X-ray Computed Tomography Imaging Research Articles

Defect detectability assessment of notches in a self-piercing rivet using X-ray computed tomography

One challenge of using X-ray computed tomography (CT) is the detection limit of the smallest feature. This is important for self-piercing riveting joints because it sets a limit on the defect size that is detectable with the technology. To address this challenge, defined size notches were generated on the surface of the rivet leg using a focused-ion beam. Five different X-ray CT parameters: distance between the X-ray source, integration time, number of integrations, number of projected images and X-ray CT voltage, were investigated. The area of the notches was measured from the X-ray CT images, which was converted into probability of detection responses. The results show that the most significant parameter is the voxel size determined by the distance between the X-ray CT source and the sample. At shorter distances, the X-ray CT can capture more detail about the defects. This factor also drives the accuracy of the area evaluation and the detected shape of the notches. In addition, the increase in scan duration can be used to further enhance the defect detectability and measurement accuracy of the X-ray CT. It was found that the smallest defects that were able to be detected were 2–4 times the voxel size whilst for the defects to be accurately measured they need to be 3–5 times the voxel size.

A Fast Object Detection-Based Framework for Via Modeling on PCB X-Ray CT Images

For successful printed circuit board (PCB) reverse engineering (RE), the resulting device must retain the physical characteristics and functionality of the original. Although the applications of RE are within the discretion of the executing party, establishing a viable, non-destructive framework for analysis is vital for any stakeholder in the PCB industry. A widely regarded approach in PCB RE uses non-destructive x-ray computed tomography (CT) to produce three-dimensional volumes with several slices of data corresponding to multi-layered PCBs. However, the noise sources specific to x-ray CT and variability from designers hampers the thorough acquisition of features necessary for successful RE. This article investigates a deep learning approach as a successor to the current state-of-the-art for detecting vias on PCB x-ray CT images; vias are a key building block of PCB designs. During RE, vias offer an understanding of the PCB’s electrical connections across multiple layers. Our method is an improvement on an earlier iteration which demonstrates significantly faster runtime with quality of results comparable to or better than the current state-of-the-art, unsupervised iterative Hough-based method. Compared with the Hough-based method, the current framework is 4.5 times faster for the discrete image scenario and 24.1 times faster for the volumetric image scenario. The upgrades to the prior deep learning version include faster feature-based detection for real-world usability and adaptive post-processing methods to improve the quality of detections.

Evaluation of Flaw Detection Algorithm Using Simulated X-Ray Computed Tomography of Ground Truth Data

Abstract A framework to generate simulated X-ray computed tomography (XCT) data of ground truth (denoted here as “GT”) flaws was developed for the evaluation of flaw detection algorithms using image comparison metrics. The flaws mimic some of those found in additively manufactured parts. The simulated flaw structure gave a GT data set with which to quantitatively evaluate, by calculating exact errors, the results of flaw detection algorithms applied to simulated XCT images. The simulated data avoided time-consuming manual voxel labeling steps needed for many physical data sets to generate GT images. The voxelated pore meshes that exactly match GT images were used in this study as opposed to using continuum pore meshes. The voxelated pore mesh approach avoids approximation error that occurs when converting continuum pore meshes to voxelated GT images. Spherical pores of varying sizes were randomly distributed near the surface and interior of a cylindrical part. XCT simulation was carried out on the structure at three different signal-to-noise levels by changing the number of frames integrated for each projection. Two different local thresholding algorithms (a commercial code and the Bernsen method) and a global thresholding algorithm (Otsu) were used to segment images using varying sets of algorithm parameters. The segmentation results were evaluated with various image evaluation metrics, which showed different behaviors for the three algorithms regarding “closeness” to the GT data. An approach to optimize the thresholding parameters was demonstrated for the commercial flaw detection algorithm based on semantic evaluation metrics. A framework to evaluate pore sizing error and binary probability of detection was further demonstrated to compare the optimization results.

