Overview of Sonic Boom Reduction Efforts on the Lockheed Martin N+2 Supersonic Validations Program
Bibliographic record
Abstract
Under the N+2 Supersonic Validations contract with NASA, Lockheed Martin has developed system-level solutions to the barriers to supersonic commercial flight, with a particular focus on the technology required to design and validate shaped sonic boom vehicles for acceptably quiet flight over land. LM’s past experience, commercial design and analysis tool advances, commercial partner expertise and NASA methodologies were successfully combined in the shaped boom design process. In the second phase of the N+2 program, we continued the work started in Phase 1 by improving low-boom performance over the full boom carpet and adding fidelity to the design in key areas including structures and aeroelastics. NASA’s support for extensive validation testing uncovered the cause of prior long-standing difficulties with sonic boom wind tunnel measurement, and resulted in the development of a “spatial averaging” solution that combines better than required accuracy with an order-of-magnitude improvement in productivity. The LM 1044 configuration designed and tested during this program has demonstrated that it is possible to develop an environmentally compliant, practical, and high efficiency supersonic transport aircraft for the next generation of air travelers.
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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 | 0.010 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".