Corrigendum to “Constraint-incorporated deep learning model for predicting heat transfer in porous media under diverse external heat fluxes” [Energy and AI 18 (2024) 100425] (Energy and AI (2024) 18, (S2666546824000910), (10.1016/j.egyai.2024.100425))

The authors regret that the citation of references in Table 1 contains error. Therefore, the authors would like to make the following correction. The major parts of amendments are in bold style: The revised Table 1 The revised references [60] Zayakin OV, Renev DS. Density of chrome–nickel ferroalloys. KnE Materials Science 2019; 5(1): 297–303. https://doi.org/10.18502/kms.v5i1.3981. [61] Wilthan B, Reschab H, Tanzer R, Schützenhöfer W, Pottlacher G. Thermophysical properties of a chromium–nickel–molybdenum steel in the solid and liquid phases. International Journal of Thermophysics 2008; 29(1): 434–444. https://doi.org/10.1007/s10765-007-0300-1. [62] Kuroki T, Kagawa N, Endo H, Tsuruno S, Magee JW. Specific heat capacity at constant volume for water, methanol, and their mixtures at temperatures from 300 K to 400 K and pressures to 20 MPa. Journal of Chemical & Engineering Data 2001;46(5): 1101–1106. https://doi.org/10.1021/je0002437. [64] Ramires ML, Nieto de Castro CA, Nagasaka Y, Nagashima A, Assael MJ, Wakeham WA. Standard reference data for the thermal conductivity of water. Journal of Physical and Chemical Reference Data 1995; 24(3): 1377–1381. https://doi.org/10.1063/1.555963. These amendments will not affect the calculation results and conclusions of the paper. The authors would like to apologise for any inconvenience caused.