The Analysis of Rigid Body Motion From Measured Data

1995 ◽  
Vol 117 (4) ◽  
pp. 578-584 ◽  
Author(s):  
G. R. Shiflett ◽  
A. J. Laub
Keyword(s):  
Rigid Body ◽  
Measured Data ◽  
Rigid Body Motion ◽  
Body Motion ◽  
New Method ◽  
Floating Point ◽  
Computationally Efficient ◽  
Floating Point Arithmetic ◽  
Point Arithmetic

In this paper, a new method for analyzing rigid body motion from measured data is presented. The approach is numerically stable, explicitly accounts for the errors inherent in measured data and those introduced by floating point arithmetic, automatically accommodates any number of rigid body particles, and is computationally efficient. The sole restriction on the data is that it represent 3 noncollinear particles of a rigid body.

Planar Circle-Point Equations for Finitely Separated and Double-Point Positions

1998 ◽  
Vol 123 (1) ◽  
pp. 157-160
Author(s):  
Hyoung Jun Kim ◽  
Raj S. Sodhi
Keyword(s):  
Rigid Body ◽  
Double Point ◽  
Rigid Body Motion ◽  
Body Motion ◽  
New Method ◽  
Planar Mechanisms ◽  
Point Position ◽  
Point Curve ◽  
New Form ◽  
Position Problem

The rigid body motion is studied for a combination of finitely and infinitesimally separated positions in planar kinematics. A general new method is developed for determining the locations of points in a rigid body moving through finitely and infinitesimally separated positions. These points would satisfy the constraints of the crank links for planar mechanisms. A new form of the circle-point curve equations is derived for the double-point position problem and also for the finitely separated position problem in planar kinematics.

A new method for simulating rigid body motion in incompressible two-phase flow

2010 ◽  
Vol 67 (6) ◽  
pp. 713-732 ◽  
Author(s):  
Jessica Sanders ◽  
John E. Dolbow ◽  
Peter J. Mucha ◽  
Tod A. Laursen
Keyword(s):  
Rigid Body ◽  
Two Phase Flow ◽  
Rigid Body Motion ◽  
Body Motion ◽  
New Method ◽  
Phase Flow ◽  
Two Phase

scholarly journals Numerical algorithms for high-performance computational science

2020 ◽  
Vol 378 (2166) ◽  
pp. 20190066 ◽  
Author(s):  
Jack Dongarra ◽  
Laura Grigori ◽  
Nicholas J. Higham
Keyword(s):  
High Performance ◽  
Numerical Algorithms ◽  
Computational Science ◽  
Floating Point ◽  
Important Criterion ◽  
Data Movement ◽  
Floating Point Arithmetic ◽  
High Performance Computers ◽  
Point Arithmetic ◽  
Speed And Accuracy

A number of features of today’s high-performance computers make it challenging to exploit these machines fully for computational science. These include increasing core counts but stagnant clock frequencies; the high cost of data movement; use of accelerators (GPUs, FPGAs, coprocessors), making architectures increasingly heterogeneous; and multi- ple precisions of floating-point arithmetic, including half-precision. Moreover, as well as maximizing speed and accuracy, minimizing energy consumption is an important criterion. New generations of algorithms are needed to tackle these challenges. We discuss some approaches that we can take to develop numerical algorithms for high-performance computational science, with a view to exploiting the next generation of supercomputers. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.

Fast and robust mesh arrangements using floating-point arithmetic

2020 ◽  
Vol 39 (6) ◽  
pp. 1-16
Author(s):  
Gianmarco Cherchi ◽  
Marco Livesu ◽  
Riccardo Scateni ◽  
Marco Attene
Keyword(s):  
Floating Point ◽  
Floating Point Arithmetic ◽  
Point Arithmetic

Floating-point arithmetic with 84-bit numbers

1964 ◽  
Vol 7 (1) ◽  
pp. 10-13 ◽  
Author(s):  
Robert T. Gregory ◽  
James L. Raney
Keyword(s):  
Floating Point ◽  
Floating Point Arithmetic ◽  
Point Arithmetic
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