Dual numbers and automatic differentiation to efficiently compute velocities and accelerations

DOI10.1007/s10440-020-00351-9zbMath1470.65031OpenAlexW3044746972MaRDI QIDQ829595

M. A. Escalante Soberanis, R. Peón, F. Peñuñuri, David González-Sánchez

Publication date: 6 May 2021

Published in: Acta Applicandae Mathematicae (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10440-020-00351-9

zbMATH Keywords

automatic differentiationdual numbersvelocities and accelerations

Mathematics Subject Classification ID

Applications to the sciences (65Z05) Numerical differentiation (65D25)

Uses Software

• Matlab
• JAP
• TAPENADE
• Sacado
• DNAD
• DiffSharp
• AlgoPy
• dco/c++
• ADiJaC

Cites Work

• Unnamed Item
• Matlab
• DNAD, a simple tool for automatic differentiation of Fortran codes using dual numbers
• Application of fast automatic differentiation for solving the inverse coefficient problem for the heat equation
• A backward automatic differentiation framework for reservoir simulation
• Do you trust derivatives or differences?
• A highly accurate 1st- and 2nd-order differentiation scheme for hyperelastic material models based on hyper-dual numbers
• Linear algebra and numerical algorithms using dual numbers
• Automatic differentiation: Applications, theory, and implementations. Selected papers based on the presentation at the 4th international conference on automatic differentiation (AD), Chicago, IL, USA, July 20--23, 2004
• Algorithmic Differentiation of Numerical Methods
• Automatic Differentiation Through the Use of Hyper-Dual Numbers for Second Derivatives
• Java Automatic Differentiation Tool Using Virtual Operator Overloading
• Efficient Expression Templates for Operator Overloading-Based Automatic Differentiation
• ADiJaC -- Automatic Differentiation of Java Classfiles
• The Tapenade automatic differentiation tool
• A vector forward mode of automatic differentiation for generalized derivative evaluation
• Evaluating Derivatives
• Introduction to Automatic Differentiation and MATLAB Object-Oriented Programming
• Fast Reverse-Mode Automatic Differentiation using Expression Templates in C++
• The complex-step derivative approximation

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