In situ X-ray computed tomography (X-ray CT) is used to investigate the effects of characteristic microstructural features on the pitting initiation and propagation in austenitic stainless steel specimens prepared with laser powder bed fusion (LPBF) additive manufacturing. In situ X-ray CT in probing the mechanism and kinetics of localized corrosion is demonstrated by immersing two LPBF specimens with different porosities in an aggressive ferric chloride solution for the evaluation of corrosion. X-ray CT images are acquired from the specimens after every 8 hours of immersion over an extended period of time (216 hours). Corrosion pit growth is then quantitatively analyzed with a data-constrained modeling method. The pitting growth mechanism of LPBF stainless steel is found to be different from that of conventional stainless steels. More specifically, the mechanism of corrosion pit initiation is closely correlated with the original lack of fusion porosity (LOF) distribution on the surface of the specimens and preferential pit propagation through the LOF pores inside the specimens. Pit growth kinetics are derived from pit volume changes determined through 3D data analysis. The pit growth kinetics in LPBF specimens are found to vary in the initial pit formation, competitive pit propagation, and the dominant pit growth stages.

Quantitative 3D Characterization for Kinetics of Corrosion In article 2201162, Jianli Li, Anthony E. Hughes, Y. S. Yang, and co-workers investigate the corrosion pitting initiation and propagation in 3D-printed austenitic stainless steel with in-situ X-ray computed tomography and data-constrained modelling analysis. For the first time the kinetics of pit volume and surface area growth in stainless steels are determined both globally and for individual pits. Quantitative knowledge in kinetics of corrosion in stainless steel has significant implications in various industrial applications.

Machine learning (ML) is providing a new design paradigm for many areas of technology, including corrosion inhibition. However, ML models require relatively large and diverse training sets to be most effective. This paper provides an overview of developments in corrosion inhibitor research, focussing on how corrosion performance data can be incorporated into machine learning and how large sets of inhibitor performance data that are suitable for training robust ML models can be developed through various corrosion inhibition testing approaches, especially high-throughput performance testing. It examines different types of environments where corrosion by-products and electrolytes operate, with a view to understanding how conventional inhibitor testing methods may be better designed, chosen, and applied to obtain the most useful performance data for inhibitors. The authors explore the role of modern characterisation techniques in defining corrosion chemistry in occluded structures (e.g., lap joints) and examine how corrosion inhibition databases generated by these techniques can be exemplified by recent developments. Finally, the authors briefly discuss how the effects of specific structures, alloy microstructures, leaching structures, and kinetics in paint films may be incorporated into machine learning strategies.

本文利用同步辐射X射线对一沁水盆地无烟煤样在24 keV的能量下进行了成像,并重构得到其CT切片.分别采用数字地形模型(DTM)和数据约束模型(DCM)对样品的CT切片进行分析.研究结果表明,对本文所用煤样,DTM计算得到的煤样孔隙率与真密度和视相对密度实验法测得孔隙率较为接近,但利用DTM确定的阈值进行阈值分割提取到的样品孔隙率与DTM计算所得孔隙率之间偏差较大.DCM计算得到的孔隙率与DTM计算得到的孔隙率及实验测试结果均较为接近.DCM模型考虑了样品CT成像过程中的部分体积效应,得到小于CT体元的孔隙分布信息,在一定程度上拓展了CT成像技术的表征尺度.DCM计算结果显示,煤样中孔隙更多与煤基质和矿物组分以部分占据CT体元的形式存在.

Agglomeration provides substantial advantages on heap leaching, such as creating a porous heap to improve low-permeability ore leaching efficiency, as well as building an environmentally friendly heap by reducing metal releases from waste rock and tailings. In this study, we employed synchrotron X-ray computed tomography (Xray CT) combined with a data-constrained modelling (DCM) approach to investigate the properties and evolution of pore networks of chalcopyrite-dominant agglomerates during leaching. In particular, these agglomerates, with and without prior CaCl2 addition to produce binding reagent gypsum, were subjected to column leaching tests for a period of 37 days. The copper recovery is found to be highly dependent on interior structures of agglomerates: oxidative dissolution of sulphide minerals within agglomerates was considerably promoted by high CaCl2 addition, through more interior connected pore network structure, resulting in effective migration and diffusion of lixiviant solution. The leaching data clearly show that sufficient binding capacity is essential for the maintenance of agglomerate structure by improving its mechanical resistance. Synchrotron X-ray CT data reveals that the decomposition of agglomerate has a performance of dispersing sulphide grains within the agglomerate particle and improved intra-particle porosity. This study demonstrates that combined synchrotron X-ray CT and DCM approach is a powerful tool for understanding the characteristics and evolution of valuable minerals during leaching of agglomerates.

