Pub Date : 2025-01-28DOI: 10.1016/j.tmater.2025.100051
Anderson T.V. Veiga , Elisa S. Ferreira , James Drummond , Lewis Mason , Samuel N.M. Brown , André Phillion , D. Mark Martinez , Emily D. Cranston
In this study, we present a protocol to visualize the architecture of tracer fibers in paper using X-ray tomography. We prepared tracer fibers by depositing iron oxide nanoparticles on the surface of select papermaking fibers, through a multicycle labeling technique that achieved 14 wt% of iron. Labeled and unlabeled fibers on their own, as well as laboratory-formed paper containing a small fraction of the tracer fibers, were imaged in air and after immersion in a non-polar oil. We found that labeled fibers could be segmented from the background through simple binarization when in the immersed state whereas segmentation failed when the samples were imaged in air. We propose that the oil served as a mask, created through compositional and density matching of the unlabeled fibers to the saturated void volume. This new labeling and immersion protocol opens avenues to enhance the contrast of tracers for improved characterization of cellulosic materials via X-ray tomographic imaging in an approach that does not require advanced image processing methods for segmentation.
{"title":"Visualizing pulp fibers using X-ray tomography: Enhancing the contrast by labeling with iron oxide nanoparticles and the use of immersion oil","authors":"Anderson T.V. Veiga , Elisa S. Ferreira , James Drummond , Lewis Mason , Samuel N.M. Brown , André Phillion , D. Mark Martinez , Emily D. Cranston","doi":"10.1016/j.tmater.2025.100051","DOIUrl":"10.1016/j.tmater.2025.100051","url":null,"abstract":"<div><div>In this study, we present a protocol to visualize the architecture of tracer fibers in paper using X-ray tomography. We prepared tracer fibers by depositing iron oxide nanoparticles on the surface of select papermaking fibers, through a multicycle labeling technique that achieved 14 wt% of iron. Labeled and unlabeled fibers on their own, as well as laboratory-formed paper containing a small fraction of the tracer fibers, were imaged in air and after immersion in a non-polar oil. We found that labeled fibers could be segmented from the background through simple binarization when in the immersed state whereas segmentation failed when the samples were imaged in air. We propose that the oil served as a mask, created through compositional and density matching of the unlabeled fibers to the saturated void volume. This new labeling and immersion protocol opens avenues to enhance the contrast of tracers for improved characterization of cellulosic materials via X-ray tomographic imaging in an approach that does not require advanced image processing methods for segmentation.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100051"},"PeriodicalIF":0.0,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-26DOI: 10.1016/j.tmater.2025.100050
Shuvam Gupta , Vivian Moutinho , Jose R.A. Godinho , Bradley M. Guy , Jens Gutzmer
This study documents a significant enhancement to the recently introduced Mounted Single Particle Characterization and Mineralogical Analyses (MSPaCMAn) workflow for particulate samples by X-ray computed tomography analyses. This enhancement is used to quantify the abundance of small grains of rare earth minerals within particulate samples of iron ore. In the studied samples, rare earth minerals are typically present as minute grains. The small size creates challenges for X-ray computed tomography due to the well-known partial volume and blurring effects. This effect is particularly pronounced when the sizes of grains start to approach the sizes of voxels. The enhanced MSPaCMAn workflow incorporates new steps to improve the reliability of mineral characterization by simultaneously analyzing the grey values and geometrical properties of rare earth mineral grains and their host minerals. The refined workflow also enables the comprehensive characterization of particle surfaces. The results of the MSPaCMAn were validated by scanning electron microscopy-based automated mineralogy and X-ray powder diffraction data. The study is a step towards accurate and reproducible mineralogical quantification of particulate processing samples using X-ray 3D imaging.
