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Software . 2020
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FE model updating in Python

Authors: Bjørn T. Svendsen;

FE model updating in Python

Abstract

Finite element (FE) model updating in Python by an example. The framework of sensitivity-based FE model updating is implemented in Python and validated through a simple numerical case study utilizing the FE model program Abaqus. FE model updating is performed by considering a simply supported beam. The files include: Implementation of the theoretical framework of sensitivity-based FE model updating by perturbation analysis. Demonstration of an analysis framework, or workflow setup, utilizing the numerical FE model program Abaqus. Description of a numerical case study including results for validation. Experience with Abaqus and Abaqus scripting is not needed, but preferable, for an increased understanding of the numerical case study implementation. The workflow setup is general and the theoretical framework of the model updating can be utilized with other FEM programs by simple modifications to the provided files. The easiest way to get into the use and understanding is to download and run the example files (01_run.py and 02_run_pp.py). The analysis framework is established using Python version 3.7.2, including Scipy version 1.3.2. The numerical FE model is established in Abaqus/CAE release 2017.

Keywords

structural-engineering, abaqus, model-updating, optimization, finite-element-analysis

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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average