[Beowulf] Re: Beowulf Digest, Vol 15, Issue 16

Jim Lux James.P.Lux at jpl.nasa.gov
Mon May 9 12:02:51 PDT 2005

At 09:49 AM 5/9/2005, David Mathog wrote:

> >
> > It's a design problem ripe for interaction too.  There's a lot of
> > parameters I can change (size and shape of the patches, segmentation,
> > spacing, etc.), so running a "try all possible values of all variables
> > overnight" strategy won't work.  Equally poor would be a "submit massive
> > batch job to the JPL DELL 1024 processor cluster", mostly because the
> > design space probably spans several thousand parameter combinations.  I
> > want to try a few things, then try some more, and use my experience to
> > guide the process, not depend on a optimizing program, for which I'd have
> > to come up with a goal function that is sort of ill-defined.
>So you have a calculation problem that's embarrassingly parallel
>but an infinite parameter space to search.  Seems to me that if
>this process is to be automated you will need to define a goal
>function, presumably based primarily on the far field results,
>and then use some search strategy or other to try to find at
>least a local "best" design in your parameter space. For instance,
>this probem might be amenable to a genetic algorithm approach.

Actually, the ideal "goal evaluator" is me, looking at the results of 
several runs and comparing them, then telling the "box" which way to go 
next. As you say, if you could define a goal function with sufficient 
clarity, then any manner of optimizers could grind away on the problem 
overnight.  Unfortunately, most real design problems have requirements that 
are a bit fuzzy:  Don't make it "too big" or "too flimsy".  terms like 
"flimsy" are hard to encapsulate succinctly in a mathematical formulation 
(although, gosh, we certainly try, by requiring certain mechanical 
resonance properties and failure strengths). Much like other things, you 
know them when you see them.

>I know essentially nothing about antenna design so take the following
>suggestion with the requisite large crystal of salt.  Can you
>subdivide the available (flat?) radiating area into a grid of
>identical squares which are classified as antenna/non-antenna?
>At that point your parameters may reduce to:  1) number of squares,
>2) their distribution.  The first is a single integer and the second
>is a bit vector (ie, MxN bits, 1 for cells that are
>antenna, 0 for cells that are not.) This is a simple enough
>parameter space that a genetic algorithm should be relatively
>simple to implement.  Hopefully you can make this work with so
>many itty bitty squares that the little squares are much smaller
>than the shortest wavelength so that the jaggedy edges won't
>change the results significantly.

Aha... your idea has been anticipated!  Several people have done just this 
(using a Beowulf, even, for the optimizing).  Randy Haupt did a fair amount 
of it with wire antennas (and others, I'm sure).  There was also someone at 
UCLA who designed wireless antennas using just what you describe (adding 
and removing small patches of conductive surface).  They then fabricated 
the antennas and tested them.

>You can employ your design expertise by starting the genetic
>algorithm with a few designs that you have reason to think might
>work reasonably well.  Also a bunch of random ones.  Then let
>the software mutate and recombine to see if it can do any
>David Mathog
>mathog at caltech.edu
>Manager, Sequence Analysis Facility, Biology Division, Caltech

James Lux, P.E.
Spacecraft Radio Frequency Subsystems Group
Flight Communications Systems Section
Jet Propulsion Laboratory, Mail Stop 161-213
4800 Oak Grove Drive
Pasadena CA 91109
tel: (818)354-2075
fax: (818)393-6875

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