Performance of 3-D Printed Thermoplastic Polyurethane Under Quasi-Static and High-Strain Rate Loading
Bibliographic record
Abstract
As 3-D printed materials are being embraced by the manufacturing industries, understanding the response mechanism to high strain rate events becomes a concern to meet requirements for a specific application. In order to improve the mechanical performance of a 3-D printed part, it is necessary to quantify the impact of various printing parameters on the mechanical properties. Initial studies have shown that a difference in 3-D printed material is expected due to the effect of manufacturing parameters such as anisotropy relating to printing direction, infill pattern, infill percentage, layer height and orientation of the part being printed. The main focus of the study is to characterize the effect of the previously mentioned printing parameters under quasi-static and high strain rate (100–1000 /s). In this strain rate regime, the most common apparatus used is the Split Hopkinson pressure bar (also known as Kolsky bar). It consists of a cylindrical metallic bar that has a striker, input and output bar. While the specimen is fixated between the input and output bar, the striker bar is accelerated and triggers the incident bar. As a result, an elastic wave is generated which travels towards the specimen/input bar interface, where some part of it is reflected and the rest is transmitted. The Kolsky bar is adjusted by using a hollow transmitter tube and pulse shaper. Due to an impedance mismatch between the samples and bar material, the amplitude of the transmitted pulse is low. Using a hollow transmitter bar increases this amplitude due to area mismatch between the specimen and tube. Using a pulse shaper between the striker and input bar, the rise time of the elastic compressive wave increases and assists in achieving a constant rate of loading. The compressive stress strain curves were obtained under high strain rates to determine the strain rate effect. To measure the response under static testing conditions, a commercial load frame was used. A comprehensive comparison of dynamic compressive response of samples was performed to characterize the effect of printing parameters.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".