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Record W2586583784 · doi:10.1109/iclp.2010.7845965

Modelling the lightning return-stoke current using Heidler function

2010· article· en· W2586583784 on OpenAlexaff
Khaled Elrodesly, Ali M. Hussein

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsWaveformLightning (connector)SIGNAL (programming language)Peak currentPulse (music)TowerCurrent (fluid)Noise (video)AcousticsElectrical engineeringComputer sciencePhysicsEngineeringPower (physics)VoltageArtificial intelligenceStructural engineering

Abstract

fetched live from OpenAlex

Different functions have been used to model the lightning return-stroke current with the aid of direct current measurements at tall structures. In this paper, a comparison between the Pulse function and Heilder function is carried out to determine the suitability of each of these functions for simulating the lightning return-stroke current, measured at the CN Tower. An automated system for estimating the lightning return-stroke current waveform parameters from the measured current derivative signal will be introduced. The curve fitting technique of the system, initial values and feasible regions of the function parameters will be discussed. Also, the idea of using an artificial lightning signal free of noise and reflections as a reference signal for evaluating the parameter extraction system will be presented. Finally, the lightning return-stroke current waveform parameters (peak, maximum rate of rise, risetime, pulse width, decay time and charge) are expressed in term of the Pulse or Heidler function parameters.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.019
GPT teacher head0.236
Teacher spread0.216 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations4
Published2010
Admission routes1
Has abstractyes

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