Effect of Nickel Content on the Corrosion Behaviour of Stainless Steel at 80 °C
Notice bibliographique
Résumé
A range of Fe-Cr-Ni alloys are used in nuclear power plants due to their high mechanical strength and corrosion resistance. As a major component of these alloys, Ni contributes to the formation of austenite microstructures. In many nuclear reactor applications the alloys are exposed to ionizing radiation (g-rays) that can continuously decompose water to a range of highly redox active species (such as •OH, H 2 O 2 , O 2 ). The change in water chemistry induced by radiation can affect both the general and localized corrosion behaviour of these alloys. In particular, its influence on the susceptibility of an alloy to localized corrosion such as crevice and stress corrosion cracking (SCC) are important for assessment of reactor component aging. As well, corrosion products that dissolve into the reactor coolant can be transported to the reactor core where they can be neutron activated. This can create a radiological hazard for reactor maintenance personnel. Thus, quantifying the rate of general corrosion and the corrosion product transport in a reactor are important safety, operation and maintenance issues. It has been well established that the type of oxide that forms on a surface is a critical factor in determining both general and localized corrosion behaviour. Both alloy composition and water chemistry affect the type of oxide that forms. Systematic studies that examine the effect of alloy composition on corrosion are rare and those available have been conducted mostly from a metallurgical perspective. There are even fewer studies that examine the combined effects of alloy composition and corrosion environment. A fundamental understanding of the mechanism by which the Fe to Ni ratio in a steel alloy influences the corrosion rate in different environments will provide valuable information that can be used for alloy selection and usage. We have investigated the effect of the Fe to Ni ratio of alloy on oxide formation and growth kinetics. For this study, customized steel alloys with different Ni contents and constant Cr content (18 ± 1 %) were prepared. The Ni content ranged from 15 to 25 wt.%, within the range between AISI 316L and Alloy 800 (Fig. 1). The corrosion kinetics was investigated using a combination of coupon corrosion tests and electrochemical measurements. These measurements were augmented by oxide surface and depth analyses using several spectroscopic and imaging techniques, and by post-test solution analyses for dissolved metal loss. We found that the oxide formed at pH 10.6 and 80 °C has a graded layer structure, consisting of a mixed spinel oxide (FeCr 2 O 4 /Fe 3 O 4 /NiFe 2 O 4 ) as an inner layer and Ni(OH) 2 as an outer layer. The increase in Ni content from 15 to 25 wt.% does not affect the inner layer but increases the thickness of the Ni(OH) 2 layer. The increase in Ni content also decreases the total amount of dissolved metal loss. Gamma-irradiation of the corroding system increases the corrosion potential on these alloys. Correspondingly, gamma-radiation accelerates the formation of passive oxide layers and decreases the overall rate of metal dissolution. The observed kinetics of oxide growth and metal dissolution can be explained by the competition kinetics of oxide growth and dissolution for oxidized metals. Figure 1
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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 | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».