Digital Volume Correlation Approach Research Articles

Pore-scale deformation characteristics of hydrate-bearing sediments with gas replacement

Gas replacement method enables the simultaneous exploitation of natural gas and the realization of carbon capture, utilization, and storage (CCUS). Safe exploitation of hydrate-bearing sediments (HBS) has garnered significant attention, particularly concerning the engineering geological risks involved. Understanding deformation characteristics during shear after the replacement of HBS is crucial for safe and efficient exploitation. This study employs microfocus computer tomography and digital volume correlation (DVC) to investigate the deformation characteristics of HBS samples with varying replacement percentages. Key findings include: 1. An increase in failure strength of HBS is observed with higher replacement percentages due to improved hydrate cementation and consolidation under confining pressure. 2. DVC analysis shows that narrower radial displacement ranges are associated with increased pore compression, while wider ranges indicate greater particle repositioning. Frequent large axial displacements suggest significant pore compaction, whereas smaller axial displacements indicate particle movement and pore-filling phenomena. 3. The gas replacement process enhances the cementation structure of HBS without altering hydrate saturation, resulting in thinner shear bands and accelerated strain softening with higher replacement percentages. 4. The DVC approach effectively captures volumetric strain and deformation behaviors, offering valuable insights into sediment responses under shear. This study provides a theoretical reference for geological safety evaluation during gas replacement exploitation.

Evaluation of compressive behaviour of porous structures under large deformation using micro‐CT, DVC and micro‐FE

AbstractCompressive behaviour of open and closed cell polyurethane foam samples under large deformation is studied using micro‐Computed Tomography (micro‐CT), Digital Volume Correlation (DVC) technique and micro‐Finite Element (micro‐FE) modelling. The micro‐CT images of the foam samples at different compression strains are used to determine anisotropy in the foams, to obtain qualitative information on deformation mechanisms, to quantify the deformation and strains using a local DVC approach and to generate images for micro‐FE modelling of the foam samples. Micro‐FE modelling predicts the deformation using an elastoplastic material model coupled with continuum damage mechanics. Two different types of boundary conditions, experimentally derived (ExBC) and interpolated from DVC (IPBC), were implemented to evaluate the displacements in the micro‐FE models. A reduced integration scheme in micro‐FE analysis resulted in high artificial energy and was discarded in favour of full integration. The displacement predicted by IPBC matched with DVC displacement contours for closed cell foam. The ExBC‐predicted axial displacement (W) showed a better agreement with DVC than transverse displacements (U, V) contours. However, a significant statistical comparison (R2 > 0.70) of all displacements was obtained for both IPBC and ExBC. For open cell foam, both boundary conditions predicted a significant difference in the displacement contours with respect to DVC measurements. Still, the axial displacements of ExBC and IPBC showed a better statistical significance (R2 > 0.70).

Bone metastases do not affect the measurement uncertainties of a global digital volume correlation algorithm.

Introduction: Measurement uncertainties of Digital Volume Correlation (DVC) are influenced by several factors, like input images quality, correlation algorithm, bone type, etc. However, it is still unknown if highly heterogeneous trabecular microstructures, typical of lytic and blastic metastases, affect the precision of DVC measurements. Methods: Fifteen metastatic and nine healthy vertebral bodies were scanned twice in zero-strain conditions with a micro-computed tomography (isotropic voxel size = 39 μm). The bone microstructural parameters (Bone Volume Fraction, Structure Thickness, Structure Separation, Structure Number) were calculated. Displacements and strains were evaluated through a global DVC approach (BoneDVC). The relationship between the standard deviation of the error (SDER) and the microstructural parameters was investigated in the entire vertebrae. To evaluate to what extent the measurement uncertainty is influenced by the microstructure, similar relationships were assessed within sub-regions of interest. Results: Higher variability in the SDER was found for metastatic vertebrae compared to the healthy ones (range 91-1030 με versus 222-599 με). A weak correlation was found between the SDER and the Structure Separation in metastatic vertebrae and in the sub-regions of interest, highlighting that the heterogenous trabecular microstructure only weakly affects the measurement uncertainties of BoneDVC. No correlation was found for the other microstructural parameters. The spatial distribution of the strain measurement uncertainties seemed to be associated with regions with reduced greyscale gradient variation in the microCT images. Discussion: Measurement uncertainties cannot be taken for granted but need to be assessed in each single application of the DVC to consider the minimum unavoidable measurement uncertainty when interpreting the results.

