Deeply buried and ultrahigh-strength protective structures often require multiple sequential penetration-explosion cycles to be effectively neutralized. This study focuses on the secondary penetration behavior of ultrahigh-performance concrete (UHPC) targets after an initial penetration and explosion sequence, a subject that has received limited systematic attention. First, a series of penetration-explosion-penetration tests was performed on UHPC targets, with systematically varying secondary impact locations to examine their effect on penetration depth and local failure characteristics. Experimental results reveal that secondary penetration performance varied significantly with impact position, showing distinct differences in both the increase in penetration depth and the degree of projectile redirection across tested locations. In addition, a computational model incorporating the restart method was developed and rigorously validated through comparisons with experimental data. Furthermore, a systematic parametric study was conducted to examine the influence of impact location, velocity, and accumulated material damage on secondary penetration behavior, accompanied by a discussion of the underlying physical mechanisms.

Rapid assessment of damage under combined penetration-explosion loading remains challenging due to the high cost of conventional simulations and experiments. Data-driven models improve efficiency but often lack physical consistency and struggle to capture the damage evolution process of concrete under extreme loading. This study introduces GAT-ImpactNet-an attention-enhanced graph neural network designed to advance engineering informatics by enabling real-time, physics-guided damage assessment for defense-related structural analysis. The model leverages high-fidelity numerical simulations, validated through projectile penetration and explosion tests on ultra-high-performance concrete targets, to establish a reliable dataset. GAT-ImpactNet incorporates physical priors via the loss function, allowing the graph attention mechanism to effectively capture complex structural interactions while enhancing prediction accuracy and computational efficiency. Validation against LS-DYNA simulations shows relative errors of 4.84% for penetration depth and 3.92-4.19% for blast cavity dimensions. Attention visualizations further demonstrate the model's interpretability by highlighting critical structural interactions. This work contributes a novel, physics-guided deep learning framework that integrates fundamental engineering principles with neural networks, offering a robust informatics tool for real-time safety evaluation under extreme dynamic loads.

This study integrates molecular dynamics simulations with shock compression experiments to elucidate the hierarchical phase transition mechanisms of black phosphorus under extreme pressure conditions. By establishing a phase transformation pathway model (orthorhombic -> rhombohedral -> simple cubic phase), we quantitatively determined the phase transition thresholds at 38.7 GPa under both ambient and elevated temperatures, and achieved controllable preparation of simple cubic phase black phosphorus through shock loading. The material porosity mediated pressure attenuation effect was found to critically influence the phase transition initiation pressure, while microsecond-scale pressure release characteristics enabled metastable phase retention by suppressing reverse transition kinetics. Atomic-scale analysis demonstrates that three-dimensional hydrostatic pressure drives anisotropic bonding reconstruction, characterized by 78.6 % preferential compression along the b-axis and continuous bond-angle distortion from 103 degrees to 90 degrees, which collectively induce electron cloud rearrangement and symmetry breaking transition from layered to cubic configurations. The developed simulationexperiment dual-validation methodology provides new perspectives for high-pressure phase transition research, with the revealed phase nucleation reverse transition competition mechanism offering critical guidance for metastable material design.

The increase in complexity arising from topology design and morphology optimization hinders a deep understanding of the dynamic response of sandwich structures (SSs). Accordingly, a tailored framework of Sandwich Structure Performance Lifecycle Engine (SSPLE) is proposed by integrating eXtreme Gradient Boosting (XGBoost), SHapley Additive exPlanations (SHAP), and Nondominated Sorting Genetic Algorithm II (NSGA-II). To demonstrate its superiority, an SS with three-layer aluminum foam cores is selected as the case study. Firstly, specific energy absorption (SEA) and peak deflection (PD) are employed to characterize the SS's blast resistance performance, considering the influence of 11 features encompassing geometry, material, bonding, and loading parameters. Subsequently, 600 instances are collected from validated numerical simulations. Employing the trained XGBoost (R2 = 0.9443 on the test set) and SHAP, Ttop (thickness of the top sheet) is identified as the most influential feature with an effect range from -0.32 kJ center dot kg-1 to 0.91 kJ center dot kg-1, and is confirmed to exhibit a substantial interaction effect with SoD (standoff distance) on SEA. As for PD, the main effect of AM (adhesive material) is restricted to the range of -2.35 mm to 7.27 mm following the exclusion of interaction effects. In addition, two optimization strategies provide explainable schemes for performance enhancement, with an increase of 67.39 % in SEA and a decrease of 32.60 % in PD. These findings confirm that the SSPLE can provide a systematic solution for dynamic response analysis and design optimization of SSs. Lastly, a software tool is developed to facilitate the implementation of SSPLE functionalities in practical applications.

