No abstract

The enhancement of convective heat transfer in single-phase heat transfer through the use of helicoidally corrugated tubes has been studied numerically. By comparing the large eddy simulation (LES) results with detailed Stereo-PIV and Liquid Crystal Thermography measurements obtained at the von Karman Institute for Fluid Dynamics (VKI), a validated numerical framework was obtained. Heat transfer enhancements of 83-119% were seen, at the cost of pressure losses that were approximately 5.6 to 6.7 times higher than for a bare tube. To extrapolate the results to industrial Reynolds numbers at which experimental data is scarce, the simulation data was used to develop an improved near-wall Reynolds stress transport model (RSTM) that more accurately describes the heat flux vector. Comparison of both global and local flow characteristics at different Reynolds numbers confirms that the approach allows more accurate predictions over a wider range of design and operating parameters than using two-equation turbulence models, while the computational cost is still significantly lower than LES.

Streamwise periodic boundary conditions (SPBCs) have been successful in reducing the computational cost of simulating high aspect ratio processes. Extending beyond the classic assumptions of constant property flows, a novel approach incorporating non‐equilibrium kinetics was developed and implemented for the simulation of an industrial propane steam cracker. Comparison with non‐periodic benchmarks provided validation as relative errors on the main product yields were consistently below 1% for different reactor configurations. A further order‐of‐magnitude reduction of the radial errors on product concentrations was obtained via an intuitive correction method based on the concept of local fluid age. The computational speedup achieved through application of SPBCs was a factor 16–250 compared to the non‐periodic simulations. The presented methodology thus serves as a quick screening tool for the development of novel reactor designs and unlocks the potential for using more elaborate kinetic models or a more fundamental approach toward turbulence modeling. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1715–1726, 2017