Digital volume correlation for the characterization of musculoskeletal tissues: Current challenges and future developments.

Biological tissues are complex hierarchical materials, difficult to characterise due to the challenges associated to the separation of scale and heterogeneity of the mechanical properties at different dimensional levels.The Digital Volume Correlation approach is the only image-based experimental approach that can accurately measure internal strain field within biological tissues under complex loading scenarios. In this minireview examples of DVC applications to study the deformation of musculoskeletal tissues at different dimensional scales are reported, highlighting the potential and challenges of this relatively new technique.The manuscript aims at reporting the wide breath of DVC applications in the past 2 decades and discuss future perspective for this unique technique, including fast analysis, applications on soft tissues, high precision approaches, and clinical applications.

MicroFE models of porcine vertebrae with induced bone focal lesions: Validation of predicted displacements with digital volume correlation

The evaluation of the local mechanical behavior as a result of metastatic lesions is fundamental for the characterization of the mechanical competence of metastatic vertebrae. Micro finite element (microFE) models have the potential of addressing this challenge through laboratory studies but their predictions of local deformation due to the complexity of the bone structure compromized by the lesion must be validated against experiments. In this study, the displacements predicted by homogeneous, linear and isotropic microFE models of vertebrae were validated against experimental Digital Volume Correlation (DVC) measurements. Porcine spine segments, with and without mechanically induced focal lesions, were tested in compression within a micro computed tomography (microCT) scanner. The displacement within the bone were measured with an optimized global DVC approach (BoneDVC). MicroFE models of the intact and lesioned vertebrae, including or excluding the growth plates, were developed from the microCT images. The microFE and DVC boundary conditions were matched. The displacements measured by the DVC and predicted by the microFE along each Cartesian direction were compared. The results showed an excellent agreement between the measured and predicted displacements, both for intact and metastatic vertebrae, in the middle of the vertebra, in those cases where the structure was not loaded beyond yield (0.69 < R2 < 1.00). Models with growth plates showed the worst correlations (0.02 < R2 < 0.99), while a clear improvement was observed if the growth plates were excluded (0.56 < R2 < 1.00). In conclusion, these simplified models can predict complex displacement fields in the elastic regime with high reliability, more complex non-linear models should be implemented to predict regions with high deformation, when the bone is loaded beyond yield.

In Vivo Deformation and Strain Measurements in Human Bone Using Digital Volume Correlation (DVC) and 3T Clinical MRI.

Strains within bone play an important role in the remodelling process and the mechanisms of fracture. The ability to assess these strains in vivo can provide clinically relevant information regarding bone health, injury risk, and can also be used to optimise treatments. In vivo bone strains have been investigated using multiple experimental techniques, but none have quantified 3D strains using non-invasive techniques. Digital volume correlation based on clinical MRI (DVC-MRI) is a non-invasive technique that has the potential to achieve this. However, before it can be implemented, uncertainties associated with the measurements must be quantified. Here, DVC-MRI was evaluated to assess its potential to measure in vivo strains in the talus. A zero-strain test (two repeated unloaded scans) was conducted using three MRI sequences, and three DVC approaches to quantify errors and to establish optimal settings. With optimal settings, strains could be measured with a precision of 200 με and accuracy of 480 με for a spatial resolution of 7.5 mm, and a precision of 133 με and accuracy of 251 με for a spatial resolution of 10 mm. These results demonstrate that this technique has the potential to measure relevant levels of in vivo bone strain and to be used for a range of clinical applications.

