Bibliographic record
Abstract
Polymer composite piping that is composed of a fiber reinforcement phase embedded in a continuous polymer matrix is associated with high specific strength and excellent corrosion properties. The fiber reinforcement is often considered to dominate the mechanical performance of composite structures. Consequently, principal design parameters for composite piping are usually associated with the fiber architecture, which in many practical applications has been limited to simple angle-ply configurations. Nevertheless, the function of the polymer phase is not limited to merely providing rigidity to the otherwise pliable fiber architecture. In fact, the often quoted high strength of composites is sustained by a load-sharing mechanism that the matrix enables between filaments. In this manner, the effect of localized flaws and filament damage is mitigated, and only the accumulation of numerous micro damage events leads to component failure. An additional function of the polymer matrix is to prevent ingress of fluid into the composite and possible leakage in pressure-bearing components. The design of composite piping therefore needs to consider a matrix-sensitive damage criterion. In view of variable loading conditions and multi-angle fiber architectures this study investigates design optimization techniques intended to yield better performance in terms of strength and especially fluid permeation resistance.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".