Minimizing distortion in truss structures - A Hopfield network solutionDistortions in truss structures can result from random errors in element lengths that are typical of a manufacturing process. These distortions may be minimized by an optimal selection of elements from those available for placement between the prescribed nodes - a combinatorial optimization problem requiring significant investment of computational resource for all but the smallest problems. The present paper describes a formulation in which near-optimal element assignments are obtained as minimum-energy stable states, of an analogous Hopfield neural network. This requires mapping of the optimization problem into an energy function of the appropriate Liapunov form. The computational architecture is ideally suited to a parallel processor implementation and offers significant savings in computational effort. A numerical implementation of the approach is discussed with reference to planar truss problems.
Document ID
19920051899
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Fu, B. (NASA Lewis Research Center Cleveland, OH, United States)
Hajela, P. (Rensselaer Polytechnic Institute, Troy, NY, United States)
Date Acquired
August 15, 2013
Publication Date
January 1, 1992
Subject Category
Structural Mechanics
Report/Patent Number
AIAA PAPER 92-2302
Meeting Information
Meeting: AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference