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Paper w78-1993-36:
Semantic topology: the management of shape definition

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Willems P H, Tolman F B

Semantic topology: the management of shape definition

Abstract: Over the last decade Computer Aided Design (CAD) systems have found their way in the building industry and have become a mayor tool for defining the shape of a prod- uct. However, CAD systems still do not really seem to aid the design process during all its stages. They fail to assist the early design phases, where shape definitions are not fixed yet, but exist stilr as roughly sketched contours. This paper investigates shortcomings of the state of the art CAD-systems, with regard to their application in all design stages, especially within the building industry. A new approach for shape definition is intrduced. This approach, called ‘Semantic Topology’, should be able to bridge the gap between advanced product model struc- tures and conventional geometric modelling. ’ This implies bringing in features for: - adjusting the tolerancing level, eg, a liberal tolerancing level in the early design stage ending in the accepted manufacturing tolerances after the completion of the final design. defining shape constraints, shape constraints should clearly define the modelling freedom to define a cer- tain shape. This feature is particular important for realising concurrent engi- neering. modular structures, in contrast to monolithic structures, are essential to ma- nipulate product models, standard part libraries and very large shape models. a consistent shape decomposition helps to integrate shape definition with product definition. It is insportant to stress that Semantic Topology does not introduce a new kind of geometric modelling, yet it acts as an intermediary layer between a product model kernel and a geometric model. I making geometrical structures fit for modular handling, - shape decomposition support,

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Full text: content.pdf (1,756,871 bytes) (available to registered users only)

Series: w78:1993 (browse)
Cluster: papers of the same cluster (result of machine made clusters)
Class: class.synthesis (0.035822) class.represent (0.029391) class.legal (0.002341)
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Permission to reproduce these papers has been graciously provided by the National University of Singapore. The assistance of the editors, particularly Prof. Martin Betts, is gratefully appreciated.

 

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