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Record W2937851636 · doi:10.31399/asm.cp.itsc2019p0520

Techno-Economic Assessment of Coating-Based Resistive Heating Systems versus Conventional Heat Tracers

2019· article· en· W2937851636 on OpenAlex
Kingsley Ngaokere, Amit Kumar, André McDonald, Daniel Hayden

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

VenueThermal spray · 2019
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCoatingMaterials scienceNichromeFabricationThermal sprayingTracingThermal energy storageResistive touchscreenElectric heatingComposite materialNuclear engineeringMetallurgyEngineeringComputer scienceElectrical engineering

Abstract

fetched live from OpenAlex

Abstract The economic feasibility of using thermal-sprayed heat generating coatings for temperature control in steel pipes was investigated. A data-intensive model was developed to compare fabrication, installation, operation, and maintenance expenditures with those of conventional heating cables. The multi-layered coating consists of flame-sprayed Al2O3 and NiCr layers and cold-sprayed copper. Scalability factors were incorporated in the model to estimate the total projected costs for fabricating the coatings as opposed to installing heat tracing. Although material costs for the coating and heat tracing were approximately the same, the cost of fabrication for the coating was higher due mainly to labor expenses. However, the coating-based system was found to be more energy efficient than heat tracing due to the good adhesion and reduced thermal contact resistance between the heating elements and pipe.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score0.821

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 head0.011
GPT teacher head0.256
Teacher spread0.245 · 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