Computational Aerodynamics of Shuttle Orbiter Damage Scenarios in Support of the Columbia Accident Investigation
Bibliographic record
Abstract
In support of the Columbia Accident Investigation, inviscid computations of the aerodynamic characteristics for various Shuttle Orbiter damage scenarios were performed using the Felisa unstructured CFD solver. Computed delta aerodynamics were compared with the reconstructed delta aerodynamics in order to postulate a progression of damage through the flight trajectory. By performing computations at hypervelocity flight and CF4 tunnel conditions, a bridge was provided between wind tunnel testing in Langley’s 20-Inch CF4 facility and the flight environment experienced by Columbia during re-entry. The rapid modeling capability of the unstructured methodology allowed the computational effort to keep pace with the wind tunnel and, at times, guide the wind tunnel efforts. These computations provided a detailed view of the flowfield characteristics and the contribution of orbiter components (such as the vertical tail and wing) to aerodynamic forces and moments that were unavailable from wind tunnel testing. The damage scenarios are grouped into three categories. Initially, single and multiple missing full RCC panels were analyzed to determine the effect of damage location and magnitude on the aerodynamics. Next is a series of cases with progressive damage, increasing in severity, in the region of RCC panel 9. The final group is a set of wing leading edge and windward surface deformations that model possible structural deformation of the wing skin due to internal heating of the wing structure. By matching the aerodynamics from selected damage scenarios to the reconstructed flight aerodynamics, a progression of damage that is consistent with the flight data, debris forensics, and wind tunnel data is postulated. Nomenclature bref Reference length for rolling and yawing moments C Force or moment coefficient, force normalized by 1 and rolling and yawing moments by 1 cref Reference length for pitching moment
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".