Existing single-degree-of-freedom (SDOF) methods inadequately capture the influence of localized damage on the global response of reinforced concrete (RC) structures subjected to close‑in blast loading. This study aims to addresses this limitation. Close‑in explosion experiments were conducted on RC beams at five scaled height of burst, demonstrating that localized effects are non-negligible in the structural response. A validated numerical model was subsequently developed, and regression analysis of the simulation data was used to establish a predictive model for local damage characteristic dimensions. Furthermore, a modified SDOF framework was formulated to capture the coupled local–global response of RC beams under close-in explosions. A local response model for RC beams under close‑in explosions was first formulated based on the traveling hinge concept. A structural resistance-deflection relationship was then developed to account for cross-sectional loss induced by localized damage. The influence of local damage evolution on the mass transformation coefficient and stiffness transformation coefficient was subsequently analyzed, and an equivalent SDOF model was established to characterize the global structural response of RC beams under varying degrees of cross-sectional damage. By integrating the local response model with the equivalent SDOF approach, a global response model incorporating localized damage effects was established and validated against experimental data. The model improves the prediction accuracy, especially for scaled heights of burst below 0.45 m/kg1/3. For maximum displacement prediction, the traditional SDOF model yields a mean absolute percentage error of 23.28%, while the improved model reduces this error to 6.49%.

An urgent need for novel structures to enhance the blast resilience of reinforced concrete infrastructures has emerged in response to the increasing frequency of explosive events. This study presents, for the first time, an experimental perspective into the effectiveness of auxetic and conventional honeycomb sandwich (HS) beams in enhancing the blast resistance of reinforced concrete (RC) beams under close-in explosions. In the experiment, RC beams were reinforced with HS beams on the top side and subjected to close-in explosion conditions. The performance of these composite structures was compared to a control group of RC beams with homogenous steel plate reinforcements, lacking any additional protective measures. The findings reveal that incorporating auxetic HS beams substantially enhances the blast resistance of RC beams. This improvement is indicated by the significantly smaller midspan maximum displacements and less severe spalling of auxetic HS beams protected RC beams. To better understand the protective mechanisms of auxetic HS beams under blast loading, a validated finite element model was employed to analyze energy absorption characteristics, damage modes, and plastic deformation behavior under varying blast loads.

Two-dimensional (2D) black phosphorus (BP), as a representative layered van der Waals (vdW) material, exhibits unique polymorphic transitions under high pressure, which lays the foundation for its functional regulation. This study systematically investigates the mechanical, electronic, and bonding evolution mechanisms of high pressure phases (orthorhombic, rhombohedral, cubic) of 2D BP and their titanium (Ti)-doped systems through first principles calculations, aiming to fill the gap in the property modulation of 2D layered BP under extreme conditions. Using the VASP 6.4.3 platform, Ti-doped BP models with a Ti:P atomic ratio of 1:20 were constructed based on the three high pressure phases. Geometric optimization was performed via PAW pseudopotentials and PBE-GGA functionals, incorporating DFT-D3 corrections to accurately describe interlayer vdW interactions-an essential feature of layered 2D materials. Elastic constant calculations confirm that all Ti-doped high pressure phase structures satisfy the mechanical stability criteria of their respective crystal systems, with the cubic phase showing the most significant enhancement in Young's modulus (reaching 78.62 GPa after doping). Band structure analysis reveals phase dependent electronic reconstruction characteristics of this 2D layered system: Ti doping induces bandgap narrowing (from 0.82 eV to 0.70 eV) in the orthorhombic phase, a semimetal to metal transition in the rhombohedral phase, and optimized carrier mobility via sp3-d orbital hybridization in the cubic phase. Three-dimensional charge differential density reconstructions, combined with Bader charge analysis, further decode Ti-driven bonding evolution in the 2D lattice: strong covalent Ti-P bonds in the orthorhombic phase, distinct ionic characteristics in the rhombohedral phase, and dominant delocalized metallic bonds in the cubic phase. The established "doping-lattice symmetry-bonding" multiscale model for 2D BP provides theoretical guidance for tailoring the performance of BP-based 2D functional materials in high temperature electronic devices and flexible sensor systems

