4.7 Article

On the visco-elasto-plastic response of additively manufactured polyamide-12 (PA-12) through selective laser sintering

Journal

POLYMER TESTING
Volume 57, Issue -, Pages 149-155

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.polymertesting.2016.11.032

Keywords

-

Funding

  1. Strategic Initiative for Materials (SIM-Flanders) through the M3-AMCAE (IWT-project) [130526/27]
  2. A-STREAM-AFO (IWT-project) [140164/65]

Ask authors/readers for more resources

This work presents an in-depth study on the mechanical behavior of selective laser sintered (SLS) nylon (PA-12). The entire visco-elasto-plastic response is determined based on experimental data obtained through tensile, compression, shear and relaxation testing. In addition, ultrasonic non-destructive testing is proposed as an alternative to conventional testing for the derivation of the elastic properties of this material. An isotropic elastic behavior was observed, while a clear orthotropic and non-linear response was found for both the plastic curves and the relaxation behavior. Strength data suggests laser sintered PA-12 will fail in tension rather than in shear. The ultrasonic tests correspond well to conventional tensile data (at high rates), and represent a cost-effective alternative to extensive conventional tensile testing. The presented test data can potentially be used to derive a detailed material model suitable for modelling static, fatigue and impact applications using 3D printed PA-12. (C) 2016 Elsevier Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Instruments & Instrumentation

3D intra-cellular wave dynamics in a phononic plate with ultra-wide bandgap: attenuation, resonance and mode conversion

Saeid Hedayatrasa, Mathias Kersemans

Summary: The intra-cellular wave dynamics of a water jetted phononic plate were experimentally investigated using high-resolution three-dimensional scanning laser Doppler vibrometry. The study focused on the vibrational behavior around the ultra-wide bandgap of the plate and validated the attenuation and resonance of both symmetric and antisymmetric wave modes. The results demonstrated the effective excitation of symmetric modes through mode conversion.

SMART MATERIALS AND STRUCTURES (2022)

Article Construction & Building Technology

Phase inversion in (vibro-)thermal wave imaging of materials: Extracting the AC component and filtering nonlinearity

Saeid Hedayatrasa, Gaetan Poelman, Joost Segers, Wim Van Paepegem, Mathias Kersemans

Summary: The study introduces the concept of phase inversion in thermographic inspection to decouple the AC component and filter second-order nonlinearities from the thermal response. The effectiveness of this phase inversion thermography (PIT) is theoretically substantiated and verified by finite element simulation. PIT robustly resolves the transient excitation and systematically decouples an AC response equivalent to the thermal response to an ideally linear and bipolar excitation.

STRUCTURAL CONTROL & HEALTH MONITORING (2022)

Article Engineering, Multidisciplinary

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

Vahid Yaghoubi, Liangliang Cheng, Wim Van Paepegem, Mathias Kersemans

Summary: Using vibration data and pattern recognition methods together is a common fault detection strategy for structures. This study proposes a deep learning framework, called CNN-DST, which combines convolutional neural networks and Dempster-Shafer theory to automate the feature extraction, selection, and classification processes. The proposed framework achieves a high prediction accuracy of 97.19% in classifying turbine blades with different types and severities of damage and shows robustness against measurement noise.

STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2022)

Article Engineering, Multidisciplinary

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

Liangliang Cheng, Vahid Yaghoubi, Wim Van Paepegem, Mathias Kersemans

Summary: This paper proposes a novel Integrated Interval Mahalanobis Classification System (IIMCS) to accurately classify turbine blades based on vibrational response data with measurement uncertainty.

STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL (2023)

Article Mechanics

A comparative study for calculating dispersion curves in viscoelastic multi-layered plates

Adil Han Orta, Mathias Kersemans, Koen Van Den Abeele

Summary: This study critically compares various commonly used models for calculating complex wavenumbers in viscoelastic orthotropic multi-layer materials. The accuracy and computational efficiency of these models are analyzed for material characterization. A comparative analysis is also performed on the through thickness displacement fields in the solid medium.

COMPOSITE STRUCTURES (2022)

Article Chemistry, Analytical

On the Identification of Orthotropic Elastic Stiffness Using 3D Guided Wavefield Data

Adil Han Orta, Mathias Kersemans, Koen Van den Abeele

Summary: This study investigates the effect of using the in-plane and out-of-plane components of the recorded vibration velocity in the inverse determination of stiffness parameters in scanning laser Doppler vibrometry. The results show that accounting for the in-plane component leads to a more accurate and robust determination of the stiffness parameters.

SENSORS (2022)

Article Engineering, Multidisciplinary

Enhanced thermographic inspection of woven fabric composites by k-space filtering

Gaetan Poelman, Saeid Hedayatrasa, Wim Van Paepegem, Mathias Kersemans

Summary: This paper introduces an improved infrared thermography method for detecting defects in woven fabric composites. The k-space filtering technique is applied to automatically decompose the thermographic image into a structured thermal background image related to the weave pattern, and a residual image representing other features (such as defects). The proposed method demonstrates enhanced performance in defect detection and sizing.

COMPOSITES PART B-ENGINEERING (2023)

Article Engineering, Multidisciplinary

Machine learning-based orthotropic stiffness identification using guided wavefield data

Adil Han Orta, Jasper De Boer, Mathias Kersemans, Celine Vens, Koen Van Den Abeele

Summary: In this study, the elastic stiffness parameters of orthotropic plates are identified using a multilayer perceptron algorithm and guided wavefield data. A large training dataset is created using a semi-analytical finite element model, and the influence of training dataset size and signal-to-noise ratio on the inference outcome is examined. The performance of the multilayer perceptron-based method is validated on a numerical dataset and applied to experimental data from a multilayered glass-fiber reinforced polyamide 6 composite plate. The results of the multilayer perceptron-based method are compared with a traditional inversion algorithm, showing a difference of less than 0.5%.

