Worst-Case Rigidity Analysis and Optimization for Assemblies with Mechanical Joints

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Date
2022
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Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
We study structural rigidity for assemblies with mechanical joints. Existing methods identify whether an assembly is structurally rigid by assuming parts are perfectly rigid. Yet, an assembly identified as rigid may not be that ''rigid'' in practice, and existing methods cannot quantify how rigid an assembly is. We address this limitation by developing a new measure, worst-case rigidity, to quantify the rigidity of an assembly as the largest possible deformation that the assembly undergoes for arbitrary external loads of fixed magnitude. Computing worst-case rigidity is non-trivial due to non-rigid parts and different joint types. We thus formulate a new computational approach by encoding parts and their connections into a stiffness matrix, in which parts are modeled as deformable objects and joints as soft constraints. Based on this, we formulate worst-case rigidity analysis as an optimization that seeks the worst-case deformation of an assembly for arbitrary external loads, and solve the optimization problem via an eigenanalysis. Furthermore, we present methods to optimize the geometry and topology of various assemblies to enhance their rigidity, as guided by our rigidity measure. In the end, we validate our method on a variety of assembly structures with physical experiments and demonstrate its effectiveness by designing and fabricating several structurally rigid assemblies.
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CCS Concepts: Computing methodologies --> Modeling and simulation

        
@article{
10.1111:cgf.14490
, journal = {Computer Graphics Forum}, title = {{
Worst-Case Rigidity Analysis and Optimization for Assemblies with Mechanical Joints
}}, author = {
Liu, Zhenyuan
 and
Hu, Jingyu
 and
Xu, Hao
 and
Song, Peng
 and
Zhang, Ran
 and
Bickel, Bernd
 and
Fu, Chi-Wing
}, year = {
2022
}, publisher = {
The Eurographics Association and John Wiley & Sons Ltd.
}, ISSN = {
1467-8659
}, DOI = {
10.1111/cgf.14490
} }
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