Evaluating the Application of CBR in Mesh
Design for Simulation Problems

Neil Hurley
Hitachi Dublin Laboratory. Trinity College Dublin 2, IRELAND
(E-mail: nhurley@hdl.ie)

Abstract. One of the great difficulties facing a designer of a knowledge-based
interface to a numerical simulation engine is acquiring sufficient domain
knowledge to cover a significant range of problems to a depth that will make the
system useful for real problem-solving. It is difficult to enumerate a priori all the
different scenarios which may be encountered and to devise rules to cater for each.
Indeed, it is true to say that often the tuneable parameters of a numerical algorithm
(such as the error tolerance in a matrix inversion technique or the mesh density in
a finite element analysis) are determined on a trial and error basis when the
problem is first encountered. Setting up a knowledge-base therefore requires a lot
of time-consuming experimentation over a range of different problems. There is
no easy way to avoid this knowledge acquisition task if a robust system to tackle
real-world problems is to be created. Furthermore, we must accept that the system
at some stage is likely to encounter problems outside its coverage. It is therefore
worthwhile examining alternative reasoning techniques which can be utilised
when domain knowledge is lacking, as well as ways that new knowledge can be
incorporated into the knowledge-base as problem-solving takes place. Towards
this end, we have examined the application of case-based reasoning (CBR) to
finite element simulation and in particular to the sub-task of finite element mesh
design. In [5] a CBR approach to mesh design was outlined. In the current paper
we evaluate that system, assess its performance at problem solving, discuss the
lessons learned from its development and what implications these have for CBR in
general.
References
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