Investigation of expansion percentages and groove inclusions on the performance of welded, expanded, welded-expanded tube-to-tubesheet joints
Bibliographic record
Abstract
Tube-to-tubesheet joints play a crucial role in providing structural integrity to the shell and tube heat exchangers. This research investigated the combined effect of roller expansion percentages and grooves on the performance of expanded and welded-expanded tube-to-tubesheet joints. The results indicated that the joint strength of welded-expanded (except for 6% tube expansion and 2 grooves) and welded joints exceeded the nominal axial strength of the tube, 404.90 MPa. The highest tube pull-out strength of 290.77 MPa in the expanded only joint (10% tube expansion and 2 grooves), lesser than the axial strength of the tube by 28.25%, suggested avoiding the expansion process alone for 23 mm thick tubesheets. High dilution and inadequate minimum leak path (<1.78 mm) result in the failure of the welded-expanded joint. The highest hardness of 216 HV is formed at the weld zone comprising of α ferrite and widmanstatten ferrite. From 4% to 10% tube expansion percentages, the grains at the inner tube edges were refined from 8.33 μm to 6.25 μm at the expanded zone and from 9.09 μm to 6.66 μm at the transition zone due to intensive plastic deformation caused by the rollers. Grain refinement by expansion process resulted in high hardness of 182.3 HV and 156.1 HV at the inner tube edges of the expanded and transition zone, respectively. The grains were coarser, and hardness was less at the outer tube edges of expanded and transition zone. This study is promising for selecting the appropriate manufacturing process and conditions for the optimum performance of tube-to-tubesheet joints.
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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) | 0.000 | 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) | 0.001 | 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".