Abstract
Of the two main geometric representations used in computer aided design, namely parametric and implicit representations, parametric representations have been the most dominant since their initial use in computer systems of the 1960s. This was mainly due to them being simple to evaluate, making applications like visualization possible, as well as having intuitive design characteristics through representations such as Bezier and B-spline curves and surfaces. However, despite their many advantages, parametric representations often become unwieldy and lack watertightness when modelling complex geometries and non-trivial topologies – issues which implicit representations tend to solve with ease.
In this talk we will discuss both types of representation, their relative pros and cons, as well as methods for change of representation. We will also discuss how modern computational hardware, coupled with advances in fields such as additive manufacturing and machine learning are driving an ascendancy in the use of implicit representations for novel applications such as generative design.
In this talk we will discuss both types of representation, their relative pros and cons, as well as methods for change of representation. We will also discuss how modern computational hardware, coupled with advances in fields such as additive manufacturing and machine learning are driving an ascendancy in the use of implicit representations for novel applications such as generative design.