{"title":"3D mineral quantification of particulate materials with rare earth mineral inclusions: Achieving sub-voxel resolution by considering the partial volume and blurring effect","authors":"Shuvam Gupta , Vivian Moutinho , Jose R.A. Godinho , Bradley M. Guy , Jens Gutzmer","doi":"10.1016/j.tmater.2025.100050","DOIUrl":"10.1016/j.tmater.2025.100050","url":null,"abstract":"<div><div>This study documents a significant enhancement to the recently introduced Mounted Single Particle Characterization and Mineralogical Analyses (MSPaCMAn) workflow for particulate samples by X-ray computed tomography analyses. This enhancement is used to quantify the abundance of small grains of rare earth minerals within particulate samples of iron ore. In the studied samples, rare earth minerals are typically present as minute grains. The small size creates challenges for X-ray computed tomography due to the well-known partial volume and blurring effects. This effect is particularly pronounced when the sizes of grains start to approach the sizes of voxels. The enhanced MSPaCMAn workflow incorporates new steps to improve the reliability of mineral characterization by simultaneously analyzing the grey values and geometrical properties of rare earth mineral grains and their host minerals. The refined workflow also enables the comprehensive characterization of particle surfaces. The results of the MSPaCMAn were validated by scanning electron microscopy-based automated mineralogy and X-ray powder diffraction data. The study is a step towards accurate and reproducible mineralogical quantification of particulate processing samples using X-ray 3D imaging.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100050"},"PeriodicalIF":0.0,"publicationDate":"2025-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-20DOI: 10.1016/j.tmater.2025.100049
Qinyi Tian , Sara Goodhue , Hou Xiong , Laura E. Dalton
X-ray micro-computed tomography scanning and tomographic image processing is a robust method to quantify various features in geomaterials. The accuracy of the segmented results can be affected by factors including scan resolution, scanning artifacts, and human bias. To overcome these limitations, deep learning techniques are being explored to address these challenges. In the present study, a novel deep learning model called Geo-SegNet was developed to enhance segmentation accuracy over traditional U-Net models. Geo-SegNet employs contrastive learning for feature extraction by integrating this extractor as the encoder in a U-Net architecture. The model is tested using 10 feet of sandstone cores containing significant changes in porosity and pore geometries and the segmentation results are compared to common segmentation methods and U-Net. Compared to a U-Net-only model, Geo-SegNet demonstrates a 2.0 % increase in segmentation accuracy, indicating the potential of the model to improve the segmentation porosity which can also improve subsequent metrics such as permeability.
{"title":"Geo-SegNet: A contrastive learning enhanced U-net for geomaterial segmentation","authors":"Qinyi Tian , Sara Goodhue , Hou Xiong , Laura E. Dalton","doi":"10.1016/j.tmater.2025.100049","DOIUrl":"10.1016/j.tmater.2025.100049","url":null,"abstract":"<div><div>X-ray micro-computed tomography scanning and tomographic image processing is a robust method to quantify various features in geomaterials. The accuracy of the segmented results can be affected by factors including scan resolution, scanning artifacts, and human bias. To overcome these limitations, deep learning techniques are being explored to address these challenges. In the present study, a novel deep learning model called Geo-SegNet was developed to enhance segmentation accuracy over traditional U-Net models. Geo-SegNet employs contrastive learning for feature extraction by integrating this extractor as the encoder in a U-Net architecture. The model is tested using 10 feet of sandstone cores containing significant changes in porosity and pore geometries and the segmentation results are compared to common segmentation methods and U-Net. Compared to a U-Net-only model, Geo-SegNet demonstrates a 2.0 % increase in segmentation accuracy, indicating the potential of the model to improve the segmentation porosity which can also improve subsequent metrics such as permeability.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100049"},"PeriodicalIF":0.0,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-08DOI: 10.1016/j.tmater.2025.100048
K.N. Cundiff , T.F. Morgeneyer , A.A. Benzerga
The effect of stress triaxiality on the strain-to-fracture of as-received and photo-oxidized polyamide-6 (PA-6) was investigated using mechanical testing, synchrotron X-ray tomography, and finite element analyses. Mechanical tests were conducted on cylindrical and round notched specimens, where different notch radii were used to vary the stress triaxiality. The specimens were aged by exposure to ultra-violet (UV) radiation at 60∘, causing photo-oxidation. As-received and so-aged specimens were loaded to failure (complete loss of load carrying capacity). For both unaged and aged specimens, a higher triaxiality led to a lower strain-to-fracture. To elucidate the micromechanical damage that mediates fracture in both conditions, specimens with an intermediate notch sharpness were loaded to the peak load, unloaded, and scanned ex situ using synchrotron X-ray tomography. Damage in the unaged bar was found to occur by cavitation and was concentrated at the center of the specimen, where the triaxiality is highest. In the UV-aged bar, a network of inter-connected chemical cracks were found on the notch surface, where the triaxiality is lowest. Finite element analyses were deployed to approximate the local triaxiality at damaged regions in the unaged and UV-aged specimens using a constitutive relation for semicrystalline polymers. From these analyses, the relationship between local triaxiality and strain-to-fracture was quantified for both unaged and photo-oxidized PA-6. Both unaged and photo-oxidized PA-6 showed similar decreases in ductility with triaxiality, hinting at common ductile fracture processes.
