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Biaxial Thermo-mechanical Response of ABS Sheet Above Tg Using DIC-Based Bubble Inflation Technique

JOURNAL OF POLYmER SCIENCE 2025年第3期63卷 724-738页

作者： Varedi, S. Rasoul Buffel, Bart Desplentere, Frederik Katholieke Univ Leuven Dept Mat Engn ProPoliS Res Grp Brugge Belgium SIM M3 Program Zwijnaarde Belgium

In this study, we examine the biaxial, large, and rapid deformation characteristics of heavy-gauge ABS sheets within the temperature range of 120 degrees C to 160 degrees C, relevant to the industrial forming process. A custom-built bubble inflation apparatus with a 300 mm diameter was designed for this purpose. Temperature uniformity across the sheet was verified using a thermal camera, while the temperature profile through the material's thickness was monitored during the heating using thermocouples near the top and bottom surfaces of the sheet. The bubble inflation test, combined with displacement, strain fields, and deformation rates at different locations, enables detailed characterization of the bubble's shape under large deformation. To address early-stage geometric instabilities due to sagging from thermal expansion, airflow was regulated with a precise flow control valve before inflation, while 3D-DIC monitored the real-time displacements to correct for sag deformation. The inflation pressure profile was recorded and synchronized with 3D-DIC strain evolution data for each test, allowing for analysis of the characteristic stress-strain curve at the pole. By evaluating the material's equi-biaxial properties at the pole and biaxial strain measurements away from the pole, the collected data provides a strong basis for future calibration of constitutive material models through an inverse approach, enabling accurate integration into process simulations.

关键词： above Tg | 3D-DIC biaxial large deformation bubble inflation test polymeric sheet strain evolution temperature uniformity thermoforming thickness calculation

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CNN-DST: Ensemble deep learning based on Dempster-Shafer theory for vibration-based fault recognition

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STRUCTURAL HEALTH mONITORING-AN INTERNATIONAL JOURNAL 2022年第5期21卷 2063-2082页

作者： Yaghoubi, Vahid Cheng, Liangliang Van Paepegem, Wim Kersemans, mathias Univ Ghent Mech Mat & Struct MMS Zwijnaarde Belgium SIM M3 Program Zwijnaarde Belgium

Nowadays, using vibration data in conjunction with pattern recognition methods is one of the most common fault detection strategies for structures. However, their performances depend on the features extracted from vibration data, the features selected to train the classifier, and the classifier used for pattern recognition. Deep learning facilitates the fault detection procedure by automating the feature extraction and selection, and classification procedure. Though, deep learning approaches have challenges in designing its structure and tuning its hyperparameters, which may result in a low generalization capability. Therefore, this study proposes an ensemble deep learning framework based on a convolutional neural network (CNN) and Dempster-Shafer theory (DST), called CNN-DST. In this framework, several CNNs with the proposed structure are first trained, and then, the outputs of the CNNs selected by the proposed technique are combined by using an improved DST-based method. To validate the proposed CNN-DST framework, it is applied to an experimental dataset created by the broadband vibrational responses of polycrystalline nickel alloy first-stage turbine blades with different types and severities of damage. Through statistical analysis, it is shown that the proposed CNN-DST framework classifies the turbine blades with an average prediction accuracy of 97.19%. The proposed CNN-DST framework is benchmarked with other state-of-the-art classification methods, demonstrating its high performance. The robustness of the proposed CNN-DST framework with respect to measurement noise is investigated, showing its high noise-resistance. Further, bandwidth analysis reveals that most of the required information for detecting faulty samples is available in a small frequency range.

关键词： Ensemble deep learning convolutional neural network Dempster-Shafer theory of evidence classifier selection fault recognition

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A Digital twin framework for Visco-Hyperelasticity calibration: Experiment and simulation

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INTERNATIONAL JOURNAL OF mECHANICAL SCIENCES 2025年 296卷

