PLANETARY EMBRYO BOW SHOCKS AS A MECHANISM FOR CHONDRULE FORMATION
Bibliographic record
Abstract
ABSTRACT We use radiation hydrodynamics with direct particle integration to explore the feasibility of chondrule formation in planetary embryo bow shocks. The calculations presented here are used to explore the consequences of a Mars-size planetary embryo traveling on a moderately excited orbit through the dusty, early environment of the solar system. The embryo’s eccentric orbit produces a range of supersonic relative velocities between the embryo and the circularly orbiting gas and dust, prompting the formation of bow shocks. Temporary atmospheres around these embryos, which can be created via volatile outgassing and gas capture from the surrounding nebula, can non-trivially affect thermal profiles of solids entering the shock. We explore the thermal environment of solids that traverse the bow shock at different impact radii, the effects that planetoid atmospheres have on shock morphologies, and the stripping efficiency of planetoidal atmospheres in the presence of high relative winds. Simulations are run using adiabatic and radiative conditions, with multiple treatments for the local opacities. Shock speeds of 5, 6, and 7 km s−1 are explored. We find that a high-mass atmosphere and inefficient radiative conditions can produce peak temperatures and cooling rates that are consistent with the constraints set by chondrule furnace studies. For most conditions, the derived cooling rates are potentially too high to be consistent with chondrule formation.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".