Sandeep Pandey

Sandeep Pandey

Engineer with a PhD in applied machine learning and scientific computing.

Journal articles

Published:

  1. Pandey S., Teutsch P., Mäder P., Schumacher J., 2022. Direct data-driven forecast of local turbulent heat flux in Rayleigh–Bénard convection, Physics of Fluids.

  2. Pandey S., Laurien E., 2021. [Effects of variable heat flux at supercritical pressure in vertical pipe flow](https://www.researchgate.net/publication/346005356_Effects_of_variable_heat_flux_at_supercritical_pressure_in_vertical_pipe_flow, International Journal of Heat and Mass Transfer.

  3. Pandey S., Evrim C., Laurien E., 2021. Numerical Analysis of Relaminarization in Turbulent Channel Flow. In High Performance Computing in Science and Engineering´ 19. Springer, Cham.

  4. Pandey S., Schumacher J., 2020. Reservoir computing model of two-dimensional turbulent convection, Physical Review Fluids.

  5. Pandey S., Chu X., Weigand B., Laurien E., Schumacher J., 2020. Relaminarized and recovered turbulence under nonuniform body forces, Physical Review Fluids.

  6. Pandey S., Schumacher J., Sreenivasan K.R., 2020. A perspective on machine learning in turbulent flows, Journal of Turbulence.

  7. Chu, X., Yang, G., Pandey, S. and Weigand, B., 2019. Direct numerical simulation of convective heat transfer in porous media. International Journal of Heat and Mass Transfer, 133, pp.11-20.

  8. Föll, F., Pandey, S., Chu, X., Munz, C.-D., Laurien, E., and Weigand, B., 2019. High-Fidelity Direct Numerical Simulation of Supercritical Channel Flow Using Discontinuous Galerkin Spectral Element Method. In High Performance Computing in Science and Engineering’18 (pp. 275-289). Springer, Cham.

  9. Chu, X., Chang, W., Pandey, S., Luo, J., Weigand, B. and Laurien, E., 2018. A computationally light data-driven approach for heat transfer and hydraulic characteristics modeling of supercritical fluids: From DNS to DNN. International Journal of Heat and Mass Transfer, 123, pp.629-636.

  10. Pandey, S., Chu, X., Laurien, E. and Weigand, B., 2018. Buoyancy induced turbulence modulation in pipe flow at supercritical pressure under cooling conditions. Physics of Fluids, 30(6), p.065105.

  11. Chang, W., Chu, X., Fareed, A.F.B.S., Pandey, S., Luo, J., Weigand, B. and Laurien, E., 2018. Heat transfer prediction of supercritical water with artificial neural networks. Applied Thermal Engineering, 131, pp.815-824.

  12. Pandey, S., Chu, X. and Laurien, E., 2018. Numerical analysis of heat transfer during cooling of supercritical fluid by means of direct numerical simulation. In High Performance Computing in Science and Engineering’17 (pp. 241-254). Springer, Cham.

  13. Pandey, S., Chu, X. and Laurien, E., 2017. Investigation of in-tube cooling of carbon dioxide at supercritical pressure by means of direct numerical simulation. International Journal of Heat and Mass Transfer, 114, pp.944-957.

  14. Pandey, S., Laurien, E. and Chu, X., 2017. A modified convective heat transfer model for heated pipe flow of supercritical carbon dioxide. International Journal of Thermal Sciences, 117, pp.227-238.

  15. Pandey, S. and Laurien, E., 2016. Heat transfer analysis at supercritical pressure using two layer theory. The Journal of Supercritical Fluids, 109, pp.80-86.

  16. Chu, X., Laurien, E. and Pandey, S., 2016. Direct Numerical Simulation of Heated Pipe Flow with Strong Property Variation. In High Performance Computing in Science and Engineering´ 16 (pp. 473-486). Springer, Cham.