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  • Effect of B4C variation on the mechanical, fractographic and tribological performance of hybrid composites Al7075/Gr/ZrO₂

    Effect of B4C variation on the mechanical, fractographic and tribological performance of hybrid composites Al7075/Gr/ZrO₂
    Jan 10 2026
    The current study focuses on the influence of varying levels of boron-carbide (B4C) particles on mechanical and tribological characteristics of Al7075 hybrid composites that are strengthened by fixed percentages of graphite (Gr) and zirconia (ZrO2). Hybrid composites were made by stir casting the 2 and 4 wt.% of B4C to Al7075-Gr-ZrO2 matrix in two-steps. The reinforcements were evenly spread throughout the matrix was confirmed by analysis through electron microscopy SEM together with elemental mapping through energy dispersive spectroscopy was utilized. Microstructural properties, tensile, hardness, and wear behaviour of the resulting hybrid composites were tested. The findings suggest that the adding of 4 wt.% B4C shall improve the hardness of Al7075 hybrid reinforced composites to 87 BHN, the UTS by 37% (214 MPa to 293 MPa) and vice versa slight decrease in ductility was attributed due to the addition of B4C. The tribological study revealed that the resistance to wear increased with additions of B4C as the hard ceramic particles served as load bearing phases. These results demonstrate the importance of B4C variation in improving mechanical and tribological behaviour of Al7075-Gr-ZrO2 hybrid reinforced composites in potential structural and aerospace application.
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    5 Min.
  • Hybrid feedforward neural network for pressure vessel internal corrosion prediction: integrating chemical models with inspection data for structural integrity assessment

    Hybrid feedforward neural network for pressure vessel internal corrosion prediction: integrating chemical models with inspection data for structural integrity assessment
    Jan 6 2026
    This study presents a hybrid framework integrating a physics-based corrosion model with a feedforward neural network (FNN) to predict corrosion rates and estimate the remaining useful life (RUL) of industrial pressure vessels for condition-based maintenance. Using non-destructive evaluation (NDE) wall thickness measurements from 24 inspection points over multiple years (2002–2008) and physics-based training data, a three-layer FNN with Monte Carlo dropout predicts localized corrosion rates, while exponential and linear degradation models project future wall thickness. The FNN achieved a coefficient of determination (R²) of 0.975 for corrosion rate prediction and a mean absolute error (MAE) of 0.1204 mm/year. For thickness prediction, the exponential model achieved R² = 0.99 with MAE = 0.0389 mm, outperforming the linear model (MAE) = 0.1350 mm. The framework was integrated with Fitness-for-Service (FFS) assessment based on API 579-1/ASME FFS-1 standards, enabling classification of vessel components and identification of sections requiring maintenance. This hybrid approach translates predictive analytics into standards-compliant engineering decisions for structural integrity management.
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    5 Min.
  • Experimental calibration of a virtual raster section for high-accuracy FDM simulation in Abaqus

    Experimental calibration of a virtual raster section for high-accuracy FDM simulation in Abaqus
    Jan 2 2026
    This study presents an experimentally calibrated methodology to enhance the predictive accuracy of finite element simulations for Fused Deposition Modeling (FDM) parts in Abaqus by replacing idealized filament geometry with a physically accurate “corrected virtual raster section.” A Box-Behnken Design of Experiments (DoE) across 27 ABS specimens systematically quantifies how key printing parameters, layer thickness, raster width, extrusion temperature, and print speed, influence the true cross-sectional geometry of deposited filaments, as measured via Scanning Electron Microscopy (SEM). These data inform a predictive mathematical model that transforms the conventional circular filament shape into an experimentally grounded oval-rectangular profile, accurately capturing extrusion-induced flattening and lateral spreading. The calibrated virtual section is integrated into a custom Python-based tool that parses G-code toolpaths and sweeps the corrected geometry along deposition trajectories to generate high-fidelity, mesh-ready Abaqus models. The workflow is validated through tensile testing of ASTM D638 specimens printed at 0°, 45°, and 90° raster orientations (n=3 per orientation). Error analysis against the experimental mean demonstrates that the corrected model reduces simulation errors from catastrophic levels in the non-corrected approach (7–92% relative error, 2.5–19 MPa absolute) to engineering-grade precision (0.03–7% relative error, ≤1.3 MPa absolute). This workflow bridges G-code to physical behavior, enabling reliable simulation of FDM anisotropy.
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    5 Min.
  • Guided waves with machine learning for structural health monitoring: transparent features and Monte Carlo confidence

