PHYSICS-INFORMED HYBRID DEEP LEARNING APPROACH IN RADIATIVE TRANSPORT OF MICRO-NANOSCALE POROUS MEDIUM
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Publisher
Begellhouse
Reference8 articles.
1. Y.S. Yang, J.R. Howell, D.E. Klein, 'Radiative Heat Transfer Through a Randomly Packed Bed of Spheres by the Monte Carlo Method', Journal of Heat Transfer, 105 (1983) 325-332.
2. S. Hajimirza, G. El Hitti, A. Heltzel, J. Howell, 'Using inverse analysis to find optimum nano-scale radiative surface patterns to enhance solar cell performance', International Journal of Thermal Sciences, 62 (2012) 93-102.
3. H.H. Kang, M. Kaya, S. Hajimirza, 'A data driven artificial neural network model for predicting radiative properties of metallic packed beds', Journal of Quantitative Spectroscopy and Radiative Transfer, 226 (2019) 66-72.
4. F. Tabassum, A. Eghtesad, G.-R. Domenikos, S. Hajimirza, 'ESTIMATING RADIATIVE PROPERTIES IN ARBITRARY POROUS MEDIA USING CASE-SPECIFIC DATA DRIVEN MACHINE LEARNING FRAMEWORKS', Begel House Inc., 2023.
5. F. Tabassum, A. Eghtesad, S. Hajimirza, 'ACCURATE ESTIMATION OF RADIATION HEAT TRANSFER IN HETEROGENEOUS PACKED BEDS USING DATA-DRIVEN MODELING', Begel House Inc., 2023.
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