Development of an implosion-driven hypervelocity launcher for orbital debris impact simulation
Why this work is in the frame
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Bibliographic record
Abstract
The ability to soft-launch projectiles to velocities exceeding 10 km/s is of interest for a number of scientific fields, including orbital debris impact testing. Current soft-launch technologies have reached a performance plateau below this operating range. In the implosion-driven launcher (IDL) concept, explosives are used to linearly implode a pressurized steel tube, thereby dynamically compressing a light driver gas to significantly higher pressures and temperatures than typical light-gas launchers. As a result, the IDL has the potential to significantly outperform current state of the art hypervelocity launchers. This work will focus on establishing an understanding of the critical design parameters of the IDL with the goal of improving the velocity potential of the launcher. For this purpose, a computational gasdynamics solver capable of simulating the internal ballistics of the IDL has been developed. The elevated pressure and temperature in the driver gas lead to a number of non-ideal effects during the launch cycle, including expansion of the launcher walls, convective heat transfer, and gas leakage, which have a significant effect on launcher performance. These effects have been simulated by coupling the gasdynamics solver to loss models. Specifically, a structural hydrocode has been developed to provide a realistic model of reservoir and launch tube expansion, which has been identified as the main source of performance loss in the launch cycle. The complete internal ballistics solver will be used in conjunction with classical internal ballistics theory and experimental results, in order to gain valuable understanding of the key design parameters of the launcher and improve the design of the McGill IDL. This analysis has led to the development of an IDL capable of launching a 0.1-g projectile to 9.1 km/s.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 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 it