Cold spray additive manufacturing (CSAM) is a solid-state deposition process well-suited to titanium that has the potential to make large, near-net-shape parts at high productivity. However, further research is required to truly accomplish the freedom of design expected from CSAM and, in particular, to address how to manufacture a specific 3D object with minimal porosity. Therefore, this paper focuses on understanding how tool path planning strategy and robot kinematics affect the geometry and porosity distribution in a 3D object. Square titanium frames were manufactured layer-by-layer using a continuous tool path planning strategy in which the contour spray angle, traverse speed and corner smoothing radius were varied selectively. The sample geometry was analysed by 3D laser scanning, and the capacity to produce straight, vertical walls and square corners were demonstrated. The total porosity in the manufactured objects was measured using the Archimedes’ principle, further investigated by metallographic cross-section analysis, and then validated by X-ray computed tomography on selected samples. Porosity was distributed layer by layer, creating a fishbone structure in the cross-section with higher porosity between the layers and near the edges of the walls and corners. The influence of robot kinematics and toolpath planning on forming underbuilt and overbuilt structures and how they influenced porosity development are also discussed. The knowledge generated from this research can significantly influence the development of tool path planning strategies in CSAM, providing the means to produce improved near-net-shapes with controlled porosity formation.

Localised corrosion of 316 L stainless steel (316 L SS) produced by selective laser melting (SLM) was investigated by two and three-dimensional techniques. It was revealed that porosity, which inevitably exists in the SLM-produced parts, is a critical factor determining the susceptibility to localised corrosion. Specimens containing lack-of-fusion (LOF) pores were found to be extremely susceptible to localised corrosion, as indicated by their lower breakdown potentials measured in polarisation tests. Computed tomography (CT) analysis, capable of linking the microstructure and corrosion propagation paths in three dimensions, showed the development of localised corrosion at the sites of LOF pores upon exposure to ferric chloride solution.

A long-term leach investigation was undertaken on particles of a sulfide ore to determine the nature of solution transport into large particles and to identify the primary roles concentrations of acid and oxidant on controlling solution transport. Bulk leaching results showed that in the case of Fe leaching, both [Fe3+] and [H2SO4] promoted the extent of Fe extraction whereas the extent of Zn and Pb extraction was dependent only on [H2SO4]. Based on the bulk extraction of Al and Mg, it appears that [H2SO4] drives the expansion of inner particle pores by promoting the dissolution of gangue minerals. The findings indicated that the generation of cracks and/or pores to enhance solution contact with the value minerals remains the critical factor in improving value metal recovery from this type of material during heap leaching. Comparative laboratory and synchrotron X-CT studies were also undertaken on single ore particles using a novel in–situ leach cup technique. Similar to the solution results, the acid concentration was shown to be critical in creating effective porosity and pore networks through the centre of the particles for the transport of solution to value minerals and subsequent leaching and transport to the bulk solution. This occurred primarily through the dissolution of auxiliary aluminosilicate gangue minerals, which in turn created networks of porosity for effective bulk solution transport into large particles during heap leaching. This, in turn, enables local solution micro-environments where leaching occurs at the solid-liquid interface. Following the accessibility of bulk solution into the particle, the reaction is then governed by surface-mineral reactions between the sulfidic minerals.

Despite the obvious advantages of additive manufacturing (AM) in producing metallic parts, defect formation remains a challenge that deleteriously impacts some critical materials properties of AM parts. Here, through electron microscopy and X-ray computed tomography (X-ray CT), new insights are revealed about lack-of-fusion (LOF) pores; the most common defect reported for AM. We show that LOF pores are not simply a void but a complex structure comprising oxide films decorating pore walls and grain refined regions with dislocation structures surrounding the pore. The formation of a thin nanocrystalline metallic layer on the pore wall is also observed. Spatter particles are the source of most LOF structures at high densities typical of recommended processing conditions and can only be eliminated by careful selection of processing parameters. Data constrained modelling, which uses the materials' properties, was used for generating 3D representations of the complex structure surrounding LOF pores from X-ray CT datasets.

