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Going Nuclear: Notes from the officially unofficial book tour
I work in the analytical labs at one of Europe’s oldest and largest nuclear sites: Sellafield, in northwestern England. I spend my days at the fume hood front, pipette in one hand and radiation probe in the other (and dosimeter pinned to my chest, of course). Outside the lab, I have a second job: I moonlight as a writer and public speaker. My new popular science book—Going Nuclear: How the Atom Will Save the World—came out last summer, and it feels like my life has been running at full power ever since.
Gretar Tryggvason, Ming Ma, Jiacai Lu
Nuclear Science and Engineering | Volume 184 | Number 3 | November 2016 | Pages 312-320
Technical Paper | doi.org/10.13182/NSE16-10
Articles are hosted by Taylor and Francis Online.
The transient motion of bubbly flows in vertical channels is studied, using direct numerical simulation (DNS) in which every continuum length and time scale is resolved. A simulation of a large number of bubbles of different sizes at a friction Reynolds number of 500 shows that small bubbles quickly migrate to the wall, but the bulk flow takes much longer to adjust to the new bubble distribution. Simulations of much smaller laminar systems with several spherical bubbles have been used to examine the full transient motion; those show a nonmonotonic evolution where all the bubbles first move toward the walls, and the liquid then slowly slows down, eventually allowing some bubbles to return to the center of the channel. Unlike the statistically steady state, where the flow structure is relatively simple and in some cases depends only on the sign of the bubble lift coefficient, the transient evolution is more sensitive to the governing parameters. Early efforts to use DNS results to provide values for the unresolved closure terms in a simple average model for the flow found by statistical learning from the data using neural networks are discussed. The prospect for using the results from simulations of large systems with bubbles of different sizes in turbulent flows for large eddy–like simulations are explored, including the simplification of the interface structure by filtering. Finally, preliminary results for flows undergoing topology changes are shown.