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Title: Passive force balancing of an active magnetic regenerative liquefier

Active magnetic regenerators (AMR) have the potential for high efficiency cryogen liquefaction. One active magnetic regenerative liquefier (AMRL) configuration consists of dual magnetocaloric regenerators that reciprocate in a persistent-mode superconducting solenoid. Issues with this configuration are the spatial and temporal magnetization gradients that induce large magnetic forces and winding currents. To solve the coupled problem, we present a force minimization approach using passive magnetic material to balance a dual-regenerator AMR. A magnetostatic model is developed and simulated force waveforms are compared with experimental measurements. A genetic algorithm identifies force-minimizing passive structures with virtually ideal balancing characteristics. Finally, implementation details are investigated which affirm the potential of the proposed methodology.
Authors:
 [1] ;  [2] ;  [2] ;  [2] ;  [3] ;  [4] ;  [2] ;  [5]
  1. Univ. of Victoria, Inst. for Integrated Energy Systems (IESVIC), Victoria, BC (Canada); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  3. Ames Lab. and Iowa State Univ., Ames, IA (United States)
  4. Univ. of Victoria, Inst. for Integrated Energy Systems (IESVIC), Victoria, BC (Canada)
  5. Emerald Energy NW LLC (EENW), Bothell, WA (United States)
Publication Date:
Report Number(s):
IS-J-9628
Journal ID: ISSN 0304-8853; PII: S0304885317329086
Grant/Contract Number:
AC02-07CH11358
Type:
Accepted Manuscript
Journal Name:
Journal of Magnetism and Magnetic Materials
Additional Journal Information:
Journal Volume: 451; Journal Issue: C; Journal ID: ISSN 0304-8853
Publisher:
Elsevier
Research Org:
Ames Laboratory (AMES), Ames, IA (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY; Active magnetic regenerator; Gadolinium; Liquefaction; Superconducting; Genetic algorithm
OSTI Identifier:
1433668

Teyber, R., Meinhardt, K., Thomsen, E., Polikarpov, E., Cui, J., Rowe, A., Holladay, J., and Barclay, J.. Passive force balancing of an active magnetic regenerative liquefier. United States: N. p., Web. doi:10.1016/j.jmmm.2017.11.002.
Teyber, R., Meinhardt, K., Thomsen, E., Polikarpov, E., Cui, J., Rowe, A., Holladay, J., & Barclay, J.. Passive force balancing of an active magnetic regenerative liquefier. United States. doi:10.1016/j.jmmm.2017.11.002.
Teyber, R., Meinhardt, K., Thomsen, E., Polikarpov, E., Cui, J., Rowe, A., Holladay, J., and Barclay, J.. 2017. "Passive force balancing of an active magnetic regenerative liquefier". United States. doi:10.1016/j.jmmm.2017.11.002. https://www.osti.gov/servlets/purl/1433668.
@article{osti_1433668,
title = {Passive force balancing of an active magnetic regenerative liquefier},
author = {Teyber, R. and Meinhardt, K. and Thomsen, E. and Polikarpov, E. and Cui, J. and Rowe, A. and Holladay, J. and Barclay, J.},
abstractNote = {Active magnetic regenerators (AMR) have the potential for high efficiency cryogen liquefaction. One active magnetic regenerative liquefier (AMRL) configuration consists of dual magnetocaloric regenerators that reciprocate in a persistent-mode superconducting solenoid. Issues with this configuration are the spatial and temporal magnetization gradients that induce large magnetic forces and winding currents. To solve the coupled problem, we present a force minimization approach using passive magnetic material to balance a dual-regenerator AMR. A magnetostatic model is developed and simulated force waveforms are compared with experimental measurements. A genetic algorithm identifies force-minimizing passive structures with virtually ideal balancing characteristics. Finally, implementation details are investigated which affirm the potential of the proposed methodology.},
doi = {10.1016/j.jmmm.2017.11.002},
journal = {Journal of Magnetism and Magnetic Materials},
number = C,
volume = 451,
place = {United States},
year = {2017},
month = {11}
}