Time-dependent modelling of short-term variability in the TeV-blazar VER J0521+211 during the major flare in 2020
: Abe, S.; Abhir, J.; Abhishek, A.; Acciari, V. A.; Aguasca-Cabot, A.; Agudo, I.; Aniello, T.; Ansoldi, S.; Antonelli, L. A.; Arbet Engels, A.; Arcaro, C.; Artero, M.; Asano, K.; Baack, D.; Babić, A.; Barres de Almeida, U.; Barrio, J. A.; Batković, I.; Bautista, A.; Baxter, J.; Becerra González, J.; Bednarek, W.; Bernardini, E.; Bernete, J.; Berti, A.; Besenrieder, J.; Bigongiari, C.; Biland, A.; Blanch, O.; Bonnoli, G.; Bošnjak, Ž.; Bronzini, E.; Burelli, I.; Campoy-Ordaz, A.; Carosi, A.; Carosi, R.; Carretero-Castrillo, M.; Castro-Tirado, A. J.; Cerasole, D.; Ceribella, G.; Chai, Y.; Cifuentes, A.; Colombo, E.; Contreras, J. L.; Cortina, J.; Covino, S.; D’Amico, G.; D’Elia, V.; Da Vela, P.; Dazzi, F.; De Angelis, A.; De Lotto, B.; de Menezes, R.; Delfino, M.; Delgado, J.; Delgado Mendez, C.; Di Pierro, F.; Di Tria, R.; Di Venere, L.; Dominis Prester, D.; Donini, A.; Dorner, D.; Doro, M.; Eisenberger, L.; Elsaesser, D.; Escudero, J.; Fariña, L.; Fattorini, A.; Foffano, L.; Font, L.; Fröse, S.; Fukami, S.; Fukazawa, Y.; García López, R. J.; Garczarczyk, M.; Gasparyan, S.; Gaug, M.; Giesbrecht Paiva, J. G.; Giglietto, N.; Giordano, F.; Gliwny, P.; Gradetzke, T.; Grau, R.; Green, D.; Green, J. G.; Günther, P.; Hadasch, D.; Hahn, A.; Hassan, T.; Heckmann, L.; Herrera Llorente, J.; Hrupec, D.; Imazawa, R.; Ishio, K.; Jiménez Martínez, I.; Jormanainen, J.; Kankkunen, S.; Kayanoki, T.; Kerszberg, D.; Kluge, G. W.; Kobayashi, Y.; Kouch, P. M.; Kubo, H.; Kushida, J.; Láinez, M.; Lamastra, A.; Leone, F.; Lindfors, E.; Lombardi, S.; Longo, F.; López-Coto, R.; López-Moya, M.; López-Oramas, A.; Loporchio, S.; Lorini, A.; Lyard, E.; Machado de Oliveira Fraga, B.; Majumdar, P.; Makariev, M.; Maneva, G.; Manganaro, M.; Mangano, S.; Mannheim, K.; Mariotti, M.; Martínez, M.; Martínez-Chicharro, M.; Mas-Aguilar, A.; Mazin, D.; Menchiari, S.; Mender, S.; Miceli, D.; Miener, T.; Miranda, J. M.; Mirzoyan, R.; Molero González, M.; Molina, E.; Mondal, H. A.; Moralejo, A.; Morcuende, D.; Nakamori, T.; Nanci, C.; Neustroev, V.; Nickel, L.; Nievas Rosillo, M.; Nigro, C.; Nikolić, L.; Nilsson, K.; Nishijima, K.; Njoh Ekoume, T.; Noda, K.; Nozaki, S.; Ohtani, Y.; Okumura, A.; Otero-Santos, J.; Paiano, S.; Paneque, D.; Paoletti, R.; Paredes, J. M.; Peresano, M.; Persic, M.; Pihet, M.; Pirola, G.; Podobnik, F.; Prada Moroni, P. G.; Prandini, E.; Principe, G.; Rhode, W.; Ribó, M.; Rico, J.; Righi, C.; Sahakyan, N.; Saito, T.; Saturni, F. G.; Schmidt, K.; Schmuckermaier, F.; Schubert, J. L.; Schweizer, T.; Sciaccaluga, A.; Silvestri, G.; Sitarek, J.; Sliusar, V.; Sobczynska, D.; Spolon, A.; Stamerra, A.; Strišković, J.; Strom, D.; Strzys, M.; Suda, Y.; Tajima, H.; Takahashi, M.; Takeishi, R.; Temnikov, P.; Terauchi, K.; Terzić, T.; Teshima, M.; Truzzi, S.; Tutone, A.; Ubach, S.; van Scherpenberg, J.; Vazquez Acosta, M.; Ventura, S.; Verna, G.; Viale, I.; Vigorito, C. F.; Vitale, V.; Vovk, I.; Walter, R.; Wersig, F.; Will, M.; Wunderlich, C.; Yamamoto, T.; Bachev, R.; Fallah Ramazani, V.; Filippenko, A. V.; Hovatta, T.; Jorstad, S. G.; Kiehlmann, S.; Lähteenmäki, A.; Liodakis, I.; Marscher, A. P.; Max-Moerbeck, W.; Omeliukh, A.; Pursimo, T.; Readhead, A. C. S.; Rodrigues, X.; Tornikoski, M.; Wierda, F.; Zheng, W.
