Litcius/Paper detail

An adaptive model order reduction technique for parameter-dependent modular structures

Stephan Ritzert, Domen Macek, Jaan‐Willem Simon, Stefanie Reese

2023Computational Mechanics11 citationsDOIOpen Access PDF

Abstract

Abstract This work is concerned with an adaptive reduced order model of modular structures assembled from parameter-dependent substructures. The substructures are reduced by proper orthogonal decomposition (POD) and connected by means of a tied contact formulation. We present a method to adapt the matrices of the substructures to parameter changes. We employ interpolation on Grassmann manifolds for the parametric adaption of the projection matrices. For the adaptation of the stiffness matrices, we use the direct empirical interpolation method (DEIM). Manifold interpolation of the reduced stiffness matrices, cannot be applied here since it would require semi-positive definiteness, which is here not fulfilled because of necessary rigid body motion modes. The novelty of this work is the application of these interpolation methods to the special problem class of POD-based tied contact model order reduction. Furthermore, we show a methodology to compute significant snapshots on the substructure level to compute a POD basis that can be used in different global structures.

Topics & Concepts

Interpolation (computer graphics)MathematicsModel order reductionReduction (mathematics)SubstructureProjection (relational algebra)Applied mathematicsPositive definitenessModular designParametric statisticsManifold (fluid mechanics)Mathematical optimizationAlgorithmComputer scienceMotion (physics)GeometryPositive-definite matrixArtificial intelligenceEigenvalues and eigenvectorsStructural engineeringPhysicsQuantum mechanicsOperating systemEngineeringMechanical engineeringStatisticsModel Reduction and Neural NetworksDynamics and Control of Mechanical SystemsVibration and Dynamic Analysis
An adaptive model order reduction technique for parameter-dependent modular structures | Litcius