Skip to main content

A Modular and Extensible Open-Source Framework for Symbolic Creating Bicycle-Rider Models

Project description

SymBRiM

A Modular and Extensible Open-Source Framework for Creating Symbolic Bicycle-Rider Models.

As of October 2024, BRiM has been renamed to SymBRiM.

Links with more information:

This package is still under development, therefore there is no guarantee on backward compatibility.

Installation

SymBRiM is currently not available on PyPI. Therefore, you'll need to install the development version from GitHub using:

pip install git+https://github.com/mechmotum/symbrim.git

The optional dependencies can be installed with:

pip install git+https://github.com/moorepants/BicycleParameters.git
pip install symmeplot

Contributing

Contributions are welcome! Please refer to the contributing page for more information.

Citing

If you use SymBRiM in your research, please cite the following paper:

@inproceedings{stienstra_2023_brim,
    title = {BRiM: A Modular Bicycle-Rider Modeling Framework},
    abstract = {The development of computationally efficient and validated single-track vehicle-rider models has traditionally required handcrafted one-off models. Here we introduce BRiM, a software package that facilitates building these models in a modular fashion while retaining access to the mathematical elements for handcrafted modeling when desired. We demonstrate the flexibility of the software by constructing the Carvallo-Whipple bicycle model with different numerical parameters representing different bicycles, modifying it with a front fork suspension travel model, and extending it with moving rider arms driven by joint torques at the elbows. Using these models we solve a lane-change optimal control problem for six different model variations which solve in mere seconds on a modern personal computer. Our tool enables flexible and rapid modeling of single-track vehicle-rider models that give precise results at high computational efficiency.},
    keywords = {Bicycle Dynamics, BRiM, Computational Modeling, Open-source, SymPy, Simulation, Trajectory Tracking Problem},
    author = {Timótheüs J. Stienstra and Samuel G. Brockie and Jason K. Moore},
    booktitle = {The Evolving Scholar - BMD 2023, 5th Edition},
    year = {2023},
    language = {en},
    doi = "10.59490/6504c5a765e8118fc7b106c3",
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

symbrim-0.1.0.tar.gz (51.9 kB view details)

Uploaded Source

Built Distribution

symbrim-0.1.0-py3-none-any.whl (72.9 kB view details)

Uploaded Python 3

File details

Details for the file symbrim-0.1.0.tar.gz.

File metadata

  • Download URL: symbrim-0.1.0.tar.gz
  • Upload date:
  • Size: 51.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.9.19 Windows/10

File hashes

Hashes for symbrim-0.1.0.tar.gz
Algorithm Hash digest
SHA256 5aff45fd399cbdfe50bd6e731ac7529aef6ff73af2e9b091596fd6effaaec2f6
MD5 1b2c0a80e873cb0b0b4539f83f745e4c
BLAKE2b-256 869c51b55f8988ce2252c9c4de7ed7be404be89f31590addb2ffa49016b7315e

See more details on using hashes here.

File details

Details for the file symbrim-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: symbrim-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 72.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.9.19 Windows/10

File hashes

Hashes for symbrim-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 a3bd80061da7cb60ad273926cd8752f6c9370125e7c6e06d57308885a990af68
MD5 f737e444a98bd04a684227e4e23e827e
BLAKE2b-256 3a274cea24ce4d4a51a3dc6a2c8807707e348d33d6462918ed34dd78df715b03

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page