uraeus.smbd


Symbolic Multi-Body Dynamics in Python | A python package for the symbolic creation and analysis of constrained multi-body systems.

Note

The documentation is still under construction …


Multi-Body Systems

In modern literature, multi-body systems refer to modern mechanical systems that are often very complex and consist of many components interconnected by joints and force elements such as springs, dampers, and actuators. Examples of multi-body systems are machines, mechanisms, robotics, vehicles, space structures, and bio-mechanical systems. The dynamics of such systems are often governed by complex relationships resulting from the relative motion and joint forces between the components of the system. [1]

Therefore, a multi-body system is hereby defined as a finite number of material bodies connected in an arbitrary fashion by mechanical joints that limit the relative motion between pairs of bodies. Practitioners of multi-body dynamics study the generation and solution of the equations governing the motion of such systems [2].


Audience and Fields of Application

Initially, the main targeted audience was the Formula Student community. The motive was to encourage a deeper understanding of the modeling processes and the underlying theories used in other commercial software packages, which is a way of giving back to the community, and supporting the concept of “knowledge share” adopted there by exposing it to the open-source community as well.

Currently, the tool aims to serve a wider domain of users with different usage goals and different backgrounds, such as students, academic researchers and industry professionals.

Fields of application include any domain that deals with the study of interconnected bodies, such as:

  • Ground Vehicles’ Systems.
  • Construction Equipment.
  • Industrial Mechanisms.
  • Robotics.
  • Biomechanics.
  • etc.

Features

Currently, uraeus.smbd provides:

  • Creation of symbolic template-based and standalone multi-body systems using minimal API via python scripting.
  • Convenient and easy creation of complex multi-body assemblies.
  • Convenient visualization of the system topology as a network graph.
  • Viewing the system’s symbolic equations in a natural mathematical format using Latex printing.
  • Optimization of the system symbolic equations by performing common sub-expressions elimination.
  • Creation of symbolic configuration files to facilitate the process of numerical simulation data entry.


References

[1]Shabana, A.A., Computational Dynamics, Wiley, New York, 2010.
[2]McPhee, J.J. Nonlinear Dyn (1996) 9: 73. https://doi.org/10.1007/BF01833294

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