditions such as laser irradiation, electrostatic discharge or friction, HMX may experience transient electron removal or accumulation. Experimental observations suggest that early-stage decomposition can be influenced by electron-rich or electron-deficient environments, although the underlying mechanisms remain unclear. In this work, the initial unimolecular decomposition mechanisms of HMX are systematically investigated under neutral, positively and negatively charged states using density functional theory combined with the CI-NEB method. Seven representative reaction pathways are examined, including N–NO2 dissociation, HONO elimination, ring opening, rearrangement and fragmentation. The results show that charging not only lowers the energetic barriers of early decomposition steps but also alters the preferred sequence of bond-breaking and bond-forming events. Negative charging facilitates N–NO2 dissociation and C–N bond cleavage within the ring, enabling competing ring-opening and multistep rearrangement pathways that are unfavorable in the neutral state. In contrast, positive charging promotes hydrogen-transfer-assisted processes, favoring HONO elimination and related rearrangements. The structural flexibility of HMX is further amplified under charged conditions, giving rise to a more complex and diverse reaction network. Overall, these findings demonstrate how charging reshapes the early decomposition landscape of HMX and offer molecular-level insight into charge-related experimental observations.
Solid propellants typically incorporate approximately 15%–20% aluminum particles to enhance energy density. The transport behavior of aluminum particles, such as agglomeration, ignition and combustion near the propellant combustion surface, significantly impacts propellant combustion efficiency. To observe burning particles, this study developed a digital in-line holographic (DIH) laser testing system with a 4f optical amplification component and a coaxial holographic reconstruction algorithm based on angular spectrum analysis. Calibration using standard particle size plates demonstrated particle size measurement errors within 5% and z-axis positioning errors within 2.2%. Ignition and high-speed digital holographic tests were conducted on aluminum (Al) and aluminum-lithium alloy (Al-Li) based solid propellants to evaluate the irregular morphology and agglomeration dynamics of particles near the combustion surface. Statistical analysis of high-speed data acquisition yielded the particle size distribution. The average particle size of the Al-Li propellant is 24.10% smaller than that of traditional pure Al propellant demonstrating a reduction in agglomeration. Furthermore, a depth-of-field extension algorithm was developed to obtain particle position information along the laser direction, enabling the calculation of three-dimensional velocity vectors for particles near the combustion surface.
This paper proposes a fragility-free performance guarantees-based near optimal enclosing controller for uncrewed aerial vehicles (UAVs), which achieves circumnavigation around a given target with performance guarantees and obstacle avoidance. The proposed strategy can effectively eliminate the fragility problems inherent in available prescribed performance control and ensure safety under a modified adaptive dynamic programming (ADP) through three steps. First, to realize the prescribed specification on enclosing error, a prescribed time flexible behavior envelope is presented to characterize the prescribed performance constraints. Specially, the proposed envelope relaxes the choices on initial enclosing error and handles the singularity problem caused by collision avoidance manners. And a transformed enclosing error is generated by converting constrained original error into an equivalent unconstrained one. Second, by considering the relative positions and relative velocities between the UAVs and obstacles, a skilled barrier function is constructed to encode safety constraints. Third, by minimizing the cost function related to the transformed enclosing error, the skilled barrier function and control consumption, the near optimal enclosing controller is obtained to approximate the numerical solution of the Hamilton-Jacobi-Bellman equation. Especially, a modified prescribed time learning rule driven by weight errors is elaborated by revisiting real-time and historical information, which could realize the convergence of weights within a user-defined constant. The prominent improvement is that the optimal enclosing with fragility-free performance guarantees can be achieved by a prescribed time ADP. Involved error variables are proven to be ultimately limited and resultant controller satisfies optimality. Finally, simulations and comparisons verify the values and superiority of the proposed method.
This study provides a comparative assessment of how matrix type and expanded graphite (EG) addition influence the compression-after-impact (CAI) performance of carbon-fiber composites. EG was incorporated at 0.1 wt.% into thermoset epoxy and liquid thermoplastic Elium® matrices and evaluated under 30 and 100 J low-velocity impacts. The results indicate distinct impact-response characteristics at the two investigated impact energies. At 30 J, the CF/epoxy laminates exhibited slightly higher CAI strength retention than the corresponding CF/Elium® laminates, consistent with their higher mean stiffness and lower absorbed energy, while EG addition produced mean increases in ultimate CAI load of 5.6% for CF/epoxy and 7.2% for CF/Elium®. At 100 J, complete perforation occurred in all laminates; the neat CF/Elium® laminate retained 65.7% of its non-impacted CAI strength, compared with 60.7% for neat CF/epoxy, despite its lower initial stiffness. At 100 J, the addition of 0.1 wt.% EG produced mean increases in ultimate CAI load of approximately 9.6% for CF/epoxy and 8.9% for CF/Elium®. The two impact conditions produced distinct combinations of absorbed energy, damage extent, and residual CAI performance. Overall, post-impact performance varied with matrix type, EG addition, and impact condition. This work provides a quantitative assessment of how nanofiller reinforcement, matrix characteristics, and impact energy affect the impact and residual compressive responses of carbon-fiber composites.
