In this section, you will explore a use case demonstrating the Adapt Fillet Radius update strategy.
| This technical practice highlights the strategy that is used primarily to update the raduis value within defined deviation to validate the model. It is aslo use to autonomously solve the update error in the edge fillet, face-face fillet features caused by an incompatible radius value. |
In 3D modelling, one of the most challenging aspects for designers is the update of dress-up features such as Edge fillet and Face-Face fillet. Due to design modifications or increased geometric complexity, these fillet features frequently encounter update errors or computation failures. As a result, designers often spend significant time manually adjusting radius values to suit evolving geometric conditions. This not only reduces design productivity but may also compromise the quality and continuity of the resulting fillet surfaces. The Adapt Fillet Radius strategy plays a critical role in mitigating such issues. It dynamically adjusts fillet parameters to maintain feature robustness and surface quality during updates. |
This technical practice focuses on the Adapt Fillet Radius strategy within resilient modelling. This strategy addresses update errors in Edge Fillet and Face Fillet features that result from incompatible radius values. When applied to a fillet feature in error, the strategy allows the designer to define positive and negative deviation limits through the Radius Deviation parameters. Based on these limits, the system recalculates and rebuilds the affected fillet feature using an adjusted radius value, thereby restoring feature validity and ensuring model continuity. |
All roles that include the Part Design app, Part Design Plus app, Generative Shape Design app and Generative Shape Design Plus app |
Mechanical Designers, Conceptual Designers, Mechanical Surface Designers |
Radius Adaptation Sequence: The strategy evaluates alternative radius values in the following sequence: 1st build: Current radius − 1% of negative deviation 2nd build: Current radius − 10% of negative deviation 3rd build: Current radius − 100% of negative deviation 4th build: Current radius + 1% of positive deviation 5th build: Current radius + 10% of positive deviation 6th build: Current radius + 100% of positive deviation This ordered evaluation ensures minimal deviation from the original design intent while maximizing the likelihood of successful feature regeneration. |
Use Case: Update edge fillet radius in defined deviationScenario: In a 3D design, when you need to update the rib thicknesswhich has edge fillets as child features.You can implement the Adopt Edge Fillet Radius strategy to retain the child feature outputs. This ensures robust updates even when the parent geometry changes. |
Play the video to watch how to update the edge fillet radius within defined deviation.
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To learn more about Adapt Fillet Radius, explore the M3S learning module. |
