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Record W4311238859 · doi:10.18280/mmep.090522

Validating the Reliability Simulation Using Bohlamp Circuit with Accelerated Life Test Method

2022· article· en· W4311238859 on OpenAlexvenueno aff
Bagus Wahyudi, Hangga Wicaksono

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2022
Typearticle
Languageen
FieldEngineering
TopicReliability and Maintenance Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsReliability (semiconductor)Computer scienceReliability engineeringSeries (stratigraphy)FidelitySimilarity (geometry)Test (biology)Artificial intelligenceEngineering

Abstract

fetched live from OpenAlex

Learning media is very importance tools to achieved the learning outcome like capable to design reliability engineering system (RES). The students should be understanding with basic theory of reliability and also have technical skill based on need analysis. Unfortunately, the RES learning media are still not available specially to implement of several type of reliability system. Objective of the study is introducing reliability device model simulation with choice option series, parallel and combine series-parallel system. Method of the study are using accelerated life testing method (ALT) which has been analyzed with statistical method to estimate life-time at normal condition. Validating value of each reliability system are have similarity between experimental test (Re) and theoretical (Rt) i.e.: series (Rt=0.329; Re=0.359); parallel (Rt=0.976; Re=0.972.), and combined of series-parallel (Rt=0. 651; Re=0.686). The conclusion is the parallel have high-fidelity on application of reliability simulation with error 0.000409.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.815
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.060
GPT teacher head0.247
Teacher spread0.187 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2022
Admission routes1
Has abstractyes

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