Innovative 3D FE Modeling of Mechanical Rolling in Tube-to-Tubesheet Joints: A Comparative Analysis With Hydraulic Expansion
Bibliographic record
Abstract
Abstract Despite considerable technological and industrial advancements over the past decades, mechanical rolling remains the process of choice for many industries. This is largely due to its short preparation time, ease of application, and relatively low cost compared to alternative expansion methods. In this paper, an innovative 3D modeling of mechanical rolling is presented to shed light on this complex process and its impact on the integrity of the tube-to-tubesheet joint. Two models are investigated; the first one is with three roll expanders sliding on the tube inner surface, and the second one is with three roll expanders spinning on the tube inner surface in order to cover the two possible cases reported in the literature while being in line with industrial applications. The sliding scenario was examined as it is a likely occurrence during mechanical rolling, where the roll expanders become lodged inside the mandrel and are unable to rotate as intended. The investigation not only explores the complex nature of the mechanical rolling but also highlights the potential limitations and challenges that arise in real-world applications. Furthermore, three metrics: residual contact pressure, pull-out force and wall thinning obtained from the mechanical rolling modeling have been compared with their hydraulic expansion counterparts obtained from analytical modeling proposed in the literature and finite element analysis. The results indicate that hydraulic expansion improves joint integrity by providing higher residual contact pressure for low and medium tube ID expansions. For higher tube ID expansions, the sliding model generates higher residual contact pressure. Nonetheless, the wall thinning at this expansion level shows that the joint integrity is compromised due to significant deformation and dentation. In both scenarios, spinning roll expanders yield lower integrity and demand greater roller thrust, which is the real case in the industry. However, wall thinning is less significant in hydraulic expansion.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".