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Record W2526072779 · doi:10.11159/htff16.121

Flow Characteristics in an Inter-Turbine Duct Under Off Design Conditions

2016· article· en· W2526072779 on OpenAlexvenueno aff
Abhinesh Kumar, A. M. Pradeep

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsTurbineDuct (anatomy)Computer scienceFlow (mathematics)Design flowMarine engineeringMechanicsMechanical engineeringPhysicsEngineeringEmbedded system

Abstract

fetched live from OpenAlex

In the present numerical study, flow characteristics of an aggressive inter-turbine duct under design and off-design inflow conditions, are reported. Two duct geometries (1) un-strutted and (2) strutted are considered. An un-strutted duct with sector angle of 20 o and a strutted duct with 40 o sector angle are analyzed. The performance of the duct is evaluated using static pressure recovery and total pressure loss. For simulating off design conditions, the duct inlet boundary is imposed with a typical tip leakage profile (reminiscent of the exit flow from the preceding high pressure turbine stage) and swirl. The swirl is varied between 10 o to 30 o . Under off-design conditions, the un-strutted duct shows only marginal deviation in its performance. However, the strutted duct showed a significant increase in loss under off-design conditions.

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 score0.121
Threshold uncertainty score0.587

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 head0.008
GPT teacher head0.203
Teacher spread0.195 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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