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(1 - 3 of 3)
- Title
- COMPUTATIONAL STUDIES OF HEAT TRANSFER IN TURBULENT WAVY CHANNEL FLOWS
- Creator
- Dzubur, Amar
- Date
- 2018, 2018-05
- Description
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Heat transfer is studied in fully-developed turbulent flows through channels with various geometries using Direct Numerical Simulations (DNS)....
Show moreHeat transfer is studied in fully-developed turbulent flows through channels with various geometries using Direct Numerical Simulations (DNS). Channels where a sinusoidal wave is mapped along the wall in either the streamwise direction or spanwise direction are studied, and comparisons to a simple channel with flat walls (rectangular channel) are provided. The fluid flow velocities fi elds, and pressure fi elds are analyzed along with the vorticity generated in the flow, and are utilized in tandem with the Nusselt number calculated along the heat transfer boundaries, to derive a clearer description of the heat transfer performance of the various geometries. The geometries that have a sinusoidal wave mapped along the spanwise direction and not along the streamwise direction showed the poorest heat transfer performance, as exhibited by the lowest average Nusselt number. The performance of two channels, with an in-phase and out of phase sinusoidal wave mapped along the streamwise direction exhibited heat transfer performance signifi cantly higher than that shown by the rectangular channel, which served as baseline. The heat transfer differences can be largely attributed to the vorticity generation and superior fluid mixing that is generated by the periodic streamwise mapped sinusoid. Streamwise sinusoidal channels exhibit Nusselt numbers that are more than three times greater than the spanwise mapped sinusoid, and almost three times greater than that of the rectangular channel. It is shown that the difference among an in-phase and out of phase wave mapping exists, but is found to be minimal. Further exploration regarding potential geometries with various phase shifts, non-rounded corners, and longer simulation times would be beneficial.
M.S. in Mechanical and Aerospace Engineering, May 2018
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- Title
- An Experimental Investigation of Single Jet Heat Transfer with Surrounding Microjets
- Creator
- Ma, Weicong
- Date
- 2019
- Description
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An experimental investigation of a single main jet with surrounding microjets impinging on a flat heated surface was performed to understand...
Show moreAn experimental investigation of a single main jet with surrounding microjets impinging on a flat heated surface was performed to understand the role of the higher-speed microjets on the surface heat transfer. Eight microjets 45-degrees apart were fabricated on a circular disk mounted at the exit of the main jet axisymmetric. Heat transfer enhancement on the flat surface was evaluated by comparison with the results of a baseline single round jet with the same flow rate. The average Nusselt Number and the local Nusselt number in the radial direction are reported as functions of dimensionless nozzle-to-plate distance, dimensionless radial distance, and dimensionless mass flow rate ratio. Local Nusselt number contours are plotted as a function of radial position. The area-averaged Nusselt number and local Nusselt number beyond the near-field impingement jet region increases monotonically with increasing mass flow rate ratio and decreasing of nozzle-to-target distance. The local Nusselt number at the stagnation region shows a more complex behavior with the mass flow rate ratio and nozzle-to-target distance.
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- Title
- Data-Driven Methods for Soft Robot Control and Turbulent Flow Models
- Creator
- Lopez, Esteban Fernando
- Date
- 2022
- Description
-
The world today has seen an exponential increase in its usage of computers for communication and measurement. Thanks to recent technologies,...
Show moreThe world today has seen an exponential increase in its usage of computers for communication and measurement. Thanks to recent technologies, we are now able to collect more data than ever before. This has dawned a new age of data-driven methods which can describe systems and behaviors with increasing accuracy. Whereas before we relied on the expertise of a few professionals with domain-specific knowledge developed over years of rigorous study, we are now able to rely on collected data to reveal patterns, develop novel ideas, and offer solutions to the world’s engineering problems. No domain is safe. Within the engineering realm, data-driven methods have seen vast usage in the areas of control and system identification. In this thesis we explore two areas of data-driven methods, namely reinforcement learning and data-driven causality. Reinforcement learning is a method by which an agent learns to increase its selection of ideal actions and behaviors which result in an increasing reward. This method was applied to a soft-robotic concept called the JAMoEBA to solve various tasks of interest in the robotics community, specifically tunnel navigation, obstacle field navigation, and object manipulation. A validation study was conducted to show the complications that arise when applying reinforcement learning to such a complex system. Nevertheless, it was shown that reinforcement learning is capable of solving three key tasks (static tunnel navigation, obstacle field navigation, and object manipulation) using specific simulation and learning hyperparameters. Data-driven causality encompasses a range of metrics and methods which attempt to uncover causal relationships between variables in a system. Several information theoretic causal metrics were developed and applied to nine mode turbulent flow data set which represents the Moehlis model. It was shown that careful consideration into the method used was required to identify significant causal relationships. Causal relationships were shown to converge over several hundred realizations of the turbulent model. Furthermore, these results match the expected causal relationships given known information of self-sustaining processes in turbulence, validating the method’s ability to identify causal relationships in turbulence.
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