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Record W2016199174 · doi:10.1115/1.4004113

Spring Stiffness Selection Criteria for Nozzle Check Valves Employed in Compressor Stations

2011· article· en· W2016199174 on OpenAlexaff
K. K. Botros

Bibliographic record

VenueJournal of Engineering for Gas Turbines and Power · 2011
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsNova Chemicals (Canada)
Fundersnot available
KeywordsGas compressorCheck valveStiffnessGate valveNozzleSpring (device)EngineeringFlow (mathematics)Globe valveMechanical engineeringStructural engineeringMarine engineeringMechanicsPhysics

Abstract

fetched live from OpenAlex

Nozzle type check valves are often employed in compressor stations in three locations: compressor outlet, station discharge, and station bypass. The fundamental design concept of these valves is based on creating a converging diverging flow through the valve internal geometry such that a minimum area is achieved at a location corresponding to the back of the check valve disk at the fully open position. This will ensure maximum hydrodynamic force coefficient which allows the valve to be fully open with minimum flow. Spring forces and stiffness determine the performance of this type of check valves and impact the overall operation and integrity of the compressor station. This paper examines the effects of various spring characteristics and stiffness in relation to the compressor and station flow characteristics. The results show that when the spring forces are higher than the maximum hydrodynamic force at minimum flow, the disk will not be at the fully open position, which will give rise to disk fluttering and potential for cyclic high velocity impact between components of the internal valve assembly. This could lead to self destruction of the check valve and subsequent risk of damage to the compressor unit itself. The paper also points to the fact that the spring selection criteria for a unit check valve are different than that for station and bypass check valves. An example of a case study with actual field data from a high pressure ratio compressor station employing this type of check valves is presented to illustrate the associated dynamic phenomena and fluid-structure interaction within the internal assembly of the check valve.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.023
GPT teacher head0.252
Teacher spread0.229 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations15
Published2011
Admission routes1
Has abstractyes

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