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Record W2765827898 · doi:10.1115/pvp2017-66275

Analytical Modelling of Elastic Interaction in Bolted Flange Gasketed Joints

2017· article· en· W2765827898 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEngineering Structural Analysis Methods
Canadian institutionsÉcole de Technologie Supérieure
FundersNational Science and Technology Major ProjectNational Science Foundation
KeywordsFlangeStructural engineeringBolted jointGasketFinite element methodEngineeringTension (geology)PreloadMaterials scienceCompression (physics)Composite materialMechanical engineering

Abstract

fetched live from OpenAlex

Bolted flange joints are widely used in the fossil and nuclear power plants and other industrial complex. During their assembly, it is extremely difficult to achieve the target bolt preload and tightening uniformity due to elastic interaction. In addition to the severe service loadings the initial bolt load scatter increases the risk of leakage failure. The objective of this paper is to present an analytical model to predict the bolt tension change due to elastic interaction during the sequence of initial tightening. The proposed analytical model is based on the theory of circular beams on linear elastic foundation. The elastic compliances of the flanges, the bolts, and the gasket due to bending, twisting and axial compression are involved in the elastic interaction. The developed model can be used to optimize the initial bolt load tightening to obtain a uniform final preload under minimum number of tightening passes. The approach is validated using finite element analysis and experimental tests conducted on a NPS 4 class 900 weld neck bolted flange joint.

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.

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 score0.241
Threshold uncertainty score0.376

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 head0.052
GPT teacher head0.300
Teacher spread0.248 · 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

Quick stats

Citations3
Published2017
Admission routes1
Has abstractyes

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