Increased market role for long fiber thermoplastics

2019 ◽  
Vol 63 (5) ◽  
pp. 262-266
Author(s):  
Mark Holmes
Keyword(s):  
Long Fiber Thermoplastics

Colored inorganic-pigmented long-fiber thermoplastics

2013 ◽  
Vol 28 (12) ◽  
pp. 1627-1643 ◽  
Author(s):  
Uday K Vaidya ◽  
K Balaji Thattaiparthasarthy ◽  
Selvum Pillay ◽  
Shalmalee Vaidya ◽  
Haibin Ning ◽  
...  
Keyword(s):  
Long Fiber Thermoplastics

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.

Mechanics of Random Discontinuous Long-Fiber Thermoplastics—Part I: Generation and Characterization of Initial Geometry

2013 ◽  
Vol 80 (5) ◽  
Author(s):  
Ahmed I. Abd El-Rahman ◽  
Charles L. Tucker
Keyword(s):  
Aspect Ratio ◽  
Spatial Correlation ◽  
Distribution Functions ◽  
Random Structure ◽  
Quasi Equilibrium ◽  
Fiber Aspect Ratio ◽  
Metropolis Monte Carlo ◽  
Long Fiber Thermoplastics ◽  
Deformation Mechanics ◽  
Orientational Correlation

The deformation mechanics of dry networks of large-aspect-ratio fibers with random orientation controls the processing of long-fiber thermoplastics (LFTs) and greatly affects the mechanical properties of the final composites. Here, we generate initial geometries of fiber networks in a cubic unit cell with a fiber aspect ratio of l/d = 100 and fully periodic boundary conditions for later numerical simulation. The irreversible random sequential adsorption (RSA) process is first used to generate a quasi-random structure due to the excluded-volume requirements. In order to investigate the nonequilibrium character of the RSA, a second method, which is similar to the mechanical contraction method (MCM) (Williams and Philipse, 2003, “Random Packings of Spheres and Spherocylinders Simulated by Mechanical Contraction,” Phys. Rev. E, 67, pp. 1–9) and based on a simplified Metropolis Monte Carlo (MC) simulation is then developed to produce quasi-equilibrium fiber geometries. The RSA packing results (ϕ ≈ 4.423% when using a fiber aspect ratio of 100) are in good agreement with the maximum unforced random packing limits (Evans and Gibson, 1986, “Prediction of the Maximum Packing Fraction Achievable in Randomly Oriented Short-Fibre Composites,” Compos. Sci. Technol., 25, pp. 149–162). The fiber structures were characterized by several distribution functions, including pair-spatial and pair-orientation distributions, based on either the center-to-center distance or the shortest distance between the particles. The results show that the structures generated by the RSA have an easily-detectable long-range spatial correlation but very little orientational correlation. In contrast, the quasi-equilibrium structures have reduced spatial correlation but increased short-range orientational correlation.

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