Although considerable progress has been achieved in impact resistance of shear thickening fluid (STF)-filled honeycomb structures, research on their blast performance remains relatively scarce, with a notable lack of reliable experimental data. In this paper, the blast performance of STF-filled auxetic honeycomb sandwich beams (AHSBs) is investigated by experimental and numerical approach. The dynamic response of STF under high-strain-rate conditions is first characterized through the split Hopkinson pressure bar (SHPB) tests. Three constitutive models for STF (power-law, Johnson-Cook and visco-hyperelastic) are compared and validated in numerical simulations of SHPB tests. Numerical simulations indicate that the visco-hyperelastic model most accurately represents the dynamic behavior of STF under high-strain-rate impact. Subsequent blast experiments and corresponding numerical analysis examine the effect of STF filling on the dynamic response of AHSBs. Experimental results demonstrate that the STF-filled AHSB exhibits significantly improved blast resistance relative to the unfilled AHSB, with 23.57% smaller residual midspan displacement and reduced local damage. Numerical results further indicate that STF filling increases structural flexural stiffness and promotes stress dispersion. Despite these advantages, the STF-filled AHSB exhibits a 20.58% lower specific energy absorption (SEA) than its unfilled counterpart. Consequently, STF is selectively introduced into critical cells to improve SEA while preserving the overall bending resistance of the structure. This work advances the application of STFs in honeycomb-based lightweight structures for blast resistance.

Reliable and timely safety assessment under blast loading constitutes a critical, expertise-driven challenge, requiring the accurate evaluation of damage effects on specific targets under prescribed conditions. Despite advances in related fields, such as ammunition theory and vulnerability analysis, fully reliable and intelligent safety assessment systems are still in their fancy. This study proposes a novel framework that integrates large language model (LLM) reasoning with multi-agent coordination, featuring domain expertise embedded in customized safety assessment tools, which eliminates the dependency on large-scale training datasets. Experiments across diverse LLM scales, query complexities, and target conditions demonstrate the excellent stability and adaptability of the proposed framework to autonomously complete complex tasks without human intervention. An empirical investigation of system-level target safety assessment substantiates the necessity of an agentic design framework, as the standalone LLM fails to produce correct results even despite employing detailed chain-of-thought reasoning. Complementary evidence from a case study on component-level targets further underscores the importance of the multi-agent architecture. Specifically, the simplified dual-agent configuration struggles to effectively handle more complex task demands. This study highlights the potential of combining artificial intelligence with traditional methodologies, offering a promising pathway for advancing safety assessment and its engineering applications.

A critical challenge for polyurea-coated ceramic/metal composite structures, frequently employed in used as military applications, is understanding how the polyurea layer thickness influences ballistic behavior and patterns. This study examined the energy absorption of each constituent material within the composite structure using numerical and theoretical approach, revealing a significant transition in failure mechanisms and damage progression within ceramic blocks as the polyurea layer thickness increased. Utilizing dimensional analysis, a semi-empirical model was established to predict the ballistic limit. The ballistic limit of the composite structure initially increased with increasing of the polyurea thickness but subsequently decreased, corroborating the transition. Additionally, a theoretical model was constructed to determine the ballistic limit velocity in relation to thickness ratios, leading to the proposal of two types of optimization problems based on this model. These results indicated that the thickness of polyurea should be chosen wisely for optimization problem of ballistic performance, even without any mass or volume constraints. This research sheds light on the influence of the polyurea layer on the ballistic performance of composite structures, offering valuable insights for the design of novel composite structures.

Simple cubic black phosphorus (BP) has been recognized as a strategic material due to its exceptional structural stability under extreme conditions. In this investigation, simple cubic BP was successfully synthesized through shock-induced phase transformation, utilizing amorphous red phosphorus as the precursor material. The phase evolution process was systematically investigated using plane shock loading apparatus, with shock pressure and temperature parameters being precisely controlled to optimize transformation kinetics. Comprehensive phase characterization revealed the correlation between thermodynamic loading profiles and cubic BP formation efficiency. Precursor modification strategies were implemented through orthorhombic BP utilization, resulting in enhanced cubic phase yield and crystallinity. The synthesized cubic BP variants are considered promising candidates for advanced protective material systems, particularly where combinations of mechanical resilience and thermal stability are required under extreme operational conditions. This research provides critical insights into shock-induced phase transformation mechanics, while establishing foundational protocols for manufacturing non-equilibrium materials with potential applications in next-generation defensive technologies.

