Abstract

Computational fluid dynamics (CFD) has become a popular tool for investigating indoor convective heat transfer. Two methods are used for dealing with the convective heat transfer of walls in CFD. One is to apply wall functions, and the other is to implement near-wall modeling by generating sufficiently fine mesh in the boundary layer. The former method is very simple; however, it may not be applicable to indoor environments. The latter method is generally more accurate but requires a significant number of grid mesh to capture the viscous boundary sublayer. This investigation proposes to tune the wall Prandtl number to modify the standard temperature wall function for applicability to indoor convective heat transfer modeling. The adjustment attempts to obtain convective heat transfer coefficients of walls that match those provided by the correlation formulas. Because the variation of the convective heat transfer coefficients with the wall Prandtl number is nonlinear, it is necessary to repeat the CFD simulations by following the developed procedure. The proposed method has been applied to model both heat transfer and flow motion in a mixing ventilation mode and an under-floor displacement ventilation mode, respectively. The results reveal that the adjusted temperature wall function is able to solve accurately indoor convective heat transfer with a moderate grid number. The standard temperature wall function with the default wall Prandtl number yields an unacceptable temperature distribution; hence, it is not appropriate for indoor convective heat transfer modeling.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.