Metal additive manufacturing (MAM) has found emerging application in the aerospace, biomedical and defence industries. However, the lack of reproducibility and quality issues are regarded as the two main drawbacks to AM. Both of these aspects are affected by the distribution of defects (e.g. pores) in the AM part. Computed tomography (CT) allows the determination of defect sizes, shapes and locations, which are all important aspects for the mechanical properties of the final part. In this paper, data-constrained modelling (DCM) with multi-energy synchrotron X-rays is employed to characterise the distribution of defects in 316L stainless steel specimens manufactured with laser metal deposition (LMD). It is shown that DCM offers a more reliable method to the determination of defect levels when compared to traditional segmentation techniques through the calculation of multiple volume fractions inside a voxel, i.e. by providing sub-voxel information. The results indicate that the samples are dominated by a high number of small light constituents (including pores) that would not be detected under the voxel size in the majority of studies reported in the literature using conventional thresholding methods.

Understanding fluid flow behavior in coal is of great significance for coal-bed methane exploration. X-ray CT and image segmentation have been widely used to extract pore network and generate flow field grids for flow simulation in coal samples. However, these techniques have fundamental limitations for the multi-scale characterization of coal samples, where the sub-voxel scale details could not be resolved for millimeter scale macroscopic samples. This makes it difficult to simulate the multi-scale flow behavior of fluid transport in coal sample with varying pore scales. The primary challenge is to make connection between simulation results of different scales. In the present work, multi-scale fluid flow in an anthracite coal sample was simulated by incorporating the data-constrained modeling (DCM), molecular dynamics (MD) method and partially-percolating lattice Boltzmann method (PP-LBM). In this multi-scale simulation method, three-dimensional (3D) flow field containing multi-scale structural information of the coal sample was generated by combining DCM with multi-energy synchrotron radiation CT. Multi-scale fluid flow was simulated by PP-LBM. In PP-LBM, an effective percolation fraction parameter which represents the effective volume fraction of the fluid that contributed to the flow for the voxel was used as a bridge to connect the fluid flow pattern of sub-voxel scales and voxel scales. The effective percolation fraction of a voxel versus its porosity was derived by MD simulations at the sub-voxel size level. The 3D distribution of fluid speed in the coal sample and its permeability were obtained by this multi-scale method. The numerical results are consistent with published laboratory measurements. Our proposed approach incorporated multi-scale effects and offered a more realistic fluid transport simulation method for a coal sample with varying pore size scales from the microscopic to macroscopic level. The method would be applicable for fluid transport simulations for other multi-scale porous materials.

Unlike many other clastic rocks, relating velocity and permeability to porosity for micrite-bearing carbonate rocks has been largely unsuccessful. Recent studies have shown that additional parameters, most notably the distribution and/or proportion of micrite, can be used to parameterize the velocity and permeability behavior. However, there is currently no scale-consistent, 3D methodology for differentiating macroporosity and microporosity from the total porosity measured on bench-top laboratory equipment. Previous studies estimated microporosity and micrite content by combining total porosity measurements conducted on whole 50 mm cores with measurements of phase volumes on 1 mm digital rocks (i.e., scale-inconsistent). As a step forward from those, we imaged dual-porosity carbonate rocks using X-ray microcomputed tomography and then leveraged a recently developed, optimization-based technique, called data-constrained modeling, to map the macroporosity and microporosity distribution of our samples. We evaluate the volumetric proportions of macropores, micropores, and coarse-grained calcite as a function of micrite content — with their respective uncertainties — all measured on the same digital rock and with the same method. Finally, we determine how measurements of the volumetric phase proportions could be extended using standard effective medium models to predict reservoir physical properties. The sensitivity of these models to the proportion of micrite and microporosity within the micrite is evidence that the nonuniqueness among permeability, velocity, and porosity that is commonly observed of micrite-bearing carbonate rocks can be explained by a variation of micrite content and microporosity at a similar porosity.

