4D-QMPM – 4D data processing to Quantify the Mechanics of Porous Media

Traditional experimental mechanics analysis approaches, whereby a few measurements (e.g., of forces or displacements) are made at the boundary of a test specimen, can at best describe only an average “macroscopic” response of a material. However, in the presence of pre-existing or evolving material heterogeneity (including microstructural variations and strain localisation) such “average” measures loose their pertinence. Such heterogeneity is more the rule than the exception, especially in natural materials. Therefore a new class of measurement approaches has been evolving that permit “full-field” measurements over whole test specimens during the process of mechanical evolution (e.g., during loading experiments).

Aims
The potential for advancing the understanding of the mechanics of porous media with experiments carried out in-situ within x-ray and neutron imaging facilities to provide 4D characterisation (3D in space plus time) is huge, but this potential can be limited by available computing power and algorithms. This project will develop advanced, efficient 3(+)D data processing techniques for N-D multi-scale analysis of material property evolution and deformation mechanisms in different porous materials.

Methods
3(+)D data processing techniques will be developed for efficient processing over realistic time-scales by employing parallel/distributed processing and rapid data storage to have fast access to the large data volumes for both cluster and desktop processing. Scalability of the tools is desirable to enable processing on different systems.
Existing and new data from experiments carried out on different porous materials in-situ in neutron/x-ray imaging facilities will be analysed with the aim of identification of the structures and mechanisms that must be described by models and for quantification of the input parameters. The focus is towards providing support for the development of simulation models of porous materials. Initial interest is the characterisation of soils (e.g., sand), but this will lead on to generalisation/adaptation for other porous materials.
The data analysis tools will include methods for analysis of 3D morphology evolution (e.g., grain contact evolution) and deformation characterisation (including 3D-volume digital image correlation and full grain kinematics measurements) from time-lapse 3D images plus internal (grain) strain measurements using 3D spatially resolved x-ray/neutron diffraction data.

Research group

PI: Stephen Hall
Division of Solid Mechanics, LTH
Matti Ristinmaa
Division of Solid Mechanics, LTH
Kent Persson
Division of Structural mechanics, LTH