CAD Technique for Microwave Chemistry Reactors with Energy Efficiency Optimized for Different Reactants
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CAD Technique for Microwave Chemistry Reactors with Energy Efficiency Optimized for Different ReactantsAbstract
Upgrading successful processes of microwave-assisted organic synthesis to the level of industrial technology is currently slowed by difficulties in experimental development of largescale and highly-productive reactors. This paper proposes to address this issue by developing microwave chemistry reactors as microwave systems, rather than as black-box-type units for chemical reactions. We suggest an approach based on the application of a neural network optimization technique to a microwave system in order to improve its coupling (and thus energy efficiency). The RBF network optimization with CORS sampling introduced in our earlier work and capable of exceptionally quick convergence to the optima due to a dramatically reduced number of underlying 3D FDTD analyses, is upgraded here to account for an additional practically important condition requiring optimal design of the reactor for different reactants. Viability of the approach is illustrated by three examples of finding the geometry of a conventional 99% energy efficient microwave reactor for 3/3/6 different materials; with 1/5/1 liter reactants, seven-parameter optimization yields the best configurations taking only 16/38/115 hours of CPU time of a regular PC.
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References
P. Lidstrom, J. Tierney, B. Wathey, and J. West-
man, “Microwave assisted organic synthesis – a re-
view,” Tetrahedron, vol. 57, pp. 9225-9283, 2001.
D. Bodgal, Microwave-Assisted Organic Synthesis,
Elsevier, 2005.
C. O. Kappe and A. Stadler, Practical Microwave
Synthesis for Organic Chemists: Strategies, Instru-
ments, and Protocols, Wiley-VCH, 2009.
J. M. Kremsner, A. Stadler, and C. O. Kappe, “The
scale-up of microwave-assisted organic synthesis,”
Top Curr Chem, vol. 266, pp. 233-278, 2006.
V. V. Komarov and V. V Yakovlev, “CAD of
efficient TMmn0 single-mode elliptical applicators
with coaxial excitation,” J. Microwave Power &
Elec-tromag. Energy, vol. 40, no. 3, pp. 174-185,
M. Celuch, W. K. Gwarek, and M. Sypniewski, “A
novel FDTD system for microwave heating and
thawing analysis with automatic time-variation of
enthalpy-dependent media parameters,” Advances
in Microwave and Radio-Frequency Processing,
pp. 199-207, 2006.
P. Kopyt and M. Celuch, “Coupled electromagnetic
thermodynamic simulations of microwave heating
ACES JOURNAL, VOL. 25, NO. 12, DECEMBER 2010
problems using the FDTD algorithm,” J. Micro-
wave Power & Electromag. Energy, vol. 41, no. 1,
pp. 18-29, 2007.
M. Celuch and P. Kopyt, “Modeling microwave
heating of food,” Development of Packaging and
Products for Use in Microwave Ovens, pp. 307-
, 2009.
V. A. Mechenova and V. V. Yakovlev, “Efficiency
optimization for systems and components in micro-
wave power engineering,” J. Microwave Power &
Electromag. Energy, vol. 39, no. 1, pp. 15-29,
B. G. Cordes and V. V. Yakovlev, “Computational
tools for synthesis of a microwave heating process
resulting in the uniform temperature field,” Proc.
th AMPERE Conf. Microwave and High Fre-
quency Heating, pp. 71-74, September 2007.
E. E. Eves, B. G. Cordes and V. V. Yakovlev,
“Modeling-based synthesis of a microwave heating
process producing homogeneous temperature
field,” Proc. 24 th Annual Review of Progress in
Applied Computational Electromagnetics, pp. 542-
, 2008.
S. Kalhori, N. Elander, J. Svennebrink, and S.
Stone-Elander, “A re-entrant cavity for microwave-
enhanced chemistry,” J. Microwave Power & Elec-
tromag. Energy, vol. 38, no. 2, pp. 125-135, 2004.
K.-M. Huang, Z. Lin, and X.-Q. Yang, “Numerical
simulation of microwave heating of chemical reac-
tion in dilute solution,” Progress in Electromagne-
tics Research (PIER), vol. 49, pp. 273-289, 2004.
E. K. Murphy and V. V. Yakovlev, “RBF network
optimization of complex microwave systems
represented by small FDTD modeling data sets,”
IEEE Trans. Microwave Theory Tech., vol. 54, no.
, pp. 3069-3083, 2006.
H. Kabir, Y. Wang, M. Yu, and Q. J. Zhang, “Neu-
ral network inverse modeling and applications to
microwave filter design,” IEEE Trans. Microwave
Theory and Tech., vol. 56, no. 4, pp. 867–879,
E. K. Murphy and V. V. Yakovlev, “Reducing a
number of full-wave analyses in RBF neural net-
work optimization of complex microwave struc-
tures,” IEEE MTT-S Intern. Microwave Symp. Dig.,
pp. 1253-1256, June 2009.
H. Kabir, Y. Wang, M. Yu, and Q. J. Zhang, “Ad-
vances of neural network modeling methods for
RF/microwave applications,” ACES Journal, vol.
, no. 5, pp. 423–432, 2010.
R. G. Regis and C. A. Shoemaker, “Constrained
global optimization of expensive black box func-
tions using radial basis functions,” J. Global
Optim., vol. 31, no. 1, pp. 153–171, 2005.
QuickWave-3D, QWED, http://www.qwed/com/pl,
-2009.
E. K. Murphy and V. V. Yakovlev, “RBF network
optimization with CORS sampling for practical
CAD of microwave applicators,” Proc. 12th
AMPERE Conf. Microwave and High Frequency
Heating, pp. 79-82, September 2009.
E. K. Murphy and V. V. Yakovlev, “Efficiency
optimization for microwave thermal processing of
materials with temperature-dependent media
parameters,” Proc. Progress in Electromagnetics
Research Symp., pp. 400-401, August 2009.
