CAD Model Update Method Using Sub-Operand Caching
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Solution Overview
Problem
Current CAD systems face inefficiencies in updating modeled objects due to slow update times, particularly when dealing with complex parts or frequent modifications, as existing methods either recompute unnecessary operations or lack semantic preservation of design intent.
Innovation Solution
A method that classifies sub-operands into two sets, retrieving old sub-results for partially identical sub-operands to minimize recomputation, thereby accelerating the update process while maintaining design intent, applicable to both Boolean and non-Boolean operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system recomputes all operations when updating a modeled object, then the design intent is preserved, but the update time increases significantly
Solution Approach 1:
The patent segments the history of operations into two categories: those that need to be recomputed and those that can be reused. By dividing the operation history based on whether sub-operands have changed, the system selectively applies recomputation only to necessary segments, preserving design intent where needed while avoiding unnecessary recomputation elsewhere.
Solution Approach 2:
The patent applies local quality by treating different operations differently based on their specific characteristics. Operations whose sub-operands remain identical are marked for reuse, while those with modified sub-operands are marked for recomputation. This localized approach ensures design intent is preserved only where necessary while optimizing update performance elsewhere.
2Productivity
If the system retrieves old sub-results for identical sub-operands, then the update speed increases, but the complexity of managing operation history increases
Solution Approach 1:
The patent performs preliminary action by pre-computing and storing the results of operations during the initial model creation. These pre-computed results are then readily available for reuse during updates, eliminating the need to recompute identical operations and significantly improving update speed while the system manages the stored history efficiently.
Solution Approach 2:
The patent uses copying by retrieving and reusing old sub-results from the operation history when sub-operands remain identical. Instead of recomputing operations, the system copies the previously computed results, which accelerates the update process while the history management system handles the storage and retrieval of these copied results.
3Loss of time
If the system stores all intermediate results of history operations, then the update process is accelerated, but the memory consumption increases
Solution Approach 1:
The patent applies local quality by storing intermediate results selectively rather than universally. Only the results of operations that are likely to be reused during updates are stored in memory, while other results are not retained. This selective storage approach accelerates updates for critical operations while minimizing overall memory consumption.
Solution Approach 2:
The patent implements discarding and recovering by managing the lifecycle of stored intermediate results. Results are stored when computed, reused when applicable during updates, and then discarded when no longer needed. This cyclic pattern of storing, reusing, and discarding optimizes memory utilization while maintaining update performance.
Data Source
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AI summary
A computer-implemented method for updating a modeled object comprises providing an old operand of an operation, a result of applying the operation to the old operand, wherein applying the operation to the old operand includes computing old sub-results, each old sub-result being determined by a respective old sub-operand of the old operand, and a new operand including a first set of sub-operands of the new operand at least partially identical to old sub-operands of the old operand, and a second set of new sub-operands. The method further comprises applying the operation on the new operand, including computing new sub-results determined by a respective sub-operand of the second set; and retrieving the old sub-results determined by the old sub-operands of the old operand to which sub-operands of the first set are at least partially identical. Such a method improves the update of the modeled object.