A clustering tool for interrogating finite element models based on eigenvectors of graph adjacency
This provides a practical tool for engineers to debug finite element models, but it is incremental as it applies existing clustering methods to a specific domain.
The paper tackles the problem of debugging errors in finite element simulation models by introducing an unsupervised learning algorithm that clusters degrees of freedom based on the adjacency of the stiffness matrix, and it has been deployed as a commercial tool called 'Model Stability Analysis' in Oasys GSA, with successful real-world use by end-users.
This note introduces an unsupervised learning algorithm to debug errors in finite element (FE) simulation models and details how it was productionised. The algorithm clusters degrees of freedom in the FE model using numerical properties of the adjacency of its stiffness matrix. The algorithm has been deployed as a tool called `Model Stability Analysis' tool within the commercial structural FE suite Oasys GSA (www.oasys-software.com/gsa). It has been used successfully by end-users for debugging real world FE models and we present examples of the tool in action.