Notice bibliographique
Résumé
A methodology to reliably combine the effects of building aerodynamics and site climatology as a function of wind direction is needed to quantify the effects of wind directionality. It has been previously noted that considerations of wind directionality would result in risk-consistent, safer and more economical designs of buildings. In this doctoral exposition the author makes use of data collected at Texas Tech University to define such methodology. The West Texas Mesonet is used to define the mean and extreme climate in West Texas while the Wind Engineering Research Field Laboratory provides the aerodynamic data in representation of low-rise buildings. A novel approach to separate extremes in non-hurricane regions is presented by assuring that events are independent using atmospheric pressure data and using information from the continuous wind data sets. The aerodynamic extreme directional assessment of the low-rise building is based on estimates of pressure coefficients of building components representing the design of cladding and lateral and vertical forces representing the design of portal frames. \n \nThe current standards of minimum loading of structures in the United States and Canada take into account wind directionality by stating that there is a reduced probability of the extreme winds not necessarily coming from the most aerodynamically vulnerable direction. However, no systematic reliable measure is available to-date to establish such reduced probability using extreme value distributions. In the research presented in this investigation the combination of two databases (climatic and aerodynamic) to estimate wind directionality effects corroborate the assumptions in the Standard and provide a methodology to quantify the factor in a reliable way. Results indicate that while the use of a wind directionality factor is not recommended for structural building components, if non-structural (cladding) components (which have a more pronounced directionality effect) get a discount of approximately 20% in the wind load, roughly 18% of the building population in open terrain is seeing wind loads that exceed the specified design and thus will be exposed to larger risks. This level of risk is perhaps considered acceptable but these results are based on the assumption that the code has a consistent definition of loading coefficients on the 37th percentile (or FT1 mode). Since the ASCE 7 Standard was found to possess loading coefficients with smaller percentiles (i.e. most below the 15th percentile) the risk is actually larger. Due to the large uncertainties in the wind directionality factor produced by: (1) unknown random building orientations and (2) large probabilities of exceedance in the loading coefficients specified in the standard, the true directionality issue should only be accounted through detailed analysis and not by a wind directionality reduction factor irrespective of wind direction.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,031 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,007 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».