2020
DOI: 10.31224/osf.io/7z8qr
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

An algorithm for imposing local boundary conditions in peridynamic models on arbitrary domains

Abstract: Imposing local boundary conditions in nonlocal/peridynamic models is often desired/needed. Fictitious nodes methods (FNMs) are commonly used techniques for this purpose but they are limited, in general, to domains with simple geometry. FNMs also mitigate the well-known peridynamic surface/skin effect at boundaries/surfaces. Here, we introduce a general algorithm that automatically locates mirror nodes for fictitious nodes in the mirror-based FNM, without requiring an explicit mathematical description of the bo… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
23
0

Year Published

2021
2021
2023
2023

Publication Types

Select...
4
1
1
1

Relationship

1
6

Authors

Journals

citations
Cited by 21 publications
(23 citation statements)
references
References 53 publications
0
23
0
Order By: Relevance
“…The approach is investigated numerically and it shows better agreement with classical solutions, while also being able to handle non-smooth boundaries, and even crack lines. Similar as the mirror FNM idea in [63] and the vanishing horizon idea in [14], in [42] the authors propose two methods for dealing with boundary conditions in one-dimensional bond-based peridynamics model. The Extended Domain Method (EDM) adds a layer to the domain Ω on which an odd reflection of the classical solution is imposed.…”
Section: Constant Extension Linear Extension Smooth Extension Local S...mentioning
confidence: 99%
See 2 more Smart Citations
“…The approach is investigated numerically and it shows better agreement with classical solutions, while also being able to handle non-smooth boundaries, and even crack lines. Similar as the mirror FNM idea in [63] and the vanishing horizon idea in [14], in [42] the authors propose two methods for dealing with boundary conditions in one-dimensional bond-based peridynamics model. The Extended Domain Method (EDM) adds a layer to the domain Ω on which an odd reflection of the classical solution is imposed.…”
Section: Constant Extension Linear Extension Smooth Extension Local S...mentioning
confidence: 99%
“…While for a local problem data on the domain's surface can be easily provided by experimentalists through surface measurements, in the nonlocal setting one must provide volumetric data for the boundary collar, which may be difficult (or even impossible) to obtain. Thus, practioners must introduce ad-hoc methods for prescribing both Dirichlet and Neumann-type boundary conditions for nonlocal problem [8,14,16,31,48,58,62,63], and in this work we mainly focus on the Dirichlet-type volume constraints. Most commonly, the convergence of nonlocal solutions to classical counterparts has been studied for homogeneous Dirichlet-type boundary conditions in second order ( [36,37]), or higher order ( [43]) problems.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…The thickness is required because of the special way that nonlocal boundary conditions are defined in PD problems. Details on nonlocal boundary conditions are available in [58,59]. The rest of the boundaries (including the symmetry line) are free boundaries and the no-flux conditions is naturally satisfied.…”
Section: Computational Model Setupmentioning
confidence: 99%
“…In addition to that, we show how to implement the fictitious node method in state‐based Peridynamics with a fictitious layer of thickness δ (instead of 2δ as in Reference 23) via the truncated Taylor series up to a general order n . The surface effect is mitigated by the presence of the fictitious nodes and Dirichlet boundary conditions are applied similarly to what is done in References 31,35. On the other hand, we propose an innovative method to impose Neumann boundary conditions in a “peridynamic way”, namely by means of the peridynamic concept of force flux .…”
Section: Introductionmentioning
confidence: 99%