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Record W2024186016 · doi:10.1115/pvp2007-26649

An Update on Selecting the Optimum Bolt Assembly Stress for Piping Flanges

2007· article· en· W2024186016 on OpenAlexaboutno aff
Warren Brown, David Reeves

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEngineering Structural Analysis Methods
Canadian institutionsnot available
Fundersnot available
KeywordsGasketFlangePipingStructural engineeringStress (linguistics)Leakage (economics)Joint (building)Bolted jointCompressive strengthEngineeringComposite materialMaterials scienceFinite element methodMechanical engineering

Abstract

fetched live from OpenAlex

In order to minimize the likelihood of leakage from flanged piping joints, it is a good practice to maximize the initial bolt assembly stress. Present bolting guidelines (ASME PCC-1 [1]) outline the use of a percent of bolt yield across all flange sizes and classes to set the assembly stress level. These guidelines do indicate that aspects such as component strength and gasket stress should be considered, however the most common application of the approach is to use a standard percentage of bolt yield across all flange sizes and classes. This approach does allow for adjustment for differences in material yield strengths (carbon steel versus stainless steel) and raised face (RF) versus ring type joint (RTJ) flange configurations. It does not, however, adjust for the difference in strength between standard pipe flange sizes nor the actual gasket stress achieved across all flange sizes and classes. Since there is no assessment of flange strength, such an approach may cause failure of joint components. In addition, because the standard percentage of bolt yield technique does not look at gasket stress, it is prone to gasket leakage due to low stress or gasket destruction due to over-compression for some joints. In addition, some joints may require bolt loads well in excess of the standard value to develop an acceptable gasket stress level in order to prevent leakage. This paper is a continuation of the paper presented during PVP 2006 in Vancouver (Brown [2]), which examined the variables that must be considered and drew some preliminary conclusions regarding the use of flange stress limits in determining the maximum allowable bolt load for a given flange size. Subsequent to writing that paper, further investigation found that the code calculated flange stresses are a poor indicator of the maximum acceptable bolt load. The most practical measure of this load is obtained by using elastic-plastic finite element analysis (FEA) to determine the point of gross plastic deformation of the flange. This paper details the maximum bolt load limit results of elastic-plastic FEA on most sizes of standard ASME weld neck flange sizes. The practical application of this method is in the development of standard bolt assembly stress (or torque) tables for standard pipe flanges using a given gasket type. In addition, a new code equation and additional limits are developed, by comparison to the elastic-plastic FEA results, which allow the determination of the maximum assembly bolt load for non-standard weld-neck flanges and standard weld-neck flanges with different bores, materials or gaskets than used in the elastic-plastic FEA presented in this paper.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0040.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0170.014

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 head0.013
GPT teacher head0.295
Teacher spread0.282 · 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 designTheoretical or conceptual
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".

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Citations4
Published2007
Admission routes1
Has abstractyes

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