Efficient a Posteriori Error Control of a Consistent Atomistic/Continuum Coupling Method for Two Dimensional Crystalline Defects

TL;DR

This paper introduces a theoretically justified approximation for residual-based a posteriori error estimation in atomistic/continuum coupling methods, significantly improving computational efficiency while maintaining optimal convergence in simulating crystalline defects.

Contribution

It proposes a new approximation technique for residual error estimation that reduces computational cost without sacrificing accuracy in adaptive atomistic/continuum simulations.

Findings

Reduces computational cost by one order of magnitude.

Maintains optimal convergence rate of error.

Effective for various crystalline defect types.

Abstract

Adaptive atomistic/continuum (a/c) coupling method is an important method for the simulation of material and atomistic systems with defects to achieve the balance of accuracy and efficiency. Residual based a posteriori error estimator is often employed in the adaptive algorithm to provide an estimate of the error of the strain committed by applying the continuum approximation for the atomistic system and the finite element discretization in the continuum region. In this work, we propose a theory based approximation for the residual based a posteriori error estimator which greatly improves the efficiency of the adaptivity. In particular, the numerically expensive modeling residual is only computed exactly in a small region around the coupling interface but replaced by a theoretically justified approximation by the coarsening residual outside that region. We present a range of adaptive computations based on our modified a posteriori error estimator and its variants for different types of crystalline defects some of which are not considered in previous related literature of the adaptive a/c methods. The numerical results show that, compared with the original residual based error estimator, the adaptive algorithm using the modified error estimator with properly chosen parameters leads to the same optimal convergence rate of the error but reduces the computational cost by one order with respect to the number of degrees of freedom.