Estimating the permeability of soils under different tillage practices and cropping systems: Roles of the three percolating pore radii derived from X-ray CT

Soil permeability associated with pore characteristics is a critical factor affecting water and nutrient transport in agricultural fields. However, which soil pore characteristics determine soil permeability remains inconclusive due to high heterogeneity of soil pore structure affected by soil and crop management practices. The objective of this study was to compare the pore characteristics of soils under various field management and assess the performance of different pore radii in estimating soil permeability. In this study, we utilized X-ray computed tomography (XCT) to quantify the pore characteristics of soil cores from three treatments: no-tillage under continuous maize cropping (NT-MM), no-tillage under continuous soybean cropping (NT-SS) and conventional tillage under continuous maize cropping (CT-MM). Subsequently, we calculated the permeability with pore-scale numerical simulations directly based on XCT images. Our results revealed that compared to the NT-MM treatment, the NT-SS and CT-MM treatments significantly increased soil porosity of > 200 µm pore classes (soil depths of 2–8 cm and 2–14 cm), as well as pore compactness, specific surface area, fractal dimension, and global connectivity. Among the three XCT-derived pore radii, the critical pore radius (CR) exhibited excellent performance in estimating permeability for samples from the NT-SS and CT-MM treatments, surpassing the hydraulic radius (HR) and mean pore radius of the limiting layer (MRLL). For samples from the NT-MM treatment, the CR and MRLL had similar estimation capabilities (R2 = 0.429, P = 0.110), but both were not as good as the HR (R2 = 0.539, P = 0.060). Furthermore, when estimating the permeability of all the aforementioned soil samples, the CR demonstrated the best estimation performance (R2 = 0.838, P < 0.001). In conclusion, utilizing CR as a predictor for estimating permeability in naturally structured soils is a good choice, which provides valuable insights into improving the accuracy of estimating soil permeability.

Tree Core Analysis with X-ray Computed Tomography.

An X-ray computed tomography (CT) toolchain is presented to obtain tree-ring width (TRW), maximum latewood density (MXD), other density parameters, and quantitative wood anatomy (QWA) data without the need for labor-intensive surface treatment or any physical sample preparation. The focus here is on increment cores and scanning procedures at resolutions ranging from 60 µm down to 4 µm. Three scales are defined at which wood should be looked at: (i) inter-ring scale, (ii) ring scale, i.e., tree-ring analysis and densitometry scale, as well as (iii) anatomical scale, the latter approaching the conventional thin-section quality. Custom-designed sample holders for each of these scales enable high-throughput scanning of multiple increment cores. A series of software routines were specifically developed to efficiently treat three-dimensional X-ray CT images of the tree cores for TRW and densitometry. This work briefly explains the basic principles of CT, which are needed for a proper understanding of the protocol. The protocol is presented for some known species that are commonly used in dendrochronology. The combination of rough density estimates, TRW and MXD data, as well as quantitative anatomy data, allows us to broaden and deepen current analyses for climate reconstructions or tree response, as well as further develop the field of dendroecology/climatology and archeology.

Core analysis in a changing world – how technology is radically benefiting the methodology to acquire, the ability to visualize and the ultimate value of core data