    Guided waves with machine learning for structural health monitoring: transparent features and Monte Carlo confidence
    Jan 2 2026
    Reliable discrimination of small damage states under operational variability requires uncertainty aware Structural Health Monitoring. A pipeline is presented that couples guided wave physics with supervised machine learning to classify damage severity in a metallic panel. The experimental platform is a 310 × 190 × 1 mm aluminum plate with one central piezoelectric actuator and three receivers, interrogated by five cycle tone bursts at 20 kHz and sampled at 250 kHz. Signals are reduced to vectors of 20 physics informed features including root mean square, peak measures, analytic envelope statistics in fundamental and second harmonic bands, band limited energies, a spectral peak near 20 kHz, inter channel correlation, and a second harmonic index that captures weak interface nonlinearity. Uncertainty is propagated with Monte Carlo waveform perturbations, 5 000 realizations per condition, using amplitude scaling around 5 percent, time of flight jitter around 20 µs, and broadband noise near 2 percent of peak. These perturbations yield prediction bands and calibrated decision scores. The method is benchmarked across four learners: random forest, support vector machine with radial basis function kernel, additive boosting, and a hierarchical screener that first detects any mass and then separates severities. A finite element model provides a physics baseline for feature design. The study is a laboratory proof of concept on one specimen and three conditions, practical implications for aerospace deployment are outlined, including transfer to composite skins and links to certification metrics such as probability of detection. Calibration against the pristine response verified timing and mode content.
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    5 Min.
  • Mechanical and morphological evaluation of jute fiber reinforced epoxy composites for sustainable structural and automotive applications

    Mechanical and morphological evaluation of jute fiber reinforced epoxy composites for sustainable structural and automotive applications
    Jan 2 2026
    This study investigates jute fibre reinforced epoxy composites fabricated using a controlled vacuum bag moulding process, with emphasis on establishing reliable structure property relationships relevant to sustainable engineering applications. To address limitations in earlier jute/epoxy studies such as generic claims, limited processing transparency, and weak correlation between impact behaviour and fracture mechanisms laminates containing 5, 10, 15, 20, and 25 wt.% jute fibre were produced and systematically characterized. Tensile strength and modulus increased with fibre content, reaching peak values of 95 MPa and 4.5 GPa at 20 wt.%, while reduced elongation at break indicated enhanced stiffness. Flexural strength and modulus exhibited similar trends, attaining maximum values of 150 MPa and 4.8 GPa, respectively, consistent with improved load transfer and crack-bridging mechanisms. Hardness and low-velocity impact energy absorption were also optimized at 20 wt.% fibre loading due to strengthened fibre matrix interfacial bonding and more uniform stress distribution. A decline in mechanical performance at 25 wt.% was attributed to fibre agglomeration, micro-void formation, and localized interfacial debonding. Scanning electron microscopy revealed matrix-dominated fracture at low fibre contents 5 to 10 wt.%, optimal dispersion and interfacial integrity at intermediate contents 15 to 20 wt.%, and severe clustering at higher loading. These findings identify 15 to 20 wt.% jute fibre as the optimal range for achieving a balanced combination of stiffness, strength, and impact resistance, supporting potential application in lightweight, non-critical structural and automotive components.
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    5 Min.
  • Modified elastic-plastic model: implementation algorithm and comparison of computational efficiency with the elastic-viscoplastic model

