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Record W2330327515 · doi:10.1061/41016(314)157

Cross-Border Connections: Guideline Documents, Codes, and Standards for wind

2008· article· en· W2330327515 on OpenAlexaffabout
Peter Irwin

Bibliographic record

VenueStructures Congress 2008 · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsRowan Williams Davies & Irwin (Canada)
Fundersnot available
KeywordsBridge (graph theory)Wind powerEngineeringWork (physics)Building codeAerodynamicsWind engineeringArchitectural engineeringMeteorologyTelecommunicationsCivil engineeringGeographyMechanical engineeringElectrical engineeringAerospace engineering

Abstract

fetched live from OpenAlex

Canada and the US have been leaders in developing the field of wind engineering. In the US one can go back to the collapse of Tacoma Narrows Bridge in 1940 as a triggering event for much of the early research by F.B Farquharson, von-Karman and others during the 1940's and 1950's into bridge aerodynamics. Later, in the 1960's J. Cermak and his co-workers at Colorado State University undertook pioneering work in developing accurate simulations of the natural wind within the planetary boundary layer. Almost in parallel, in Canada, at the University of Western Ontario techniques were being developed by A.G. Davenport and co-workers for measuring the complex wind loading patterns on buildings, and for studying the dynamic response of large structures such as tall buildings (e.g. the original World Trade Centre towers of New York) and bridges. Cermak was very instrumental in having wind runnel testing methods recognized in wind codes and standards and in developing wind loading provisions in the US. In Canada Davenport was equally active in developing the wind provisions for the National Building Code of Canada. As the 1970's progressed the knowledge of wind effects on buildings was greatly advanced by both Cermak's and Davenport's teams. Also other institutes in Canada such as the National Research Council of Canada, the University of British Columbia, the University of Toronto and Concordia in Montreal became active in the field of wind engineering research and consultation as well as several others such as MIT, Texas Tech and Johns Hopkins in the US. R. Scanlan pioneered advanced methods for analyzing bridge flutter in the US at Princeton and Johns Hopkins Universities. In the early 1970's the first purely private consulting firm in wind engineering was formed in Guelph, Ontario, Canada. It built its own wind tunnels and eventually became known as RWDI (short for Rowan Williams Davies and Irwin Inc.). Also in the US in the early 1980's the private firm of CCP, short for Cermak Peterka Peterson Inc., was formed by members of the group at Colorado State University to provide wind engineering services similar to RWDI's. By the 1990's the field of wind engineering had grown substantially and besides the major research programs going on at Universities such as Texas Tech, Colorado State, Western Ontario, and Concordia, wind tunnel testing of large buildings, stadiums and bridges had become routine at the private wind tunnel testing houses such as RWDI and CPP. All of this activity meant that there was considerable world leading expertise present on both sides of the border and the competition between the various test houses led to an acceleration in the range of wind engineering services provided and techniques used. It also led to numerous collaborative efforts in the development of various wind codes and standards, which this paper will now briefly summarise.

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)0.019
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.578
Threshold uncertainty score0.850

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.049
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.008
Science and technology studies0.0050.003
Scholarly communication0.0080.004
Open science0.0070.003
Research integrity0.0090.007
Insufficient payload (model declined to judge)0.0110.011

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 head0.010
GPT teacher head0.331
Teacher spread0.320 · 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 designNot applicable
Domainnot available
GenreOther

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 routes2
Has abstractyes

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