作者： Varedi, S. Rasoul Buffel, Bart Desplentere, Frederik Katholieke Univ Leuven Dept Mat Engn ProPoliS Res Grp Bruges CampusSpoorwegstr 12 B-8200 Brugge Belgium SIM M3 Program Technol Pk Zwijnaarde 48 B-9052 Zwijnaarde Belgium

modeling heavy gauge vacuum-assisted thermoforming is challenging due to material deformation, timedependent behavior, and mould-sheet friction. This study develops an adaptive methodology that integrates Finite Element model Updating (FEmU) to calibrate the visco-hyperelastic properties of ABS thermoplastic material within the thermo-vacuum forming range. Experimental data from a 3D Digital Image Correlation (DIC)-equipped biaxial bubble inflation test and step-strain relaxation tests were used to characterize the material behavior at 140 degrees C. A 2-term Ogden model combined with a Prony series captured material behavior. The objective function minimizes the Root mean Square (RmS) error between experimental and simulated strain data, focusing on equibiaxial deformation at the bubble's pole. The calibrated visco-hyperelastic model is further assessed under off-center biaxial deformation modes during bubble formation, leveraging the unique advantage of the bubble inflation test in capturing multiple deformation modes simultaneously. By integrating a real-time digital twin approach, an adapting method is proposed to dynamically optimize friction coefficient using strain evolution data from the contact zone during thermoforming. This ensures a more representative characterization of friction under actual forming conditions, capturing the interaction between the mould and the thermoplastic sheet more effectively. Subsequently, a vacuum-assisted thermoforming simulation on a positive semi-spherical mould was performed to validate the calibrated model. The thickness distribution along the centerline of the sheet showed strong agreement with experimental data, particularly in capturing the thinning effect in highly stretched regions near the corner. This research improves predictive modeling for industrial thermoforming processes.

关键词： material characterization Viscoelasticity Bubble inflation test Digital twin Vacuum-Assisted Thermoforming Thickness Variation

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Integrated interval mahalanobis classification system for the quality classification of turbine blades based on vibrational data incorporating measurement uncertainty

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STRUCTURAL HEALTH mONITORING-AN INTERNATIONAL JOURNAL 2023年第1期22卷 166-179页

作者： Cheng, Liangliang Yaghoubi, Vahid Van Paepegem, Wim Kersemans, mathias Univ Ghent Mech Mat & Struct MMS Technol Pk B-9052 Ghent 46 Zwijnaarde Belgium SIM Program M3 Detect ION Ghent Zwijnaarde Belgium

measurements are not exactly accurate, and measurement errors could lead to a biased trained classifier, and finally to a wrong classification of the parts. This paper extends the recently proposed (Integrated) mahalanobis Classification System with the concept of Interval mahalanobis distance (ImD) in order to account for measurement uncertainty. This novel Integrated Interval mahalanobis Classification System (IImCS) is applied to an experimental case study of complex shaped metallic turbine blades with various damage types. The turbine blades have been vibrationally tested in a wide frequency range. The IImCS selects a subset of optimal features that contribute the most to the system under the framework of Binary Particle Swarm Optimization, and determines the optimal decision threshold based on Particle Swarm Optimizer. A monte Carlo method (mCm) is implemented to account for measurement uncertainty, and as such yields an indicator of reliability, implying the confidence level of the classification results. The obtained results illustrate a high performance of the IImCS for classifying turbine blades based on vibrational response data with measurement uncertainty.

关键词： integrated mahalanobis classification system interval mahalanobis distance feature selection classification binary particle swarm optimization non-destructive testing uncertainty propagation monte Carlo method

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Investigation of microstructural and mechanical properties of weld lines in injection-molded short glass fiber-reinforced polyamide 6

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POLYmER COmPOSITES 2024年第10期45卷 8905-8920页

作者： mokarizadehhaghighishirazi, majid Buffel, Bart Lomov, Stepan V. Desplentere, Frederik KU Leuven Campus Bruges Dept Mat Engn Res Grp ProPoliS Spoorwegstr 12 B-8200 Brugge Belgium SIM M3 Program Leuven Belgium Katholieke Univ Leuven Dept Mat Engn Leuven Belgium

This research investigates the impact of weld lines on the mechanical properties and fracture behavior of injection-molded unfilled and glass fiber-reinforced polyamide 6 (PA6). The study aims to predict the weld line strength by analyzing the composite's microstructure at the weld line and investigating the influence of injection molding parameters. While weld lines had minimal effects in unfilled PA6 thanks to the matrix's high healing capability, composite samples showed reduced mechanical properties due to unfavorable fiber orientation at the weld line. Fracture surfaces revealed a bell-shaped structure linked to the 'underflow' process caused by flow imbalances during injection molding. This phenomenon impacts fiber orientation at the weld line, affecting mechanical properties. The 'underflow' is simulated using Autodesk moldflow (R), predicting enhanced fiber alignment along the flow direction. Regarding processing parameters, both melt and mold temperatures showed negligible impacts, while enhanced mechanical properties were observed at elevated packing pressures. The analysis of fracture surfaces showed intensified "underflow" with increased packing pressure. A relationship is established between weld line strength and fiber orientation at the weld line, potentially serving as a predictive tool for estimating weld line strength. Highlights Weld lines in unfilled PA6:Negligible impact on the mechanical properties. In the PA6 composite: significant drop due to unfavorable fiber orientation. Fracture behavior of the composite: Bell-shaped weld line linked to "underflow." melt and mold temperature: minor effect;packing pressure enhances properties. Correlation established between the weld line strength and fiber orientation.