Abstract Core analysts principally study the storage, flow and saturation properties of porous rocks and sediments. Some of the derived parameters are specific to hydrocarbon production but many have commonality with other subsurface disciplines such as hydrology and soil science. Traditional core analysis involves direct physical experimentation on core plugs to derive a range of parameters used as calibration for conventional well logs, and to predict hydrocarbon reserves and recovery. The mechanisms and processes for obtaining such data have evolved significantly during the last century, from the manual instruments of the mid-twentieth century to the accredited digital data collection and recording of the 1990s onwards. X-ray micro- and nano-scale computed tomography (CT) imaging led to the development of the digital rock physics subdiscipline in the early 2000s. This has subsequently allowed direct visualization of fluid flow at the pore scale, imaging the wetting phase and multiphase fluid mobility. Multiscale imaging workflows are being developed to overcome issues around heterogeneous rock and the limited field of view associated with the highest resolution X-ray CT images. Hybrid workflows, which combine digital rock physics with traditional core analysis, are becoming increasingly common to meet the challenges associated with some of the most difficult to constrain properties, such as relative permeability. At a larger scale, the recent development of multisensor core logging (MSCL) tools has allowed the cost-effective acquisition of essentially continuous high-resolution 1D, 2D and 3D datasets from both slabbed and unslabbed whole core. Often aided by artificial intelligence to manage and interpret these large physical and chemical datasets, both new and legacy core can be rapidly screened to allow representative subsampling for detailed laboratory experimentation. The context and data provided by the MSCL then allows effective upscaling of these time- and cost-intensive point-source measurements. In the last decade, extended reality (XR) has resulted in a step change in the ability to visualize and integrate core and core-derived information with other subsurface datasets. A very wide range of scales can be managed effectively, from micrometre- to centimetre-scale petrographical and core analysis data, to metre-scale well logs and up to kilometre-scale 3D and 4D seismic. These tools allow stakeholders to work and meet from any location in a common workspace, and efficiently scale and interrogate data in a virtual 3D environment. The various advances in core analysis and associated technologies during the early twenty-first century mean that the study of porous media to help enable the energy transition looks assured. During the coming decades, applications as diverse as carbon capture, utilization and storage (CCUS), hydrogen storage, geothermal energy generation, mining for critical minerals, palaeoclimate studies, radioactive waste management, and site surveys for windfarms will all continue to benefit from the data and understanding derived from core analysis.

The use of non-invasive imaging modalities for the assessment of skeletal muscle quantity and quality in people with HIV: A narrative review.

People with HIV (PWH) are prone to mobility impairments and physical dysfunction, with the loss of skeletal muscle quantity and quality being a major contributor to the dysfunction. Assessment of skeletal muscle is an important component of care for this patient population for early intervention and treatment. The use of non-invasive imaging techniques to evaluate skeletal muscle, such as dual X-ray absorptiometry, computer tomography and magnetic resonance imaging, has increased in popularity in recent years. This narrative review synthesizes the use of these techniques and summarizes the associations between outcomes from these imaging modalities and physical function in PWH.

Phase segmentation in X-ray CT images of concrete with implications for mesoscale modeling

X-ray computed tomography (XRCT) is a valuable tool for characterizing the microstructure of concrete and for developing 3D mesoscale numerical models directly from experimental data. However, the results of imaging and subsequent modeling are reliable only if individual phases can be identified and segmented accurately. Siliceous aggregates and cement paste are difficult to separate in XRCT images because of their similar X-ray attenuation coefficients. This work examines the quality of aggregate phase segmentation in XRCT images using (1) a standard deviation thresholding approach and (2) a random forest classification. Both approaches were validated with ground truth data for concrete samples with different aggregate volume fractions. Our findings show that either approach may successfully be used to segment aggregate phases if appropriate post-processing is performed. However, our results emphasize the critical need to preserve both aggregate size and shape during post-processing as illustrated through mesoscale modeling.

Using Multiscale Direct Simulation Approach to Understanding Transports Behavior Inside PEM Water Electrolyzer

In this work, numerical modeling techniques were developed to predict oxygen bubble evolution through complex pore geometries to provide information of gas transport pathways inside saturated porous transport layers (PTL). Each PTL undergoes an image processing technique that uses X-ray CT images to generate accurate 3D microstructures. An example of a generated PTL structure is shown in Figure 1.Historically, meshing of the complex geometry was tedious and non-automated. Due to the random particle size across the geometry, a constant base size for meshing resulted in an inadequate mesh for accurate predictions. The Lattice-Boltzmann method is therefore more commonly used because a lattice is easier than a finite volume mesh to generate. Although sufficiently fine lattices adhered to the topology of the physical structure, simulations required a timestep between 1e-8 and 1e-10 seconds, resulting in long computational time.Meshing techniques have improved and can now be applied to complex geometries. Using the finite volume method accompanied with an adaptive mesh and adaptive time scale, provides an accurate representation of the PTL structure and larger timesteps. A volume of fluid (VoF) method was used to model two phase flow, using liquid water and gaseous oxygen, through different PTL structures. Evolution, growth, size, velocity, and surface interaction of oxygen bubbles through microstructures were studied as also shown in Figure 2. Findings from the work will provide better understanding of oxygen evolution through saturated PTLs Figure 1