Anisotropic self-adaptive digital volume correlation with optimal cuboid subvolumes

Conventional digital volume correlation (DVC) approaches all use cubic subvolumes for full-field internal displacement mapping. In practical applications, however, real test samples would undergo heterogeneous deformations in three directions due to anisotropic material properties, complex microstructures and/or nonuniform boundary conditions. Based on the self-adaptive DVC (SA-DVC) algorithm we developed recently, here we propose a novel anisotropic self-adaptive DVC (ASA-DVC) approach using cuboid subvolumes and the first-order shape function to realize accuracy-enhanced 3D internal deformation measurement. We first briefly introduce the V-shaped theoretical error model as a function of subvolume size to facilitate optimal subvolume size identification in x, y and z directions. Then, the basic framework of the presented ASA-DVC method capable of automatically specifying optimal subvolume size in three directions at each calculation point is described. Finally, both numerically simulated and real-world experiments are employed to demonstrate the accuracy advantages of the ASA-DVC over routine DVC.

Uncertainties of synchrotron microCT-based digital volume correlation bone strain measurements under simulated deformation

Digital Volume Correlation (DVC) is used to measure internal displacements and strains in bone. Recent studies have shown that Synchrotron radiation micro-computed tomography (SR-microCT) can improve the accuracy and precision of DVC. However, only zero-strain or virtually-moved test have been used to quantify the DVC uncertainties, leading to potential underestimation of the measurement errors.In this study, for the first time, the uncertainties of a global DVC approach have been evaluated on repeated SR-microCT scans of bovine cortical bone (voxel size: 1.6 μm), which were virtually deformed for different magnitudes and along different directions.The results showed that systematic and random errors of the normal strain components along the deformation direction were higher than the errors along unstrained directions. The systematic percentage errors were smaller for larger virtual deformations. The random percentage error was in the order of 10% of the virtual deformation. However, higher errors were localized at the boundary of the volumes of interest, perpendicular to the deformation direction. When only the central region of the samples was considered (100 µm layers removed from the borders where the deformation was applied), the errors in the direction of virtual deformation were comparable to the errors in the unstrained directions.In conclusion, the method presented to estimate the uncertainties of DVC is suitable for testing anisotropic specimens as cortical bone. The good agreement between the uncertainties in measurements of strain components obtained with this approach and with the simpler zero-strain-test suggests that the latter is adequate in the tested deformation scenarios.

Self-Adaptive Digital Volume Correlation for Unknown Deformation Fields

Digital volume correlation (DVC) has evolved into a powerful tool for quantifying full-field internal deformation. In existing subvolume-based local DVC, subvolume size and shape function are two key user-defined parameters closely related to the DVC measurement errors. In routine implementation, the user must define fixed subvolume size and shape function according to prior experience and intuition, which cannot ensure accurate measurements, particularly for unknown complex heterogeneous deformation fields. Self-adaptive selection of optimal subvolume size and the best shape function is therefore highly desirable to realize full-automatic and quality DVC measurements. In this work, we first establish theoretical error models that relate total displacement errors to subvolume sizes and shape functions. By minimizing the V-shaped models of theoretically predicted total errors, optimal subvolume size and the best shape function can be identified as inputs for self-adaptive DVC analysis at each calculation point. The accuracy advantage of the presented self-adaptive DVC approach over classic one using fixed subvolume size and shape function is demonstrated through numerically simulated three-point bending tests.

Variability in strain distribution in the mice tibia loading model: A preliminary study using digital volume correlation

It is well known that bone has an enormous adaptive capacity to mechanical loadings, and to this extent, several in vivo studies on mouse tibia use established cyclic compressive loading protocols to investigate the effects of mechanical stimuli. In these experiments, the applied axial load is well controlled but the positioning of the hind-limb between the loading endcaps may dramatically affect the strain distribution induced on the tibia. In this study, the full field strain distribution induced by a typical in vivo setup on mouse tibiae was investigated through a combination of in situ compressive testing, µCT scanning and a global digital volume correlation (DVC) approach. The precision of the DVC method and the effect of repositioning on the strain distributions were evaluated. Acceptable uncertainties of the DVC approach for the analysis of loaded tibiae (411 ± 58µɛ) were found for nodal spacing of approximately 50 voxels (520 µm). When pairs of in situ preloaded and loaded images were registered, low variability of the strain distributions within the tibia were seen (range of mean differences in principal strains: 585–1800µɛ). On contrary, larger differences were seen after repositioning (range of mean differences in principal strains: 2500–5500µɛ). To conclude, these preliminary results on thee specimens showed that the DVC approach applied to the mouse tibia can be precise enough to evaluate local strain distributions under loads, and that repositioning of the hind-limb within the testing machine can induce large differences in the strain distributions that should be accounted for when modelling this system.