This study investigates the spalling effect and critical collapse thickness (CCT) of steel-reinforced concrete (SRC) slabs subjected to embedded explosions through combined experimental and numerical approaches. Tests on cased charges in SRC targets demonstrated that spalling damage on the rear surface intensified with burial depth. The CCT was also determined when the spalling damage depth equals the residual thickness. Comparative simulations using Smoothed Particle Galerkin (SPG) versus conventional Lagrangian methods validated through experiments demonstrated SPG's superior spalling damage characterization. Through numerical parametric analysis, the influence of steel reinforcement was quantified: increasing reinforcement ratios from 0.28 % to 0.63 % reduced CCT by 21.8 %, while concrete strength improvements from 45 MPa to 120 MPa resulted in a 54.5 % increase in load-bearing capacity. In order to calculate the CCT of the SRC target, the established empirical formula for CCT prediction was enhanced through incorporation of a concrete strength coefficient (k) and an equivalent strength calculation method that accounts for steel reinforcement contributions.

Functionally graded multi-layered metallic (FGMM) plates integrated with graduation of constituent, lightweight, high-strength and customised properties are highly desired as blast-resistant structures. Meanwhile, very limited investigation on their dynamic response to localised blast loading involving large deflection has been reported. Here, we develop an analytical model to investigate the large inelastic deformation response of FGMM plates under localised air blast loading. Nonlinear loading and constitutive characteristics, such as the localised variability and exponential decay shape from a close-in blast, as well as the effects of strain rate sensitivity and strain hardening, were considered. Extended Hamilton's principle is applied to derive the governing equation of motion for FGMM plates. Blast tests were performed to validate the analytical predictions of the temporal evolution of transverse central deflection and permanent transverse deflection. The analytical model is used to discuss a number of issues relevant to the dynamic response of FGMM plate, including the effect of loading distribution, influence of different constitutive behaviours, energy partitioning, blast resistance and deformation mechanism. Results in this work show that FGMM plate has superior blast resistance (with 14.9% less permanent transverse deflection) to that of a monolithic steel plate with identical weight, which was attributed to the higher effective specific strength. Localised explosive action triggers a distinct initial bulging deformation phase, resulting in significant external work done. This study provides new insights into the dynamic response of the blast-loaded FGMM plates, while further highlighting their potential in the application of blast-resilient systems.

This study establishes a novel analytical model for blast response prediction in auxetic and regular honeycomb sandwich beams (AHSBs and RHSBs). The model advances blast analysis by integrating the core's compressive dynamic strength, explicitly addressing auxetic negative Poisson's ratio effects. A refined average compressive strain formulation captures core deformation non-uniformity. This framework accurately quantifies maximum deflection and energy absorption. Validation used experimental deflection data and numerical energy results. Results show significant blast performance superiority of AHSBs versus size-matched RHSBs. At 0.7971 m/kg1/3 scaled distance, deflections reduced by 20 % with 10.47 % higher energy absorption. At 0.8617 m/kg1/3, deflections lowered 11.41 % with 42.39 % greater energy absorption. The performance enhancement stems from auxetic cores' greater average compressive strain. NSGA-II optimization applied to this validated model generated HSB designs maximizing specific energy absorption while minimizing deflection.

The N, N-dimethylformamide (DMF) organic solvent was deliberately chosen as the optimal medium for this investigation. To achieve uniform dispersion of black phosphorus powder, which was obtained via shock-induced phase transformation, it was effectively dispersed in the DMF solution, resulting in a homogeneous black phosphorus-DMF suspension. Subsequently, a liquid-phase pulsed discharge experiment was conducted. This experimental setup harnessed the shockwave and tensile stripping effects generated by the rapid expansion of plasma during the liquid-phase pulsed discharge. These phenomena facilitated the interlayer exfoliation and dispersion of black phosphorus molecules, ultimately leading to the formation of a suspension containing black phosphorus quantum dots. In-depth investigation into the formation mechanism of black phosphorus quantum dots was also undertaken. Our findings reveal a pivotal influence of the charging voltage on the microstructure of the recovered samples. Specifically, as the charging voltage increases, the lateral dimensions of the retrieved twodimensional black phosphorus powder undergo a remarkable reduction, transitioning from the micron-scale to less than 10 nm. The above results, which stem from meticulous experimentation and analysis, emphasize the significance of controlled synthesis in producing black phosphorus quantum dots with varying microstructures. Such insights hold substantial promise for advancing the field of materials science and enhancing the applicability of black phosphorus quantum dots in diverse applications.

