Fluid Behavior in Stochastic Porous Structures
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
View Video Presentation: https://doi.org/10.2514/6.2021-1443.vid Ablative materials in thermal protection systems (TPS) are used in aerospace applications to protect passengers and payload from critical degradation in high temperature conditions. The standard ablator, phenolic impregnated carbon ablator (PICA), is composed of carbon fibers embedded in a phenolic resin. It has a highly complex microstructure – a highly porous fibrous mat with its components oriented randomly in the transverse plane. As such, the calculation of its fluid behavior requires a robust approach. Here, we present a stochastic modeling approach that allows for assessment of properties as a function of local structure. The approach includes a computational toolkit for generating physically-motivated model representative volume elements (mRVE’s), which are confirmed to exhibit transverse isotropy (just as PICA). We also present a methodology for computing the distribution of fluid behavior for sets of mRVE’s using the lattice Boltzmann method (LBM). Based on our results, local variation in fiber geometry within fibrous ablators has little effect on fluid behavior but their global orientation has a significant one and must be a major design consideration moving forward.
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) | 0.000 | 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