X-ray Micro-computed Tomography Imaging Research Articles

A New Validation Methodology for In Silico Tools Based on X-ray Computed Tomography Images of Tablets and a Performance Analysis of One Tool.

In silico tools which predict the dissolution of pharmaceutical dosage forms using virtual matrices can be validated with virtual matrices based on X-ray micro-computed tomography images of real pharmaceutical formulations. Final processed images of 3 different tablet batches were used to check the performance of the in silico tool F-CAD. The goal of this work was to prove the performance of the software by comparing the predicted dissolution profiles to the experimental ones and to check the feasibility and application of the validation concept for in silico tools. Both virtual matrices based on X-ray micro-computed tomography images and designed by the software itself were used. The resulting dissolution curves were compared regarding their similarity to the experimental curve. The kinetics were analysed with the Higuchi and Korsmeyers–Peppas plot. The whole validation concept as such was feasible and worked well. It was possible to identify prediction errors of the software F-CAD and issues with the virtual tablets designed within the software.

Determination of 3D pore network structure of freeze-dried maltodextrin

This article describes and discusses the determination of the pore network structure from X-ray microcomputed tomography images of freeze-dried maltodextrin based on image processing. Maltodextrin is used because of its relevance for research and pharmaceutical applications. Image processing is based on conventional methods for image filtering and binarization, which are specifically the Gaussian filter, anisotropic diffusion filter, and Otsu thresholding as well as adaptive thresholding. It is shown, that the combination of the different image processing methods has only a minor impact on the final results of the estimated porosity. More critical is the segmentation of the overall void space into individual pores using the watershed algorithm, especially if the markers of the Euclidean distance map are not accurately defined. Oversegmentation of the void space into too many small pores was obviated by the use of a Gaussian smoothing filter on the Euclidean distance map. The approximation of the structure by spherical or cylindrical geometrical objects was addressed in further discussions as an essential step for the determination of the mathematical pore network model. It was found that the choice of the specific geometrical object has a major impact on the final pore size distribution of the generated pore networks. For the case of maltodextrin, with long and narrow pores, the approximation by segmented cylinders, replacing the individual pore subvolumes, yields the best agreement. The computed pore network structures are further investigated in regard of the correlation of vapor transport regimes and structure variation. It is shown that the small differences obtained from the various combinations of image processing and network reconstruction methods have a negligible impact if temperature and pressure are low (T = −18 °C, P = 10 Pa) and constant.

Evaluation of different segmentation methods of X-ray micro computed tomography images

In silico tools for the prediction of disintegration and/or dissolution of tablets can be validated using adequate images of real pharmaceutical formulations. X-ray micro-computed tomography images of 12 different tablet batches prepared from binary mixtures of API and excipient were used. The goal of this work was to compare different segmentation methods to improve the results and processing time of an evaluation of pre-processing methods. The open source software ImageJ was utilised for the image processing. Different threshold algorithms were applied as well as different cluster numbers for the k-means clustering. The pathways were analysed regarding their desirability which was calculated from the recovery rates and their ratios. It was possible to identify suitable pathways for each single batch as well as for combinations of several batches. The recovery rates of the best pathways were always approximately 100%. It was possible to confirm the correctness of the image processing by visual perception. The image processing could be improved and sped up.

Exposure dating of detrital magnetite using <sup>3</sup>He enabled by microCT and calibration of the cosmogenic <sup>3</sup>He production rate in magnetite