关键词： fiber orientation injection molding short fiber reinforced polymers weld lines

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A novel multi-classifier information fusion based on Dempster-Shafer theory: application to vibration-based fault detection

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STRUCTURAL HEALTH mONITORING-AN INTERNATIONAL JOURNAL 2022年第2期21卷 596-612页

作者： Yaghoubi, Vahid Cheng, Liangliang Van Paepegem, Wim Kersemans, mathias Univ Ghent Mech Mat & Struct MMS Technol Pk 46 B-9052 Ghent Belgium SIM M3 Program Ghent Belgium

Achieving a high prediction rate is a crucial task in fault detection. Although various classification procedures are available, none of them can give high accuracy in all applications. Therefore, in this article, a novel multi-classifier fusion approach is developed to boost the performance of the individual classifiers. This is acquired by using Dempster-Shafer theory. However, in cases with conflicting evidences, the Dempster-Shafer theory may give counterintuitive results. In this regard, a preprocessing technique based on a new metric is devised in order to measure and mitigate the conflict between the evidences. To evaluate and validate the effectiveness of the proposed approach, the method is applied to 15 benchmarks datasets from UCI and KEEL. Furthermore, it is applied for classifying polycrystalline nickel alloy first-stage turbine blades based on their broadband vibrational response. Through statistical analysis with different noise levels, and by comparing with four state-of-the-art fusion techniques, it is shown that the proposed method improves the classification accuracy and outperforms the individual classifiers.

关键词： Ensemble learning classifier fusion fault detection Dempster-Shafer theory vibration data

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Relation between ASTm E606 specimen geometry and misalignment in strain-controlled fatigue testing

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INTERNATIONAL JOURNAL OF FATIGUE 2023年 166卷

作者： Han, Shiwei Dinh, Tien Dung De Baere, Ives Van Paepegem, Wim Univ Ghent Fac Engn & Architecture Dept Mat Text & Chem Engn Technologiepk Zwijnaarde 46 B-9052 Zwijnaarde Belgium SIM M3 Program Technologiepk-Zwijnaarde 48 B-9052 Zwijnaarde Belgium

In strain-controlled fatigue testing, a conventional extensometer is usually used to measure the average strain between its two blades. However, the actual strain distribution in the gauge section cannot be revealed by the extensometer. To measure this distribution during strain-controlled fatigue testing of 304 stainless steel, stereo Digital Image Correlation (stereo-DIC) was used in this study. Three different geometries with two of them satisfying ASTm standard E606/E606m-12 were tested in strain-controlled fatigue testing with two representative strain amplitudes of +/- 1.0% and +/- 1.5% on a properly aligned testing machine. At both strain amplitudes, the two geometries in line with ASTm standard E606/E606m-12 exhibit evident nonuniform strain distribution under compression already from the very first cycle while the geometry proposed by the authors (not according to the ASTm standard E606/E606m-12) has better uniformity in axial strain ***, a novel fixture is designed to monitor the misalignment of the specimens in the fatigue testing. Benefiting from the novel fixture and the stereo-DIC technique, not only the deformation in the gauge section of the specimen can be captured but also the misalignment between both ends of the specimen can be extracted by post-processing. The measured misalignment has been further used as boundary conditions in simulating the mechanical response of those three geometries under cyclic loading. Numerical simulation has successfully reproduced the nonuniform strain distribution under compression, which validates the stereo-DIC measurements. It suggests that while even following the ASTm standard E606/E606m-12, uniformity in strain distribution under compression cannot be ensured and thus might render the constitutive laws calibrated from strain-controlled fatigue testing invalid, since uniform stress and strain across the gauge section of the specimens were falsely assumed.

