MICROSTRUCTURE-BASED HOMOGENIZATION OF ELASTIC PROPERTIES IN ADDITIVELY MANUFACTURED THERMOPLASTIC COMPOSITES

Additive manufacturing (AM) of fiber-reinforced thermoplastic composites has emerged as a promising technology, enabling the fabrication of lightweight, complex geometries with reduced material waste and lower production costs. Among various AM methods, composites-based additive manufacturing (CBAM) has gained attention for its rapid prototyping and producing parts with enhanced mechanical properties. Regardless of these benefits, CBAM-printed composites may inherently possess a certain level of defects introduced during the manufacturing process, such as voids, microcracks, and non-uniform porosity. To address these challenges, understanding the relationship between microstructural characteristics and effective mechanical properties is critical. Micro-computed tomography (μCT) is a powerful technique for characterizing the internal microstructure (i.e., fiber and porosity size, distribution) of a composite. This study presents a microstructure-based micromechanical finite element (FE) model predicting the effective mechanical properties of non-woven carbon fabric (CF) reinforced nylon (PA-12) composites, fabricated using CBAM. Three distinct RVE models of various sizes were developed, each capturing μCT image from different locations, and used to determine the effective properties of CBAM-printed CF/PA-12 specimens. This work aims to develop an efficient micromechanical framework to understand the relationship between microstructural characteristics and effective properties of additively manufactured thermoplastic composites.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.33599/nasampe/s.25.0113
Citations
3
Primary Topic
Additive Manufacturing and 3D Printing Technologies
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article
Field-Weighted Citation Impact
2.05
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article

MICROSTRUCTURE-BASED HOMOGENIZATION OF ELASTIC PROPERTIES IN ADDITIVELY MANUFACTURED THERMOPLASTIC COMPOSITES

Moustapha Hassan, Juhyeong Lee, Samiul Alam
3 citations
Additive Manufacturing and 3D Printing Technologies
2.05
article

MICROSTRUCTURE-BASED HOMOGENIZATION OF ELASTIC PROPERTIES IN ADDITIVELY MANUFACTURED THERMOPLASTIC COMPOSITES

Moustapha Hassan, Juhyeong Lee, Samiul Alam
article en
3 citations

Abstract

Additive manufacturing (AM) of fiber-reinforced thermoplastic composites has emerged as a promising technology, enabling the fabrication of lightweight, complex geometries with reduced material waste and lower production costs. Among various AM methods, composites-based additive manufacturing (CBAM) has gained attention for its rapid prototyping and producing parts with enhanced mechanical properties. Regardless of these benefits, CBAM-printed composites may inherently possess a certain level of defects introduced during the manufacturing process, such as voids, microcracks, and non-uniform porosity. To address these challenges, understanding the relationship between microstructural characteristics and effective mechanical properties is critical. Micro-computed tomography (μCT) is a powerful technique for characterizing the internal microstructure (i.e., fiber and porosity size, distribution) of a composite. This study presents a microstructure-based micromechanical finite element (FE) model predicting the effective mechanical properties of non-woven carbon fabric (CF) reinforced nylon (PA-12) composites, fabricated using CBAM. Three distinct RVE models of various sizes were developed, each capturing μCT image from different locations, and used to determine the effective properties of CBAM-printed CF/PA-12 specimens. This work aims to develop an efficient micromechanical framework to understand the relationship between microstructural characteristics and effective properties of additively manufactured thermoplastic composites.

Openalex Percentile: Top 13%
Additive Manufacturing and 3D Printing Technologies
2.05
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MICROSTRUCTURE-BASED HOMOGENIZATION OF ELASTIC PROPERTIES IN ADDITIVELY MANUFACTURED THERMOPLASTIC COMPOSITES — Moustapha Hassan, Juhyeong Lee, et al. · (2025) | TGRS Research Map | TGRS