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Record W7015488772

TORNADO HAZARD ASSESSMENT

2008· article· en· W7015488772 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMeteorological Phenomena and Simulations
Canadian institutionsnot available
Fundersnot available
KeywordsTornadoNatural hazardHazard analysisFujita scaleRisk assessmentProbabilistic logicHazard
DOInot available

Abstract

fetched live from OpenAlex

Tornadoes are one of the leading causes of property damage and death in North America, especially in the United States. Although the average number of tornadoes per year in Canada is far less than that in the US, in some regions such as southern Ontario, tornadoes are one of the most destructive natural hazards in terms of property damage and death. However, quantitative tornado hazard assessment has not been reported for this region. Such an assessment for normal buildings, infrastructure systems and critical facilities is needed to better understand and reduce natural disaster and to promote public health, safety and prosperity. The assessment should consider single as well as multiple facilities experiencing the same tornado event; it should also consider the possibility of a tornado outbreak. To carry out tornado hazard assessment considering a single tornado, in the present study, a statistical characterization of tornado parameters in southern Ontario is developed using the tornado database of Ontario as well as that of the neighbouring regions in the United States. These parameters include the tornado occurrence rate, the intensity, path length and width, and direction of motion. Using the developed statistics and an existing wind field model, a probabilistic assessment of the tornado hazards for point-like structures and line structures or elongated systems such as transmission lines in terms of wind speed are obtained for southern Ontario. A probabilistic assessment is also carried out for multiple critical facilities or infrastructural systems such as power plants, hospitals, power transmission lines etc. experiencing the same tornado. The assessment is focused on a sensitivity analysis of the tornado hazard considering multiple ‘facilities’ with different orientations, footprints and spatial separations. It is hoped that such an assessment will facilitate and guide disaster mitigation planning. Furthermore, an approach for characterizing tornado outbreak and extreme wind hazard due to tornado outbreak is also developed. The statistical characterization of tornado outbreaks is obtained using the tornado database of the neighbouring regions of southern Ontario in the United States. Using the proposed approach and developed statistics, an assessment of hazard due to tornado outbreaks is carried out for an area representing a city or any urban or suburban area in southern Ontario. Finally, a procedure for assessing global structural capacity of a latticed transmission line tower under extreme wind load is given by considering that the tower could be adequately treated as two-dimensional model. Both the nonlinear static pushover analysis and incremental dynamic analysis are incorporated in this assessment procedure. The procedure is implemented to evaluate the capacity of a tower designed according to design code. It is expected that such a simplified analysis for transmission towers will facilitate possible future quantitative reliability and risk assessment of transmission lines under the tornado hazard.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.362

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.002

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 head0.139
GPT teacher head0.306
Teacher spread0.166 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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