An MLP-P1model for indirect temperature predictions fromtotal incident radiation measurements

Tauana Ohland dos Santos, Gabriel Ribeiro Padilha, Pedro Henrique de Almeida Konzen

Resumo


n this work we present an artificial neural network (ANN) model for indirect temperaturepredictions from total incident radiation measurements in a given participating media. The inverseradiative heat transfer problem is set as a regression problem that has the total incident radiationmeasurements as dependent variables. [...]

Texto completo:

PDF

Referências


Frank, M., Seaid, M., Klar, A., Pinnau, R. and Th ̈ommes, G. A comparison of approximatemodels for radiation in gas turbines,Progress in Computational Fluid Dynamics, 4:191–197,2004. DOI:10.1504/PCFD.2004.004087.

Haykin, S.Redes neurais: princ ́ıpios e pr ́atica, 2a. edi ̧c ̃ao. Bookman, Porto Alegre, 2007.[3] Larsen, E. W., Th ̈ommes, G., Klar, A., Sei ̈ad, M. and G ̈otz, T. SimplifiedPNapproximationsto the equations of radiative heat transfer and applications,Journal of Computational Physics,183:652–675, 2002. DOI:10.1006/jcph.2002.7210.

Logg, A., Mardal, K.-A., Wells, G. N., et al. Automated Solution of Differential Equationsby the Finite Element Method. InLecture Notes in Computational Science and Engineering.Springer, volume 84, 2021. DOI: 10.1007/978-3-642-23099-8

.[5] Modest, M. F.Radiative Heat Transfer, 3a. edi ̧c ̃ao. Elsevier, New York, 2013.

Pedregosa, F., Varoquaux, G., Gramfort, A., et al. Scikit-learn: Machine Learning in Python,Journal of Machine Learning Research, 12:2825–2830, 2011.


Apontamentos

  • Não há apontamentos.


SBMAC - Sociedade de Matemática Aplicada e Computacional
Edifício Medical Center - Rua Maestro João Seppe, nº. 900, 16º. andar - Sala 163 | São Carlos/SP - CEP: 13561-120
 


Normas para publicação | Contato