{"title":"Photo-oxidation of semicrystalline polymers: Effect of stress triaxiality on ductility","authors":"K.N. Cundiff , T.F. Morgeneyer , A.A. Benzerga","doi":"10.1016/j.tmater.2025.100048","DOIUrl":"10.1016/j.tmater.2025.100048","url":null,"abstract":"<div><div>The effect of stress triaxiality on the strain-to-fracture of as-received and photo-oxidized polyamide-6 (PA-6) was investigated using mechanical testing, synchrotron X-ray tomography, and finite element analyses. Mechanical tests were conducted on cylindrical and round notched specimens, where different notch radii were used to vary the stress triaxiality. The specimens were aged by exposure to ultra-violet (UV) radiation at 60<sup>∘</sup>, causing photo-oxidation. As-received and so-aged specimens were loaded to failure (complete loss of load carrying capacity). For both unaged and aged specimens, a higher triaxiality led to a lower strain-to-fracture. To elucidate the micromechanical damage that mediates fracture in both conditions, specimens with an intermediate notch sharpness were loaded to the peak load, unloaded, and scanned <em>ex situ</em> using synchrotron X-ray tomography. Damage in the unaged bar was found to occur by cavitation and was concentrated at the center of the specimen, where the triaxiality is highest. In the UV-aged bar, a network of inter-connected chemical cracks were found on the notch surface, where the triaxiality is lowest. Finite element analyses were deployed to approximate the local triaxiality at damaged regions in the unaged and UV-aged specimens using a constitutive relation for semicrystalline polymers. From these analyses, the relationship between local triaxiality and strain-to-fracture was quantified for both unaged and photo-oxidized PA-6. Both unaged and photo-oxidized PA-6 showed similar decreases in ductility with triaxiality, hinting at common ductile fracture processes.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100048"},"PeriodicalIF":0.0,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-02DOI: 10.1016/j.tmater.2024.100047
Thomas Lang , Anja Heim , Christoph Heinzl
Metal matrix composites are utilized in a multitude of applications due to their mechanical and thermodynamical properties, which are highly dependent on the microstructure. A detailed characterization is thus vital for a sound understanding of the material’s properties. X-ray computed tomography, in particular high resolution synchrotron imaging, presents a promising inspection method for this purpose. However, a high-resolution inspection of medium-sized samples produces very large volumetric datasets, which prevents a proper data analysis with commonly available tools and software. We propose a workflow for analyzing large volumetric datasets of particle-reinforced metal matrix composites, from 3D renderings of the datasets to qualitative and quantitative characterizations of the material regarding shape and spatial distribution of the contained particles. Each step in this workflow is designed to be applicable to arbitrarily large volumetric datasets. Application-dependent visualizations facilitate derived secondary information to become accessible, generating in-depth insights despite the large number of particles. The workflow is demonstrated on a large high-resolution dataset in qualitative and quantitative evaluations, whose visual representations confirm that the distribution of particles within the sample is quite homogeneous albeit the presence of minor agglomerations.
