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Record W2093669104 · doi:10.1080/05698190490494822

Automatic Feedback Control of Mechanical Gas Face Seals via Clearance Control

2004· article· en· W2093669104 on OpenAlexaboutno aff
Sachin S. Yelma, B. Miller, Robert G. Landers

Bibliographic record

VenueTribology Transactions · 2004
Typearticle
Languageen
FieldEngineering
TopicTribology and Lubrication Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsControl theory (sociology)StatorStiffnessNonlinear systemSeal (emblem)Mechanical systemFace (sociological concept)EngineeringMechanical engineeringControl engineeringMechanicsComputer scienceStructural engineeringControl (management)Physics

Abstract

fetched live from OpenAlex

A new analytical approach is presented for designing controllers to regulate the axial clearance of a coned-face flexibly mounted stator mechanical gas face seal. The seal axial clearance is controlled by regulating the back-pressure force acting on the stator. The controllers are systematically designed using a completely analytical seal system model in which the linearized gas film stiffness and damping properties are represented by a constitutive model. An algorithm based on this model is derived to calculate the critical axial clearance where the seal is marginally stable, and a stable reference axial clearance is chosen. Proportional and proportional-plus-integral controllers are designed and analytically studied in terms of closed-loop stability and speed of response using the system model. The controllers are verified using a full numerical simulation (including nonlinear effects) of the mechanical gas face seal system, and the results demonstrate the effectiveness of both controllers to maintain the reference axial clearance.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.006
GPT teacher head0.206
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2004
Admission routes1
Has abstractyes

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