Notice bibliographique
Résumé
The microstructural basis of wear and surface degradation mechanisms in Al-Si alloys has been investigated in order to improve the current understanding of the requirements for wear resistant aluminum alloy design. The wear behaviour of three commercial alloys namely: a sand cast A390 (Al-18.4%Si), a spray formed Al-25%Si, and a die cast 383 (Al-9.5%Si) have been investigated. Dry sliding wear tests were performed using a block on ring type tribometer under controlled environments. The experiments were performed in a load range between 0.2 N and 300 N at a constant speed of 1 m/s. The testing environments were a dry air (5% RH), a humid air (95% RH), and an argon atmosphere. In dry air (5% RH), two main wear regimes namely, mild wear (MW), and severe wear (SW) were identified. The (MW) regime consisted of two sub-regimes: first and second regimes of mild wear, (MW-1) and (MW-2). The mild wear was controlled by the formation and destruction (spallation) of hardened tribolayers composed of Fe, Al, Si, and O which gave rise to steady state wear rates in both sub-regimes. The transition to second sub-regime was attributed to the destabilization and partial removal of the tribolayers on the contact surfaces. Severe wear occurred at loads exceeding 150 N irrespective of the alloy when the contact surface temperature reached a critical value (210-240°C). The wear rates (W) in each sub-regime of the MW obeyed the relation, W=CLn, where C and n were the wear coefficient and the wear exponent, respectively. The wear exponents, n, were similar in each of the sub-regimes for all three alloys, indicating that the same mechanisms controlled the wear rates. However, the wear coefficients, C, and the transition loads to the second sub-regime were considerably different for each alloy. A method of analyzing the wear coefficients and the transition loads of the alloys, based on pair-wise comparison between them, was developed. This method demonstrated that small equiaxed silicon particles, high alloy hardness, and high silicon content promoted a better wear resistance in the Al-Si alloys by delaying MW-1 to MW-2 transition, and reducing the wear coefficients. Wear tests performed on A390 in air with 95% RH and in argon atmospheres resulted in a 10-fold reduction of wear rates and formation of an ultra mild wear (UMW) regime at loads less than 10 N. UMW in an argon atmosphere was due to the formation of highly deformed Al-(Si) tribolayers, which were less brittle and were not removed as easily as Fe-Al-Si-O tribolayers formed in dry air (5% RH). UMW of A390 samples could be also achieved in dry air (5% RH) when the tests were performed against a diamond-like carbon (DLC) coated counterface at loads less than 10 N. The analysis showed that DLC reduced the wear and friction significantly through preventing the formation of Fe rich oxidized tribolayers and Al transfer to the counterface.Dept. of Electrical and Computer Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .E46. Source: Dissertation Abstracts International, Volume: 66-11, Section: B, page: 6210. Thesis (Ph.D.)--University of Windsor (Canada), 2005.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
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 tête enseignante, 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 ».