Combination of neutron imaging (NI) and digital image correlation (DIC) to determine intra-ring moisture variation in Norway spruce

The hygroscopic behavior of wood has a strong influence on its mechanical performance, yet the moisture gradients within the growth ring structure have not been sufficiently investigated. The main challenge is that moisture variations are coupled with strong sample deformation, which complicates the spatial referencing of moist and dry states. In this work, neutron imaging (NI) for the detection of water and digital image correlation (DIC) for the detection of local deformation were combined to calculate the local gravimetric moisture content (MCgrav) and the volumetric moisture content (MCvol) within single growth rings. Specimens of Norway spruce [Picea abies (L.) Karst.] were exposed to an adsorption-desorption cycle, with relative humidity (RH) steps varying from 0% (oven dry) up to 95% RH. After each acclimatization step, neutron transmission and DIC images were acquired. The local deformations determined by DIC were used to assign the corresponding dry density in the undeformed state to the compartment in a moist state and thus to calculate its MC by NI. No significant MC gradients could be found between earlywood (EW) and latewood (LW) within ±0.5% accuracy. However, strong density gradients between EW and LW can be directly correlated with MCvol. It appears that the MC in the cell wall is constant regardless of the particular growth ring positio

Adaptive Neutron Radiography Correlation for Simultaneous Imaging of Moisture Transport and Deformation in Hygroscopic Materials

ISSN:0014-4851ISSN:1741-276

Adaptive neutron radiography correlation for simultaneous imaging of moisture transport and deformation in hygroscopic materials

Neutron radiography is a key non-destructive testing technology for the investigation of moisture transport in materials. However, quantitative moisture measurements in swelling materials are currently challenging due to the lack of referencing between moist and dry state radiographs. A novel adaptive texture correlation algorithm is presented to simultaneously image inhomogeneous moisture distributions and moisture-induced strain fields. The proposed method provides a valuable tool for the study of time- and position-dependent hygromechanical interactions. Moreover, it requires no modification of existing neutron installations. The method was validated against gravimetric moisture content and optic surface deformation measurements. Its applicability was demonstrated for two actual topics in wood science, the investigation of moisture gradients within the growth ring microstructure and the study of moisture transport processes in wood-fiber composites. The algorithm can be widely used to characterize hygroscopic materials with heterogeneous texture, as frequently found in wood constructions, food industry, engineering and soil science