Optimization of digital volume correlation computation in SR-microCT images of trabecular bone and bone-biomaterial systems.

A micromechanical characterization of biomaterials for bone tissue engineering is essential to understand the quality of the newly regenerated bone, enabling the improvement of tissue regeneration strategies. A combination of microcomputed tomography in conjunction with in situ mechanical testing and digital volume correlation (DVC) has become a powerful technique to investigate the internal deformation of bone structure at a range of dimensional scales. However, in order to obtain accurate three-dimensional strain measurement at tissue level, high-resolution images must be acquired, and displacement/strain measurement uncertainties evaluated. The aim of this study was to optimize imaging parameters, image postprocessing and DVC settings to enhance computation based on 'zero-strain' repeated high-resolution synchrotron microCT scans of trabecular bone and bone-biomaterial systems. Low exposures to SR X-ray radiation were required to minimize irradiation-induced tissue damage, resulting in the need of advanced three-dimensional filters on the reconstructed images to reduce DVC-measured strain errors. Furthermore, the computation of strain values only in the hard phase (i.e. bone, biomaterial) allowed the exclusion of large artefacts localized in the bone marrow. This study demonstrated the suitability of a local DVC approach based on synchrotron microCT images to investigate the micromechanics of trabecular bone and bone-biomaterial composites at tissue level with a standard deviation of the errors in the region of 100 microstrain after a thorough optimization of DVC computation. LAY DESCRIPTION: Understanding the quality of newly regenerated bone after implantation of novel biomaterials is essential to improve bone tissue engineering strategies and formulation of biomaterials. The relationship between microstructure and mechanics of bone has been previously addressed combining microcomputed tomography with in situ mechanical testing. The addition of an image-based experimental technique such as digital volume correlation (DVC) allows to characterize the deformation of materials in a three-dimensional manner. However, in order to obtain accurate information at the micro-scale, high-resolution images, obtained for example by using synchrotron radiation microcomputed tomography, as well as optimization of the DVC computation are needed. This study presents the effect of different imaging parameters, image postprocessing and DVC settings for as accurate investigation of trabecular bone structure and bone-biomaterial interfaces. The results showed that when appropriate image postprocessing and DVC settings are used DVC computation results in very low strain errors. This is of vital importance for a correct understanding of the deformation in bone-biomaterial systems and the ability of such biomaterials in producing new bone comparable with the native tissue they are meant to replace.

Validation of finite element models of the mouse tibia using digital volume correlation.

The mouse tibia is a common site to investigate bone adaptation. Micro-Finite Element (microFE) models based on micro-Computed Tomography (microCT) images can estimate bone mechanical properties non-invasively but their outputs need to be validated with experiments. Digital Volume Correlation (DVC) can provide experimental measurements of displacements over the whole bone volume. In this study we applied DVC to validate the local predictions of microFE models of the mouse tibia in compression. Six mouse tibiae were stepwise compressed within a microCT system. MicroCT images were acquired in four configurations with applied compression of 0.5 N (preload), 6.5 N, 13.0 N and 19.5 N. Failure load was measured after the last scan. A global DVC algorithm was applied to the microCT images in order to obtain the displacement field over the bone volume. Homogeneous, isotropic linear hexahedral microFE models were generated from the images collected in the preload configuration with boundary conditions interpolated from the DVC displacements at the extremities of the tibia. Experimental displacements from DVC and numerical predictions were compared at corresponding locations in the middle of the bone. Stiffness and strength were also estimated from each model and compared with the experimental measurements. The magnitude of the displacement vectors predicted by microFE models was highly correlated with experimental measurements (R2 >0.82). Higher but still reasonable errors were found for the Cartesian components. The models tended to overestimate local displacements in the longitudinal direction (R2 = 0.69-0.90, slope of the regression line=0.50-0.97). Errors in the prediction of structural mechanical properties were 14% ± 11% for stiffness and 9% ± 9% for strength. In conclusion, the DVC approach has been applied to the validation of microFE models of the mouse tibia. The predictions of the models for both structural and local properties have been found reasonable for most preclinical applications.

