MétaCan
Menu
Back to cohort
Record W3145344095 · doi:10.1109/mper.2002.4312298

Stochastic Evaluation of Turbine-Generator Shaft Torsional Torques in an HVAC/DC Power System

2002· article· en· W3145344095 on OpenAlex

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

VenueIEEE Power Engineering Review · 2002
Typearticle
Languageen
FieldEngineering
TopicMachine Fault Diagnosis Techniques
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsTorqueTurbineControl theory (sociology)Generator (circuit theory)Power (physics)Steam turbineMonte Carlo methodContext (archaeology)EngineeringMaximum power principleComputer scienceAutomotive engineeringMechanical engineeringElectrical engineeringPhysicsVoltageMathematics

Abstract

fetched live from OpenAlex

This paper presents a Monte Carlo based approach to evaluate the maximum torsional torques induced in turbine-generator shafts during faults on a HVac/dc power system. In this context, investigations have been conducted on a large turbine-generator model taking into consideration the uncertainty of various factors associated with the practical operation of a power system. The results of these investigations are presented in the form of probability distributions of the maximum torsional torques induced in the turbine-generator shaft sections. A risk index that reflects the likelihood that the torque induced in a turbine-generator shaft exceeds its design value is also presented. Moreover, the paper presents a method for calculating the expected life expenditure ratio and the expected lifetime of turbine-generator shafts.

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)0.001
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 score0.294
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.022
GPT teacher head0.289
Teacher spread0.266 · 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