Predictive Engineering Tools for Injection-Molded Long-Carbon-Fiber Thermoplastic Composites

Nguyen, Ba Nghiep; Simmons, Kevin L.

doi:10.2172/1089084

Cited by 7 publications

(60 citation statements)

References 3 publications

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“…iARD-RPR Prediction. Most long-fiber orientation predictions from the 3D mesh computation have yet to produce satisfactory results [1,20]. Here we utilized a commercial injection-molding simulation software [32,48] attached with the iARD-RPR fiber orientation model.…”

Section: Methodsmentioning

confidence: 99%

“…Following the 3D computation issue, the so-called 3D inlet boundary condition has been applied to effectively improve the accuracy of the fiber orientation prediction by the RSC model and the ARD-RSC model in 3D mesh computation [45]. In our 3D computation, the use of the inlet condition was unnecessary because of the higher 3D numerical resolution and the solid runner system.…”

Section: Governing Equations Of Fluid Mechanicsmentioning

confidence: 99%

“…For injection-molded long-carbon-fiber thermoplastic composites, the U.S. Department of Energy (DOE) has plans to develop predictive engineering tools as lightweight materials for use in the automotive industry [1][2][3]. The long-fiber-reinforced-thermoplastic (FRT) compounds now commercially available are the candidate materials which significantly improve the mechanical/structural performance and the shrinkage/warpage deformation, thereby enhancing both safety and durability.…”

Section: Introductionmentioning

confidence: 99%

“…It is noteworthy that the inlet condition strongly influences the predictions of the RSC model [20]. Nguyen et al [1] demonstrated that the 3D inlet condition improved an inaccurate prediction of fiber orientation. Furthermore, Wang et al [21] examined the midplane-mesh version with ARD-RSC and, with an inlet condition set around the gate area, was able to obtain good orientation predictions of long-carbon-fiber composites.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, Wang et al [21] examined the midplane-mesh version with ARD-RSC and, with an inlet condition set around the gate area, was able to obtain good orientation predictions of long-carbon-fiber composites. The inlet condition involves the user-defined mode and the specified mode [1].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Accurate predictions of fiber orientation and mechanical properties in long‐fiber‐reinforced composite with experimental validation

Tseng¹,

Goto²,

Chang³

et al. 2017

Polymer Composites

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Mechanical performance of lightweight automotive materials made of long fiber‐reinforced thermoplastic composites is potentially superior to that of short fiber. However, accurate prediction of fiber orientation is critical for determining reliable mechanical properties. Thus, we investigate the representative fiber orientation models under simple shear flow and discuss in regard to a variety of long fiber suspensions. In addition, the laminate orientation structure of skin–shell–core pattern predicted in 3D injection molding simulation is quantitatively compared with experimental data measured via the micro‐computed tomography. Significantly, we show the effect of fiber orientation states on mechanical properties, including tensile modulus and stress–strain response. POLYM. COMPOS., 39:3434–3445, 2018. © 2017 Society of Plastics Engineers

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Section: Methodsmentioning

confidence: 99%

Section: Governing Equations Of Fluid Mechanicsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Accurate predictions of fiber orientation and mechanical properties in long‐fiber‐reinforced composite with experimental validation

Tseng¹,

Goto²,

Chang³

et al. 2017

Polymer Composites

View full text Add to dashboard Cite

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A review of Long fibre thermoplastic (LFT) composites

Ning

Lü

Hassen

et al. 2019

International Materials Reviews

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Long fibre-reinforced thermoplastic or long fibre thermoplastic (LFT) composites possess superior specific modulus and strength, excellent impact resistance, and other advantages such as ease of processability, recyclability, and excellent corrosion resistance. These advantages make LFT composites one of the most advanced lightweight engineering materials and enable their increasing use in various applications. This review paper summarises the research and development work that has been conducted on LFT composites since their initial development. Different aspects of LFTs, such as process development, fibre orientation distribution (FOD), fibre length distribution (FLD), and their effects on the mechanical properties of LFT composites are described. The characterisation of the FOD and FLD in the LFT composites using advanced imaging technology such as highresolution 3D micro-CT scanning technique is summarised. Research and development of LFT hybridisation and LFT additives are also discussed. Finally, conclusions are made and the future outlook of LFT composites is given.

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Effect of the initial fiber alignment on the mechanical properties for GMT composite materials

Song¹,

Gandhi²,

Koziel³

et al. 2017

Journal of Thermoplastic Composite Materials

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A glass-mat-reinforced thermoplastic (GMT) material is widely used in the automotive industry for components such as underbody shields, seat structures, front/rear bumper, and front-end modulus. Due to the higher residual length of the glass strands, GMT usually offers better mechanical properties than injection-molded fiber-reinforced thermoplastics. The GMT material is typically manufactured by compression molding (CM) of preimpregnated fibers–reinforced resin sheets called mat. Two types of mats, one with discontinuous random (RD) fibers and other with aligned continuous fibers, are considered in this study. A stack of such mats with different combinations is used to tailor the mechanical properties of the final part. During the CM, the fibers in the mat flow with the resin and change the alignment. In this study, we are presenting an approach to account for the initial condition, such as fiber length, orientation and concentration of the fibers in the mat, and process conditions used, to develop a material model for the finished part. First, a stack of mat with known fiber orientation, length, and concentration as initial conditions is simulated for CM to predict the fiber orientation in the finished part. Next, the material model for the finished parts is developed using a Mori–Tanaka homogenization approach. The fiber orientation in the finished part is mapped from the CM simulation. For the fiber concentration and fiber length distribution, we used an empirical approach. The cross section of the finished part is investigated under optical microscope, and the fiber length and concentration are estimated based on the microstructure and initial stacking of mats. The predicted fiber orientation tensor is verified with orientations measured using computerized tomography (CT) scan on actual parts. The material model is verified by comparing the predicted performance with the actual tensile and bending test results.

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Predictive Engineering Tools for Injection-Molded Long-Carbon-Fiber Thermoplastic Composites

Cited by 7 publications

References 3 publications

Accurate predictions of fiber orientation and mechanical properties in long‐fiber‐reinforced composite with experimental validation

Accurate predictions of fiber orientation and mechanical properties in long‐fiber‐reinforced composite with experimental validation

A review of Long fibre thermoplastic (LFT) composites

Effect of the initial fiber alignment on the mechanical properties for GMT composite materials

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