Estimating the thermal insulating performance of multi-component refractory ceramic systems based on a machine learning surrogate model framework (2020)
- Authors:
- Autor USP: MELLO, RODRIGO FERNANDES DE - ICMC
- Unidade: ICMC
- DOI: 10.1063/5.0004395
- Subjects: APRENDIZADO COMPUTACIONAL; MÉTODO DOS ELEMENTOS FINITOS; FORNO ELÉTRICO; TRANSFERÊNCIA DE CALOR
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Journal of Applied Physics
- ISSN: 0021-8979
- Volume/Número/Paginação/Ano: v. 127, n. 21, p. 215104-1-215104-7, June 2020
- Este artigo NÃO possui versão em acesso aberto
-
ABNT
SANTOS, Denise P et al. Estimating the thermal insulating performance of multi-component refractory ceramic systems based on a machine learning surrogate model framework. Journal of Applied Physics, v. 127, n. 21, p. 215104-1-215104-7, 2020Tradução . . Disponível em: https://doi.org/10.1063/5.0004395. Acesso em: 06 mar. 2026. -
APA
Santos, D. P., Pelissari, P. I. B. G. B., Mello, R. F. de, & Pandolfelli, V. C. (2020). Estimating the thermal insulating performance of multi-component refractory ceramic systems based on a machine learning surrogate model framework. Journal of Applied Physics, 127( 21), 215104-1-215104-7. doi:10.1063/5.0004395 -
NLM
Santos DP, Pelissari PIBGB, Mello RF de, Pandolfelli VC. Estimating the thermal insulating performance of multi-component refractory ceramic systems based on a machine learning surrogate model framework [Internet]. Journal of Applied Physics. 2020 ; 127( 21): 215104-1-215104-7.[citado 2026 mar. 06 ] Available from: https://doi.org/10.1063/5.0004395 -
Vancouver
Santos DP, Pelissari PIBGB, Mello RF de, Pandolfelli VC. Estimating the thermal insulating performance of multi-component refractory ceramic systems based on a machine learning surrogate model framework [Internet]. Journal of Applied Physics. 2020 ; 127( 21): 215104-1-215104-7.[citado 2026 mar. 06 ] Available from: https://doi.org/10.1063/5.0004395 - A novel approach to quantify novelty levels applied on ubiquitous music distribution
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