In this study, a bio-based additive nanosheet (PP-Fe) with multifunctionality was synthesized using self-assembly technology. The multidisciplinary performance of polylactic acid (PLA) composites with addition of PP-Fe was explored, including fire safety, mechanical properties, ultraviolet resistance (UV), electromagnetic interference (EMI) shielding, and flame retardancy. Good dispersion and interfacial compatibility of PP-Fe give its PLA nanocomposites excellent properties. Loading of 20.0 wt% PP-Fe nanosheets on PLA resulted in significant reductions in the maximum heat release rate (72.7%), total heat release (41.6%), and total smoke production (64.7%). More important, the ultraviolet protection factor (UPF) value for the PLA/20PP-Fe composite was 120%, which is categorized as excellent UV-shielding. In general, traditional flame-retardant approaches significantly reduce mechanical performance. Compared to neat PLA, PLA/20PP-Fe exhibited reinforced mechanical properties. The mechanism of the improved multi-performance of the PLA nanocomposite was also determined.

Summary The objective of this study was to study the effect of load details of successive explosions on the blast behaviors of reinforced concrete (RC) beams. First, the effect of the successive loading of two identical explosions was discussed by considering the influences of standoff distance, charge mass on the failure states, and structural responses (displacement and support reaction force). And keeping the total TNT charge mass of 1 kg unchanged, the effect of loading numbers was investigated by loading two 0.5 kg TNT successively and a single 1 kg TNT on RC beams, respectively. Besides, the successive loading of two different explosions was also considered by investigating the effects of loading sequences and the first explosion induced pre‐damage on the ultimate accumulated damage of RC beams. At last, based on the reaction force and displacement responses, a nonlinear relationship between the dynamic residual load‐carrying capacity and the accumulated residual displacement was obtained to assess the damage states of the tested beams. The results show that the local failure range along the beam span direction (length of peeling‐off and length of spallation) caused by the first blast load did not apparently increase when the damaged beams were subjected to another blast load. With the increase in explosion numbers, depth of compressive crushing increases gradually. At the same stand‐off distance (from 0.25 to 0.45 m), due to the damage accumulation effect, successive loading of two 0.5 kg TNT can trigger more severe local failure but smaller accumulated residual deflection to beams than the single loading of a 1 kg TNT. Besides, when two different blast loads are loaded on tested beams, the loading sequence of the larger one first and then the smaller one (1 kg TNT/0.5 kg TNT at h = 0.45 m) can trigger larger damage to beams than the opposite loading sequence (0.5 kg TNT/1 kg TNT at h = 0.45 m). And for the beams subjected to a smaller blast load first and then a larger one, a stiffer behavior may be triggered by the second blast load on the beam after the first loading of the smaller blast load due to the residual strain in longitudinal reinforcement. Furthermore, based on the nonlinear relationship between residual load‐carrying capacity and residual displacement, the accumulated damage of RC beams was divided into mainly four phases.

Aiming to investigate the impact of cross-sectional size on the close -in blast performance of reinforced concrete (RC) beams, the local damage features and structural responses of RC beams with varying cross-sectional widths and depths subjected to close -in explosions were investigated experimentally and numerically. Experiments were conducted on ten RC beams with a crosssectional size of 25 cm x 12.5 cm to study the influence of scaled distance and charge mass on the local damage size and structural responses (displacement and reaction force). The results indicate that the blasting face damage to tested beams, such as the crushing crater of concrete cover and side peeling -off damage, is more sensitive to the scaled distance (intensity of applied blast loads) compared to the rear spalling damage. And the peak reaction force exhibited a gradual increase within the range of 0.5 m/kg 1/3 , eventually reaching an average maximum value of 93.5 kN, and remained unchanged after the scaled distance was greater than 0.5 m/kg 1/3 , indicating that the dynamic load-carrying capacity of tested beams increased with the increasing scaled distance and the maximum dynamic load-carrying capacity of these beams is around 93.5 kN. Furthermore, a numerical model of RC beams subjected to close -in explosions was established based on the Fluid -Structure -Interaction (FSI) method. For validation, the local damage morphology and sizes of RC beams and their dynamic responses (displacement and reaction force) were computed and compared with the corresponding experimental results, concluding that the numerical results are in good agreement with the experimental findings. A parametric analysis was conducted to study the impact of cross-sectional size on the development process of initial local damage, stress distribution in cross sections, local damage sizes, and structural responses. Moreover, a damage index of the dynamic load-carrying capacity was derived from the relationship between the normalized maximum reaction force and the normalized maximum displacement to assess the damage degree of RC beams with varying cross-sectional sizes. This work can serve as a partial reference for relevant research.