An anisotropic rotary diffusion model for fiber orientation in short- and long-fiber thermoplastics

2009 ◽  
Vol 156 (3) ◽  
pp. 165-176 ◽  
Author(s):  
Jay H. Phelps ◽  
Charles L. Tucker
Keyword(s):  
Diffusion Model ◽  
Fiber Orientation ◽  
Long Fiber Thermoplastics ◽  
Rotary Diffusion

scholarly journals Fiber Orientation Predictions—A Review of Existing Models

2020 ◽  
Vol 4 (2) ◽  
pp. 69 ◽  
Author(s):  
Susanne Katrin Kugler ◽  
Armin Kech ◽  
Camilo Cruz ◽  
Tim Osswald
Keyword(s):  
Fiber Orientation ◽  
Mechanical Performance ◽  
Historical Review ◽  
Fiber Reinforced Polymers ◽  
Strong Impact ◽  
Fiber Reinforced ◽  
Reinforced Polymers ◽  
Virtual Engineering ◽  
Rotary Diffusion ◽  
Orientation Phenomenon

Fiber reinforced polymers are key materials across different industries. The manufacturing processes of those materials have typically strong impact on their final microstructure, which at the same time controls the mechanical performance of the part. A reliable virtual engineering design of fiber-reinforced polymers requires therefore considering the simulation of the process-induced microstructure. One relevant microstructure descriptor in fiber-reinforced polymers is the fiber orientation. This work focuses on the modeling of the fiber orientation phenomenon and presents a historical review of the different modelling approaches. In this context, the article describes different macroscopic fiber orientation models such as the Folgar-Tucker, nematic, reduced strain closure (RSC), retarding principal rate (RPR), anisotropic rotary diffusion (ARD), principal anisotropic rotary diffusion (pARD), and Moldflow rotary diffusion (MRD) model. We discuss briefly about closure approximations, which are a common mathematical element of those macroscopic fiber orientation models. In the last section, we introduce some micro-scale numerical methods for simulating the fiber orientation phenomenon, such as the discrete element method (DEM), the smoothed particle hydrodynamics (SPH) method and the moving particle semi-implicit (MPS) method.

Creep Modeling for Injection-Molded Long-Fiber Thermoplastics

2008 ◽  
Author(s):  
Ba Nghiep Nguyen ◽  
Vlastimil Kunc ◽  
Satish K. Bapanapalli
Keyword(s):  
Fiber Orientation ◽  
Fiber Length ◽  
Creep Model ◽  
Elastic Fibers ◽  
Injection Molding Process ◽  
Creep Response ◽  
Equivalent Inclusion Method ◽  
Long Fiber Thermoplastics ◽  
Orientation Distributions ◽  
Injection Molded

This paper proposes a model to predict the creep response of injection-molded long-fiber thermoplastics (LFTs). The model accounts for elastic fibers embedded in a thermoplastic resin that exhibits the nonlinear viscoelastic behavior described by the Schapery’s model. It also accounts for fiber length and orientation distributions in the composite formed by the injection-molding process. Fiber length and orientation distributions were measured and used in the analysis that applies the Eshelby’s equivalent inclusion method, the Mori-Tanaka assumption (termed the Eshelby-Mori-Tanaka approach) and the fiber orientation averaging technique to compute the overall strain increment resulting from an overall constant applied stress during a given time increment. The creep model for LFTs has been implemented in the ABAQUS finite element code via user-subroutines and has been validated against the experimental creep data obtained for long-glass-fiber/polypropylene specimens. The effects of fiber orientation and length distributions on the composite creep response are determined and discussed.

scholarly journals Assessment of Analytical Orientation Prediction Models for Suspensions Containing Fibers and Spheres

2021 ◽  
Vol 5 (4) ◽  
pp. 107
Author(s):  
Bastien Dietemann ◽  
Fatih Bosna ◽  
Harald Kruggel-Emden ◽  
Torsten Kraft ◽  
Claas Bierwisch
Keyword(s):  
Diffusion Model ◽  
Prediction Models ◽  
Rotational Diffusion ◽  
Spherical Particles ◽  
Model Parameters ◽  
Closure Model ◽  
Filling Fraction ◽  
Complex Orientation ◽  
Complex Models ◽  
Rotary Diffusion

