Výsledky vyhledávání - "West, Brendan"

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

Autor: Davis, Andrew D., West, Brendan A., Frisch, Nathanael J., O'Connor, Devin T., Parno, Matthew D.

Publikováno v: Computational Particle Mechanics (2021)

ParticLS (\emph{Partic}le \emph{L}evel \emph{S}ets) is a software library that implements the discrete element method (DEM) and meshfree methods. ParticLS tracks the interaction between individual particles whose geometries are defined by level sets

Externí odkaz: http://arxiv.org/abs/2204.10855

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Bonded discrete element simulations of sea ice with non-local failure: Applications to Nares Strait

Autor: West, Brendan, O'Connor, Devin, Parno, Matthew, Krackow, Max, Polashenski, Chris

The discrete element method (DEM) can provide detailed descriptions of sea ice dynamics that explicitly model floes and discontinuities in the ice, which can be challenging to represent accurately with current models. However, floe-scale stresses tha

Externí odkaz: http://arxiv.org/abs/2105.05143

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A Bayesian Approach for Inferring Sea Ice Loads

Autor: Parno, Matthew, Hodgdon, Taylor, West, Brendan, O'Connor, Devin, Song, Arnold

The Earth's climate is rapidly changing and some of the most drastic changes can be seen in the Arctic, where sea ice extent has diminished considerably in recent years. As the Arctic climate continues to change, gathering in situ sea ice measurement

Externí odkaz: http://arxiv.org/abs/2102.08444

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Akademický článek

Peridynamic modeling of the micromechanical response of snow under high strain rates

Autor: West, Brendan, Hodgdon, Taylor, O'Connor, Devin, Parno, Julie, Courville, Zoe

Publikováno v: In Cold Regions Science and Technology February 2024 218

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Improved Workflow for Unsupervised Multiphase Image Segmentation

Autor: West, Brendan A., Hodgdon, Taylor S., Parno, Matthew D., Song, Arnold J.

Quantitative image analysis often depends on accurate classification of pixels through a segmentation process. However, imaging artifacts such as the partial volume effect and sensor noise complicate the classification process. These effects increase

Externí odkaz: http://arxiv.org/abs/1710.09671

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