Abstract. We test whether X-ray micro-computed tomography (microCT) imaging can be used as a tool for screening magnetite grains to improve the accuracy and precision of cosmogenic 3He exposure dating. We extracted detrital magnetite from a soil developed on a fanglomerate at Whitewater, California, which was offset by the Banning strand of the San Andreas Fault. This study shows that microCT screening can distinguish between inclusion-free magnetite and magnetite with fluid or common solid inclusions. Such inclusions can produce bulk 3He concentrations that are significantly in excess of the expected spallation production. We present Li concentrations, major and trace element analyses, and estimated magnetite (U–Th) / He cooling ages of samples in order to model the contribution from fissiogenic, nucleogenic, and cosmogenic thermal neutron production of 3He. We show that mineral inclusions in magnetite can produce 3He concentrations of up to 4 times that of the spallation component, leading to erroneous exposure ages. Therefore, grains with inclusions must be avoided in order to facilitate accurate and precise magnetite 3He exposure dating. Around 30 % of all grains were found to be without inclusions, as detectable by microCT, with the largest proportion of suitable grains in the grain size range of 400–800 µm. While grains with inclusions have 3He concentrations far in excess of the values expected from existing 10Be and 26Al data in quartz at the Whitewater site, magnetite grains without inclusions have concentrations close to the predicted depth profile. We measured 3He concentrations in aliquots without inclusions and corrected them for Li-produced components. By comparing these data to the known exposure age of 53.5 ± 2.2 ka, we calibrate a production rate for magnetite 3He at sea level and high latitude (SLHL) of 116 ± 13 at g−1 a−1. We suggest that this microCT screening approach can be used to improve the quality of cosmogenic 3He measurements of magnetite and other opaque mineral phases for exposure age and detrital studies.

A review of experimental and theoretical research on the deformation and failure behavior of rocks subjected to cyclic loading

Rock engineering is highly susceptible to cyclic loads resulting from earthquakes, quarrying or rockbursts. Acquiring the fatigue properties and failure mechanism of rocks is pivotal for long-term stability assessment of rock engineering structures. So far, significant progress has been gained on the mechanical characteristics of rocks subjected to cyclic loading. For providing a global insight of typical results and main features of rocks under cyclic loading conditions, this study comprehensively reviews the state-of-the-art of deformation and failure mechanism and fatigue constitutive relationship of rocks subjected to cyclic loading in the past 60 years. Firstly, cyclic tests on rocks are classified into different types based on loading paths, loading parameters, loading types and environment conditions. Secondly, representative results are summarized and highlighted in terms of the fatigue response of rocks, including the deformation degradation, energy dissipation, damage evolution and failure characteristics; both laboratory testing and numerical results are presented, and various measurement techniques such as X-ray micro-computed tomography (micro-CT) and digital image correlation (DIC) are considered. Thirdly, the influences of cyclic loads on the mechanical characteristics of rocks are discussed, including the cyclic stress, frequency, amplitude and waveform. Subsequently, constitutive relationships for rocks subjected to cyclic loading are outlined, in which typical fatigue constitutive models are compared and analyzed, regarding the elastoplastic model, the internal variable model, the energy-based damage model and the discrete element-based model. Finally, some ambiguous questions and prospective research are interpreted and discussed.

3D visualized characterization of radiation energy transport in a real semitransparent foam strut under high irradiation beam

A key challenge to model the heat transfer in refractory ceramic foams at high temperature is to characterize properly the transport of thermal radiation, especially when the foams are directly exposed to a high irradiation beam such as concentrated solar radiation. Characterization of the radiation transport in a single strut is representative and fundamental for the radiation transfer modelling of foams. This study numerically investigates the radiation transport and temperature response in a real foam strut under high irradiation beam. The digitalized strut was obtained by the X-ray micro-computed tomography imaging measurements, and then meshed within the strut volume and on the surface. The Discrete Ordinate Method is used to solve the Radiative Transfer Equation, since the strut material (alumina ceramic) is by nature semitransparent for incident radiation, resulting absorbing, scattering and emitting inside the solid phase. The volumetric propagation of radiation intensity is tracked and the absorbed radiation energy is recorded. Besides, the temperature response of the strut irradiated by a beam with periodic heat flux is investigated. The knowledge of radiation transport and temperature response in foam struts can provide fundamental information for understanding the pore-level heat transfer and for developing high-quality simulation and experiments.