{"title":"Machine learning-supported visual analytics for high resolution X-ray inspection of metal matrix composites","authors":"Thomas Lang , Anja Heim , Christoph Heinzl","doi":"10.1016/j.tmater.2024.100047","DOIUrl":"10.1016/j.tmater.2024.100047","url":null,"abstract":"<div><div>Metal matrix composites are utilized in a multitude of applications due to their mechanical and thermodynamical properties, which are highly dependent on the microstructure. A detailed characterization is thus vital for a sound understanding of the material’s properties. X-ray computed tomography, in particular high resolution synchrotron imaging, presents a promising inspection method for this purpose. However, a high-resolution inspection of medium-sized samples produces very large volumetric datasets, which prevents a proper data analysis with commonly available tools and software. We propose a workflow for analyzing large volumetric datasets of particle-reinforced metal matrix composites, from 3D renderings of the datasets to qualitative and quantitative characterizations of the material regarding shape and spatial distribution of the contained particles. Each step in this workflow is designed to be applicable to arbitrarily large volumetric datasets. Application-dependent visualizations facilitate derived secondary information to become accessible, generating in-depth insights despite the large number of particles. The workflow is demonstrated on a large high-resolution dataset in qualitative and quantitative evaluations, whose visual representations confirm that the distribution of particles within the sample is quite homogeneous albeit the presence of minor agglomerations.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100047"},"PeriodicalIF":0.0,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-23DOI: 10.1016/j.tmater.2024.100046
Jiayang Shi , Louisa Brown , Amir R. Zekavat , Daniël M. Pelt , Charlotte K. Hagen
X-ray phase contrast micro-computed tomography (micro-CT) can achieve higher contrast than conventional absorption-based X-ray micro-CT by utilizing refraction in addition to attenuation. In this work, we focus on a specific X-ray phase contrast technique, edge illumination (EI) micro-CT. EI uses a sample mask with transmitting apertures that split the X-ray beam into narrow beamlets, enabling detection of refraction-included intensity variations. Between the typical mask designs (circular and slit-shaped apertures), slit-shaped apertures offer practical advantages over circular ones, as they only require sample stepping in one direction, thereby reducing scanning time. However, this leads to anisotropic resolution, as the slit-shaped apertures enhances resolution only along the direction orthogonal to the slits. To address this limitation, we propose a self-supervised method that trains on high-resolution in-plane images to enhance resolution for out-of-plane images, effectively mitigating anisotropy. Our results on both simulated and real EI micro-CT datasets demonstrate the effectiveness of the proposed method.
{"title":"Self-supervised resolution enhancement for anisotropic volumes in edge illumination X-ray phase contrast micro-computed tomography","authors":"Jiayang Shi , Louisa Brown , Amir R. Zekavat , Daniël M. Pelt , Charlotte K. Hagen","doi":"10.1016/j.tmater.2024.100046","DOIUrl":"10.1016/j.tmater.2024.100046","url":null,"abstract":"<div><div>X-ray phase contrast micro-computed tomography (micro-CT) can achieve higher contrast than conventional absorption-based X-ray micro-CT by utilizing refraction in addition to attenuation. In this work, we focus on a specific X-ray phase contrast technique, edge illumination (EI) micro-CT. EI uses a sample mask with transmitting apertures that split the X-ray beam into narrow beamlets, enabling detection of refraction-included intensity variations. Between the typical mask designs (circular and slit-shaped apertures), slit-shaped apertures offer practical advantages over circular ones, as they only require sample stepping in one direction, thereby reducing scanning time. However, this leads to anisotropic resolution, as the slit-shaped apertures enhances resolution only along the direction orthogonal to the slits. To address this limitation, we propose a self-supervised method that trains on high-resolution in-plane images to enhance resolution for out-of-plane images, effectively mitigating anisotropy. Our results on both simulated and real EI micro-CT datasets demonstrate the effectiveness of the proposed method.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100046"},"PeriodicalIF":0.0,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-11DOI: 10.1016/j.tmater.2024.100045
J. Lachambre , A. Sibellas , J. Adrien , J. Papillon , R. Bruant , G. Maurel , E. Maire
The grip and rolling resistance of car wheel tires on a road surface is strongly influenced by the mechanical properties of the rubber and especially by the deformation of this rubber during indentation by the road asperities. This paper presents the results of a simplified indentation experiment. A cylindrical block of rubber containing microstructural markers is indented by a sphere in situ inside an X-ray Computed Tomograph. The presence of markers intentionally added to the rubber gum allows us, after suitable image processing for contrast improvement, to measure with a very good precision the displacement field inside the rubber during the indentation using Digital Volume Correlation. The measured displacement is compared with the result of an axisymmetric finite element modeling calculation reproducing the experimental configuration. The close correlation between measured displacements and finite element modeling shows that the proposed method is suitable for studying rubber/road contact.
