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A feasibility study of the Master SN curve approach for short fiber reinforced composites

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Abstract
Short fiber reinforced composite (SFRC) materials have a different fiber orientation distribution (FOD) at every point. The fatigue properties of SFRC are known to depend on the FOD. The Master SN curve (MSNC) method for predicting an SN curve for a given FOD based on the known SN curve for the reference FOD is used to predict the local SN curve of a SFRC component by relating the damage at the microscopic level to the macroscopic fatigue properties. A simplified version of MSNC method, which needs even less experimental input, uses an assumption of constant SN curve slope is also presented in this paper. The paper validates both variants of the MSNC method on three sets of experimental data on fatigue of short fiber composites and analyses their accuracy. It is demonstrated that the MSNC approach needs only one SN curve as input with no specific requirements to the fiber orientation of the test coupon. Test coupons could have either uniform fiber orientation in the thickness or a "skin core" orientation variation. (C) 2016 Elsevier Ltd. All rights reserved.
Keywords
SHORT GLASS, POLYMER COMPOSITES, FATIGUE BEHAVIOR, ORIENTATION, POLYAMIDE, DAMAGE, MECHANISMS, INCLUSIONS, MATRIX, THERMOPLASTICS, Composites, Micromechanics, Simulation (numerical, experimental), SN, curves

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Chicago
Jain, Atul, Wim Van Paepegem, Ignaas Verpoest, and Stepan V. Lomov. 2016. “A Feasibility Study of the Master SN Curve Approach for Short Fiber Reinforced Composites.” International Journal of Fatigue 91: 264–274.
APA
Jain, Atul, Van Paepegem, W., Verpoest, I., & Lomov, S. V. (2016). A feasibility study of the Master SN curve approach for short fiber reinforced composites. INTERNATIONAL JOURNAL OF FATIGUE, 91, 264–274.
Vancouver
1.
Jain A, Van Paepegem W, Verpoest I, Lomov SV. A feasibility study of the Master SN curve approach for short fiber reinforced composites. INTERNATIONAL JOURNAL OF FATIGUE. Oxford: Elsevier Sci Ltd; 2016;91:264–74.
MLA
Jain, Atul, Wim Van Paepegem, Ignaas Verpoest, et al. “A Feasibility Study of the Master SN Curve Approach for Short Fiber Reinforced Composites.” INTERNATIONAL JOURNAL OF FATIGUE 91 (2016): 264–274. Print.
@article{8533621,
  abstract     = {Short fiber reinforced composite (SFRC) materials have a different fiber orientation distribution (FOD) at every point. The fatigue properties of SFRC are known to depend on the FOD. The Master SN curve (MSNC) method for predicting an SN curve for a given FOD based on the known SN curve for the reference FOD is used to predict the local SN curve of a SFRC component by relating the damage at the microscopic level to the macroscopic fatigue properties. A simplified version of MSNC method, which needs even less experimental input, uses an assumption of constant SN curve slope is also presented in this paper. The paper validates both variants of the MSNC method on three sets of experimental data on fatigue of short fiber composites and analyses their accuracy. It is demonstrated that the MSNC approach needs only one SN curve as input with no specific requirements to the fiber orientation of the test coupon. Test coupons could have either uniform fiber orientation in the thickness or a {\textacutedbl}skin core{\textacutedbl} orientation variation. (C) 2016 Elsevier Ltd. All rights reserved.},
  author       = {Jain, Atul and Van Paepegem, Wim and Verpoest, Ignaas and Lomov, Stepan V.},
  issn         = {0142-1123},
  journal      = {INTERNATIONAL JOURNAL OF FATIGUE},
  keyword      = {SHORT GLASS,POLYMER COMPOSITES,FATIGUE BEHAVIOR,ORIENTATION,POLYAMIDE,DAMAGE,MECHANISMS,INCLUSIONS,MATRIX,THERMOPLASTICS,Composites,Micromechanics,Simulation (numerical,experimental),SN,curves},
  language     = {eng},
  pages        = {264--274},
  publisher    = {Elsevier Sci Ltd},
  title        = {A feasibility study of the Master SN curve approach for short fiber reinforced composites},
  url          = {http://dx.doi.org/10.1016/j.ijfatigue.2016.06.015},
  volume       = {91},
  year         = {2016},
}

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