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Record W2069093949 · doi:10.1115/pvp2009-77147

Calculating Thermal Gradients in a B31.1 Welding End Transition Joint by Formulae

2009· article· en· W2069093949 on OpenAlexaff
David H. Creates

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsOntario Power Generation
Fundersnot available
KeywordsWeldingPipingPower (physics)Joint (building)Temperature gradientDisplacement (psychology)Structural engineeringThermal power stationThermalThermal expansionExpansion jointMechanical engineeringEngineeringMaterials scienceElectrical engineeringPhysicsComposite materialThermodynamics

Abstract

fetched live from OpenAlex

Fatigue evaluation in B31.1 is currently done based on Equation 1 & 2 [B31.1-2007] which considers only displacement load ranges. However, fatigue damage, in addition to displacement load ranges, is occurring in B31.1 piping due to pressure cycling and thermal gradients. To exacerbate this, power plant design pressures and temperatures are rising, new materials are being introduced, pipes and attached components are becoming increasingly thick, and owners are requiring power plants to heat-up and cool-down at faster rates. Also, power plant owners are more and more interested in extending the life of power plants beyond their original design life. This paper takes the first step in addressing the pressing need to address this additional fatigue damage by considering thermal gradients. Granted there are several configurations where thermal gradients could be calculated. As the first step, this paper provides formulae to quantify the thermal gradients in the prevalent B31.1 Welding End Transitions Fig. 127.4.2, or Tapered Transition Joints (TTJ) Appendix D [B31.1-2007] which produce bending loads in the pipe around the full circumference and add to the fatigue damage of these welded joints. The disadvantage of this approach is that the conservatisms inherent in the calculations of thermal gradients as per ASME Section III Subsection NB3600-2007 are also inherent in these calculations and may produce unacceptable results when evaluated as per [PVP2009-77148]. If results are unacceptable, it is warning that something else needs to be done. The advantage of this approach is that it eliminates the need for a computer program to quantify these thermal gradients, a computer program that is not normally accessible to the B31.1 designer anyway. Instead, the formulae use data that is available to the B31.1 designer, namely physical geometry, Thermal Conductivity and the Rate of temperature change of the fluid in the pipe. Calculating the magnitude of thermal gradients in a B31.1 TTJ is an essential step in evaluating their fatigue effects for design and in plant life extension considerations (see PVP2009-77148). This will further help to preserve the integrity of the piping pressure boundary and consequently, the safety of personnel in today’s power plants and into the future.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.008
GPT teacher head0.193
Teacher spread0.184 · 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

Citations2
Published2009
Admission routes1
Has abstractyes

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