Exploratory Data Analyses on CFRP Wrapped HDD Overbend Subjected to Combined Loading
Bibliographic record
Abstract
Abstract Horizontal directional drilling (HDD) is one of the popular pipeline trenchless construction techniques for sites where surface excavations and conventional trenching are not desirable. An integral part of the pipeline design and construction process is to perform stress analysis on the HDD overbends, which can be subjected to significant cross-sectional deformations due to stresses/strains imposed by thermal expansion and internal pressure. This paper proposes a novel approach to reduce the stress range in the HDD overbends using carbon fibre reinforced polymer (CFRP) wraps. Although this reinforcement technique is primarily used in the pipeline industry for repairing damaged pipes, there is a handful of recent studies that showed the promising effect of using CFRP reinforcement on undamaged pipe bends. A total of 259 finite element analyses are conducted with a different combination of pipe diameter to thickness ratio, CFRP length and thickness, fibre orientation, and internal pressure. An exploratory data analysis is then performed to demonstrate the impact of each variable on the maximum equivalent stresses imposed on the HDD overbend. The finite element results show that multi-directional fibre orientation leads to the highest reduction of peak equivalent stress on the HDD overbend. Besides, an increase in CFRP thickness results in a greater reduction of stresses on the HDD overbend. However, CFRP length does not have a noticeable effect on decreasing the stresses on the HDD overbend.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".