Bulletin of the American Physical Society
71st Annual Meeting of the APS Division of Fluid Dynamics
Volume 63, Number 13
Sunday–Tuesday, November 18–20, 2018; Atlanta, Georgia
Session F33: Heat Transfer and Forced Convection 
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Chair: Stephan Weiss, Max Planck Institute Room: Georgia World Congress Center B405 
Monday, November 19, 2018 8:00AM  8:13AM 
F33.00001: Experimental investigation of a sheared thermally unstable boundary layer Stephan Weiss, Gabriele Nunnari, Eberhard Bodenschatz In many natural and industrial systems heat is transported by mixed convection, where an externally driven flow causes advection of the temperature field in addition to the fluid motion due to buoyancy of differentially heated areas. We investigate experimentally the heat flux across a thermally unstable boundary layer subject to a shear flow. In the experiment, we use a two meter long aluminum plate that is subject to a shear flow above its heated surface. For varying Richardson and Rayleigh numbers, we measure the heat flux from the plate, as well as the vertical velocity and temperature profiles above it by using hot 
Monday, November 19, 2018 8:13AM  8:26AM 
F33.00002: Mixed convection with uniform shear flow over horizontal and vertical walls Patrick Weidman A study is made to determine similarity solutions for uniform shear flow along horizontal and vertical heated plates. For vertical walls, one momentum equation and one energy equation give rise to two similarity variables and here the temperature must decrease as the 1/3 power of the streamise coordinate along the semiinfinite plate. For horizontal walls, two momentum equations and one energy equation give rise to three similarity variables and here the temperature must increase as the 1/3 power of the streamwise coordinate. 
Monday, November 19, 2018 8:26AM  8:39AM 
F33.00003: Deep learning of turbulent heat transfer in channel flow Junhyuk Kim, Changhoon Lee With the recent development of artificial intelligence(A.I.) and its wide applications, a fundamental question arises such as 'can turbulence be learned by A.I.?' In order to provide an answer to this question, we applied deep learning to the prediction of turbulent heat transfer based only on the wall shear and pressure information which was obtained by DNS. Through this study, we also tried to see whether deep learning can help our understanding of the physics of turbulent heat transfer. Under the assumption that the wall normal heat flux can be explicitly expressed through multilayer nonlinear network in terms of nearby wall shear stresses and wall pressure fluctuations, we applied convolutional neural networks to predict the local heat flux. After an optimization of the network models, we found that the network can predict heat transfer very well with correlation of 0.980 between DNS and prediction by the network for trained $Re$, and show similar performance at a $Re$ three times higher than the trained one, indicating that relations between the wall shear and the heat flux are almost independent of $Re$ within tested range. Additionally, through a sensitivity analysis of the trained model, we found which part of the input data is important in the prediction of heat flux. 
Monday, November 19, 2018 8:39AM  8:52AM 
F33.00004: ThermoHydrodynamic Instabilities in Fluid Flow at Supercritical Thermodynamic Conditions Rebecca Barney, Robert Nourgaliev, JeanPierre Delplanque, Rose McCallen We investigate the hydrodynamic instabilities occurring in the thermally developing flow of a fluid at supercritical thermodynamic conditions in a channel. Fluid at these conditions is compressible, single phase, with highly varying properties, and vanishing Mach number. In the configuration considered, flow stability is affected by competing natural and forced convection. We do not use the Boussinesq approximation. Instead, we solve the full compressible NavierStokes equations. An advanced equation of state for supercritical water was implemented in Arbitrary LagrangianEulerian multiphysics simulation tool developed at LLNL. A newly developed, robust, 5th order in space and time, fully implicit, allspeed, reconstructed discontinuous Galerkin method is used to simulate convective heat transfer with supercritical water. We find that with an increase in the driving force for natural convection, instabilities tend to become prominent earlier in the flow field and therefore affect the overall heat transfer of the system. Results demonstrate the capability of this approach to accurately capture the nonlinear behavior and instabilities arising in supercritical water flow, which cannot be adequately modeled using traditional incompressible fluid dynamics methods. 
Monday, November 19, 2018 8:52AM  9:05AM 
F33.00005: Convective heat transfer in partially porous channel flow Shilpa Vijay, Mitul Luhar While convective heat transfer in channels completely filled with metal foams has been studied extensively, turbulent heat transfer in channels that are partially filled with porous foams is less well understood. Previous direct numerical simulations for partiallyporous channel flow indicate that large vortex structures enhance turbulent heat transfer at the porous mediumunobstructed flow interface. This project aims to experimentally investigate this interfacial thermal transport. Commercially available Aluminum foams with porosity > 90% are attached to a heater and placed into a forced convection arrangement adjacent to an obstructed channel of equal height. With water as the fluid, pressure drop measurements have been made across the porous section to quantify friction factors for bulk Reynolds numbers ranging from 8904580. A twocomponent Laser Doppler Velocimeter (LDV) is being used to generate velocity profiles at different sections across the flow and point temperature measurements are being made along the channel to estimate the Nusselt number. Ultimately, this information will be used to evaluate heat transfer efficiency with respect to pumping power requirements. 