关键词： Strain -controlled fatigue Low -cycle fatigue misalignment Stereo -digital image correlation ASTm standard E606 E606m-12

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Direct embedment of RVE-based microscale into lab size coupons to research fracture process in unidirectional and bidirectional composites

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COmPOSITES SCIENCE AND TECHNOLOGY 2023年 235卷

作者： Laheri, V. Hao, P. Gilabert, F. A. Univ Ghent Dept Mat Text & Chem Engn Tech Lane Ghent Sci Pk Campus ATechnol Pk Zwijnaa B-9052 Zwijnaarde Belgium SIM M3 Program B-9052 Zwijnaarde Belgium

The structural applicability of fibre-reinforced polymer (FRP) composites requires testing for their resilience against fracture. The paper presents a virtual tool to configure the microscale geometrical model constituting the representative volume element embedded in the homogeneous macroscale region, providing an alternative to the tedious experimental procedures. The conformal meshing strategies in the microregion are also eluci-dated in the paper. The microscale model is enriched with the constitutive material models exhibiting complex phenomena of individual constituents of the composite and cohesive damage properties. The elastoplastic and elastic-viscoplastic material models coupled with the energy-based and rate-dependent damage initiation criteria, respectively, are applied to the matrix. At the same time, the fibre-matrix interface is treated with the weak traction-separation law. Through the virtual tool, the microscale region allows to make an insightful study of the toughness mechanism and visualise the damage initiation and propagation in the FRP structure at different fracture modes.

关键词： Embedded multiscale modelling Representative volume element Strain-rate dependency Fracture toughness Single-edge notch test

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Correction of erroneous normal stress calculation for critical plane based fatigue criteria

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INTERNATIONAL JOURNAL OF FATIGUE 2025年 193卷

作者： Faes, Jana Christine Dinh, Tien Dung Lammens, Nicolas Van Paepegem, Wim Univ Ghent Dept Mat Text & Chem Engn MaTCh Technol Pk Zwijnaarde 46 B-9052 Ghent Belgium M3 Program SIM Technol Pk Zwijnaarde 48 B-9052 Ghent Belgium Siemens Ind Software NV Interleuvenlaan 68 B-3001 Leuven Belgium

Fatigue criteria for nonproportional loading often rely on the premise that damage initiates on the plane with the highest shear stress range. Due to the reciprocity of shear stress, at least two equivalent planes in 3D space can be found. Among these, the most critical plane is determined by its normal stress, as tensile stress on the crack surface facilitates damage formation. many loading scenarios give rise to multiple or even an infinite number of planes with identical shear stress ranges, making it challenging to identify the most critical one. Current critical plane search methods do not address this problem, even though incorrect assessments of normal stress can lead to substantial overestimation of the fatigue life - by up to several orders of magnitude. In this work, we present anew procedure that reliably identifies the most critical plane by explicitly considering normal stress when multiple planes exhibit equivalent shear stress ranges. Our findings show that state-ofthe-art methods introduce substantial errors in more than 10% of sinusoidal loading scenarios by failing to account for this additional criterion.

关键词： Critical plane Fatigue maximum Variance method mVm

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Parametric energy conserving sampling and weighting for the thermal analysis of Selective Laser melting

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COmPUTATIONAL mECHANICS 2024年第6期73卷 1401-1419页

作者： Ben Yahmed, mohamed Amine Naets, Frank Katholieke Univ Leuven Dept Mech Engn Celestijnenlaan 300 B-3001 Heverlee Belgium Flanders Make E2E Core Lab Celestijnenlaan 300 B-3001 Heverlee Belgium SIM M3 program Technol Pk 935 B-9052 Zwijnaarde Belgium

This work investigates the application of model Order Reduction (mOR) to the case of a non-linear heat transfer simulation, which pertains to Selective Laser melting (SLm). A hyper-reduction strategy, relying on the Energy Conserving Sampling and Weighting (ECSW) method, is presented before being implemented within an adaptative POD-Greedy algorithm to build a more general reduced order base composed of versatile thermal modes. To this end, an a-posteriori error estimator is used alongside Ordinary Kriging to evaluate the degree of error committed during the parametrized-mOR process. The approach introduces a novel scheme called parametric Energy Conserving Sampling and Weighting (pECSW), which extends the applicability of the sparse selection of finite elements for larger parametric ranges than what is possible with the regular ECSW approach. Hence, the generic property of the final layout avoids launching an optimization strategy for new model analysis.

关键词： model Order Reduction Selective Laser melting Non-linear heat transfer Parametric ECSW

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