Binary Tree CAD Modeling for Consistent Feature Update Times
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Solution Overview
Problem
Declarative modeling in CAD systems faces inefficiencies in updating solid shapes due to the use of ordered lists for combining basic volumes, leading to significant computing time and uneven update times for features based on their creation order, contradicting the desired independent behavior of feature creation order in declarative modeling.
Innovation Solution
The implementation of optimal binary trees to manage the combination of basic volumes, where non-leaf nodes perform commutative operations, and leaf nodes represent basic volumes, simplifying the update process by maintaining a balanced binary tree structure through algorithms that add or remove nodes efficiently, ensuring optimal and ideal tree balance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If ordered lists are used to combine basic volumes in input buckets, then the implementation is simple, but the update time becomes significant and proportional to the age of the modified volume
Solution Approach 1:
The patent segments the ordered list into a binary tree structure where basic volumes are organized hierarchically. Each node in the binary tree represents a combination of volumes, allowing the system to process updates by traversing only the necessary paths from leaf nodes to root, rather than processing the entire list sequentially.
Solution Approach 2:
The patent transitions from a one-dimensional ordered list to a two-dimensional binary tree structure. This dimensional change allows volumes to be organized in a hierarchical manner with left and right subtrees, enabling more efficient update operations by exploiting the tree's structural properties and reducing the number of operations needed to maintain the combination.
2Adaptability or versatility
If features are updated based on their creation order in an ordered list, then early features take longer to update, but this contradicts the declarative behavior where feature update time should be independent of creation order
Solution Approach 1:
The binary tree structure segments the feature update process into independent paths. When a feature is modified, only the specific path from the affected leaf node to the root needs to be updated, rather than reprocessing the entire feature list. This segmentation makes update time independent of feature creation order.
Solution Approach 2:
The patent introduces dynamic balancing mechanisms that automatically adjust the tree structure during updates. The balancing algorithms (such as rotations and reorganization) dynamically maintain optimal tree properties regardless of the sequence of feature modifications, ensuring consistent update performance.
3Productivity
If the predefined history tree update is optimized, then the overall computing time is reduced, but the basic volumes update time becomes significant and deserves optimization
Solution Approach 1:
The patent segments the basic volumes update process by organizing volumes in a binary tree where only the necessary nodes need to be traversed and updated. This segmentation reduces the update complexity from linear to logarithmic with respect to the number of volumes.
Solution Approach 2:
The patent performs preliminary organization of basic volumes into a balanced binary tree structure before updates occur. This preliminary action ensures that when updates are needed, the tree is already in an optimal state for efficient traversal and modification, reducing the actual update time.
Data Source
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AI summary
A computer-implemented method for designing an industrial product modeled with a binary tree having leaf nodes representing basic volumes, non-leaf nodes representing binary commutative operation combining volumes, the method comprising the steps of: - performing a design operation triggering the adding or the removing of a leaf node; and - idealizing the binary tree, i.e. modifying the binary tree while maintaining the optimality of the tree by minimizing the number of weak leaf nodes, a weak leaf node being a leaf node such that, when removed, the resulting binary tree is not optimal anymore.