Soil pore characteristics, morphology, and soil hydraulic conductivity following land subsidence caused by extraction of deep confined groundwater in Xi'an, China: Quantitative analysis based on X-ray micro-computed tomography

The extraction of deep confined groundwater has been widely identified as the main factor leading to land subsidence. However, how soil pore characteristics and morphology may change as a result of land subsidence remains unclear. The objective of this study was to (1) quantify and compare the effects of soil compression due to deep confined aquifer exploitation on soil pore characteristics and morphology and (2) assess the relationships between pore parameters and saturated hydraulic conductivity (Ksat). Three kinds of lithology (clay, silt, and silty clay soils) from two 300-m engineering geological boreholes were investigated at natural saturated state (NSS) and complete drainage state (CDS). Seventeen undisturbed soil samples, 70 and 50-mm in diameter and height, respectively, were collected and subjected to steps of uniformly increasing loads in uniaxial confined compression tests to analyze pore characteristics, morphology, and Ksat. Keeping the samples in a strain-locked state, pore parameters were assessed after each loading step by using X-ray micro-computed tomography (CT; voxel resolution: 3-μm) images. A hundred CT images were acquired and quantified for each treatment in each soil sample. Soil pore characteristics and morphological parameters including number of pores, number of macropores (diameter (∅) > 1000-μm), number of coarse mesopores (∅ 200–1000-μm), number of fine mesopores (∅ < 200-μm), porosity, macroporosity, coarse mesoporosity, fine mesoporosity, largest pore area, average pore diameter, shape factor, structure model index, degree of anisotropy, and the Euler number were analyzed using ImageJ software. All parameters differed between NSS and CDS treatments, especially in silt and silty clay soils below 100-m depth, and the differences seemed to increase with increasing depth. However, parameter variations were not obvious for clay soil. Furthermore, Ksat differed significantly between treatments. The largest pore area, average pore diameter, and regular porosity accounted for 78.2 % of the change in Ksat. Thus, the decrease in proportion of elongated macropores favors land subsidence, particularly in silt and silty clay soils below 100-m depth. Efforts such as optimization of groundwater exploitation depth should be made to alleviate and control land subsidence.

A casting method using contrast-enhanced diethylphthalate for micro-computed tomography of snow

AbstractCasting snow is necessary to prevent metamorphism and deformation prior to X-ray micro-computed tomography (μCT) imaging. Current methods are insufficient for large-scale field sampling of snow due to safety considerations associated with the casting medium and/or lengthy sample preparation times. Here, a casting method using contrast-enhanced diethylphthalate (DEP) for μCT of snow is presented. The X-ray contrast of DEP is enhanced with barium titanate nanoparticles (BaTiO3) and iodine (I2). A partially unsupervised, three-phase segmentation method utilizing traditional Gaussian smoothing followed by a three-step process to address transition voxels is also presented. Synthetic images derived from real snow samples are used to evaluate the segmentation method with various configurations of trapped air bubbles. Real snow samples spanning a range of specific surface areas (SSAs) (8–28 m2kg−1) and densities (135–463 kg m−3) are used to assess the performance of the segmentation method on real, cast samples. The method yields SSA, density and correlation length errors of less than 10% for synthetic images with air bubble surface areas less than 333 m−1per sample volume for eight of the nine snow samples. For eight of the nine cast samples, the method yields errors of less than 10% for all three parameters.

Pore-Scale Grain-Binding Cement Dissolution in Sandstone Rocks and its Effect on CO2 Injectivity