Publisher: EDP Sciences
: 2025
: Astronomy and Astrophysics
: Astronomy & Astrophysics
: 694
: A308
: 0004-6361
: 1432-0746
DOI: https://doi.org/10.1051/0004-6361/202451378
: https://doi.org/10.1051/0004-6361/202451378
: https://research.utu.fi/converis/portal/detail/Publication/491477794
Self-repairing graphite protective layer has been discovered as a suitable protective layer in blast furnace (BF) hearth in recent years. In the current study, actual samples of self-repairing graphite protective layer taken from a commercial BF were analyzed in detail. The results revealed that the hot face of graphite protective layer exhibits a distinct white graphite luster, with large areas of graphite adhering to the surface. Along the direction of its formation, the sample displays a striped pattern with alternating layers. The graphite is strip-shaped, it is relatively coarse and unevenly distributed. The coarse graphite runs in the same direction, unlike graphite in molten iron which has no fixed direction in a chaotic state. The formation process of selfrepairing graphite protective layer can be concluded, graphite precipitates at the interface through heterogeneous nucleation. Crystal nuclei often preferentially adhere to the surface of these impurities to form, owing to the fact that the nucleation energy of heterogeneous nucleation is lower than that of homogeneous nucleation. Titanium is discovered during the observation of microscopic morphology of graphite protective layer, graphite protective layer is more robust due to the strengthening effect of titanium. Titanium strengthening mechanism of self-repairing graphite protective layer is summarized, the strengthening mechanism can be divided into four steps. TiC particles are dispersed around graphite, which reduces the difficulty of the orientation of flake graphite growth. The presence of TiC increases the growth rate of crystals. The four steps are cyclically performed, so the self-repairing graphite protective layer can precipitate layer by layer through titanium strengthening mechanism, which serves to protect the carbon brick in BF hearth.
:
The financial support of the German BMBF, MPG and HGF; the Italian INFN and INAF; the Swiss National Fund SNF; the grants PID2019-104114RB-C31, PID2019-104114RB-C32, PID2019-104114RB-C33, PID2019-105510GB-C31, PID2019-107847RB-C41, PID2019-107847RB-C42, PID2019-107847RB-C44, PID2019-107988GB-C22, PID2022-136828NB-C41, PID2022-137810NB-C22, PID2022-138172NB-C41, PID2022-138172NB-C42, PID2022-138172NB-C43, PID2022-139117NB-C41, PID2022-139117NB-C42, PID2022-139117NB-C43, PID2022-139117NB-C44 funded by the Spanish MCIN/AEI/ 10.13039/501100011033 and “ERDF A way of making Europe”; the Indian Department of Atomic Energy; the Japanese ICRR, the University of Tokyo, JSPS, and MEXT; the Bulgarian Ministry of Education and Science, National RI Roadmap Project DO1-400/18.12.2020 and the Academy of Finland grant nr. 320045 is gratefully acknowledged. This work was also been supported by Centros de Excelencia “Severo Ochoa” y Unidades “María de Maeztu” program of the Spanish MCIN/AEI/ 10.13039/501100011033 (CEX2019-000920-S, CEX2019-000918-M, CEX2021-001131-S) and by the CERCA institution and grants 2021SGR00426 and 2021SGR00773 of the Generalitat de Catalunya; by the Croatian Science Foundation (HrZZ) Project IP-2022-10-4595 and the University of Rijeka Project uniri-prirod-18-48; by the Deutsche Forschungsgemeinschaft (SFB1491) and by the Lamarr-Institute for Machine Learning and Artificial Intelligence; by the Polish Ministry Of Education and Science grant No. 2021/WK/08; and by the Brazilian MCTIC, CNPq and FAPERJ. This research has made use of data from the OVRO 40-m monitoring program (Richards et al. 2011), supported by private funding from the California Institute of Technology and the Max Planck Institute for Radio Astronomy, and by NASA grants NNX08AW31G, NNX11A043G, and NNX14AQ89G and NSF grants AST-0808050 and AST- 1109911. This publication makes use of data obtained at the Metsähovi Radio Observatory, operated by the Aalto University. The research at Boston University was supported in part by the National Science Foundation grant AST-2108622, and by several NASA Fermi Guest Investigator grants, the latest is 80NSSC23K1507. This study was based in part on observations conducted using the 1.8m Perkins Telescope Observatory (PTO) in Arizona, which is owned and operated by Boston University. This research was partially supported by the Bulgarian National Science Fund of the Ministry of Education and Science under grants KP-06-H38/4 (2019) and KP-06-PN-68/1 (2022). This research has made use of data from the MOJAVE database that is maintained by the MOJAVE team (Lister et al. 2018). V.F.R. was supported by the Academy of Finland projects 317636, 320045, 346071, and 322535. J.J. was supported by the Academy of Finland projects 320085, 322535, and 345899, as well as by the Alfred Kordelin Foundation. E.L. was supported by the Academy of Finland project Nos. 317636, 320045 and 346071. M.N.R. acknowledges the funding support from the Severo Ochoa program, the Agencia Española de Investigación (Ministerio de Ciencia, Innovación y Universidades), and the European Union. A.O. was supported by DAAD funding program 57552340. X.R. was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC 2094 – 390783311.
