Methods and applications of digital volume correlation

Bay, Brian K.

doi:10.1243/03093247jsa436

Cited by 182 publications

(141 citation statements)

References 93 publications

(91 reference statements)

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“…To reduce computational load, a large sub-volume edge length (l) was set initially, being made progressively smaller at each iteration . For a more in-depth technical discussion of DVC methods, the reader is referred to (Bay, 2008) 2.4.1. Quantification of systematic DVC error resulting from imaging artifacts…”

Section: Tomographic Imagingmentioning

confidence: 99%

Mapping soil deformation around plant roots using in vivo 4D X-ray Computed Tomography and Digital Volume Correlation

Keyes

Gillard

Soper

et al. 2016

Journal of Biomechanics

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(250)The mechanical impedance of soils inhibits the growth of plant roots, often being the most significant physical limitation to root system development. Non-invasive imaging techniques have recently been used to investigate the development of root system architecture over time, but the relationship with soil deformation is usually neglected. Correlative mapping approaches parameterised using 2D and 3D image data have recently gained prominence for quantifying physical deformation in composite materials including fibre-reinforced polymers and trabecular bone.Digital Image Correlation (DIC) and Digital Volume Correlation (DVC) are computational techniques which use the inherent material texture of surfaces and volumes, captured using imaging techniques, to map full-field deformation components in samples during physical loading.Here we develop an experimental assay and methodology for four-dimensional, in vivo X-ray Computed Tomography (XCT) and apply a Digital Volume Correlation (DVC) approach to the data to quantify deformation. The method is validated for a field-derived soil under conditions of uniaxial compression, and a calibration study is used to quantify thresholds of displacement and strain measurement. The validated and calibrated approach is then demonstrated for an in vivo test case in which an extending maize root in field-derived soil was imaged hourly using XCT over a growth period of 19 h. This allowed full-field soil deformation data and 3D root tip dynamics to be quantified in parallel for the first time.This method paves the way for comparative studies of contrasting soils and plant genotypes, improving our understanding of the fundamental mechanical processes which influence root system development.

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Section: Tomographic Imagingmentioning

confidence: 99%

Mapping soil deformation around plant roots using in vivo 4D X-ray Computed Tomography and Digital Volume Correlation

Keyes

Gillard

Soper

et al. 2016

Journal of Biomechanics

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“…Through the use of CT, and associated in situ experimental approaches, it is possible to capture this form of damage progression in sufficient detail to apply the DVC technique. Image correlation of volumetric datasets was first implemented to determine continuum-level displacement and strain fields in trabecular bone [10], [11] and helped validate FE models [7], [13]. With CT resolutions now routinely reaching below the micro-meter range, 3D volumes of internal micro-architecture can now be generated with ultra-high resolution micro-focus CT systems [14], [15] and via SRCT [6], [16].…”

Section: -Introductionmentioning

confidence: 99%

Three-dimensional deformation mapping of Mode I interlaminar crack extension in particle-toughened interlayers

et al. 2016

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This paper presents the first use of Digital Volume Correlation (DVC) on Carbon Fibre Reinforced Plastics (CFRPs) to quantify the strain fields ahead of a Mode I delamination. DVC is a relatively novel tool that can be used to measure displacements and strains occurring inside materials under load. In conjunction with Computed Tomography (CT), the technique has been applied to porous materials, with results providing strain data for validation of Finite Element (FE) models. However, the application of the technique to laminated materials has been limited, with studies often requiring fiducial markings required for volume correlation. In this work, crack propagation steps were captured at a 325 nm voxel resolution using Synchrotron Radiation Computed Tomography (SRCT). The material systems investigated featured different crack bridging mechanisms such as; particle-bridges, resin ligaments, and fibre-bridges. An assessment of noise and sub-volume size on the strain measurement determined that the optimal sub-volume size was 150 voxels with 50 % overlap. This provided a spatial resolution of 48.8 µm for strain and a corresponding strain resolution ranging between 220-690 µε for the repeated reference scans. A rigid body translation study confirmed that specimen movements perpendicular to the fibre orientation support the 'real' physical displacements. However, along the fibre direction, the correlation was poor, with correct displacements being detected only within the particle-toughened interlayers. The study demonstrates that strain measurements can be made perpendicular to the fibre direction across the interlayer, which could be used to validate future FE models of these poorly understood particle-toughened interlayers.

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“…The result is that a discrete voxel grey level value may actually be encoding an edge between materials with very different attenuation properties. suitable parameters and consideration of the various sources of error, it is thus possible to derive full-field strain data without resorting to invasive and/or sparse methods such as strain gauging (Bay 2008). The implementation of DIC is very similar to that of the particle image velocimetry (PIV) approaches used in experimental fluid mechanics (Willert and Gharib 1991).…”

Section: Brief Review Of Structural Imagingmentioning

confidence: 99%

Challenges in imaging and predictive modeling of rhizosphere processes

et al. 2016

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Background Plant-soil interaction is central to human food production and ecosystem function. Thus, it is essential to not only understand, but also to develop predictive mathematical models which can be used to assess how climate and soil management practices will affect these interactions. Scope In this paper we review the current developments in structural and chemical imaging of rhizosphere processes within the context of multiscale mathematical image based modeling. We outline areas that need more research and areas which would benefit from more detailed understanding. Conclusions We conclude that the combination of structural and chemical imaging with modeling is an incredibly powerful tool which is fundamental for understanding how plant roots interact with soil. We emphasize the need for more researchers to be attracted to this area that is so fertile for future discoveries. Finally, model building must go hand in hand with experiments. In particular, there is a real need to integrate rhizosphere structural and chemical imaging with modeling for better understanding of the rhizosphere processes leading to models which explicitly account for pore scale processes.

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Methods and applications of digital volume correlation

Cited by 182 publications

References 93 publications

Mapping soil deformation around plant roots using in vivo 4D X-ray Computed Tomography and Digital Volume Correlation

Mapping soil deformation around plant roots using in vivo 4D X-ray Computed Tomography and Digital Volume Correlation

Three-dimensional deformation mapping of Mode I interlaminar crack extension in particle-toughened interlayers

Challenges in imaging and predictive modeling of rhizosphere processes

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