CO2 geological storage in depleted oil and gas reservoirs and saline aquifers is currently one of the most economical methods to mitigate CO2 emissions, mainly because of available geological data from oil and gas exploration and production in the last decades as well as abandoned wellbore facilities. Four main factors dictate the safe and economical CO2 storage and selection of a suitable storage site: while wellbore and cap rock integrity are critical to the security of stored CO2, storage capacity and CO2 injectivity are among the main factors driving the cost of storage per ton of CO2. Low or reduced CO2 injectivity at injection wellbore can significantly increase the compression costs of the project. In worst-case scenarios, a blockage can increase injection pressures above rock fracture pressure, thus critically jeopardising further injection in the same well. The global abundance, high storage capacity and potentially low chemical reactivity of sandstone reservoirs make them great candidates for CO2 geological storage sites. The matrix of siliciclastic rocks is mainly made of quartz grains, and there is negligible chemical reactivity in contact with carbonic acid formed during the injection. However, the most common cementing agents in these rocks (e.g. calcite, dolomite and, to some extent, clays) react with carbonic acid. These reactions lead to mechanisms like cement dissolution, mineral deposition, and sand fine migration (sand mobilisation). Depending on the volumetric percentage of the binding cement, its geometrical distribution within the matrix and pore (and throat) size distribution of the rock, fine migration and binding cement dissolution can enhance or impair CO2 injectivity [1,2]. Despite numerous studies regarding the effect of CO2 injection on fine migration and injectivity, there is still no consensus regarding the impact of intergranular cement dissolution on CO2 injectivity. In this study, we have focused on the effect of binding cement dissolution on pore morphology in a typical sandstone (Berea) and demonstrating how the observations of CO2 injectivity change at the core scale alone could be misleading and explain some apparent discrepancies reported in the literature. We cut three slices of this core for X-ray micro-computed tomography (MicroCT) imaging. The first slice was cut from the original clean core. After performing a coreflood experiment with carbonated water through the rest of the core, two other pieces were cut from the inlet and outlet of the core. To represent the extreme dissolution conditions (lowest pH) during CO2 injection, a batch of North Sea brine fully saturated with CO2 was prepared and injected through the core at typical reservoir conditions (50°C and 2.6×107 Pa). Three 3D models are reconstructed from images of the prepared rock slices to represent the pore structure of the rock before injection and the inlet and outlet of the core subjected to CW injection. Avizo (a commercial software) is used to calculate the permeability and velocity fields in these models. The comparison of results from micro-CT imaging and the coreflood experiment shows how single-scale studies (either core or pore-scale) of CO2 injectivity can lead to a misleading conclusion about the effect of fine migration on permeability at larger scales.

Convolutional neural networks for estimating transport parameters of fibrous materials based on micro-computerized tomography images.

This study proposes a method for estimating the transport parameters of fibrous materials from x-ray micro-computed tomography (CT) images using convolutional neural networks (CNNs). Two-dimensional (2-D) micro-CT images and numerically obtained transport parameters were used to train the CNNs; Stokes flow and potential flow were used to numerically obtain the transport parameters using geometrical models extracted from the raw CT images. Then, analogously to constructing a three-dimensional image of the fibrous material by stacking the 2-D slice images, the volumetric transport parameters of the fibrous materials were calculated using the parameters of each 2-D image predicted by the trained CNN models. The transport parameters of the fibrous volume predicted by the CNN models showed good agreement with the measured values. In addition, the sound absorption coefficient was calculated by applying both the predicted and measured transport parameters to the semi-phenomenological sound propagation model and compared with the measured sound absorption coefficient. The results of the study confirm the feasibility of predicting transport parameters of fibrous materials using a neural network model based on raw micro-CT images.

Study on the Permeability Characteristics of Foamed Concrete Using a Pore-Scale Model from X-Ray Microcomputed Tomography Image Reconstruction and Numerical Simulation

Foamed concrete has attracted increasing attention in civil engineering due to its unique properties. Permeability is one of the significant material properties that governs its long-term durability. This work presents a method to explore the permeability characteristics of foamed concrete based on X-ray microcomputed tomography (micro-CT) image reconstruction technique and Simpleware version M-2017.06 software. The pressure and water flow distributions in foamed concrete were obtained, and the permeability of the foamed concrete with different densities was calculated. The numerical simulation results showed that the proposed method can be used to predict the permeability of foamed concrete. The main factors that affect the permeability of foamed concrete are discussed. A power law model is established to reveal the relationship between the porosity and permeability of the foamed concrete, and the connectivity of pores was labeled to explain why the permeability of three different location calculation models are not the same under the same density conditions. Furthermore, the influence of boundary conditions on the calculation results of the permeability was analyzed, and a comparison of the 2D and 3D results were carried out to determine whether it is necessary to reconstruct the 2D CT images into 3D pore-scale physical models.

