Applicability of digital image correlation on characterizing shrinkage and swelling of wood and bamboo
Digital image correlation(DIC)has emerged as a robust and versatile tool for assessing the dimensional changes,i.e.,shrinkage and swelling,in wood and bamboo.Conventionally,DIC requires the application of artificial speckle patterns on the material surface to track deformation under varying environmental or loading conditions.However,recent studies have explored the feasibility of utilizing inherent features like vessels and wood fibers as natural speckles for DIC analysis.This approach aims to determine whether natural speckles can provide comparable or superior accuracy compared to artificial patterns in characterizing the dynamic changes in wood and bamboo.Despite these advancements,conclusive evidence regarding the comparative efficacy of natural versus artificial speckle patterns in DIC analysis remains inconclusive.Moreover,the optimal conditions for employing natural speckles across different tree species are poorly defined.This study addressed these gaps by focusing on poplar,Chinese fir,and moso bamboo.Moisture desorption tests from 97％relative humidity(RH)to 0％RH were conducted and subsequent adsorption tests from 0％RH to 97％RH were carried out.Shrinkage and swelling were evaluated during moisture desorption and adsorption tests.Specifically,this study compared the performances of natural and artificial speckle methods in DIC analysis and validated their accuracy by the juxtaposing hygro-deformation analysis with experimental measurements.Significant differences between natural and artificial speckle methods were observed during moisture desorption and absorption,which was influenced by factors such as tree species,grain orientation,and relative radial position.Remarkably,results obtained from natural speckle patterns closely mirrored experimental outcomes,suggesting their superiority in capturing the hygro-deformation in wood and bamboo.Natural features like vessels,wood fibers,bamboo parenchyma cells,and vascular bundles proved effective as reliable markers for DIC analysis,underscoring their potential as preferred alternatives to artificial patterns.To optimize DIC effectiveness,this study recommended adjusting pixel size relative to the size of these natural features,typically ranging between 1/10 to 1/5 of their dimensions,with the step size approximating the feature size to ensure precise subset movement tracking.These findings not only provide a robust theoretical framework but also offer practical guidelines for accurately characterizing shrinkage and swelling at the tissue scale in wood and bamboo using DIC.Such insights are pivotal for enhancing measurement precision and reliability across various applications,thereby facilitating informed decision-making in industries reliant on dimensional stability and performance of wood,bamboo,and other plant materials.
shrinkage and swellingdigital image correlationnatural pointspeckle pattern
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