Operando X-Ray CT Analysis of Composite Electrode in All-Solid-State Battery Using Silicon Anode

As a next-generation rechargeable battery, all-solid-state battery is expected for used in practical applications, in which electrolyte solution of the current lithium-ion battery is replaced with a solid electrolyte. To further increase the capacity of all-solid-state batteries, silicon is used as the anode active material forming an alloy with lithium. However, in the charge and discharge reaction using silicon anode, poor cycle capability due to the volume change of the silicon alloying reaction has been known. Many reports are limited to the analysis of the volume change of the whole electrode, and there are few reports on the quantitative analysis of the volume change of the silicon active material itself. In this study, X-ray computed tomography (X-ray CT) was used to analyze the expansion and contraction of silicon-active materials in all-solid-state battery. X-ray CT analysis can provide the contacted state information between electrode active materials and solid electrolytes [1]. By operando X-ray CT analysis, the expansion and contraction behavior of silicon particles during charging and discharging on the electrode was studied.Nb-coated LiNi1/3Co1/3Mn1/3O2(NCM), Li10GeP2S12(LGPS), acetylene black (AB) mixed at a weight ratio of 1:1:0.2 were used as the cathode composite. Silicon, LGPS, AB mixed at a weight ratio of 1:1:0.1 were used as the anode composite. All-solid-state battery, Si | LGPS | NCM was assembled in a cylinder with an inner diameter 1 mm. The cell was brought into SPring-8 BL20XU beamline, and the operando X-ray CT measurement was carried out. From the obtained X-ray CT images, the three-dimensional analysis of silicon particles was performed.Mean expansion coefficients of silicon‐particles traced during charging and discharging were calculated. The expansion of silicon particles by charging (lithiation) and the contraction of silicon particles by discharging (delithiation) are confirmed. Furthermore, the volume expansion rate of the silicon particles after the charging is average exceeded 300%. After discharge, silicon shrinkage is observed with delithiation, but the solid electrolyte cannot follow the volume change, and the silicon/solid electrolyte interface is broken. However, the contact is not completely failed, maintaining the partial contact between silicon and the electrolyte.[1] Y. Sakka, H. Yamashige, A. Watanabe, A. Takeuchi, M. Uesugi, K. Uesugi and Y. Orikasa, J. Mater. Chem. A, 10 16602–16609 (2022).Acknowledgement: This work was partially supported by the New Energy and Industrial Technology Development Organization (NEDO), JPNP20004.

Prediction of dispersion and attenuation on elastic wave velocities in partially saturated rock based on the fluid distribution obtained from three-dimensional (3D) micro-CT images

Elastic wave attenuation in partially saturated porous rock is primarily due to wave-induced fluid flow, which arises from the contrast in compressibility between air and water and is influenced by the water distribution within the rock. We propose a method for constructing a numerical model that predicts mesoscopic dispersion and attenuation. Initially, we use fluid distribution data sourced from 3D X-ray Computed Tomography images to construct the numerical model, utilizing Biot’s poroelastic equations as the governing equations. Subsequently, we implement the finite element method to derive solutions for the numerical model. Our focus is centered on two key challenges: 1) reducing memory cost, and 2) efficiently handling element intersection during the meshing process. The solutions illustrate the evolution of fluid pressure distribution and the frequency-dependent advancement of the elastic moduli, coupled with their corresponding attenuation. Ultimately, we compare these numerical predictions with previously published experimental data from a study on partially saturated Indiana limestone. The considerable agreement between our numerical results and the experimental data confirms the validity of our method, which crucially incorporates the actual fluid distribution (captured from 3D CT images) as a vital input.

