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Quantitative micromechanical analysis of tomography data using correlation methods and modeling techniques

Reference number
Coordinator RISE Research Institutes of Sweden AB - Division Säkerhet och transport
Funding from Vinnova SEK 300 000
Project duration August 2019 - June 2020
Status Completed
Venture Research infrastructure - utilisation and collaboration
Call Industrial pilot projects for utilisation of neutron- and photon based techniques at large scale infrastructures - spring 2019
End-of-project report 2019-02579_Scania.pdf (pdf, 312 kB)

Purpose and goal

The project aims at developing an analysis framework (AFW) to determine local mechanical properties from tomography data where test specimens were loaded mechanically (in-situ). Important building blocks of the AFW have been developed such as protocols for communication between analysis steps, mesh routines, correlation analysis including extraction of boundary conditions, FE-modelling and formulation of objective functions. The AFW will be further assessed in continuation projects.

Expected results and effects

As a result of the project an analysis framework, which can be used to identify local mechanical properties of a microscopically heterogeneous (on the microscale) material, has been established through a modular approach. The continued use of the framework will contribute to an increased understanding of the relation between a material’s microstructure and its mechanical performance.

Planned approach and implementation

A modular approach has been used when developing the analysis framework thereby allowing for parallel development of the underlying tools and methods. The framework is build using Python code to handle the communication of data between the analysis steps and for the evaluation of the goal functions. Open source tools have been used for all the analysis steps apart from the DVC analysis which is based on proprietary software.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 7 July 2021

Reference number 2019-02579

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