    Modified elastic-plastic model: implementation algorithm and comparison of computational efficiency with the elastic-viscoplastic model
    Dec 16 2025
    The most important element of mathematical models of thermomechanical processing of metals and alloys is the constitutive model. In recent decades, multilevel physically-oriented constitutive models (CMs) have found widespread application. The first two-level model was the rigid-plastic theory of J. Taylor,a rigorous mathematical justification of which was developed by J. Bishop and R. Hill (TBH type models). The main disadvantage of this model is the uncertainty of the choice of active slip systems when more than 5 systems are activated. Despite this, the TBH models have become widespread, and its basic provisions have been preserved in many later developments. It seems that limiting the number of active slip systems to 5 has no physical justification and is determined only by the numerical procedure for implementing the model. Since the 1970s, elastic-viscoplastic models have emerged; it has been shown that as the velocity sensitivity parameter tends to zero, the macroparameters determined in the modeling converge to a solution using an elastic-plastic model. However, the system of equations becomes rigid, requiring the use of implicit schemes and extremely small time steps, which significantly reduces the computational efficiency. The paper proposes a modification of elastic-plastic model of the TBH type, in which a procedure for overcoming the above-mentioned drawback is proposed. To compare the computational efficiency of the elastic-plastic and elastic-viscoplastic models, a series of numerical experiments was carried out.
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    12 Min.
  • Utilizing cylindrical and cubical specimens with edge notch to determine size-independent fracture quantities of rock materials

    Utilizing cylindrical and cubical specimens with edge notch to determine size-independent fracture quantities of rock materials
    Dec 11 2025
    The compliance method was first applied to short rod specimens to determine the nonlinear fracture toughness of rock materials by ISRM (International Society for Rock Mechanics) in the 1980s. In this study, utilizing the techniques of the J-integral and the crack closure integral (CCI), crucial linear elastic fracture mechanics expressions for straight-notched disk bending (SNDB) specimens, whose tests are simpler than those for short bar specimens, and single-notch cube bending (SNCB) specimens are initially derived to estimate crack propagation states in rock samples. Andesite-based SNDB specimens from the literature are examined using the compliance approach, and a strong correlation is observed between the compliance approach and the nonlinear approach reported in the literature. Subsequently, limestone-based SNCB specimens and beams containing cracks are produced and tested under bending. The fracture test data are estimated using the peak load approach, and the results of the comparative analysis are found to be satisfactorily consistent for both beams and SNCB specimens. The findings of this study reveal that the non-Hookean fracture quantities of rocks can be adequately determined using SNDB and SNCB specimens of a single size.
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    12 Min.
  • Reduction of cracks in concrete slabs through the incorporation of polypropylene synthetic fiber

    Reduction of cracks in concrete slabs through the incorporation of polypropylene synthetic fiber
    Dec 11 2025
    In Peru, research on cracking in concrete slabs has been limited, partly due to the perception that cracks do not pose an immediate problem. However, their cumulative effect over the long term can compromise structural durability, highlighting the need for further study. This research was conducted according to the recommendations of ASTM C1579, which establishes procedures for evaluating shrinkage cracking in concrete mixes with and without fiber reinforcement. The main objective was to determine the optimal proportion of polypropylene synthetic fiber that maximizes the reduction in the appearance and formation of cracks. Three dosages were evaluated: DM-01 (500 g/m³), DM-02 (1000 g/m³), and DM-03 (2000 g/m³), compared to a reference concrete (MP) during a 35-day curing period. The results indicated that dosage DM-02 (1000 g/m³) exhibited the best performance, with reductions of 18.41% in average crack thickness, 11.46% in total crack length, and 32.43% in the number of cracks compared to the control concrete. Furthermore, the Mann-Whitney U test applied to DM-02 and MP showed that the average crack thickness at 28 days (p = 0.073) showed a trend toward statistical significance, suggesting a possible reduction in crack thickness with the addition of fibers. In contrast, mixes DM-01 and DM-03 showed heterogeneous results, without substantial improvements in any of the variables; in particular, DM-03 registered an increase in crack thickness. It is concluded that a moderate fiber dosage (DM-02) is the most suitable option, since both a deficiency and an excess of fiber can compromise the material's effectiveness against cracking.
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    12 Min.