Identification and Development of a Reliable Framework to Predict Passive Scalar Transport for Turbulent Bounded Shear Flows

Dissertation advisors: Amirfarhang Mehdizadeh and Majid Bani-YaghoubVitaIncludes bibliographical references (page 159-175)Thesis (Ph.D.)--School of Computing and Engineering, Department of Mathematics and Statistics. University of Missouri--Kansas City, 2020Title from PDF of title page viewed January 31, 2022Heat transfer modeling plays an integral role in optimization and development of highly efficient modern thermal-fluid systems. However, currently available heat flux models suffer from fundamental shortcomings. For example, their development is based on the general notion that an accurate prediction of the flow field will guarantee an appropriate prediction of the thermal field, as the Reynolds Analogy does. Furthermore, literature about advanced models that aim to overcome this notion, does not provide reliable information about prediction capabilities. These advanced models can be separated into two distinct heat flux model categories, namely the implicit and explicit models. Both model categories differ fundamentally in their mathematical and physical formulation. Hence, this dissertation presents a comprehensive assessment of the Reynolds Analogy regarding steady and unsteady calculations. It further analyses the entropy generation capability in detail and evaluates the prediction accuracy of implicit and explicit models when applied to turbulent shear flows of fluids with different Prandtl numbers. Moreover, the implicit and explicit models are modified such that important thermal second order statistics are included. This enables deeper insight into the mechanics of thermal dissipation and delivers a better understanding towards the sensitivity and reliability of predictions using heat flux models. Finally, to overcome the shortcomings of the Reynolds Analogy in unsteady calculations, an anisotropic extension is proposed. This dissertation shows that even for first order statistics within steady state calculations, the Reynolds Analogy is only appropriate for fluids with Prandtl numbers around unity. For second order statistics within unsteady simulations, the Reynolds Analogy could provide acceptable results only if an appropriate grid design/resolution is provided that allows resolving essential dynamics of the thermal field. Concerning entropy generation, the Reynolds Analogy provides acceptable results only for mean entropy generation, while it fails to predict entropy generation at small/sub-grid scales. The anisotropic extension of the Reynolds Analogy is a promising approach to overcome these shortcomings. Furthermore and concerning the implicit and explicit heat flux models, this work shows that only the explicit framework is potentially capable of dealing with complex turbulent thermal fields and to address longstanding shortcomings of currently available models, if the flow field is predicted accurately. Moreover, it has been shown that thermal time scale plays an integral role to predict thermal phenomena, particularly those of fluids with low/high Pr numbers.Introduction -- A comprehensive Assessment of the Reynolds Analogy in Predicting Heat Transfer in Turbulent Wall-Bounded Shear Flows -- Entropy Generation Assessment for Wall-Bounded Turbulent Shear Flows Based on Reynolds Analogy Assumptions -- An Assessment pf the Reynolds Analogy in Predicting Heat Transfer in Turbulent Flows of Low Prandtl Numbers -- A Wall-Adapted Anisotropic Heat Flux Model for Large Eddy Simulations of Complex Turbulent Thermal Flows -- Towards Identification and Development of a Reliable Framework to Predict the Thermal Field in Turbulent Wall-Bounded Shear Flow -- Conclusion and Outloo

Entropy generation assessment for wall-bounded turbulent shear flows based on the Reynolds Analogy assumptions

Heat transfer modeling plays a major role in design and optimization of modern and efficient thermal-fluid systems. Further, turbulent flows are thermodynamic processes, and thus, the second law of thermodynamics can be used for critical evaluations of such heat transfer models. However, currently available heat transfer models suffer from a fundamental shortcoming: their development is based on the general notion that accurate prediction of the flow field will guarantee an appropriate prediction of the thermal field, known as the . In this work, an assessment of the capability of the in predicting turbulent heat transfer when applied to shear flows of fluids of different Prandtl numbers will be given. Towards this, a detailed analysis of the predictive capabilities of the concerning entropy generation is presented for steady and unsteady state simulations. It turns out that the provides acceptable results only for mean entropy generation, while fails to predict entropy generation at small/sub-grid scales

Analysis of Thermal Convection for a Large Scale Cryogenic Tank Demonstrator in OpenFOAM

Within the scope of this thesis a CFD model is developed to qualitatively described a stratification experiment performed at the DLR. To understand the physical effects the theoretical background for heat transfer, phase change and turbulence modeling is given. The stratification phenomenon is presented with a literature overview. In addition to the theoretical principle, the existing flow pattern and an overview about the present research in experiments and simulations is given. The research on stratification of cryogenic fluids is still in progress. Several up to now essential publications are from the Apollo era, especially for flow pattern. The drawback of these papers is that they discuss the stratifcation of water instead of a cryogenic liquid. Furthermore, especially the simulation of stratification in cryogenic tanks is a rather less researched field

Entropy Generation Assessment for Wall-Bounded Turbulent Shear Flows Based on Reynolds Analogy Assumptions

Heat transfer modeling plays a major role in design and optimization of modern and efficient thermal-fluid systems. Further, turbulent flows are thermodynamic processes, and thus, the second law of thermodynamics can be used for critical evaluations of such heat transfer models. However, currently available heat transfer models suffer from a fundamental shortcoming: their development is based on the general notion that accurate prediction of the flow field will guarantee an appropriate prediction of the thermal field, known as the . In this work, an assessment of the capability of the in predicting turbulent heat transfer when applied to shear flows of fluids of different Prandtl numbers will be given. Towards this, a detailed analysis of the predictive capabilities of the concerning entropy generation is presented for steady and unsteady state simulations. It turns out that the provides acceptable results only for mean entropy generation, while fails to predict entropy generation at small/sub-grid scales

Revista galega do ensino

Resumen basado en el de la publicaciónSe trata de una experiencia llevada a cabo con un alumno que no es capaz de comunicarse mediante el lenguaje oral. Se pretende dar una visión sobre las posibilidades de encontrar los canales que permitan la relación de estos jóvenes con quienes les rodean, tomando como referencia el Sistema Pictográfico de Comunicación de Mayer-Johnson. Así mismo se buscan sistemas alternativos de comunicación para niños con graves dificultades de comunicación, debido a sus limitaciones en la ejecución del habla.GaliciaES