Machine and deep learning for estimating the permeability of complex carbonate rock from X-ray micro-computed tomography

Accurate estimation of permeability is critical for oil and gas reservoir development and management, as it controls production rate. After assessing numerical techniques ranging from pore network modeling (PNM) to the lattice Boltzmann method (LBM), an AI-based workflow is developed for a quick and accurate estimation of the permeability of a complex carbonate rock from its X-ray micro-computed tomography (micro-CT) image. Following features engineering using both image processing and PNM, we trained and tested the workflow on thousands of segmented 3D micro-CT images using both shallow and deep learning algorithms to assess the permeability. A broad variety of supervised learning algorithms are implemented and tested, including linear regression, support vector regression, improved gradient boosting, and convolutional neural networks. Additionally, we explored a hybrid physics-driven neural network that takes into account both the X-ray micro-CT images and petrophysical properties. Finally, we found that the predicted permeability of a complex carbonate by machine learning (ML) agrees very well with that of a more computationally-intensive voxel-based direct simulation. In addition, the ML model developed here provides a substantial reduction in computation time by roughly three orders of magnitude compared to that of the LBM. This paper highlights the crucial role played by features engineering in predicting petrophysical properties by machine and deep learning. The proposed framework, integrating diverse learning algorithms, rock imaging, and modeling, has the potential to quickly and accurately estimate petrophysical properties to aid in reservoir simulation and characterization.

Energy savings, thermal conductivity, micro and macro structural analysis of fired clay bricks incorporating cigarette butts

In this study, lightweight structural bricks incorporating various percentages of cigarette butts (CBs) are produced to investigate the thermal properties, energy savings, porosity and micro- and macro-structure. A novel method was developed to monitor the energy consumption of the furnace during the firing process, and Scanning Electron Microscopy (SEM) and X-ray micro-Computed Tomography (micro-CT) imaging were used to characterize the quantity, distribution, size, and shape of the micro- and macro-scale pores of the brick samples incorporating CBs. The energy savings of the microporous bricks with 1% CBs by weight (wt.) varied between 8% (theoretical value) and 10.2% (measured value). Clay bricks showed an increase in porosity and a decrease in density with the increase in CB content, which reduced thermal conductivity. Thermal conductivity was measured to reduce from 0.463 to 0.347 W m−1 K−1 with the addition of 2% CBs by wt. compared to the control bricks. The 3D models of the bricks incorporating various percentages of CBs demonstrated a homogenous distribution of pores within the brick structures. On a micrometer scale, the size of the micro- and macro- pores varied within a range of 0.035 to 1.365 mm.

A Computational Fluid Dynamics Investigation of Pneumatic Atomization, Aerosol Transport, and Deposition in Aerosol Jet Printing Process

AbstractAerosol jet printing (AJP) is a direct-write additive manufacturing technique, which has emerged as a high-resolution method for the fabrication of a broad spectrum of electronic devices. Despite the advantages and critical applications of AJP in the printed-electronics industry, AJP process is intrinsically unstable, complex, and prone to unexpected gradual drifts, which adversely affect the morphology and consequently the functional performance of a printed electronic device. Therefore, in situ process monitoring and control in AJP is an inevitable need. In this respect, in addition to experimental characterization of the AJP process, physical models would be required to explain the underlying aerodynamic phenomena in AJP. The goal of this research work is to establish a physics-based computational platform for prediction of aerosol flow regimes and ultimately, physics-driven control of the AJP process. In pursuit of this goal, the objective is to forward a three-dimensional (3D) compressible, turbulent, multiphase computational fluid dynamics (CFD) model to investigate the aerodynamics behind: (i) aerosol generation, (ii) aerosol transport, and (iii) aerosol deposition on a moving free surface in the AJP process. The complex geometries of the deposition head as well as the pneumatic atomizer were modeled in the ansys-fluent environment, based on patented designs in addition to accurate measurements, obtained from 3D X-ray micro-computed tomography (μ-CT) imaging. The entire volume of the constructed geometries was subsequently meshed using a mixture of smooth and soft quadrilateral elements, with consideration of layers of inflation to obtain an accurate solution near the walls. A combined approach, based on the density-based and pressure-based Navier–Stokes formation, was adopted to obtain steady-state solutions and to bring the conservation imbalances below a specified linearization tolerance (i.e., 10−6). Turbulence was modeled using the realizable k-ε viscous model with scalable wall functions. A coupled two-phase flow model was, in addition, set up to track a large number of injected particles. The boundary conditions of the CFD model were defined based on experimental sensor data, recorded from the AJP control system. The accuracy of the model was validated using a factorial experiment, composed of AJ-deposition of a silver nanoparticle ink on a polyimide substrate. The outcomes of this study pave the way for the implementation of physics-driven in situ monitoring and control of AJP.

