Get Free Shipping on orders over $79
Simulation Techniques for Applied Dynamics : Cism International Centre for Mechanical Sciences - Martin Arnold

Simulation Techniques for Applied Dynamics

By: Martin Arnold (Editor), Werner Schiehlen (Editor)

Paperback | 19 October 2010

At a Glance

Paperback


$279.00

or 4 interest-free payments of $69.75 with

 or 

Ships in 5 to 7 business days

The coupling of models from different physical domains and the efficient and reliable simulation of multidisciplinary problems in engineering applications are important topics for various fields of engineering, in simulation technology and in the development and analysis of numerical solvers.

The volume presents advanced modelling and simulation techniques for the dynamical analysis of coupled engineering systems consisting of mechanical, electrical, hydraulic and biological components as well as control devices often based on computer hardware and software. The book starts with some basics in multibody dynamics and in port-based modelling and focuses on the modelling and simulation of heterogeneous systems with special emphasis on robust and efficient numerical solution techniques and on a variety of applied problems including case studies of co-simulation in industrial applications, methods and problems of model based controller design and real-time application.

More in Artificial Intelligence

The Tech Coup : How to Save Democracy from Silicon Valley - Marietje Schaake
Creative Machines : AI, Art & Us - Maya Ackerman

RRP $57.95

$44.75

23%
OFF
Genesis : Artificial Intelligence, Hope, and the Human Spirit - Eric Schmidt
Empire of AI : Inside the reckless race for total domination - Karen Hao
The Shortest History of AI - Toby Walsh

RRP $27.99

$22.75

19%
OFF
Life 3.0 : Being Human in the Age of Artificial Intelligence - Max Tegmark
Autonomous Cyber Resilience - Charles A. Kamhoua
Co-Intelligence : Living and Working with AI - Ethan Mollick

RRP $36.99

$29.75

20%
OFF
Artificial Intelligence : A Modern Approach, 4th Global Edition - Peter Norvig
Handbook of Reinforcement Learning - Todd Mcmullen