A family of embedded Runge-Kutta formulae
J. R. Dormand,P.J. Prince +1 more
TLDR
In this article, a family of embedded Runge-Kutta formulae RK5 (4) are derived from these and a small principal truncation term in the fifth order and extended regions of absolute stability.About:
This article is published in Journal of Computational and Applied Mathematics.The article was published on 1980-03-01 and is currently open access. It has received 3106 citations till now.read more
Citations
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Efficient simulation of Hybrid Renewable Energy Systems
Gustavo Migoni,Gustavo Migoni,Pablo Gabriel Rullo,Federico Bergero,Ernesto Kofman,Ernesto Kofman +5 more
TL;DR: A new family of numerical algorithms called Quantized State Systems (QSS) is analyzed that are more than one order of magnitude faster than the most efficient classic solvers, allowing to simulate Hybrid Renewable Energy Systems in reasonable times.
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Variable-stepsize Chebyshev-type methods for the integration of second-order I.V.P.'s
Higinio Ramos,Jesús Vigo-Aguiar +1 more
TL;DR: The question of how to extend Chebyshev approximations for numerically solving second-order differential equations to variable stepsize procedures is the primary topic of this paper.
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Orbit design for future SpaceChip swarm missions in a planetary atmosphere
Camilla Colombo,Colin R. McInnes +1 more
TL;DR: In this paper, the effect of solar radiation pressure and atmospheric drag on the orbital dynamics of satellites-on-a-chip (SpaceChips) is exploited to design equatorial long-lived orbits about the oblate Earth.
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Dynamic investigation of traction motor bearing in a locomotive under excitation from track random geometry irregularity
TL;DR: In this article, the development of railway locomotive towards high-speed and high-power has a higher requirement on traction motor bearing under the intensified wheel-rail interactions since the dynamic performance of the locomotive is increased.
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EVICAN-a balanced dataset for algorithm development in cell and nucleus segmentation
TL;DR: A new dataset, EVICAN—Expert visual cell annotation, comprising partially annotated grayscale images of 30 different cell lines from multiple microscopes, contrast mechanisms and magnifications that is readily usable as training data for computer vision applications is presented.
References
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Comparing Numerical Methods for Ordinary Differential Equations
TL;DR: According to criteria involving the number of function evaluations, overhead cost, and reliability, the best general-purpose method, if function evaluations are not very costly, is one due to Bulirsch and Stoer, however, when function evaluated methods are relatively expensive, variable-order methods based on Adams formulas are best.
Journal ArticleDOI
Coefficients for the study of Runge-Kutta integration processes
TL;DR: In this paper, a set of η first order simultaneous differential equations in the dependent variables y 1, y 2, y 3, y 4, y 5, y 6 and the independent variable x is considered.
Classical Fifth-, Sixth-, Seventh-, and Eighth-Order Runge-Kutta Formulas with Stepsize Control
TL;DR: Runge-Kutta formulas of high order with stepsize control through leading truncation error term through leading parallelogram error term.
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