Each subsequent feature is built on the previous feature. When editing, the model is "rolled back" to the point where the feature was created so that the user cannot try to apply constraints to geometry that does not yet exist. The drawback is that the user does not see how the edit will interact with the subsequent features. This is typically called "history" or "regeneration based" modeling.
Overview[ edit ] The use of solid modeling techniques allows for the automation of several difficult engineering calculations that are carried out as a part of the design process.
Simulation, planning, and verification of processes such as machining and assembly were one of the main catalysts for the development of solid modeling.
More recently, the range of supported manufacturing applications has been greatly expanded to include sheet metal manufacturinginjection moldingweldingpipe routing etc. Beyond traditional manufacturing, solid modeling techniques serve as the foundation for rapid prototypingdigital data archival and reverse engineering by reconstructing solids from sampled points on physical objects, mechanical analysis using finite elementsmotion planning and NC path verification, kinematic and dynamic analysis of mechanismsand so on.
A central problem in all these applications is the ability to effectively represent and manipulate three-dimensional geometry in a fashion that is consistent with the physical behavior of real artifacts.
Solid modeling research and development has effectively addressed many of these issues, and continues to be a central focus of computer-aided engineering. Mathematical foundations[ edit ] The notion of solid modeling as practised today relies on the specific need for informational completeness in mechanical geometric modeling systems, in the sense that any computer model should support all geometric queries that may be asked of its corresponding physical object.
The requirement implicitly recognizes the possibility of several computer representations of the same physical object as long as any two such representations are consistent.
It is impossible to computationally verify informational completeness of a representation unless the notion of a physical object is defined in terms of computable mathematical properties and independent of any particular representation.
Such reasoning led to the development of the modeling paradigm that has shaped the field of solid modeling as we know it today. These postulated properties can be translated into properties of subsets of three-dimensional Euclidean space.
The two common approaches to define solidity rely on point-set topology and algebraic topology respectively. Both models specify how solids can be built from simple pieces or cells.
Dimensional homogeneity of neighborhoods is guaranteed for the class of closed regular sets, defined as sets equal to the closure of their interior. In addition, solids are required to be closed under the Boolean operations of set union, intersection, and difference to guarantee solidity after material addition and removal.
Applying the standard Boolean operations to closed regular sets may not produce a closed regular set, but this problem can be solved by regularizing the result of applying the standard Boolean operations. A triangulation of a semi-analytic set into a collection of points, line segments, triangular faces, and tetrahedral elements is an example of a stratification that is commonly used.
The combinatorial model of solidity is then summarized by saying that in addition to being semi-analytic bounded subsets, solids are three-dimensional topological polyhedraspecifically three-dimensional orientable manifolds with boundary. The combinatorial manifold model of solidity also guarantees the boundary of a solid separates space into exactly two components as a consequence of the Jordan-Brouwer theorem, thus eliminating sets with non-manifold neighborhoods that are deemed impossible to manufacture.
The point-set and combinatorial models of solids are entirely consistent with each other, can be used interchangeably, relying on continuum or combinatorial properties as needed, and can be extended to n dimensions. Solid representation schemes[ edit ] Based on assumed mathematical properties, any scheme of representing solids is a method for capturing information about the class of semi-analytic subsets of Euclidean space.
This means all representations are different ways of organizing the same geometric and topological data in the form of a data structure. All representation schemes are organized in terms of a finite number of operations on a set of primitives. Therefore, the modeling space of any particular representation is finite, and any single representation scheme may not completely suffice to represent all types of solids.
For example, solids defined via combinations of regularized boolean operations cannot necessarily be represented as the sweep of a primitive moving according to a space trajectory, except in very simple cases.LCS Automation Solution.
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•The Solid Edge core COM type libraries are the APIs that are available to automate the Solid Edge application •These APIs can be used by any programming or scripting language.
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