Thesis - Open Access
Master of Science (MS)
computational fluid dynamics, liquid argon time projection chamber, natural convection, neutrino detector
Natural convection driven flows are present in many engineering applications such as HVAC, electronics cooling, and cryogenic systems. Predicting the flow behavior of such systems requires experimentation or numerical simulation through Computational Fluid Dynamics due to the complex interactions of natural convection. Recent advances in computing resources have made CFD increasingly popular for engineering analysis of fluid dynamics and heat transfer. CFD simulation has several advantages over experimentation including: 1) cost, 2) ease of changing design parameters, and 3) time required to obtain results. These advantages lead to an increased likelihood of discovering an optimal design. However, systems with complex geometry require large computational mesh sizes requiring large amounts of computing power, which makes model development difficult. The goal of this research is to create a modeling framework for simulating natural convection using CFD that maximizes computational efficiency without sacrificing the quality of the solution. This framework includes the selection of buoyancy models, turbulence models, mesh type, level of mesh refinement. This study specifically employs CFD to predict the flow mechanics, thermal profiles, and impurity levels of liquid argon within a large neutrino detector that is influenced greatly by natural convection. A uniform distribution of impurities is desired to ensure accurate electron lifetime readings throughout the cryostat. The analysis will investigate the optimum location of filtration inlets and outlets, as well as simulate various operating conditions the detector will experience. This study is done in collaboration with Fermilab and the Deep Underground Neutrino Experiment.
Includes bibliographical references (pages 161-164)
Number of Pages
South Dakota State University
In Copyright - Non-Commercial Use Permitted
Propst, Aaron, "CFD Analysis Methods for Systems Driven by Natural Convection" (2017). Electronic Theses and Dissertations. 2145.
Available for download on Tuesday, December 18, 2018