Fiber Orientation Distribution Predictions for an Injection Molded Venturi-Shaped Part Validated Against Experimental Micro-Computed Tomography Characterization

This work evaluates and compares the accuracy of different fiber orientation prediction models for a short fiber reinforced injection molded Venturi-shaped part which displays variable thickness. The experimental characterization of the specimen fiber orientation distribution (FOD) was carried out b...

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Main Authors: María C. Quintana, Patricia M. Frontini, Aitor Arriaga, Bernhard Plank, Zoltan Major
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-07-01
Series:Frontiers in Materials
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fmats.2020.00169/full
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spelling doaj-497ba5e994ac4db2ba04bef2d025a8522020-11-25T03:04:28ZengFrontiers Media S.A.Frontiers in Materials2296-80162020-07-01710.3389/fmats.2020.00169545036Fiber Orientation Distribution Predictions for an Injection Molded Venturi-Shaped Part Validated Against Experimental Micro-Computed Tomography CharacterizationMaría C. Quintana0Patricia M. Frontini1Aitor Arriaga2Bernhard Plank3Zoltan Major4Instituto de Investigaciones en Ciencia y Tecnología de Materiales (INTEMA), Universidad Nacional de Mar del Plata, Mar del Plata, ArgentinaInstituto de Investigaciones en Ciencia y Tecnología de Materiales (INTEMA), Universidad Nacional de Mar del Plata, Mar del Plata, ArgentinaLeartiker-Lea Artibai Ikastetxea, Markina-Xemein, SpainTechnology & Environmental Sciences Department, University of Applied Sciences Upper Austria, Wels, AustriaInstitut für Polymer Product Engineering (IPPE), Johannes Kepler Universität Linz, Linz, AustriaThis work evaluates and compares the accuracy of different fiber orientation prediction models for a short fiber reinforced injection molded Venturi-shaped part which displays variable thickness. The experimental characterization of the specimen fiber orientation distribution (FOD) was carried out by the micro computed tomography technique (micro-CT). The computational study of fiber orientation predictions was performed using Moldex3D. All the possible combinations of the Folgar-Tucker (FT) and improved Anisotropic Rotary Diffusion (iARD) rotary diffusion models and the Hybrid (Hyb), Orthotropic (ORE), and Invariant Based Optimal Fitting (IBOF) closure approximations were considered. The relevance of the Retardant Principal Rate (RPR) model on predictions results was also evaluated. The values of the fiber-fiber (Ci), matrix-fiber (Cm) interaction coefficients and the alpha-RPR parameter were varied in a significant range in order to find the set of parameters that better fits the experimental fiber orientation data. The parameters' sensitivity effect over the second order orientation tensor components was quantified via the Analysis of Variance (ANOVA) statistical method. The experimental micro-CT results show an increase in the fiber orientation degree at the specimen constriction region due to the narrowed cavity and the Venturi effect. The comparison of the experimental and predicted orientation profiles demonstrates that the predictions of the iARD model, in combination with the IBOF closure approximation, are the most accurate for the case studied. However, simulations fail to estimate the change in orientation caused by variable thickness and section. ANOVA results prove that the orientation tensor component in the flow direction (a11) is more sensitive to changes in alpha-RPR and Ci coefficient, while the perpendicular components (a22, a33) are also significantly affected by Cm. From the predictive error analysis it is seen that the optimal parameters set to capture the orientation state of the specimen is: (i) for the FT model, Ci = 0.005, alpha-RPR = 0.7 and (ii) for the iARD model, Ci = 0.005, Cm = 0.2, and alpha-RPR = 0.7.https://www.frontiersin.org/article/10.3389/fmats.2020.00169/fullshort-fiber compositesmicro-CT characterizationinjection molding simulationrotary diffusion modelsclosure approximationsexperimental validation
collection DOAJ
language English
format Article
sources DOAJ
author María C. Quintana
Patricia M. Frontini
Aitor Arriaga
Bernhard Plank
Zoltan Major
spellingShingle María C. Quintana
Patricia M. Frontini
Aitor Arriaga
Bernhard Plank
Zoltan Major
Fiber Orientation Distribution Predictions for an Injection Molded Venturi-Shaped Part Validated Against Experimental Micro-Computed Tomography Characterization
Frontiers in Materials
short-fiber composites
micro-CT characterization
injection molding simulation
rotary diffusion models
closure approximations
experimental validation
author_facet María C. Quintana
Patricia M. Frontini
Aitor Arriaga
Bernhard Plank
Zoltan Major
author_sort María C. Quintana
title Fiber Orientation Distribution Predictions for an Injection Molded Venturi-Shaped Part Validated Against Experimental Micro-Computed Tomography Characterization
title_short Fiber Orientation Distribution Predictions for an Injection Molded Venturi-Shaped Part Validated Against Experimental Micro-Computed Tomography Characterization
title_full Fiber Orientation Distribution Predictions for an Injection Molded Venturi-Shaped Part Validated Against Experimental Micro-Computed Tomography Characterization
title_fullStr Fiber Orientation Distribution Predictions for an Injection Molded Venturi-Shaped Part Validated Against Experimental Micro-Computed Tomography Characterization
title_full_unstemmed Fiber Orientation Distribution Predictions for an Injection Molded Venturi-Shaped Part Validated Against Experimental Micro-Computed Tomography Characterization
title_sort fiber orientation distribution predictions for an injection molded venturi-shaped part validated against experimental micro-computed tomography characterization
publisher Frontiers Media S.A.
series Frontiers in Materials
issn 2296-8016
publishDate 2020-07-01
description This work evaluates and compares the accuracy of different fiber orientation prediction models for a short fiber reinforced injection molded Venturi-shaped part which displays variable thickness. The experimental characterization of the specimen fiber orientation distribution (FOD) was carried out by the micro computed tomography technique (micro-CT). The computational study of fiber orientation predictions was performed using Moldex3D. All the possible combinations of the Folgar-Tucker (FT) and improved Anisotropic Rotary Diffusion (iARD) rotary diffusion models and the Hybrid (Hyb), Orthotropic (ORE), and Invariant Based Optimal Fitting (IBOF) closure approximations were considered. The relevance of the Retardant Principal Rate (RPR) model on predictions results was also evaluated. The values of the fiber-fiber (Ci), matrix-fiber (Cm) interaction coefficients and the alpha-RPR parameter were varied in a significant range in order to find the set of parameters that better fits the experimental fiber orientation data. The parameters' sensitivity effect over the second order orientation tensor components was quantified via the Analysis of Variance (ANOVA) statistical method. The experimental micro-CT results show an increase in the fiber orientation degree at the specimen constriction region due to the narrowed cavity and the Venturi effect. The comparison of the experimental and predicted orientation profiles demonstrates that the predictions of the iARD model, in combination with the IBOF closure approximation, are the most accurate for the case studied. However, simulations fail to estimate the change in orientation caused by variable thickness and section. ANOVA results prove that the orientation tensor component in the flow direction (a11) is more sensitive to changes in alpha-RPR and Ci coefficient, while the perpendicular components (a22, a33) are also significantly affected by Cm. From the predictive error analysis it is seen that the optimal parameters set to capture the orientation state of the specimen is: (i) for the FT model, Ci = 0.005, alpha-RPR = 0.7 and (ii) for the iARD model, Ci = 0.005, Cm = 0.2, and alpha-RPR = 0.7.
topic short-fiber composites
micro-CT characterization
injection molding simulation
rotary diffusion models
closure approximations
experimental validation
url https://www.frontiersin.org/article/10.3389/fmats.2020.00169/full
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