ParticLS: Object-oriented software for discrete element methods and peridynamics

Davis, A. D.; West, Brendan A.; Frisch, Nathanael J.; O’Connor, Devin; Parno, Matthew

doi:10.1007/s40571-021-00392-3

Cited by 10 publications

(8 citation statements)

References 42 publications

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“…Future work may incorporate an optimization routine to learn the appropriate model parameters from the mismatch between model output and satellite observations. Alternatively, the use of non‐local distinct lattice spring (André et al., 2019), or peridynamic models (Davis et al., 2021; Silling & Askari, 2005) could avoid the need for time intensive calibration studies, and facilitate using real‐world values for the model parameters.…”

Section: Discussionmentioning

confidence: 99%

“…In the interim, source code is hosted on a Gitlab repository, controlled by the Engineering Research and Development Center (ERDC), that US‐based researchers can access with approval from ERDC. Description and overview of the ParticLS library are in this in‐text data citation reference: (Davis et al., 2021), which is also available on arxiv at https://arxiv.org/abs/2204.10855. The simulation parameters necessary to reproduce these ParticLS simulations are in Table 1.…”

Section: Data Availability Statementmentioning

confidence: 99%

“…The system of differential Equations (2 and 3) can then be integrated numerically to evolve the particle positions and orientations. We direct the reader to (Davis et al, 2021) for additional information regarding the specifics of the numerical methods used in ParticLS.…”

Section: Model Overviewmentioning

confidence: 99%

“…Although they were able to simulate jamming behavior, they note that the simplified model misses certain aspects of observed sea ice behavior, in part due to their spherical particle shapes and particle contact laws. We use a new DEM software library called ParticLS (Davis et al., 2021) that can represent sea ice floes with convex polygons to better capture the irregular shapes often observed in sea ice. ParticLS implements the cohesive beam model (André et al., 2012), which was developed to simulate continuous materials as collections of bonded DEM particles.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Bonded Discrete Element Simulations of Sea Ice With Non‐Local Failure: Applications to Nares Strait

West

O’Connor

Parno

et al. 2022

J Adv Model Earth Syst

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Numerical models of sea ice play an important role in understanding the changing Arctic and allow researchers to predict the dynamic response of sea ice to different environmental conditions. High resolution forecasts from predictive models are also becoming increasingly important due to increased human activity in the Arctic. The recent decline in Arctic sea ice has lead to more traffic in the Arctic Ocean for fishing, resource extraction, tourism, cargo shipping, and military purposes. Sea ice models that can explicitly capture small discontinuities and fractures in the ice are particularly valuable for navigation. For example, IICWG (2019) lists high resolution information about compression and pressure ridges as one of the most important things missing in current operational ice products.Many sea ice models, such as those used in global climate models, employ continuum approaches where the sea ice is discretized with an Eulerian mesh and the ice is modeled with constitutive models such as viscous-plastic (VP) or elastic-viscous-plastic (EVP) rheologies (Hibler, 1979;Hunke & Dukowicz, 1997). Recent studies, such as (Bouchat & Tremblay, 2017) and (Hutter & Losch, 2020), have shown that VP/EVP rheologies can capture important statistics about largescale sea ice deformation. On smaller scales however, it has been shown that

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Section: Discussionmentioning

confidence: 99%

Section: Data Availability Statementmentioning

confidence: 99%

Section: Model Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Bonded Discrete Element Simulations of Sea Ice With Non‐Local Failure: Applications to Nares Strait

West

O’Connor

Parno

et al. 2022

J Adv Model Earth Syst

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“…the forces between two grains coming into contact, are computed by DEM-like contact laws between particles of distinct discretised bodies. Moreover, in [29] the coupling of PD and DEM is considered from a computational point of view with respect to the software library ParticLS, in which meshfree methods and the DEM are considered. A shortcoming of the existing framework in [28], which is tackled in this work, is that all grains are treated as peridynamic bodies.…”

Section: Introductionmentioning

confidence: 99%

A generalised multi-scale Peridynamics–DEM framework and its application to rigid–soft particle mixtures

2022

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The discrete element method (DEM) is the most dominant method for the numerical prediction of dynamic behaviour at grain or particle scale. Nevertheless, due to its discontinuous nature, the DEM is inherently unable to describe microscopic features of individual bodies which can be considered as continuous bodies. To incorporate microscopic features, efficient numerical coupling of the DEM with a continuous method is generally necessary. Thus, a generalised multi-scale PD–DEM framework is developed in this work. In the developed framework, meshfree discretised Peridynamics (PD) is used to describe intra-particle forces within bodies to capture microscopic features. The inter-particle forces of rigid bodies are defined by the DEM whereas a hybrid approach is applied at the PD–DEM interface. In addition, a staggered multi-scale time integration scheme is formulated to allow for an efficient numerical treatment of both methods. Validation examples are presented and the applicability of the developed framework to capture the characteristics mixtures with rigid and deformable bodies is shown.

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Improving discrete element simulations of sea ice break up: Applications to Nares Strait

West¹,

O’Connor²,

Parno³

et al. 2021

Preprint

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ParticLS: Object-oriented software for discrete element methods and peridynamics

Cited by 10 publications

References 42 publications

Bonded Discrete Element Simulations of Sea Ice With Non‐Local Failure: Applications to Nares Strait

Bonded Discrete Element Simulations of Sea Ice With Non‐Local Failure: Applications to Nares Strait

A generalised multi-scale Peridynamics–DEM framework and its application to rigid–soft particle mixtures

Improving discrete element simulations of sea ice break up: Applications to Nares Strait

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