Precision of Digital Volume Correlation Approaches for Strain Analysis in Bone Imaged with Micro-Computed Tomography at Different Dimensional Levels

Accurate measurement of local strain in heterogeneous and anisotropic bone tissue is fundamental to understand the pathophysiology of musculoskeletal diseases, to evaluate the effect of interventions from preclinical studies, and to optimize the design and delivery of biomaterials. Digital volume correlation (DVC) can be used to measure the three-dimensional displacement and strain fields from micro-Computed Tomography (µCT) images of loaded specimens. However, this approach is affected by the quality of the input images, by the morphology and density of the tissue under investigation, by the correlation scheme, and by the operational parameters used in the computation. Therefore, for each application the precision of the method should be evaluated. In this paper we present the results collected from datasets analyzed in previous studies as well as new data from a recent experimental campaign for characterizing the relationship between the precision of two different DVC approaches and the spatial resolution of the outputs. Different bone structures scanned with laboratory source µCT or Synchrotron light µCT (SRµCT) were processed in zero-strain tests to evaluate the precision of the DVC methods as a function of the subvolume size that ranged from 8 to 2500 micrometers. The results confirmed that for every microstructure the precision of DVC improves for larger subvolume size, following power laws. However, for the first time large differences in the precision of both local and global DVC approaches have been highlighted when SRµCT or in vivo µCT images were used instead of conventional ex vivo µCT. These findings suggest that in situ mechanical testing protocols applied in SRµCT facilities should be optimized in order to allow DVC analyses of localized strain measurements. Moreover, for in vivo µCT applications DVC analyses should be performed only with relatively course spatial resolution for achieving a reasonable precision of the method. In conclusion, we have extensively shown that the precision of both tested DVC approaches is affected by different bone structures, different input image resolution and different subvolume sizes. Before each specific application DVC users should always apply a similar approach to find the best compromise between precision and spatial resolution of the measurements.

A flexible and accurate digital volume correlation method applicable to high-resolution volumetric images

Digital volume correlation (DVC) is a powerful technique for quantifying interior deformation within solid opaque materials and biological tissues. In the last two decades, great efforts have been made to improve the accuracy and efficiency of the DVC algorithm. However, there is still a lack of a flexible, robust and accurate version that can be efficiently implemented in personal computers with limited RAM. This paper proposes an advanced DVC method that can realize accurate full-field internal deformation measurement applicable to high-resolution volume images with up to billions of voxels. Specifically, a novel layer-wise reliability-guided displacement tracking strategy combined with dynamic data management is presented to guide the DVC computation from slice to slice. The displacements at specified calculation points in each layer are computed using the advanced 3D inverse-compositional Gauss–Newton algorithm with the complete initial guess of the deformation vector accurately predicted from the computed calculation points. Since only limited slices of interest in the reference and deformed volume images rather than the whole volume images are required, the DVC calculation can thus be efficiently implemented on personal computers. The flexibility, accuracy and efficiency of the presented DVC approach are demonstrated by analyzing computer-simulated and experimentally obtained high-resolution volume images.