{"title":"Experimental method for rubber deformation analysis using in situ X-ray tomography and digital volume correlation with FEM validation","authors":"J. Lachambre , A. Sibellas , J. Adrien , J. Papillon , R. Bruant , G. Maurel , E. Maire","doi":"10.1016/j.tmater.2024.100045","DOIUrl":"10.1016/j.tmater.2024.100045","url":null,"abstract":"<div><div>The grip and rolling resistance of car wheel tires on a road surface is strongly influenced by the mechanical properties of the rubber and especially by the deformation of this rubber during indentation by the road asperities. This paper presents the results of a simplified indentation experiment. A cylindrical block of rubber containing microstructural markers is indented by a sphere in situ inside an X-ray Computed Tomograph. The presence of markers intentionally added to the rubber gum allows us, after suitable image processing for contrast improvement, to measure with a very good precision the displacement field inside the rubber during the indentation using Digital Volume Correlation. The measured displacement is compared with the result of an axisymmetric finite element modeling calculation reproducing the experimental configuration. The close correlation between measured displacements and finite element modeling shows that the proposed method is suitable for studying rubber/road contact.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100045"},"PeriodicalIF":0.0,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-28DOI: 10.1016/j.tmater.2024.100043
Richard A. Ketcham
This paper introduces new algorithms for conducting and improving watershed analysis, implemented with the particular goal of improving the ability to measure the shapes of mineral grains to be subsequently be analyzed by mass spectrometry. This application requires a high degree of accuracy and fidelity in terms of both separating all touching grains and preserving their shapes. The algorithms are designed to take advantage of a vector-based programming environment. A new implementation of the Euclidean distance transform utilizes the fact that the distance from any adjacent pair of voxels to the nearest boundary must be within one voxel of each other. In practice, however, this algorithm is outperformed by a smoothed approximate distance transform that is faster to compute and results in less irregular watershed boundaries. A one-pass rainfall-based watershed algorithm is introduced that runs in linear time with the number of segmented voxels, and requires no priority queue. Unlike marker-based watershed algorithms based on the basin-filling approach, the rainfall approach finds watersheds associated with all local maxima in the distance map, even if a marking algorithm is used. A post-watershed smoothing algorithm improves watershed boundaries and eliminates small spurious watersheds. The one-pass watershed and post-watershed smoothing algorithms run in times superior or comparable to basin-fill watershed algorithms implemented in other environments, and offers excellent ability to separate touching objects efficiently while placing watershed boundaries that maximize the preservation of details of particle shape. Further time improvement could come from implementing them in a vector-based environment that allows explicit multi-threading.
{"title":"New watershed methods for isolating and characterizing discrete objects in 3D data sets","authors":"Richard A. Ketcham","doi":"10.1016/j.tmater.2024.100043","DOIUrl":"10.1016/j.tmater.2024.100043","url":null,"abstract":"<div><div>This paper introduces new algorithms for conducting and improving watershed analysis, implemented with the particular goal of improving the ability to measure the shapes of mineral grains to be subsequently be analyzed by mass spectrometry. This application requires a high degree of accuracy and fidelity in terms of both separating all touching grains and preserving their shapes. The algorithms are designed to take advantage of a vector-based programming environment. A new implementation of the Euclidean distance transform utilizes the fact that the distance from any adjacent pair of voxels to the nearest boundary must be within one voxel of each other. In practice, however, this algorithm is outperformed by a smoothed approximate distance transform that is faster to compute and results in less irregular watershed boundaries. A one-pass rainfall-based watershed algorithm is introduced that runs in linear time with the number of segmented voxels, and requires no priority queue. Unlike marker-based watershed algorithms based on the basin-filling approach, the rainfall approach finds watersheds associated with all local maxima in the distance map, even if a marking algorithm is used. A post-watershed smoothing algorithm improves watershed boundaries and eliminates small spurious watersheds. The one-pass watershed and post-watershed smoothing algorithms run in times superior or comparable to basin-fill watershed algorithms implemented in other environments, and offers excellent ability to separate touching objects efficiently while placing watershed boundaries that maximize the preservation of details of particle shape. Further time improvement could come from implementing them in a vector-based environment that allows explicit multi-threading.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100043"},"PeriodicalIF":0.0,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01DOI: 10.1016/j.tmater.2024.100042
Marcus Iversen , Anton Årmann , Robert M. Auenhammer , Nikoleta Pasvanti , Johann Körbelin , Kai Kallio , Leif E. Asp , Renaud Gutkin
Natural fibre composites offer versatile applications across industries while being superior in sustainability aspects compared to other composite types. To unlock their full potential, it is essential to understand their complex failure involving fibre failure, matrix cracking, and debonding at the fibre-matrix interface. Efforts to address these challenges focus on advanced numerical models, probing behaviour from micro to macro scales. However, these models face complexities in handling intricate failure modes given the non-uniform nature of natural fibres. To overcome these challenges, image-based modelling using X-ray computed tomography scans is proposed. This work’s novelty lies in integrating detailed microstructure information with a nonlinear calibration procedure to accurately model damage and failure in natural fiber composites. It marks a significant step toward developing a virtual testing model, paving the way for assessing composites with varying fiber content or fiber types.
