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Fracture and Structural Integrity: The Podcast

Fracture and Structural Integrity: The Podcast

Written by: Gruppo Italiano Frattura (IGF)
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 Stay at the cutting edge of fracture mechanics and structural integrity research with the official podcast of the Fracture and Structural Integrity journal. Join us for insightful interviews with top researchers, in-depth discussions of groundbreaking papers, and explorations of emerging trends in the field.All rights reserved Education Science
Episodes
  • 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 mins
  • 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 mins
  • 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 mins
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