Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The constant increase of composite materials’ performances makes them more and more used in recent aircrafts. Structures, as the wings or the fuselage, may suffer from hail impacts that can make critical damages or even perforate them. In order to guaranty the safety of passengers, aircrafts have to be certified and simulations have to demonstrate good agreements with real behaviour of the structures and the hail projectile. The aim of this work is to propose a procedure to analyse the home made manufacturing of the ice generally performed in laboratories, its mechanical characterization and a mechanical model that can predict the time-space profile of the impact force on a rigid structure. Because of the high strain level of the hail during the impact, the Smooth Particle Hydrodynamics (SPH) method will be used. Indeed, the finite elements method needs heavy remeshing that are time consuming to avoid mesh distortion. The SPH is a numerical meshless method that calculates interactions between particles at every time increment. Models available in the literature have been studied and the model of J.D. Tippmann (Tippmann, Kim, et Jennifer D. Rhymer 2013) is chosen. In this paper, the Tippman model is presented with its solving using the SPH. A parametric study is proposed in order to catch the relevant parts of this model. A simple experimental procedure is then proposed to feed the model and the results of impact simulations at different velocities are compared to experimental measurements realized in the laboratory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.004 | 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