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Record W4210711026 · doi:10.1115/imece2021-69330

Innovation in Hydrotesting Above Ground Pipes: Analytical Solution via Integral Transforms for Discerning Test Fluid Temperatures Subject to Ambient Temperature Variations

2021· article· en· W4210711026 on OpenAlexaff
Pedro A. Isaza, K. K. Botros

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsNova Chemicals (Canada)
Fundersnot available
KeywordsBiot numberTransient (computer programming)Work (physics)MechanicsPipeline transportHydrostatic equilibriumIntegral transformTemperature measurementMaterials scienceThermodynamicsMathematicsComputer scienceMathematical analysisPhysicsEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Hydrostatic testing for strength and leaks of newly constructed pipelines are required by code. However, for exposed pipes challenges are encountered since ambient conditions can influence pressure responses. Additionally, there is uncertainty as to whether the temperatures measured at a pipe’s outer wall, which are used to compute the expected pressure profiles, are representative of the testing fluid. To help bridge the gap, this work demonstrates the use of integral transforms for analytically solving the non-homogeneous 1D transient equations prescribed for the fluid temperature inside a cylindrical pipe. The solution identified provides sufficient generality to accommodate arbitrary initial conditions and ambient temperature variations. Furthermore, a rate of change function is formulated which enables a direct assessment of the temperature equality assumption between the fluid and the pipe wall. The validity of the solution is then substantiated by demonstrating excellent agreement with results reported in the literature (for a scenario describing typical hydrotest conditions). From the results obtained it can be observed that as the Biot number increases the temperature equality assumption begins to break down. Finally, a simplified expression for the relationship between the rate of change of the ambient air and the average fluid temperatures was formulated for this special scenario, which again showed agreement with the results in the literature.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.679
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.228
Teacher spread0.217 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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