Implementation of pseudo-turbulence closures in an Eulerian–Eulerian two-fluid model for non-isothermal gas–solid flow. (2nd November 2019)

• Record Type: Journal Article
• Authors: Peng, C.; Kong, B.; Zhou, J.; Sun, B.; Passalacqua, A.; Subramaniam, S.; Fox, R.O.
• Is Part Of: Chemical engineering science. Volume 207(2019)
• Page Start: 663
• Page End: 671
• Publication Date: 2019-11-02
• Subjects: Computational fluid dynamics -- Pseudo-turbulent heat flux -- Two-fluid model -- Gas–solid flow; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; Chemical engineering; Periodicals; Electronic journals; 660
• DOI: 10.1016/j.ces.2019.06.054
• Languages: English
• ISSNs: 0009-2509

Abstract

Highlights: Pseudo-turbulence heat flux closure was modified and implemented in the two-fluid model. Pseudo-turbulence heat flux is a significant contributor to the evolution of the fluid temperature. Pseudo-turbulence heat flux cannot be neglected for high Reynolds number dilute cases. Abstract: The Eulerian–Eulerian two-fluid model is widely used for computational fluid dynamics simulations of gas–solid flows. For non-isothermal flows, the averaged conservation equations solved in the two-fluid model require closures for drag, gas–solid heat transfer, pseudo-turbulent velocity fluctuations and the pseudo-turbulent heat flux (PTHF). However, the pseudo-turbulence terms are usually neglected in two-fluid simulations due to the lack of accurate correlations. With the increase in computational power, closures for these terms are now available from particle-resolved direct-numerical simulation (PR-DNS). Here, the PTHF closure as well as the heat-transfer closure (i.e., the Nusselt number) extracted from PR-DNS are implemented in the two-fluid thermal energy equation in OpenFOAM. The implementation is validated by comparing the simulation results with the PR-DNS data for the temperature profiles. Based on the analysis of the thermal energy budget, the PTHF can have a significant contribution and neglecting it can lead to large errors.