Resumo em Inglês:

Abstract This study examines the flexural performance of partially encased concrete cellular beams (PECCBs), in which continuous openings are introduced into the web of the main steel component (MSC). To evaluate the influence of web openings and their geometries on structural behavior, six PECCBs with different configurations and one conventional partially encased concrete beam (PECB) were tested. The parameters investigated included three cellular geometries (circular, square, and hexagonal), two opening ratios, and three flange thicknesses. Experimental results indicated that conventional PECB specimens primarily failed through concrete crushing and flange buckling, whereas PECCBs exhibited lower flange tensile failure with concrete damage or upper flange buckling in compression. The presence of cellular webs enhanced the overall energy absorption capacity, with circular openings delivering the best performance, followed by hexagonal and square shapes. The cracking load was governed by both the opening ratio and geometry, with the highest value of 27.14 kN·m obtained for circular-cellular beams. Based on the test results, a cracking load prediction formula and an analytical deflection model were developed using the discounted web thickness method. Comparisons with JGJ 138-2016 and T/CECS 719-2020 demonstrated that the proposed deflection model achieved superior accuracy, with an average error of 4.20% and a standard deviation of 0.045.

Resumo em Inglês:

Abstract Ballistic equivalent thickness conversion is key in armor design and damage assessment, but traditional fixed ratio or curve-fitting methods have limited applicability, neglecting energy dissipation and hardening. Cavity expansion theory, validated for ballistic limit prediction, has not been inversely applied to establish ballistic equivalence between different targets. Using mathematical inversion, we derive an explicit analytical solution for the equivalent thickness of ductile metal plates struck by ogive-nose armor-piercing projectiles. Validated with 950+ independent penetration equivalence cases from public databases, the model achieves 7.4% MAPE for ductile hole-growth metals without empirical calibration, outperforming traditional empirical models. When inertial effects are negligible, the equivalent thickness ratio depends only on quasi-static cavity expansion resistances, independent of projectile parameters. The derived formula eliminates experimental calibration, supports lightweight protective design, and aids equivalent testing and optimization for vehicle and ship protective panels.

Resumo em Inglês:

Abstract The design of Brazilian highway bridges is based on the NBR 7188 code, which prescribes a live load model consisting of a 450 kN truck load and a distributed load of 5 kN/m2, both affected by an impact factor. Previous studies have shown that this load pattern does not adequately reproduce the effects of the real traffic. Two alternative load models that are more appropriate to represent actual Brazilian traffic effects were recently proposed; both were calibrated considering two-girder deck bridges, with span lengths up to 40 m. In such cases, the critical effects are associated with the free flow of heavy vehicles, including dynamic effects. This paper presents the procedures developed to assess the applicability of the previously proposed load models to five-girder bridges, with spans lengths ranging from 30 m to 50 m. For this span range, traffic jam scenarios are included in the analyses. The results indicate that the NBR 7188 load model is unsafe in several situations. Furthermore, one of the load models previously proposed was found to satisfactorily reproduce the effects of real traffic for this new set of bridges.

Resumo em Inglês:

Abstract Machine learning prediction of structural responses is highly efficient. The use of surrogate models to assess the reliability of small probability events is significant for engineering safety evaluations. This paper proposes a structural reliability analysis method that combines machine learning surrogate models with physical information and Subset Simulation. By using CNN to extract features from load and structural frequencies and then employing LSTM to predict responses based on the feature vector, the surrogate model is integrated with the SS method. This approach aims to address the issues of computational efficiency and accuracy in structural reliability analysis, especially for small failure probabilities. Case studies on planar truss systems and steel frame structures under random dynamic loads demonstrate the effectiveness of the method. The results show that the CNN-LSTM model achieves better prediction accuracy than LSTM. In terms of reliability results, the failure probability predicted by CNN-LSTM is closer to the finite element-Subset Simulation results, while the failure probability error of LSTM-Subset Simulation is 12.50 percentage points higher than that of CNN-LSTM-Subset Simulation. This method is significant for evaluating structural reliability.