MEASUREMENT (2023)

Article Engineering, Mechanical

Characterization of the full complex-valued stiffness tensor of orthotropic viscoelastic plates using 3D guided wavefield data

Adil Han Orta, Mathias Kersemans, Nicolaas Bernardus Roozen, Koen Van Den Abeele

Summary: A two-stage inversion scheme is proposed to determine the complex-valued stiffness properties of orthotropic viscoelastic plates using their 3D surface velocity response. The hybrid TLS-ESPRIT and IWC method is used to extract the complex-valued wavenumber-frequency pairs corresponding to relevant Lamb wave and shear horizontal plate waves. Particle swarm optimization is employed to inversely determine the plate's orthotropic viscoelastic properties. Numerical simulations and experimental measurements validate the accuracy of the proposed method, showing a close agreement with the target values.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2023)

Article Materials Science, Characterization & Testing

On the ultrasonic characterization of the stacking sequence of CFRP laminates

Xiaoyu Yang, Mathias Kersemans

Summary: This study investigates the use of pulse-echo ultrasound testing in different frequency ranges to characterize the in-plane fiber angle distribution and ply stacking sequence in a multi-layer composite laminate. Minimization of the Mumford-Shah functional is performed as an edge-preserving smoothing procedure for the recorded ultrasound dataset, followed by the application of a Gabor Filter-based Information Diagram approach to extract a 3D tomographic image of the fiber angles.

NDT & E INTERNATIONAL (2023)

Article Materials Science, Characterization & Testing

An efficient parametrized optical infrared thermography 3D finite element framework for computer vision applications

Zongfei Tong, Saeid Hedayatrasa, Liangliang Cheng, Cuixiang Pei, Zhenmao Chen, Shejuan Xie, Mathias Kersemans

Summary: This paper proposes a parametrized 3D finite element (FE) framework for simulating optical infrared thermographic inspection of multi-layer anisotropic media and generating a large-scale virtual dataset. The interface element is introduced for simulating various defect types, and non-uniform heating conditions and a stochastic morphology generator are used for realistic simulation. The trained Faster-RCNN model demonstrates excellent performance on experimental thermographic data.

NDT & E INTERNATIONAL (2023)

Article Polymer Science

Characterizing Pure Polymers under High Speed Compression for the Micromechanical Prediction of Unidirectional Composites

Pei Hao, Siebe W. F. Spronk, Ruben D. B. Sevenois, Wim van Paepegem, Francisco A. Gilabert

Summary: The nonlinear behaviour of FRPC in transverse loading is mainly induced by the constituent polymer matrix, which is rate- and temperature-dependent. This paper presents a test setup to provide robust stress-strain measurements for FRPC at high strain rates. The micro- and macroscopic thermomechanical response of CF/PR520 and CF/PEEK systems are analyzed, showing excessive strain localization and discussing the differences between thermoplastic and thermoset matrices.

POLYMERS (2023)

Article Engineering, Mechanical

Diffusion-compensated correlation analysis of frequency-modulated thermal signal for quantitative infrared thermography

Saeid Hedayatrasa, Wim Van Paepegem, Mathias Kersemans

Summary: The technique of thermal wave radar or pulse compression thermography, which utilizes a broadband modulated excitation signal and its cross-correlation with the thermal response, is widely used in active infrared thermography for defect characterization. However, the distortion of the thermal response due to heat diffusion affects the efficiency of cross-correlation analysis, especially for deep defects or materials with different thermal diffusivity. To overcome this issue, diffusion-compensated correlation analysis (DCCA) thermal signal is proposed, using a frequency-modulated sweep signal as an excitation waveform. DCCA can accurately analyze the thermal response in the presence of measurement noise, and can directly map the corresponding depth or diffusivity based on a library of template thermal responses. The performance of DCCA is analytically substantiated and verified through simulations and experiments on carbon fiber reinforced polymer plates, showing its superiority over thermal wave radar. The technique has potential for thermographic inspection of materials with artificial defects.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2023)

Article Engineering, Mechanical

Ultrasonic imaging of damage in plates in spectral ripple frequency domain

Xiaoyu Yang, Mathias Kersemans

Summary: This paper proposes a C-scan imaging technique in the spectral ripple frequency domain, which improves the evaluation of complex and distributed defects in multilayer heterogeneous materials. The method processes the full A-scan signal without time gate, making it suitable for curved or tilted parts. It has been successfully demonstrated on carbon fiber reinforced polymer laminates with barely visible impact damage, showing its capability to resolve neighboring delaminations and small defects.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2023)

Article Materials Science, Characterization & Testing

A flexible deep learning framework for thermographic inspection of composites

Zongfei Tong, Liangliang Cheng, Shejuan Xie, Mathias Kersemans

Summary: Infrared thermography (IRT) is a promising technique for defect detection in various materials. This study proposes an object detection algorithm based on Faster R-CNN for efficient extraction of defect features from IRT images. A virtual thermographic dataset for composite materials was constructed using a parameterized 3D finite element simulator. The deep learning framework trained on this dataset achieved high performance in the automated thermographic inspection of composite parts.

NDT & E INTERNATIONAL (2023)

No Data Available