Deep learning interprets failure process of coal reservoir during CO2-desorption by 3D reconstruction techniques

This work aims to investigate the failure and mechanical behaviors of coal rocks during CO2-desorption. The unconfined and confined compression experiments with certain depletion pressure-stress path and desorption of CO2 are conducted, in which the cracking process is captured by X-ray CT imaging. A deep learning-based coal fine-crack segmentation (CFCS) network with 3D reconstruction technique is proposed to study the cracking behaviors. In addition, the CO2 evolution effects on the failure process and mechanical responses are also analyzed. Results show that the proposed CFCS can effectively segment the crack-CO2-soid structure in coal with the errors all less than 10% at the range of 3.5620%–9.9967%. The failure process of coal samples can be divided into the extremely fast CO2-desorption + microcracks formation stage, fast CO2-desorption + stable microcracks propagation stage and slow stable CO2-desorption + microcracks coalescence to form macrocracks stage. The shear failures of coal samples are caused by the reduction of lateral effective stress due to CO2-desorption and drainage, which increases the anisotropy of coal samples with microcracking behaviors. The proposed method provides better understanding of failure mechanism and mechanical responses of coal reservoirs, which are helpful for the CO2 storage-based resource explorations.

A New Experimental Technique to Investigate the Load-Bearing Mechanisms of Smeared Rock-Socketed Piles Using In Situ X-ray CT Imaging

Abstract The design of rock-socketed piles at the serviceability state primarily depends on the shaft resistance (skin friction) at the interface, which may be influenced by the presence of weak smear (e.g., bentonite filter cake, soil, and remolded weak rock). To date, two-dimensional direct shear interface testing has been utilized to interpret the effect of smear on the shaft response of bored piles. However, without the nondestructive testing and three-dimensional (3D) visualization of smeared interfaces, the effect of smear at the pile-rock interface cannot be accurately assessed. This study presents a novel methodology to cast and test small-scale rock-socketed piles with 3D smeared pile-rock interfaces using in situ X-ray computed tomography (CT) imaging. A new smear casting apparatus has been designed to incorporate desired smear fabrics distribution around the model piles comprising idealized saw-tooth asperities. Different materials were trialed to represent the smeared interfaces and the most suitable one for this study was chosen to be a mixture of petroleum jelly and kaolin through the evaluation of the load-displacement behavior and the X-ray CT images. Various smear configurations were cast on the leading faces of the pile asperities (smear-dominant, balanced rock-smear, and rock-dominant) and their placement and volume were compared with the design values to provide confidence in the proposed experimental methodology. Moreover, the micromechanics evolving at the fully smeared leading-faced interface were assessed in detail using the vertical load-displacement behavior and the corresponding X-ray CT images acquired during multi-stage in situ loading. Based on the observations, the interface mechanics for the smeared shafts were classified into smear compression, subsequent smear compression with shearing, and rock shearing. The proposed experimental methodology opens new avenues for studying the smear fabric effect on the load-bearing mechanisms of smeared piles socketed in soft rock.

Effects of as-built surface with varying number of contour passes on high-cycle fatigue behavior of additively manufactured nickel alloy 718

High cycle fatigue life of laser-powder bed fusion (L-PBF) parts depends on several factors; as-built surfaces, when present, are a particular concern. This work measures as-built L-PBF surfaces with X-ray computed tomography, and uses rotating beam fatigue testing to measure high cycle fatigue life. Surfaces with different, but consistent, characteristics are achieved by building vertical specimens and changing only the number of contour passes. In this way, specimens with three different levels of surface roughness are compared to standard polished specimens. The results from this show that surface roughness increases with decreasing number of contour passes, but the impact on fatigue lifetime is not trivially related. Electron microscopy and x-ray computed tomography images show multiple initiation points and complex surface topology, but that surface feature depth is not necessarily correlated to failure location. Two primary conclusions are that (1) for the case of as-built surfaces loaded in bending, one contour pass is sufficient to achieve peak as-built performance; (2) surface feature depth, even when measured using metal-penetrating imaging, is not strongly associated with failure location in our data. When assessing AM surfaces, more factors (e.g., grain orientation) may be required to mechanistically understand the performance implications.