Accurate determination of the dielectric properties of porous rocks is important for the dielectric exploration methods in a range of applications from water resources to petroleum industry. Carefully controlled laboratory measurements offer the best way of obtaining the dielectric behaviors but they will require relatively large quantity of sample materials prepared in specific shapes, which is not always available. Numerical and theoretical simulations compensate for this weakness and can compute the dielectric dispersion at the pore-scale level on small fragments of rocks. However, whether consistent dielectric results can be obtained from the numerical computation and from the properly developed theoretical models still needs investigation. We introduced in this paper the numerical model based on the three-dimensional finite difference method (3D-FDM) and a range of theoretical models on basis of interfacial polarization for the calculation of the frequency dependent dielectric properties in porous rocks of complex geometry. The numerical and theoretical models were applied to a hypothetical porous rock with ideal shaped grains and to a real synthetic sandstone sample with complex pore and grain structure. Comparison of the simulation results from the two methods showed excellent agreement with each other with squared correlation coefficients better than R-2 = 0.98 for both relative permittivity and conductivity of the two example rocks. The consistent numerical and theoretical results provide a complementary way for the numerical and theoretical models to work together for a better simulation of the dielectric properties of porous rocks. (C) 2018 Elsevier B.V. All rights reserved.

Fractures are common features in virtually all types of geologic rocks and tend to dominate their mechanical and hydraulic properties. Detection and characterization of fractures in rocks are of interest to a variety of geophysical applications. We have investigated the frequency-dependent dielectric properties of fractured porous carbonate rocks in the frequency range [Formula: see text] and their relationships with different types of fluids filling the fractures, fracture connectivity, and directions of electrical field applied to the rocks using numerical simulation methods based on a 3D finite-difference model. We tested the validity of the modeling method on a spherical-shell model with the theoretical analytical solutions. The two fractures in the two digital carbonate rocks have the same length, but in one rock, they intersect and in the other sample they do not. The fractures in the brine-saturated digital rocks are filled either with oil or with the same brine as in the background rock. We found that although conductivity and relative permittivity are sensitive to the fracture-filling fluids, the dielectric loss factor is the best parameter discriminating the fluids. When filled with brine, the fracture connectivity does not affect the dielectric properties of the rocks. When filled with oil, the fracture connectivity can only be detected if the electrical field is parallel to the longer fracture orientation. The results provide new insights into the frequency-dependent dielectric responses of fractured sedimentary rocks and will help with the interpretation of the dielectric data acquired from rocks with fractures.

The effects of organic coating's structural characteristics such as the void structure on pipeline coating degradation under combined mechanical and environmental effects have been studied using the data-constrained modelling (DCM) technique with multi-energy X-ray computed tomography (X-ray CT), in conjunction with three dimensions (3D) finite element analysis (FEA) modelling that provides a qualitative interpretation of the DCM microstructure data in terms of the concentration of stress at heterogeneous interfaces within coatings. It has been found using the DCM technique that unstrained coating films are heterogeneous in nature, showing characteristic features similar to the D-type and I-type coating regions espoused in the historical literature. For strained coating films, the interfaces of heterogeneities were seen to provide preferential sites to form voids by mechanical straining. Moreover, the void network was also found at the interfaces of the inorganic fillers and the organic polymers. These have been corroborated by simulation carried out using the FEA modelling, with a 3D model indicating the role of fillers in the formation of a tortuous void network in a heterogeneous coating subjected to both mechanical straining and corrosive environment.

This article is a review of our recent development in data-constrained modelling (DCM) methodology for quantitative and sample-non-destructive (SND) characterization of 3D microscopic composition distribution in materials, and microstructure-based predictive modelling of material multiphysics properties. Potential impacts are illustrated with examples in a range of R&D disciplines.

Two X-ray computed tomography (CT) datasets have been acquired for a cold-sprayed titanium sample before and after heat treatment. The datasets were collected with a beam energy of 30 keV at the Australian Synchrotron. Three-dimensional (3D) distributions of porosity in the Ti sample were reconstructed using a data constrained modelling (DCM) technique. Quantitative analysis indicated that the heat treatment caused morphological changes to the pores and a small decrease in the overall porosity. After heat treatment, some fine porosity disappeared while the large porosity regions were essentially unaffected except for a change towards a more rounded pore shape. Interconnectivity between pores was reduced, which has implications for sealing and trapping of contaminant gases in cold-sprayed parts. The characterization technique and the workflow presented in the paper are applicable to non-destructive 3D characterization of other materials.