Research progress in digital volume correlation method

Full-field displacement and strain measurements of materials, structures and biological tissues subjected to various external (i.e. mechanical or thermal) loading is a primary task of experimental solid mechanics. For nearly a century, benefiting from the rapid development of different branches of physics, various new techniques for whole-field displacement and strain measurements have been developed, advocated and widely used. However, most of these techniques only allows for surface deformation measurement, while in most cases the surface deformation is very different from the actual deformation throughout the interior of a test object. To quantify full-field internal 3D deformation of various opaque materials or biologic tissues subjected to external loading, digital volume correlation (DVC) was developed at the end of last century. Thanks to the increasing popularity and constant emergence of various volumetric imaging devices (e.g., X-ray computed tomography), internal microstructure of a tested sample arising from natural texture or embedded particles can be recorded as digital volume image with distinct random grayscale distribution. By comparing the volume images recorded at different configurations, the internal kinematic filed of the sample can be accurately retrieved by DVC algorithm with the assistance of advanced 3D image registration algorithms and modern computational facilities. Benefiting from constant emergence of new 3D imaging facilities, continual refinement of image registration algorithms, and rapid development of high-performance parallel computing technologies, DVC has gained numerous successful applications in biomedicine, solid mechanics, rock and geo mechanics, material science and biomedicines etc. Basically, as an image-based experimental technique, the implementation of DVC for internal deformation measurement comprises two consecutive steps: volume image acquisition using a certain 3D imaging device and image processing using 3D image registration algorithm. Thus, the accuracy and precision of DVC measurements depend on two primary components: the quality of the recorded volumetric images and the performance of DVC algorithms. In order to satisfy the increasing requirement of measurement accuracy in practical applications, many researchers have contributed to investigate the algorithm improvement and imaging error calibration. In the past decade, plenty of methodologies and algorithmic details have been developed to realize higher measurement accuracy and computational efficiency. Although both the image quality and algorithm performance have gain significant improvement in recent years, systematic and random errors inevitably occur during DVC analyses due to the influence of internal microstructure, image acquirement system, loading environment and algorithm details, thus posing important challenge to accurate DVC measurement in practical applications. In this review, the basic principles and procedures of DVC approach and the concept of the algorithmic details are briefly described first. Then, various methodologies and algorithmic details employed in DVC for internal 3D displacement and strain measurement are systematically described and commented. Limitations and potential developments of the technique are also summarized in terms of material microstructure, volumetric imaging and algorithm performance. Despite facing several challenges such as highly dependence on internal microstructure and large data processing with relatively lower computational efficiency, it is foreseen that DVC method will play an increasingly important role in the field of experimental mechanics and definitely expect more potential applications in broad areas especially in material science and biological engineering.

Strain uncertainties from two digital volume correlation approaches in prophylactically augmented vertebrae: Local analysis on bone and cement-bone microstructures

Combination of micro-focus computed tomography (micro-CT) in conjunction with in situ mechanical testing and digital volume correlation (DVC) can be used to access the internal deformation of materials and structures. DVC has been exploited over the past decade to measure complex deformation fields within biological tissues and bone-biomaterial systems. However, before adopting it in a clinically-relevant context (i.e. bone augmentation in vertebroplasty), the research community should focus on understanding the reliability of such method in different orthopaedic applications involving the use of biomaterials. The aim of this study was to evaluate systematic and random errors affecting the strain computed with two different DVC approaches (a global one, “ShIRT-FE”, and a local one, “DaVis-DC”) in different microstructures within augmented vertebrae, such as trabecular bone, cortical bone and cement-bone interdigitation. The results showed that systematic error was insensitive to the size of the computation sub-volume used for the DVC correlation. Conversely, the random error (which was generally the largest component of error) was lower for a 48-voxel (1872micrometer) sub-volume (64–221 microstrain for ShIRT-FE, 88–274 microstrain for DaVis-DC), than for a 16-voxel (624micrometer) sub-volume (359–1203 microstrain for ShIRT-FE, 960–1771 microstrain for DaVis-DC) for the trabecular and cement regions. Overall, the local random error did not appear to be influenced by either bone microarchitecture or presence of biomaterial. For the 48-voxel sub-volume the global approach was less sensitive to the gradients in grey-values at the cortical surface (random error below 200 microstrain), while the local approach showed errors up to 770 microstrain. Mean absolute error (MAER) and standard deviation of error (SDER) were also calculated and substantially improved when compared to recent literature for the cement-bone interface. The multipass approach for DaVis-DC further reduced the random error for the largest volume of interest. The random error did not follow any recognizable pattern with the six strain components and only ShiRT-FE seemed to produce lower random errors in the normal strains. In conclusion this study has provided, for the first time, a preliminary indication of the reliability and limitations for the application of DVC in estimating the micromechanics of bone and cement-bone interface in augmented vertebrae.

