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Record W4293587182 · doi:10.31399/asm.cp.itsc2005p1416

Design of Alternative Multilayer Thick Thermal Barrier Coatings

2005· article· en· W4293587182 on OpenAlexaff
H. Samadi, T.W. Coyle

Bibliographic record

VenueThermal spray · 2005
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsCanadian Dairy Network
Fundersnot available
KeywordsThermal barrier coatingMaterials scienceCombustionCoatingDiesel fuelCubic zirconiaFuel efficiencyOperating temperatureComposite materialNOxTurbineThrust specific fuel consumptionThermalAutomotive engineeringProcess engineeringMechanical engineeringElectrical engineeringEngineeringCeramic

Abstract

fetched live from OpenAlex

Abstract Increasing the combustion temperature in diesel engines is an idea which has been pursued for over 20 years. Increased combusting temperature can increase the power and efficiency of the engine, decrease the specific fuel consumption, CO and (possibly) the NOx emission rate. At the same time, TBCs should protect the metallic substrate against the corrosive attack of fuel contaminants (Na, V, and S). The most common system used is Yittria Partially Stabilized Zirconia (Y-PSZ). However, in diesel engines Y-PSZ TBCs have not met with wide success. To reach the desirable temperature of 850-900°C in the combustion chamber from the current temperature of 350- 400°C, a coating with a thickness of at least 1mm is required. This introduces different considerations than in the case of turbine blade coatings, which are on the order of 100µm thick. The design of a multilayer coating employing relatively low cost materials with complementary thermal properties is described. Numerical models were used to optimize the thickness for the different layers to yield the minimum stress at the operating conditions while achieving the desired temperature gradient. Abstract only; no full-text paper available.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.894

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)0.0010.000

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 head0.018
GPT teacher head0.244
Teacher spread0.226 · 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 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

Citations0
Published2005
Admission routes1
Has abstractyes

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