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Prashant K. Jha's blog

Corrector operator to enhance accuracy and reliability of neural operator surrogates of nonlinear variational boundary-value problems

Submitted by Prashant K. Jha on

I am excited to announce our work (with Dr. Oden) on enhancing the accuracy of neural operators using the so-called corrector operator. This work is a culmination of our efforts in using goal-oriented a-posteriori error estimates in Bayesian inference in Jha and Oden (2022), JCP 470, 111575, and recently using a similar idea in Cao et al. (2023), JCP 486, 112104

 

Kinetic relations and local energy balance for LEFM from a nonlocal peridynamic model

Submitted by Prashant K. Jha on

Journal: International Journal of Fracture

Abstract: A simple nonlocal field theory of peridynamic type is applied to model brittle fracture. The kinetic relation for the crack tip velocity given by Linear Elastic Fracture Mechanics (LEFM) is recovered directly from the nonlocal dynamics, this is seen both theoretically and in simulations. An explicit formula for the change of internal energy inside a neighborhood enclosing the crack tip is found for the nonlocal model and applied to LEFM.

 

Numerical convergence of finite difference approximations for state based peridynamic fracture models

Submitted by Prashant K. Jha on

Prashant K. Jha and Robert Lipton

Computer Methods in Applied Mechanics and Engineering, 2019. 

https://doi.org/10.1016/j.cma.2019.03.024

 

Highlights

1. Well-posedness of a general nonlinear state based peridynamic models.

2. A priori numerical convergence rate for finite difference approximations of state based peridynamic models.

3. Numerical verification of convergence rate for samples with growing cracks.