33 citations · 60 across the 7 of their papers we have counts for
5 papers · 1 filter
Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling
Kookjin Lee, Nathaniel Trask, Panos Stinis
Discovery of dynamical systems from data forms the foundation for data-driven modeling and recently, structure-preserving geometric perspectives have been shown to provide improved…
Coupling of IGA and Peridynamics for Air-Blast Fluid-Structure Interaction Using an Immersed Approach
Masoud Behzadinasab, Georgios Moutsanidis, Nathaniel Trask +2
We present a novel formulation based on an immersed coupling of Isogeometric Analysis (IGA) and Peridynamics (PD) for the simulation of fluid-structure interaction (FSI) phenomena…
Machine learning structure preserving brackets for forecasting irreversible processes
Kookjin Lee, Nathaniel A. Trask, Panos Stinis
Forecasting of time-series data requires imposition of inductive biases to obtain predictive extrapolation, and recent works have imposed Hamiltonian/Lagrangian form to preserve st…
Parallel implementation of a compatible high-order meshless method for the Stokes' equations
Quang-Thinh Ha, Paul A. Kuberry, Nathaniel A. Trask +1
A parallel implementation of a compatible discretization scheme for steady-state Stokes problems is presented in this work. The scheme uses generalized moving least squares to gene…
An asymptotically compatible treatment of traction loading in linearly elastic peridynamic fracture
Yue Yu, Huaiqian You, Nathaniel Trask
Meshfree discretizations of state-based peridynamic models are attractive due to their ability to naturally describe fracture of general materials. However, two factors conspire to…