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Record W2901929763 · doi:10.25071/10315/35356

Testing Analysis of Freezing Phenomenon in Conventional Carbon Steel Pipes

2018· article· en· W2901929763 on OpenAlex
R. Sydney Marsden, André McDonald

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

VenueProgress in Canadian Mechanical Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPhenomenonCarbon fibersMaterials scienceComposite materialPhysicsComposite number

Abstract

fetched live from OpenAlex

Solidification of water in closed piping systems is a common phenomenon in both the industrial and residential sectors. In some cases, the resulting damage may be both costly and dangerous and thus warrants attention. Therefore, further study of the cooling and freezing behavior of stagnant water within closed pipes seems to be necessary. In this regard, several experiments were performed to investigate the freezing behavior of water in pipes. The inelastic deformation, work hardening, and fracture of the pipes that were caused by volume expansion due to the freezing of the water were also studied. Two conventional steel pipe materials, namely ASTM A333-6 and ASTM A106-B, were used in the freezing tests. The fracture surfaces of the pipes were analyzed by using both macroscale and microscale images of the surfaces. Fractography analysis of the fractured regions was also performed by using a scanning electron microscope. It was found that the damage caused during freezing to the A106-B pipe was considerably more than that in the A333-6 pipe. The results confirm that A333-6 should be used instead of A106-B in pressure equipment, such as pipes, that are exposed to low temperatures.

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 categoriesMeta-epidemiology (narrow)
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 score0.058
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.010
GPT teacher head0.213
Teacher spread0.203 · 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