Direct modeling of the elastic properties of single 3D printed composite filaments using X-ray computed tomography images segmented by neural networks

Direct modeling of the elastic properties of single 3D printed composite filaments using X-ray computed tomography images segmented by neural networks

Study of the solidification behaviour of phase change materials by in-situ X-ray computed tomography

Calcium chloride hexahydrate (CaCl2.6H2O) is a stablished inorganic salt hydrate-based phase change material (PCM) with interesting properties for low temperature latent heat thermal energy storage (LHTES) applications. However, its phase transition during melting and solidification exhibits a complex behaviour with supercooling and phase segregation effects, which critically limit their practical applications. Experimental approaches enabling tracking of the solidification process in this PCM are thus crucial for a deeper understanding of these adverse effects and to design efficient LHTES. In this study, a novel method based on dynamic X-ray computed tomography (XCT) is used to monitor the solidification process in CaCl2.6H2O through sequences of XCT images. The method was tested with a sample of 60g of CaCl2.6H2O with density of 1.71 g/cm3 and purity higher than 98%. The results reveal that solidification of CaCl2.6H2O occurs through the fusion of crystalline structures initially appearing at the side and the bottom surfaces of the sample which grow over time. In the experiment performed, the solidification process is found to be incomplete, which is frustrated after 385 min of starting the solidification. This frustration was preceded by a change in the total solidification rate which is here estimated from the transient liquid volume fraction curve computed via image processing analysis. Quantitative estimation for the crystals size is also reported.

Ultrasonication optimisation and microstructural characterisation for 3D nanoparticle dispersion in thermoplastic and thermosetting polymers

3D nanoparticles are important as reinforcing or functional phase in polymer composite materials; however, an optimised deagglomeration and uniform distribution of these particles is required to fully exploit their nanoscale properties. Classical dispersion methods like shear mixing have proven insufficient, and high-energy ultrasonication, as the preferred deagglomeration method, requires a challenging system-specific optimisation procedure. Therefore, a study was set up to reveal general scaling trends and good practices in developing an ultrasonication procedure for both thermoplastic and thermoset polymer-nanoparticle systems. The ultrasound energy density served as a universal scaling parameter and the higher power densities in the range of 1W/ml achieved by sonotrode ultrasonication were demonstrated to be necessary for complete deagglomeration. For epoxy and barium titanate (BaTiO3) as a below-percolation thermoset model system, an optimal energy density of 120 J/g was observed. Polyvinylidene difluoride (PVDF) and titanium carbonitride (TiCN) were selected as an above-percolation model thermoplastic system for which ultrasonication in suspension at an energy density of 950 J/ml followed by a crucial rotary evaporation step was necessary. X-ray computed tomography imaging has proven to be a powerful characterisation tool in combination with the matrix-free path diameter. This parameter was proposed as a novel parameter for single-parameter quantification of particle dispersibility as opposed to the commonly used and often inconclusive average cluster diameter.

Nanoceria as Safe Contrast Agents for X-ray CT Imaging.

Cerium oxide nanoparticles (CeO2NPs) have exceptional catalytic properties, rendering them highly effective in removing excessive reactive oxygen species (ROS) from biological environments, which is crucial in safeguarding these environments against radiation-induced damage. Additionally, the Ce atom's high Z number makes it an ideal candidate for utilisation as an X-ray imaging contrast agent. We herein show how the injection of albumin-stabilised 5 nm CeO2NPs into mice revealed substantial enhancement in X-ray contrast, reaching up to a tenfold increase at significantly lower concentrations than commercial or other proposed contrast agents. Remarkably, these NPs exhibited prolonged residence time within the target organs. Thus, upon injection into the tail vein, they exhibited efficient uptake by the liver and spleen, with 85% of the injected dose (%ID) recovered after 7 days. In the case of intratumoral administration, 99% ID of CeO2NPs remained within the tumour throughout the 7-day observation period, allowing for observation of disease dynamics. Mass spectrometry (ICP-MS) elemental analysis confirmed X-ray CT imaging observations.

