CATIA V5-Based Parametric Aircraft Geometry Modeler
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Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">Current transport aircraft are mature systems, thus require increased fidelity at the beginning of the design process to allow further optimization. Furthermore, a desire exists to explore unconventional aircraft configurations at the conceptual level. This has motivated the development of a tool which effectively manages the trade-off between high-fidelity levels, flexibility and short turn-around times. This paper presents a CATIA V5-based parametric aircraft geometry modeler developed by Bombardier Aerospace. The aim of the tool is to provide consistent high-fidelity geometric data early in the conceptual aircraft design process.</div><div class="htmlview paragraph">The intended near-term use of the modeler is two-fold: during the early design phase, the modeler computes geometric data such as areas, volumes, ESDU aircraft parameters, etc. In the competitive analysis domain, the tool provides a high-quality three-dimensional model with manageable effort. In both cases, the engineer is presented with a fully parametric three-dimensional CATIA V5 aircraft model. In the medium-term, use by expert departments is envisioned. </div><div class="htmlview paragraph">Moreover, the geometrical data extracted from CATALIST can be saved into a standard database and fed to various analysis codes to compute aircraft performance characteristics. As aircraft models are in native CATIA V5 format, this fits seamlessly into the established design process at Bombardier Aerospace. Additionally, this approach allows critical analyses to be performed earlier in the conceptual design phase.</div><div class="htmlview paragraph">Aircraft exterior and interior modules are in use today along with systems modules and a basic structural representation. An overview of the key features of the tool is presented along with sample applications. Tool usability and modeling quality have been extensively validated with selected regional aircraft and business jets from Bombardier.</div></div>
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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