Resumo em Inglês:

Abstract The prism charge warhead can achieve a good balance between dense damage elements and reduced aiming time. However, the conventional fragment velocity theory can’t be directly applied to calculate the fragment velocity of polygonal charges, resulting in a lack of effective metrics to evaluate their lethality and to guide practical design. In this study, the configuration decomposition method was first used to quantify the distribution relationship between polygonal charges and sandwich charges, and a preliminary model was established. Secondly, through numerical modeling, the unknown function within the model was determined, and pulsed X-ray experiments were designed and executed. Finally, the accuracy and applicability of the established model were verified using the test results, publicly published test results, and additional numerical simulations. The study's numerical simulations show high precision, with an absolute error of <5.44%. The error of the established calculation model is controlled within 7.70%. This research can provide a reliable tool for designing and optimizing the power of prism charge warheads.

Resumo em Inglês:

Abstract It remains unclear whether local stiffening or uniform thickening provides a safer balance between global deformation control and hole-edge stress margin under impact loading. This study compares 4/4 mm baseline, 4/4 mm locally stiffened, and 5/5 mm uniformly thickened 6061-T6 shells under 300 g, 2 ms base acceleration using transient finite element analyses with identical geometry, material, supports, loading, mesh, and solver settings. Within this linear-elastic relative-comparison framework, the locally stiffened shell reduces maximum deformation by 16.06%, yet increases selected hole-edge peak stress by 27.76% and unaveraged nodal peak equivalent stress by 32.52%, lowering minimum stress-margin indicator to 0.60216. In contrast, uniform thickening reduces deformation by 42.36%, decreases hole-edge stress by 5.25% and nodal peak stress by 17.34%, and raises the indicator to 0.96538. Boundary-condition sensitivity confirms that support idealization does not reverse this trend. A supplementary elastoplastic analysis using a bilinear isotropic hardening model shows that plasticity reduces peak nodal stress of the critical stiffened shell by 19.4%, confines yielding to a sub-millimeter hole-edge band, and preserves linear-elastic ranking for comparative design assessment. Therefore, displacement reduction alone is insufficient for evaluating impact-loaded perforated shells. For design under this impact condition, uniform thickening is preferable for balanced performance, while local stiffening requires hole-edge reinforcement and elastoplastic assessment.

Resumo em Inglês:

Abstract Ensuring the structural performance of reinforced concrete beams strengthened with engineered cementitious composites (ECC) demands a reliable prediction of their load-carrying capacity. This task is complicated by the nonlinear interactions among material properties, geometry, and applied loads. This study introduces a rigorously validated dense neural network model tailored to accurately predict the load-carrying capacity of ECC-strengthened reinforced concrete beams, and provides a powerful data-driven tool for advanced structural design. A comprehensive database was assembled from published experimental programs and high-fidelity numerical simulations, which includes diverse beam geometries, reinforcement ratios, and ECC layer configurations. Among a suite of machine-learning techniques, the optimized dense neural network achieved superior predictive performance (R2 = 0.975, mean absolute error = 14.544, root mean squared error = 18.190), which outperforms linear, tree-based, and other nonlinear models. Sensitivity analysis revealed beam depth and ECC tensile strength as dominant drivers of load-carrying capacity, while ECC layer thickness exerted a comparatively minor influence. Importantly, the inherent strain-hardening capacity of ECC was shown to markedly enhance ductility, energy dissipation, and seismic resilience. These findings highlight the potential of artificial-intelligence-based approaches to restructure the design of ECC-strengthened reinforced concrete beams, informed performance-based seismic design, and guide the next generation of robust, high-performance concrete infrastructure.

Resumo em Inglês:

Abstract A new finite element (FE)-based approach for calculating crack-tip strain energy density factor (SEDF) named “element strain energy density factor (ESEDF) approach” was proposed. Mode I, mode II, mode III and mixed mode cracks in both 2D models and 3D models were analyzed. A da/dN-ΔS-R equation considering stress ratios was proposed for mode I cracks and a fatigue crack growth test was done. The results show that the ESEDF approach directly computes SEDF from FE results without assuming plane stress/strain or calculating stress intensity factors. It performs best for regular mode I/II cracks in 2D and 3D models, but is less accurate for complex mixed-mode, 3D mode III, surface-cracks and coarse-mesh cases, while remaining acceptable accuracy. The proposed da/dN-ΔS-R equation correlates fatigue crack growth rate with SEDF ranges considering stress ratios in mode I cracks for steels well.