Xylem network connectivity and embolism spread in grapevine(Vitis vinifera L.).

Xylem networks are vulnerable to the formation and spread of gas embolisms that reduce water transport. Embolisms spread through interconduit pits, but the three-dimensional (3D) complexity and scale of xylem networks means that the functional implications of intervessel connections are not well understood. Here, xylem networks of grapevine (Vitis vinifera L.) were reconstructed from 3D high-resolution X-ray micro-computed tomography (microCT) images. Xylem network performance was then modeled to simulate loss of hydraulic conductivity under increasingly negative xylem sap pressure simulating drought stress conditions. We also considered the sensitivity of xylem network performance to changes in key network parameters. We found that the mean pit area per intervessel connection was constant across 10 networks from three, 1.5-m stem segments, but short (0.5 cm) segments fail to capture complete network connectivity. Simulations showed that network organization imparted additional resistance to embolism spread beyond the air-seeding threshold of pit membranes. Xylem network vulnerability to embolism spread was most sensitive to variation in the number and location of vessels that were initially embolized and pit membrane vulnerability. Our results show that xylem network organization can increase stem resistance to embolism spread by 40% (0.66 MPa) and challenge the notion that a single embolism can spread rapidly throughout an entire xylem network.

Tailoring asymmetric Al2O3 membranes by combining tape casting and phase inversion

This study aimed to combine the techniques of tape casting and phase inversion to produce highly permeable ceramic membranes suitable for microfiltration in a single sintering step. The morphological, mechanical and textural characterization was performed using SEM, flexural strength measurement, mercury porosimetry and X-ray micro-computed tomography. Alumina membranes were produced using different slurry formulations and solidified via phase inversion, followed by sintering at 1400 or 1500 °C. Additionally, a co-casting strategy was successfully used for some membranes aiming to reduce the flux resistance caused by the dense layer usually formed at the bottom of ceramic membranes produced by phase inversion while the thin skin layer is preserved. Ceramic membranes with large pore sizes of the skin layer (0.30–0.42 μm) and high total porosity (46–75%) were obtained, and a clear increase of the mechanical resistance is observed when increasing alumina loading. Pure water flux of 52.4 and 26.60 m3 m-2 h-1 at 1 bar, and 27.60 and 41.11 MPa maximum flexural strength were achieved for membranes produced from slurries containing 45 and 50 wt% alumina, respectively. Simulations of permeability carried out from X-ray micro-computed tomography images in three axes proved a preferential fluid flow in the z-axis (from top to bottom) for different membrane regions and demonstrated that permeability is mainly influenced by the top skin and bottom layer morphology, which is in agreement with the experimental results.

Topological Estimation of 2D Image Data via Subsampling and Application to Firn

We develop a novel statistical approach to estimate topological information from large, noisy images. Our main motivation is to measure pore microstructure in 2-dimensional X-ray micro-computed tomography (micro-CT) images of ice cores at different depths. The pore space in these samples is where gas can move and get trapped within the ice column and is of interest to climate scientists. While the field of topological data analysis offers tools (e.g. lifespan cutoff and PD Thresholding) for estimating topological information in noisy images, direct application of these techniques to large images often leads to inaccuracies and proves infeasible as image size and noise levels grow. Our approach uses image subsampling to estimate the number of holes of a prescribed size range in a computationally feasible manner. In applications where holes naturally have a known size range on a smaller scale than the full image, this approach offers a means of estimating Betti numbers, or global counts of holes of various dimensions, via subsampling of the image.

