Effect of Surface State on Radiative Properties of Advanced High Strength Steel Strips
Notice bibliographique
Résumé
Automotive manufacturers increasingly turn to light-weighting through galvanized advanced high strength steels (AHSS) to improve fuel efficiency and reduce pollutant emissions without compromising passenger safety. Unfortunately, Canadian steel manufacturers report unacceptably high AHSS rejection rates due to substandard mechanical properties, both in terms of strength and zinc layer adhesion. Much of the issue can be traced back to temperature excursions during intercritical annealing, caused by improper heating control and errors in the pyrometrically-inferred temperatures used to control the furnaces. These errors, in turn, originate from the changing surface state of the steel strip, in terms of roughness and oxide formation, during thermal processing. This causes issues of steel heating control and wavelength-dependent variations in spectral emissivity, which are unaccounted for in the pyrometry measurement model. \nA large number of studies have been performed on correlating the surface state (e.g. oxide, roughness) and radiative properties of metals in the context of electromagnetic wave (EM) theory. The exact EM solution, along with other more approximate physical models, have been investigated to deal with the issue. Nevertheless, most of these studies are restricted to the modeling of bi-directional radiative properties, instead of wavelength-dependent spectral emissivity, which is critical to the improvement of heating control and pyrometry measurement. In addition, very few of these studies are related to AHSS, while none of them have been performed on correlating the surface state with radiative properties of AHSS subject to different alloy compositions and annealing conditions. As a consequence, the physical correlation between the surface state and radiative properties of AHSS still remain unclear. \nThis study aims to improve the robustness of industrial pyrometry measurement and heating control of AHSS during continuous galvanizing, by determining how spectral emissivity depends on surface state, AHSS alloy composition, and annealing atmosphere. To achieve this, the relationship between AHSS surface topography and spectral emissivity is elucidated in the context of EM wave theory. First, the correlation between the surface roughness and radiative properties of several as-received and oxidized AHSS samples are investigated using the Davies’ model with wavelet-filtering technique. Secondly, the radiative properties of as-received AHSS having different surface topographies are interpreted using geometric optics approximation (GOA) ray tracing and EM diffraction models. Finally, the effect of alloy composition and annealing atmosphere on selective oxidation and radiative properties of AHSS having polished and as-received substrate states are interpreted via the thin film interference model and a hybrid thin film/geometric optics model, respectively. \nIt is found that the geometric optics ray tracing can effectively predict the spectral emissivity of as-received AHSS within its validity domain. These findings will be useful for improving heating control via a correlation between the spectral absorptivity, heat absorption, and the roughness profile of the surface. The thin film interference model is applicable to the estimation of spectral emissivity of samples annealed in their smooth state. This provides a potential means to understand oxide formation kinetics in-situ through optical measurements during annealing, as well as to improve pyrometry measurements. The hybrid thin film/geometric optics model, however, is unable to capture the spectral emissivity of oxidized samples having rough states. This highlights the need for a more rigorous model which accounts for the complex oxide profile upon the rough substrate, and the complex wave interference mechanism underlying that scenario. \nThis research provides valuable insights into the development of an in-situ emissivity model during annealing that can be used to improve pyrometry measurement and heating control for industrial continuous galvanizing lines.
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 | 0,000 |
| Science ouverte | 0,001 | 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 ».