Mechanical Characterization of Valve Compression Packing at High Temperature
Bibliographic record
Abstract
Abstract Packed stuffing boxes are sealing devices used in valves, compressors and pumps. The compression packing is the most critical element of this assembly. Packing rings are compressed axially to produce lateral contact pressures large enough to confine the processed fluid within the pressurized valve and avoids leakage to the outer boundary. Although popular, this old method of sealing has seen very limited analytical and numerical development. There is no standard design procedure for engineers to follow, and the existing standard test procedures are limited to qualification and quality control tests such as API622, 624, ISO-15848 1 and 2. As a result, structural integrity and leak tightness are rarely verified, and consequently 60 % of pressurized equipment requiring fugitive emissions compliance are valves that use this type of sealing device. The mechanical properties of compression packing materials are the main factors affecting fluid tightness at room and high temperatures and yet there is little or no data available either in manufacturer’s catalogues or in the literature. Packed stuffing box research is scant and focuses mostly on the distribution of the contact pressure between the stem and packing at room temperature without considering packing mechanical properties such as rigidity, thermal expansion, creep and aging. It is proposed, in this project, to measure the mechanical properties such as pressure transmission ratio, short-term creep deformation and thermal expansion coefficient of two packing materials at high temperature. This initiative will serve as a basis to launch a North American testing program to develop ASTM-like testing procedures for compression packing at high temperature.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".