Digital volume correlation can be used to estimate local strains in natural and augmented vertebrae: An organ-level study

Digital Volume Correlation (DVC) has become popular for measuring the strain distribution inside bone structures. A number of methodological questions are still open: the reliability of DVC to investigate augmented bone tissue, the variability of the errors between different specimens of the same type, the distribution of measurement errors inside a bone, and the possible presence of preferential directions. To address these issues, five augmented and five natural porcine vertebrae were subjected to repeated zero-strain micro-CT scan (39μm voxel size). The acquired images were processed with two independent DVC approaches (a local and a global one), considering different computation sub-volume sizes, in order to assess the strain measurement uncertainties. The systematic errors generally ranged within ±100 microstrain and did not depend on the computational sub-volume. The random error was higher than 1000 microstrain for the smallest sub-volume and rapidly decreased: with a sub-volume of 48 voxels the random errors were typically within 200 microstrain for both DVC approaches. While these trends were rather consistent within the sample, two individual specimens had unpredictably larger errors. For this reason, a zero-strain check on each specimen should always be performed before any in-situ micro-CT testing campaign. This study clearly shows that, when sufficient care is dedicated to preliminary methodological work, different DVC computation approaches allow measuring the strain with a reduced overall error (approximately 200 microstrain). Therefore, DVC is a viable technique to investigate strain in the elastic regime in natural and augmented bones.

Quantifying Bulk Electrode Strain and Material Displacement within Lithium Batteries via High-Speed Operando Tomography and Digital Volume Correlation.

Tracking the dynamic morphology of active materials during operation of lithium batteries is essential for identifying causes of performance loss. Digital volume correlation (DVC) is applied to high‐speed operando synchrotron X‐ray computed tomography of a commercial Li/MnO2 primary battery during discharge. Real‐time electrode material displacement is captured in 3D allowing degradation mechanisms such as delamination of the electrode from the current collector and electrode crack formation to be identified. Continuum DVC of consecutive images during discharge is used to quantify local displacements and strains in 3D throughout discharge, facilitating tracking of the progression of swelling due to lithiation within the electrode material in a commercial, spiral‐wound battery during normal operation. Displacement of the rigid current collector and cell materials contribute to severe electrode detachment and crack formation during discharge, which is monitored by a separate DVC approach. Use of time‐lapse X‐ray computed tomography coupled with DVC is thus demonstrated as an effective diagnostic technique to identify causes of performance loss within commercial lithium batteries; this novel approach is expected to guide the development of more effective commercial cell designs.

A Fast Iterative Digital Volume Correlation Algorithm for Large Deformations

Digital volume correlation (DVC), the three-dimensional (3D) extension of digital image correlation (DIC), measures internal 3D material displacement fields by correlating intensity patterns within interrogation windows. In recent years DVC algorithms have gained increased attention in experimental mechanics, material science, and biomechanics. In particular, the application of DVC algorithms to quantify cell-induced material deformations has generated a demand for user-friendly, and computationally efficient DVC approaches capable of detecting large, non-linear deformation fields. We address these challenges by presenting a fast iterative digital volume correlation method (FIDVC), which can be run on a personal computer with computation times on the order of 1–2 min. The FIDVC algorithm employs a unique deformation-warping scheme capable of capturing any general non-linear finite deformation. The validation of the FIDVC algorithm shows that our technique provides a unique, fast and effective experimental approach for measuring non-linear 3D deformations with high spatial resolution.

High resolution measurement of internal full-field displacements and strains using global spectral digital volume correlation

Thanks to its ability to non-destructively access internal strains in materials, Digital Volume Correlation (DVC) is gaining growing interest from both experimental and theoretical mechanics communities. One important issue in the implementation of DVC is the considerable computational costs associated with the huge amount of data, which hinders the applications of the technique, especially for high-resolution displacement and strain measurements. In this paper, we propose an accurate global DVC approach based on a Fourier decomposition for the kinematic basis of the sought displacement field. The approach, referred to as IS-DVC, leads to an algorithm whose computational complexity is not considerably increased by increasing the number of Degrees of Freedom (DOF) of the kinematic basis, thus being computationally efficient using the Fast Fourier Transform (FFT). Artificial experiments have been used to evaluate the uncertainties of IS-DVC at high resolutions. Especially, displacement fields of 3D composites with spherical and non-aligned ellipsoidal particles at small scales were reconstructed. Resulting measurements revealed close similarities in terms of strain heterogeneities throughout the volume with the benchmark strains. Furthermore, it was shown that, in the presence of a discontinuity, the measurement uncertainties are not significantly affected, except for regions surrounding the discontinuity, hence validating the robustness of the reconstructed displacement field at a large number of DOF.