天然纤维复合材料可广泛应用于各行各业，同时在可持续性方面优于其他类型的复合材料。要充分挖掘天然纤维复合材料的潜力，就必须了解其复杂的失效情况，包括纤维失效、基体开裂以及纤维-基体界面的脱粘。应对这些挑战的努力主要集中在先进的数值模型上，以探测从微观到宏观尺度的行为。然而，由于天然纤维的非均匀性，这些模型在处理复杂的失效模式时面临着复杂性。为了克服这些挑战，我们提出了利用 X 射线计算机断层扫描进行图像建模的方法。这项工作的新颖之处在于将详细的微观结构信息与非线性校准程序整合在一起，以准确地模拟天然纤维复合材料的损伤和失效。这标志着向开发虚拟测试模型迈出了重要一步，为评估不同纤维含量或纤维类型的复合材料铺平了道路。
{"title":"Numerical failure modelling of natural fibre composite coupons using X-ray computed tomography based modelling","authors":"Marcus Iversen , Anton Årmann , Robert M. Auenhammer , Nikoleta Pasvanti , Johann Körbelin , Kai Kallio , Leif E. Asp , Renaud Gutkin","doi":"10.1016/j.tmater.2024.100042","DOIUrl":"10.1016/j.tmater.2024.100042","url":null,"abstract":"<div><div>Natural fibre composites offer versatile applications across industries while being superior in sustainability aspects compared to other composite types. To unlock their full potential, it is essential to understand their complex failure involving fibre failure, matrix cracking, and debonding at the fibre-matrix interface. Efforts to address these challenges focus on advanced numerical models, probing behaviour from micro to macro scales. However, these models face complexities in handling intricate failure modes given the non-uniform nature of natural fibres. To overcome these challenges, image-based modelling using X-ray computed tomography scans is proposed. This work’s novelty lies in integrating detailed microstructure information with a nonlinear calibration procedure to accurately model damage and failure in natural fiber composites. It marks a significant step toward developing a virtual testing model, paving the way for assessing composites with varying fiber content or fiber types.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"6 ","pages":"Article 100042"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142551919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01DOI: 10.1016/j.tmater.2024.100041
Jose Ricardo Assuncao Godinho , Hannah Vogel , Oliver Plümper , Laurenz Schröer , Florian Buyse , Veerle Cnudde , Peter Moonen
X-ray computed micro tomography (CT) is the main 3D technique for imaging the internal microstructures of samples. Experimental planning is crucial to ensure the adequacy of CT results to answer specific scientific questions, optimizing the use of resources and maximizing the quality of results. Proper planning requires a certain level of expertise in the technique and the details of the specific scientific question to be answered. Notably, potential new CT users who have formulated a scientific question may not have the in-depth knowledge about CT necessary to make a first assessment of whether CT is suitable for their work. Here, a step-by-step protocol to plan CT experiments and an interactive graphical user interface (XCT-Explorer) are proposed to guide users through the different steps of the protocol and to link the various CT parameters required to perform a scan. The protocol is based on the experience gained within EXCITE (Electron and X-ray microscopy Community for structural and chemical Imaging Techniques for Earth materials) through interactions between facility managers and users from various scientific fields. The planning protocol aims to 1) help potential CT users with limited knowledge of CT (e.g. first-time users) to decide whether CT can answer their scientific question; 2) guide users to decide which parameters are the most appropriate for their sample/problem; 3) facilitate the initial contact between CT provider and new users; and 4) standardize the planning stage of CT experiments as the foundation for FAIR (Findable Accessible Interoperable and Reusable) practices.
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