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Console app and Python API implementing a generalization of eigenvalue problem within the harmonic coupled finite strip method, used for parametric modeling of static and dynamic inelastic buckling, free vibration, damage and failure in prismatic shell structures.

Project description

About

Console app and Python API implementing a generalization of eigenvalue problem within the harmonic coupled finite strip method, used for parametric modeling of static and dynamic inelastic buckling, free vibration, damage and failure in prismatic shell structures.

This work is a part of the investigation within the research project [ON174027], supported by the Ministry for Science and Technology, Republic of Serbia. This support is gratefully acknowledged.

References

[Milasinovic1997]Milašinović, D.D. “The Finite Strip Method in Computational Mechanics”. Faculties of Civil Engineering: University of Novi Sad, Technical University of Budapest and University of Belgrade: Subotica, Budapest, Belgrade. (1997)
[ON174027]“Computational Mechanics in Structural Engineering”

Installation

To install fsm_eigenvalue run:

$ pip install fsm_eigenvalue

Console app usage

Quick start:

$ fsm_eigenvalue <filename>

Show help:

$ fsm_eigenvalue --help

Python API usage

Quick start:

>>> import logging
>>> logging.basicConfig(level=logging.DEBUG)

>>> from fsm_eigenvalue.compute import parameter_sweep
>>> from fsm_eigenvalue.load import load_data_from
>>> from fsm_eigenvalue.store import store_results_to

>>> data_file = 'examples/data-files/barbero-viscoelastic.yaml'
>>> results_file = data_file.replace('.yaml', '.hdf5')

>>> beam_type_id, search_space, nodal_graph, strip_data, materials, astiff_shape = load_data_from(data_file)
>>> with parameter_sweep(beam_type_id, search_space, strip_data, materials, astiff_shape) as results_iterator:
...     store_results_to(results_file, data_file, search_space, astiff_shape, results_iterator)

Contribute

If you find any bugs, or wish to propose new features please let us know.

If you’d like to contribute, simply fork the repository, commit your changes and send a pull request. Make sure you add yourself to AUTHORS.

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