Analytical orientation models like the Folgar Tucker (FT) model are widely applied to predict the orientation of suspended non-spherical particles. The accuracy of these models depends on empirical model parameters. In this work, we assess how well analytical orientation models can predict the orientation of suspensions not only consisting of fibers but also of an additional second particle type in the shape of disks, which are varied in size and filling fraction. We mainly focus on the FT model, and we also compare its accuracy to more complex models like Reduced-Strain Closure model (RSC), Moldflow Rotational Diffusion model (MRD), and Anisotropic Rotary Diffusion model (ARD). In our work, we address the following questions. First, can the FT model predict the orientation of suspensions despite the additional particle phase affecting the rotation of the fibers? Second, is it possible to formulate an expression for the sole Folgar Tucker model parameter that is based on the suspension composition? Third, is there an advantage to choose more complex orientation prediction models that require the adjustment of additional model parameters?

A new lithium diffusion model in layered oxides based on asymmetric but reversible transition metal migration

2020 ◽  
Vol 13 (4) ◽  
pp. 1269-1278 ◽  
Author(s):  
Kyojin Ku ◽  
Byunghoon Kim ◽  
Sung-Kyun Jung ◽  
Yue Gong ◽  
Donggun Eum ◽  
...  
Keyword(s):  
Transition Metal ◽  
Diffusion Model ◽  
Layered Oxides ◽  
Layered Oxide ◽  
Reversible Transition ◽  
Lithium Diffusion ◽  
Metal Migration

We propose a new lithium diffusion model involving coupled lithium and transition metal migration, peculiarly occurring in a lithium-rich layered oxide.

Does the Name-Race Implicit Association Test Measure Racial Prejudice?

2011 ◽  
Vol 58 (4) ◽  
pp. 271-277 ◽  
Author(s):  
Don van Ravenzwaaij ◽  
Han L. J. van der Maas ◽  
Eric-Jan Wagenmakers
Keyword(s):  
Diffusion Model ◽  
Implicit Association Test ◽  
Alternative Explanation ◽  
Group Membership ◽  
Racial Prejudice ◽  
Decision Time ◽  
Association Test ◽  
Implicit Association ◽  
Model Decomposition ◽  
Test Measure

Research using the Implicit Association Test (IAT) has shown that names labeled as Caucasian elicit more positive associations than names labeled as non-Caucasian. One interpretation of this result is that the IAT measures latent racial prejudice. An alternative explanation is that the result is due to differences in in-group/out-group membership. In this study, we conducted three different IATs: one with same-race Dutch names versus racially charged Moroccan names; one with same-race Dutch names versus racially neutral Finnish names; and one with Moroccan names versus Finnish names. Results showed equivalent effects for the Dutch-Moroccan and Dutch-Finnish IATs, but no effect for the Finnish-Moroccan IAT. This suggests that the name-race IAT-effect is not due to racial prejudice. A diffusion model decomposition indicated that the IAT-effects were caused by changes in speed of information accumulation, response conservativeness, and non-decision time.

Impact of Context Information on Metaphor Elaboration

2018 ◽  
Vol 65 (6) ◽  
pp. 370-384 ◽  
Author(s):  
Veronika Lerche ◽  
Ursula Christmann ◽  
Andreas Voss
Keyword(s):  
Diffusion Model ◽  
Processing Speed ◽  
A Priori ◽  
Model Fit ◽  
Verbal Task ◽  
Context Information ◽  
Speed Of Processing ◽  
Good Account ◽  
Dependent Variables ◽  
Decision Settings

Abstract. In experiments by Gibbs, Kushner, and Mills (1991) , sentences were supposedly either authored by poets or by a computer. Gibbs et al. (1991) concluded from their results that the assumed source of the text influences speed of processing, with a higher speed for metaphorical sentences in the Poet condition. However, the dependent variables used (e.g., mean RTs) do not allow clear conclusions regarding processing speed. It is also possible that participants had prior biases before the presentation of the stimuli. We conducted a conceptual replication and applied the diffusion model ( Ratcliff, 1978 ) to disentangle a possible effect on processing speed from a prior bias. Our results are in accordance with the interpretation by Gibbs et al. (1991) : The context information affected processing speed, not a priori decision settings. Additionally, analyses of model fit revealed that the diffusion model provided a good account of the data of this complex verbal task.

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