Numerical Modeling and Prediction of Irreversibilities in Sub- and Supercritical Turbulent Near-Wall Flows

Most of heat transport and fluid flow occurring in nature and in technical applications are inherently turbulent. On closer inspection of turbulent flows, a wide range of length and time scales can be observed and it is obvious that these turbulent motions are unsteady, irregular and chaotic. Turbulent structures generally increase the disorder of the system resulting in a loss of available mechanical power, which can be expressed in terms of entropy production. This is the fundamental reason for irreversibilities in turbulent heat and fluid flows, and responsible for decreasing thermodynamic efficiency in many engineering devices. In spite of decades of research in the field of numerical simulations, it is still difficult to predict turbulent flows and causes of irreversibilities accurately. In this respect, large eddy simulations (LES) provide a promising approach, especially in dealing with turbulent flows with large scale, unsteady characteristics. Despite the great potential of LES, the extent of its usage for entropy generation analysis and thermodynamic optimization has been insignificant up to now. This can be mainly attributed to the high challenges in modeling of the unresolved irreversibilities in the subgrid. The present work is focused on the development of a reliable LES framework combined with the second law of thermodynamics that allows to characterize and optimize sub- and supercritical wall-bounded flow applications. This is progressively accomplished in a series of development steps including (1) the development of reliable numerical treatments to simulate turbulent heat and fluid flow in the context of large eddy and direct numerical simulations (DNS), (2) the development of advanced, wall-adapting subgrid-scale models for momentum transport, heat transport and entropy production, and (3) the generation of comprehensive DNS databases that allow to evaluate the present LES framework under realistic flow situations with complex thermodynamic properties. In order to establish the validity of the present approach, the numerical methods and models are systematically assessed by comparison with experimental and DNS reference data. Finally, the proposed LES framework is utilized to characterize supercritical fuel injection processes and to optimize impingement cooling devices based on the concept of entropy generation minimization (EGM). Important milestones towards LES as a reliable engineering tool for entropy generation analysis are achieved in this work. In particular, a new wall-adapting one-equation subgrid-scale model is proposed, which provides the correct asymptotic behavior in the near-wall region without using any ad-hoc or dynamic procedure. Regarding the subgrid-scale heat flux, a thermodynamically consistent heat flux model suitable for wall-bounded turbulent heat transport is proposed. Finally, using the inertial-convective subrange theory, appropriate closure terms for the subgrid-scale entropy generation related to friction loss and heat transport are derived. The developed LES framework is then used to characterize supercritical injection processes and to optimize impingement cooling. Based on entropy generation analysis, distinctive features of the disintegration process under supercritical conditions are described and optimal designs for impingement cooling devices are identified. This work demonstrates, that LES combined with second law analysis is a very valuable and viable tool for predictive engineering and design optimization of complex heat and fluid flow applications