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Record W2792249633 · doi:10.4236/eng.2018.103006

Distance Control and Positive Security for Intrinsic Equipment Working in Explosive Potential Atmospheres

2018· article· en· W2792249633 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

VenueEngineering · 2018
Typearticle
Languageen
FieldEngineering
TopicIndustrial Automation and Control Systems
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsExplosive materialIntrinsic safetyMATLABElevatorProcess (computing)Control (management)Coal miningComputer scienceComputer securityEngineeringSimulationCoalWaste managementArtificial intelligenceStructural engineering

Abstract

fetched live from OpenAlex

In this paper, intrinsic safety and positive security distance control for an up/down elevator which extracts the materials from an underground coal mine is approached. For a better understanding of intrinsic safety and positive security, the first part of the paper describes the potential risk the workers are facing while working in dangerous environments like coal mining with “grisou” atmospheres and what the conditions of an unfortunate event to take place are. We presented the diagram and working principle for intrinsic safety equipment used in potential explosive areas based on which we modeled and simulated the intrinsic and positive security distance control in order to get a software solution for it. We created an algorithm and simulated the process in Matlab Simulink. The simulation results done in Matlab Simulink were then entered into a Moeller PLC using a ladder-type programming language. For protection against explosive atmospheres, the PLC is inserted into a metal housing with intrinsic protection and Positive Security.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.342
Threshold uncertainty score0.598

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 head0.006
GPT teacher head0.187
Teacher spread0.182 · 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