Experimental characterization of impact damage in foam-core sandwich structures using acoustic emission, optical scanning and X-ray computed tomography techniques

Sandwich structures used in transportation and energy industries are commonly subjected to low-velocity impact in the course of manufacturing, service and maintenance, which can lead to the premature degradation of structural stiffness and strength. A single non-destructive evaluation technique is often difficult to provide a comprehensive assessment on impact damage from online to offline and from visible to invisible. In the present study, acoustic emission (AE), three-dimensional (3D) optical scanning and X-ray computed tomography (CT) techniques are combined to provide a systematic approach for damage characterization of thick foam-core sandwich panels under low-velocity impact. In the tests, the mechanical responses such as force-time and force-displacement curves are obtained from the testing system. The AE technique is adopted to monitor damage initiation and evolution in situ; optical scanning and X-ray computed tomography techniques are used for off-line damage identification and quantification. The results show that the AE signal waveform stream, cumulative counts and cumulative energy correlate well with the mechanical responses of the sandwich panel under the low-velocity impact, enabling capture of valuable information for online damage monitoring. Unlike general cases, the AE signals generated from low-velocity impact are found to be presented in strong bursts of nearly coincident events in the short duration. Therefore, the distributions of AE amplitude and peak frequency between adjacent AE counts are extracted to study the different damage modes and damage mechanisms. The X-ray computed tomography images enable to precisely visualize the fracture behaviors of the PET foam-core inside the sandwich panel in a nondestructive fashion, which evidently supports the AE and optical scanning results. The study is anticipated to demonstrate effectiveness and capability of the proposed experimental methodology for damage detection and characterization on sandwiched composite structures subjected to impact loading.

Strain measurement with multiplexed FBG sensor arrays: An experimental investigation

In conventional rock mechanics testing, radial strain measuring devices are usually attached to the sample's surface at its mid-height. Although this procedure provides a realistic picture of the lateral deformation undergone by homogeneous samples, however, this assumption may not be accurate if the tested rock has significant heterogeneity. Fibre Bragg Grating (FBG) sensors have recently been introduced to various rock testing applications due to their versatility over conventional strain gauges and radial cantilevers. FBG sensors have small size, multiplexing capability, and immunity to magnetic interference. The main objective of this study is to explore and understand the capabilities of FBG sensing for strain measurement during rock mechanics testing, including under confining. To do so, two limestone plugs (Savonnières limestone) and one acrylic Poly Methyl Methacrylate (PMMA) plug, all of 38 mm diameter, were prepared. The acrylic plug and one of the Savonnières samples plugs were subjected to Unconfined Compressive Strength (UCS) tests. The second Savonnières plug was subjected to a hydrostatic test up to 20 MPa confining at room temperature. FBG sensors of 125 μm cladding diameter with ceramics (Ormocer) coating were glued on the surface of each sample, spreading across the entire sample's height. Strain gauges and cantilever-type radial gauges were used on the samples submitted to UCS for comparison. Results show that radial strain measurements and calculated elastic properties derived from the FBG readings for samples are comparable to readings from the conventional strain gauges and cantilever-type devices. Apparent bulk moduli based on volumetric strain computed from FBG radial strain readings during the hydrostatic test on the Savonnières sample was consistent with benchtop measurements conducted on the Savonnières sample and another plug extracted from the same parental block, as well as published literature data. Moreover, variations in the calculated elastic properties are interpreted as evidence that the FBG sensors detected heterogeneities in the samples' inner structure, which can be seen in the density profiles computed from x-ray CT images. Such observation confirms the potential of the presented FBG sensors configuration for 3D strain mapping in rock mechanics tests.