D
David C. Arney
Researcher at United States Military Academy
Publications - 29
Citations - 265
David C. Arney is an academic researcher from United States Military Academy. The author has contributed to research in topics: Partial differential equation & Adaptive mesh refinement. The author has an hindex of 9, co-authored 29 publications receiving 263 citations.
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An adaptive mesh-moving and local refinement method for time-dependent partial differential equations
TL;DR: In this paper, the authors discuss mesh-moving, static mesh-regeneration, and local mesh-refinement algorithms that can be used with a finite difference or finite element scheme to solve initial-boundary value problems for vector systems of time-dependent partial differential equations in two space dimensions and time.
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An adaptive local mesh refinement method for time-dependent partial differential equations
TL;DR: An adaptive local mesh refinement procedure for solving time-dependent initial boundary value problems for vector systems of partial differential equations on rectangular spatial domains, simplifying the prescription of interface conditions at boundaries between fine and coarse meshes.
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A two-dimensional mesh moving technique for time-dependent partial differential equations
TL;DR: An adaptive mesh moving technique that can be used with a finite difference or finite element scheme to solve initial-boundary value problems for systems of partial differential equations in two space dimensions and time is discussed.
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Exhibiting chaos and fractals with a microcomputer
David C. Arney,B.T. Robinson +1 more
TL;DR: In this article, the microcomputer and its graphics capabilities are used to investigate chaos in Newton's method for a complex-valued quartic polynomial, and convergence maps that show fractal geometry are presented.
Cooperation in Social Networks: Communication, Trust, and Selflessness
David C. Arney,Elisha Peterson +1 more
TL;DR: A new framework in which measures of cooperation can be precisely defined is introduced, demonstrated how the framework can be applied to social networks, and the dynamic networks arising in the case of pursuit and evasion games are examined.