INJECTION MOLDING OF FLAX FIBER BIOCOMPOSITES BY SIMULATION AND OPTIMIZATION
Bibliographic record
Abstract
Flax (Linum usitatissimum) fibers have the advantages of low density, low cost, and recyclability and are considered as a potential material to reinforce plastic materials. Though Canada is one of the largest seed flax growing countries in the world, the utilization of flax fibers as reinforcement in composites is not as developed as in Europe. Indeed, in Canada, a large amount of flax straws are left in the fields and burned by farmers each year. Therefore, development of technologies to make use of flax straws for reinforcement in composites and for other purposes has huge benefits to both the material industries and flax farmers in Canada. This thesis presented a study of flax fibers reinforced biocomposites by injection molding through modeling and optimization. The focus of the study was to understand the relationships between the properties of biocomposites and the processing conditions through the experiment and improve the qualities of biocomposites by optimizing the processing conditions. In this thesis, biocomposites were successfully produced by injection molding with a proposed processing scheme. The influence of flax fiber loading and processing conditions, including injection temperature and pressure on the mechanical properties (tensile properties and flexural properties), and water absorption of biocomposites was investigated. The study also experimentally investigated the effect of the processing conditions (fiber content and temperature) on the rheological properties of biocomposites. In order to implement the simulation analysis of injection molding for biocomposites, the Cross-WLF model was employed to obtain the rheological information of biocomposites. Further, a systematic approach on simulation analysis and optimization of injection molding was proposed to minimize the shrinkage and warpage of biocomposites. Several conclusions are drawn from this study: 1) With respect of the influence of the processing conditions on the properties of biocomposites, (a) Fiber content is the most significant impact factor influencing the mechanical properties of biocomposites compared with the other two processing conditions and the tensile properties and flexural properties of biocomposites dreamingly increased with flax fiber content; (b) lower injection temperature led to higher tensile properties and flexural properties; (c) Water absorption of biocomposites was significantly dependent on fiber content and injection temperature; (d) Injection pressure had no significant effect on either mechanical properties or water absorption. 2) In the study on the rheological characteristics, (a) The shear viscosity of biocomposites increased with fiber content, but at very high shear rates (from 5,000 to 10,000 S−1), the shear viscosities of biocomposites with various fiber content (from 0 to 30%) tended to be the same; (b) The shear viscosity of biocomposites decreased with temperature, and at higher shear rate, all the shear viscosity variations as function of shear rates followed the same rate for different temperatures; (c) At high shear rate, the shear viscosity mostly depended on the shear rate rather than fiber content and temperature; (d) A method was presented to determine the seven parameters of the Cross-WLF model for biocomposites. 3) For minimizing the shrinkage and warpage of injection molded biocomposites, (a) The significant factors on the shrinkage and warpage of biocomposites by injection molding were injection temperature, packing time, and packing pressure; (b) The optimization of the injection molding of biocomposites for reducing the shrinkage and warpage of biocomposites was successful by integrating design of experiment (DOE) and simulation technique. The contribution of this thesis includes: 1) In the field of biocomposites reinforcement, the study has shown a great promise to use flax fibers to enhance the mechanical properties of thermoplastics, in particular an increase of 41.83% in tensile strength and an increase of 47.13% in flexural strength. In addition, this work has provided a mathematical relationship between the processing condition of injection molding and the mechanical properties of biocomposites, which would be important to control the manufacturing process to reach desired mechanical properties. 2) In the field of optimal design and manufacturing of flax fiber biocomposites, this work has provided: (a) an effective method to determine the parameters in the rheology model of the biocomposites melt, which has been an important step in simulating the process, and this method has a generalized implication to other types of biocomposites; and (b) a systematic approach to optimize the injection molding process for minimizing the shrinkage and warpage of biocomposites, which are the two most important quality issues in biocomposites.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".