Predicting Critical Loads in U-Notched 3D-Printed ASA and Carbon Fiber Reinforced ASA Specimens Using Failure Assessment Diagrams

Abstract The mechanical behavior of 3D printed polymeric materials, and particularly those obtained through Fused Filament Fabrication (FFF), is being increasingly investigated in the last years with the aim of scaling the use of such materials from prototyping purposes to structural applications. In this regard, acrylonitrile-styrene-acrylate (ASA) terpolymer emerges as a promising option, whether printed alone or as the matrix in diverse composite materials. ASA polymer displays outstanding resistance to weathering agents and, interestingly, to ultraviolet (UV) light, making it more appropriate for outdoors applications than other widely used alternatives such as acrylonitrile butadiene styrene (ABS) which tend to degrade faster. ASA also presents heat and oil resistance (preventing discoloration), reasonable mechanical properties, both dimensional and thermal stability and relatively greater resistance to environmental stress cracking (when compared to ABS), among other properties. This being said, one of the necessary requirements when studying the structural use of a given material is to have tools for evaluating its structural integrity in the presence of defects, regardless of their origin (e.g., material manufacturing, structural design, construction process, operational use, etc.) and their severity (from sharp cracks to blunt notches). In this sense, this paper provides an analysis of fracture loads in 3D printed (FFF) single edge notched bending (SENB) specimens containing U-notches and made of pure ASA and carbon fiber reinforced (10 wt.%) ASA. The specimens cover three different raster orientations (0/90, 45/−45 and 30/−60) and contain four different notch radii (0 mm – corresponding to crack-like defects-, 0.5 mm, 1 mm and 2 mm). Additionally, six specimens per combination of material, raster orientation and notch radius were tested in order to capture the scatter of the fracture results. The fracture loads were predicted using the FAD (Failure Assessment Diagram, BS7910 Option 1) methodology in conjunction with the Theory of Critical Distances (TCD, which evaluates the material sensitivity to the notch effect), leading to the FAD-TCD approach. The results show how this FAD-TCD approach, in spite of the fact that FADs were originally proposed for the analysis of metallic materials and crack-like defects, is capable of providing accurate predictions of fracture loads for this type of 3D printed polymeric and composite materials when containing notch-type defects. The safety of the predictions relies directly on the criterion (in terms of probability of failure) assumed to define the fracture toughness level included in the FAD approach.

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Published
2025-07-20
DOI
https://doi.org/10.1115/pvp2025-152706
Primary Topic
Industrial Vision Systems and Defect Detection
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article
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article

Predicting Critical Loads in U-Notched 3D-Printed ASA and Carbon Fiber Reinforced ASA Specimens Using Failure Assessment Diagrams

Borja Arroyo, Sergio Cicero, Sergio Arrieta, Fabrizia Devito
Industrial Vision Systems and Defect Detection
article

Predicting Critical Loads in U-Notched 3D-Printed ASA and Carbon Fiber Reinforced ASA Specimens Using Failure Assessment Diagrams

Borja Arroyo, Sergio Cicero, Sergio Arrieta, Fabrizia Devito
article en

Abstract

Abstract The mechanical behavior of 3D printed polymeric materials, and particularly those obtained through Fused Filament Fabrication (FFF), is being increasingly investigated in the last years with the aim of scaling the use of such materials from prototyping purposes to structural applications. In this regard, acrylonitrile-styrene-acrylate (ASA) terpolymer emerges as a promising option, whether printed alone or as the matrix in diverse composite materials. ASA polymer displays outstanding resistance to weathering agents and, interestingly, to ultraviolet (UV) light, making it more appropriate for outdoors applications than other widely used alternatives such as acrylonitrile butadiene styrene (ABS) which tend to degrade faster. ASA also presents heat and oil resistance (preventing discoloration), reasonable mechanical properties, both dimensional and thermal stability and relatively greater resistance to environmental stress cracking (when compared to ABS), among other properties. This being said, one of the necessary requirements when studying the structural use of a given material is to have tools for evaluating its structural integrity in the presence of defects, regardless of their origin (e.g., material manufacturing, structural design, construction process, operational use, etc.) and their severity (from sharp cracks to blunt notches). In this sense, this paper provides an analysis of fracture loads in 3D printed (FFF) single edge notched bending (SENB) specimens containing U-notches and made of pure ASA and carbon fiber reinforced (10 wt.%) ASA. The specimens cover three different raster orientations (0/90, 45/−45 and 30/−60) and contain four different notch radii (0 mm – corresponding to crack-like defects-, 0.5 mm, 1 mm and 2 mm). Additionally, six specimens per combination of material, raster orientation and notch radius were tested in order to capture the scatter of the fracture results. The fracture loads were predicted using the FAD (Failure Assessment Diagram, BS7910 Option 1) methodology in conjunction with the Theory of Critical Distances (TCD, which evaluates the material sensitivity to the notch effect), leading to the FAD-TCD approach. The results show how this FAD-TCD approach, in spite of the fact that FADs were originally proposed for the analysis of metallic materials and crack-like defects, is capable of providing accurate predictions of fracture loads for this type of 3D printed polymeric and composite materials when containing notch-type defects. The safety of the predictions relies directly on the criterion (in terms of probability of failure) assumed to define the fracture toughness level included in the FAD approach.

Universidad de Cantabria (ES), Polytechnic University of Bari (IT)
Openalex Percentile: Top 60%
Industrial Vision Systems and Defect Detection
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