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Enregistrement W2765908446

Architects' perception of selected bio-based building materials in France and Gabon

2017· preprint· en· W2765908446 sur OpenAlexaboutno aff
Rostand Moutou Pitti, Alexia Jourdain, Manja Kitek Kuzman

Notice bibliographique

RevueHAL (Le Centre pour la Communication Scientifique Directe) · 2017
Typepreprint
Langueen
DomaineEngineering
ThématiqueForest Biomass Utilization and Management
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésHectareFirewoodGeographyForestryEurosAgroforestryArchaeologyEnvironmental protectionEnvironmental science
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

As a part of a larger research project that examined bio-based building materials that are underutilized in the construction of non-residential buildings, the presented mail survey was conducted in France and Gabon to determine how architects specify selected bio-based building materials. This study provides a preliminary assessment of the potential segments of architects in practice based on their attitudes to the use of wood in non-residential construction. France Among the most wooded countries, Russia ranks first (809 million hectares), then, Brazil (478 million hectares), Canada (310 million hectares), the United States (303 million hectares) ... In Europe, France occupies the fourth place-behind Sweden, Finland and Spain-with its 18 million hectares. It is a little less than 30% of the French territory. The French forest is very diverse, with 136 different species of trees. The area of French hardwood forests is 11.2 million hectares, or 71.2% of the forest. Private forest is dominated mainly by oaks, which occupy about 5 million hectares. Chestnut and poplar are specific species of the private forest. A little more than 4.4 million hectares are made up of coniferous forests with a great diversity of species: maritime pine, Scots pine, fir, spruce, Douglas-fir... The French forest employs 440,000 people, more than the automobile industry. It has a turnover of 60 billion euros per year, or nearly 3% of PIB (Produit Interieur Brut or GDP I think). The sector includes operators, sawmills, pulp mills, panel and furniture manufacturers, and firewood. A large part of the French forest is private: 3.3 million owners share it. Gabon In Central Africa and particularly in equatorial region, the forest plays a key role in this regulation. In the year 2000, Gabon produced more than 4 million m3 timber, of which 72% was Aucoumea Klaineana Pierre (AKP). However, in 2004, only 1.6 million m3 was produced, of which 61% was AKP. This decrease in lumber production was due to a new regulations of exploitation of trees. In 2009, after the prohibition by the Gabonese government of the exportation of logs, more structures focalised on the study and the exploitation of wood were born. Since then, a particular attention is done on the mechanical characterization of some species which are usually used in timber structures. One of more those species is AKP which is an endemic specie in central Africa's forest which is a long time, associated at the life of locals. In the recent past, AKP represents 80% of annual wood's production in this country and 90% of this specie is exported all over the world and particularly in Europa and Asia. It is used largely for plywood in building, in veneer, finished or semi-finished products and in the design of the paper. Using the information obtained in this study will contribute to an understanding of the probability that bio-based building materials are chosen in residential and non-residential buildings and to an understanding of the drivers and barriers for increased use. Change is difficult – the barriers to wood are complex and the building industry is both averse to risk and slowed by inertia – but with the right focus, the wood industry can make a difference. The study is extended to selected European countries and the US, as well as to Central Africa. The study is extended to selected European countries and the US, as well as to Central Africa. The first results show that several architects in Gabon have not given response the survey due to the difficulty to have computer and excellent web connection. However, the obtained results are very interesting and promised. These results will help the architects to choose efficiently the wood product for civil engineering constructions.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,254
Score d'incertitude au seuil0,977

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,008
Tête enseignante GPT0,215
Écart entre enseignants0,207 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2017
Routes d'admission1
Résumé présentoui

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