Coordination numbers in natural beach sand

Coordination number controls elastic moduli, seismic velocity, and force transmission in sands and is thus a critical factor controlling the resistance of sands to deformation. Previous studies quantified relationships between coordination number, porosity, grain size, sphericity, and effective stress in pluviated or modeled sands. Here, we determine if these relationships hold in naturally-deposited beach sands. We collect samples while preserving their microstructures and use x-ray computed microtomography images to characterize grain properties. Similar to pluviated and modeled sand studies, we find that average coordination numbers and porosities for freshly deposited natural sands are 8.1 ± 2.8 and 0.37 ± 0.01, respectively. The range and standard deviation in coordination numbers of the natural beach sands are, however, significantly higher than observed in pluviated and modeled sand studies. At the same effective stress and porosities, coordination number is linearly proportional to grain surface area except for the smallest and largest grains. Coordination number depends non-linearly on sphericity. We attribute the higher ranges and standard deviations of coordination numbers in the natural sands to its broader grain size distribution, and we propose that the largest grains limit grain rearrangement, which influences spatial distributions of coordination numbers in natural sands.

Shear fracture of longitudinally reinforced concrete beams under bending using Digital Image Correlation and FE simulations with concrete micro-structure based on X-ray micro-computed tomography images

The paper presents experimental and numerical investigations of the shear fracture in rectangular concrete beams longitudinally reinforced with steel or basalt bar under quasi-static three point bending. Shear fracture process zone formation and development on the surface of beams was investigated by Digital Image Correlation (DIC) whereas thorough analyses of 3D material micro-structure, air voids, width and curvature of shear cracking were carried out by X-ray micro-computed tomography (micro-CT). Moreover, the 2D shear fracture patterns in beams were numerically simulated with the finite element method (FEM) using isotropic coupled elasto-plastic-damage constitutive model for concrete enhanced by a characteristic length of micro-structure. Concrete meso-structure was modelled as a random heterogeneous four-phase material composed of aggregate particles, cement matrix, ITZ zones and air voids on the basis of X-ray micro-CT images. Experimental and numerical results revealed a satisfactory agreement regarding to the mechanism of failure, load-bearing capacity as well as cracking pattern.

Development of Neonectria punicea Pathogenic Symptoms in Juvenile Fraxinus excelsior Trees.

When monitoring the state of health of Fraxinus excelsior trees, unusual symptoms were discovered within a F. excelsior plantation in Bosnia and Herzegovina. These symptoms included the appearance of necrosis and cankers in the basal parts of the trees, followed by the formation of fruiting bodies, however, none of these symptoms were found in the crowns. After sampling and isolation of the necrotic parts from the stem base, pathogen Neonectria punicea was isolated and identified from the characteristics of pure cultures, morphology of the fruiting bodies, and from multilocus sequencing. In field conditions, juvenile F. excelsior trees were inoculated with two N. punicea isolates obtained from the necrotic tissues of both juvenile F. excelsior and mature Fagus sylvatica trees. In both isolates, 12 months post inoculation, the lengths and widths of the necroses were significantly larger compared to the control. Necroses of significantly larger lengths, widths and surfaces were found again in both tested isolates 24 months post inoculation. In the case of the F. excelsior isolate, the lengths of the necroses at both the stem base and at breast height increased by 1.6 times, whereas the F. sylvatica isolate increased in size by up to 1.7 and 1.8 times, respectively. Trees inoculated without a previous bark wound showed no symptoms, similar to the control trees. Scanning electron microscopy and X-ray micro-computed tomography imaging revealed that N. punicea hyphae penetrated from the cankers to the woody outermost annual growth ring and that hyphae were present mostly in the large earlywood vessels and rarely in the axial parenchyma cells. Hyphae also spread radially through the pits in vessels. The infected trees responded with the formation of tyloses in the vessels to prevent a rapid fungal spread through the axial vascular transport pathway. The ability of N. punicea to cause necroses in juvenile ash trees was demonstrated for the first time during this study. It poses a serious threat to planted forests and natural regenerations of F. excelsior especially if F. sylvatica is considered as a possible inoculum reservoir for future infections. This pathogen should be integrated within future ash resistance or breeding programs.