Monday, November 19, 2018 9:05AM  9:18AM 
F33.00006: Abstract Withdrawn

Monday, November 19, 2018 9:18AM  9:31AM 
F33.00007: Fountain entrainment in a filling box at low Reynolds numbers Nan Xue, Sepideh Khodaparast, Howard A Stone Pouring a lighter liquid into a container filled with a denser liquid creates a downward jet. The penetration of this jet into the tank is opposed by buoyancy, thus a return flow towards the upper surface occurs and forms a fountain. In such a condition, due to entrainment, a mixed layer of the two liquids is created in the upper part of the tank, whilst the lower section is only filled with the original denser liquid. In this experimental study, we characterize the behavior of fountains in bounded containers based on the Reynolds Re and Froude Fr numbers. Unlike a conventional turbulent fountain, we focus on the regime at lower Reynolds numbers Re < 500. We measure the fountain entrainment coefficient B by modeling this configuration as a filling box problem. We then show that B is a function of both Re and Fr, in contrast to the turbulent regime where B remains constant. For a given Fr, the fountain entrainment reaches a local peak at an intermediate Reynolds number Re ～ 200. We reason that this local peak of entrainment occurs due to the enhanced penetration of the downward jet and the moderate fountain entrainment coefficient at intermediate Reynolds numbers. Results of this study provide guidelines to achieve effective jetdriven mixing of two miscible liquids. 
Monday, November 19, 2018 9:31AM  9:44AM 
F33.00008: Forced convection heat transfer from a particle at small and large Peclet numbers Esmaeil Dehdashti, Hassan Masoud We theoretically study the forced convection heat transfer from a single particle in uniform laminar flows. We consider asymptotic limits of small and large Peclet numbers Pe. For Pe<<1 (diffusiondominated regime) and constant heat flux boundary condition on the surface of the particle, we derive a closedform expression for the heat transfer coefficient that is valid for arbitrary particle shape and flow Reynolds number. Remarkably, our formula for the average Nusselt number Nu is identical to the one obtained by Brenner for a uniform temperature boundary condition (Chem. Eng. Sci., vol. 18, 1963, pp. 109122). We also present a framework for calculating the average Nu of axisymmetric and twodimensional objects with a constant heat flux surface condition in the limits of Pe>>1 and small or moderate Reynolds numbers. Specific results are obtained for the heat transfer from spheroidal particles in Stokes flow. 
Monday, November 19, 2018 9:44AM  9:57AM 
F33.00009: Numerical simulation of heat transfer and fluid flow of low density polyethylene extrusion process using solar energy Jose Nunez Gonzalez, Alberto Beltran Morales In this work we examined the necessary conditions to use concentrating solar energy to carry out the melting process of low density polyethylene. The objective is to obtain a strip of recycled material. A numerical simulation of the heat transfer and fluid flow in an extruder will be performed. The recycling process for low density polyethylene is modeled using the conservation of mass, momentum and energy equations for a nonNewtonian fluid. The COMSOL Multiphysics and ANSYS Polyflow software are used to solve the governing equations. Based on the numerical simulation, the effect of the incident radiation, the velocity input and the viscosity of the fluid in the extrusion process are analyzed. 
Monday, November 19, 2018 9:57AM  10:10AM 
F33.00010: Bioinspired G. dalenii Surface for Condensation and Fog Harvesting applications Daniel Orejon, Vipul Sharma, Venkata Krishnan, Yasuyuki Takata, Sivasankaran Harish In this work we study the condensation and fog harvesting performance of a natural/fixated G. dalenii leaf and those of a replicated G. dalenii sample. Microstructure surface replication by our soft lithography procedure was found to be remarkable. In addition, both the mechanisms of nucleation and the dynamics of droplet growth showed a remarkable agreement within the standard deviation both in the presence and absence of noncondensable gases when comparing fixated and replicated G. dalenii samples. On the other hand, up to 200% greater fog harvesting performance was reported on the replicated G. dalenii sample when compared to the flat control one. The greater fog harvesting performance on the replicated sample was attributed to the presence of microstructures. A drop energy of adhesion analysis supports the better fog harvesting performance of the replicated sample. We conclude on the excellent surface structure, condensation mechanisms and fog harvesting performance replication by our soft lithography procedure. 
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