Analytical and Numerical Evaluation of the Axial Stress Distribution of Two Soft-Packed Stuffing-Box Configurations
Bibliographic record
Abstract
Stuffing-box packed valves which confine high-pressure fluids are often subjected to leakage failure. The lack of a design procedure and the vulnerability of packing ring sealing materials to withstand different operating conditions are the root cause of the problem. The sealing performance of valves with packed stuffing-box depends on the ability of the assembly to maintain a minimum threshold contact pressure between the packing and the stem and the packing and the housing throughout service operation. The distribution of the contact stresses in the packing materials is a key parameter to efficient sealing performance. This study presents a contact stress modeling study of two different design configurations that are helpful to produce a uniform distribution of the contact stress. The first model is based on the introduction of a variable gap between the packing and the side walls. The second model is based on a multistage loading of the packing rings. The two developed analytical models are validated by comparison with the numerical simulation using FE method and the results show a good agreement. The two design configurations can be used to improve valve sealing performance.
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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 | 0.001 | 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 | 0.000 |
| 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".