Search Results (34)

Progressive damage evolution in rock masses serves as the fundamental mechanism driving geological hazards by controlling deformation patterns and failure predictability. To address the critical challenge of predicting fracture behaviors in heterogeneous geological media, this study pioneers the integration of real-time computed tomography (CT) scanning and acoustic emission (AE) monitoring to investigate self-organized criticality and fracture predictability in Cretaceous sandstone under uniaxial compression. By systematically analyzing internal structural evolution and damage parameters, this established a multiparameter framework to characterize self-organized processes and critical phase transitions during progressive fracturing. Key findings include the following: (1) Distinct critical thresholds emerge during yield-stage self-organization, marked by abrupt transitions in AE signals and crack metrics—from microdamage coalescence initiating volumetric expansion (first critical point) to macrocrack nucleation preceding peak strength (second critical point). (2) AE-crack evolution follows power–law statistics, where elevated scaling exponents (r > 0.85) correlate with intensified nonlinear damage, accelerated localization, and progressive rate enhancement. Yield-stage power–law acceleration provides quantifiable failure precursors. (3) Yield-stage damage patterns exhibit 85% similarity with terminal failure configurations, confirming yield-stage as the definitive precursor with critical temporal signatures for failure prediction. A conceptual framework integrating multiparameter responses (AE signals, crack metrics) was developed to decipher self-organized critical phase transitions during deformation-failure processes. This work establishes methodological foundations for investigating damage mechanisms and predictive strategies in heterogeneous rock systems. Full article

This review focuses on the contribution of medical imaging in the diagnosis of peripheral vestibular disorders. This is a narrative review based on a focused literature search conducted using PubMed and the Cochrane Library. Imaging is not usually recommended in initial consultations for vestibular disorders because only 5–10% of MRI scans reveal findings directly related to the disease. The study is a review of the literature that highlights the utility and limitations of imaging such as computed tomography (CT) and magnetic resonance imaging (MRI). It follows the diagnostic approach from history and physical examination to laboratory tests and imaging. Some conditions like vestibular neuritis and benign paroxysmal positional vertigo (BPPV) have limited imaging utility due to the fine details required. Conversely, high-resolution CT and MRI are important for diagnosing Meniere’s disease, acoustic neuroma, and superior canal dehiscence. The role of imaging varies a lot among specific conditions. Advances in imaging technology, particularly high-resolution MRI, promise enhanced diagnostic capabilities. Full article

The demand for integrated circuit (IC) chips has risen markedly across various industries in conjunction with advancements in global technology. Prior to packaging, IC elements undergo several processes, including wafer dicing, wire bonding, and encapsulation. Scanning Acoustic Tomography (SAT) effectively analyzes the internal structures of integrated circuit products, thereby preventing the supply of defective components, including chip fractures, delamination, voids, and adhesion issues. The study aims to reduce operator eye strain, enhance productivity, and minimize employee turnover rates by proposing the use of convolutional neural networks (CNN) to develop a predictive model for automating defect detection in integrated circuit (IC) products within SAT images, replacing traditional visual inspections. To enhance the accuracy of the CNN model, we implement the flood-fill algorithm as the primary augmentation strategy and create an image augmentation model in Python. This method produces a training set that accurately reflects the true characteristics of defects, thereby mitigating the problem of limited defect data and ensuring the model is trained on reliable information. The incorporation of various rates and scaling factors into SAT defect images, along with the manipulation of the original defect, contributes to the development of a robust dataset suitable for real-world testing. The CNN model is trained using various batch sizes, resulting in customized training datasets and predictive models to improve accuracy. Key findings indicate that employing 40× augmentation alongside a batch size of 32 enhances the model’s performance, yielding a missed detection rate below 0.4% and a false alarm rate of 0.1%. This model offers an improved solution to the issue of manual inspections on assemblies, thereby alleviating operator stress and establishing a robust framework for automated integrated circuit quality management. Full article

This study investigates the flexural behavior of three sandwich panels composed of an agglomerated cork core and skins made up of cross-ply [0,90]₂ flax or glass layers with areal densities of 100 and 300 g/m². They are designated by SF100, SF300, and SG300, where S, F, and G stand for sandwich material, flax fiber, and glass fiber, respectively. The three sandwich materials were fabricated in a single step using vacuum infusion with the liquid thermoplastic resin Elium^®. Specimens of these sandwich materials were subjected to three-point bending tests at five span lengths (80, 100, 150, 200, and 250 mm). Each specimen was equipped with two piezoelectric sensors to record acoustic activity during the bending, facilitating the identification of the main damage mechanisms leading to flexural failure. The acoustic signals were analyzed to first track the initiation and propagation of damage and, second, to correlate these signals with the mechanical behavior of the sandwich materials. The obtained results indicate that SF300 exhibits 60% and 49% higher flexural and shear stiffness, respectively, than SG300. Moreover, a comparison of the specific mechanical properties reveals that SF300 offers the best compromise in terms of the flexural properties. Moreover, the acoustic emission (AE) analysis allowed the identification of the main damage mechanisms, including matrix cracking, fiber failure, fiber/matrix, and core/skin debonding, as well as their chronology during the flexural tests. Three-dimensional micro-tomography reconstructions and scanning electron microscope (SEM) observations were performed to confirm the identified damage mechanisms. Finally, a correlation between these observations and the AE signals is proposed to classify the damage mechanisms according to their corresponding amplitude ranges. Full article

Geometrical models of the airways offer a comprehensive perspective on the complex interplay between lung structure and function. Originating from mathematical frameworks, these models have evolved to include detailed lung imagery, a crucial enhancement that aids in the early detection of morphological changes in the airways, which are often the first indicators of diseases. The accurate representation of airway geometry is crucial in research areas such as biomechanical modeling, acoustics, and particle deposition prediction. This review chronicles the evolution of these models, from their inception in the 1960s based on ideal mathematical constructs, to the introduction of advanced imaging techniques like computerized tomography (CT) and, to a lesser degree, magnetic resonance imaging (MRI). The advent of these techniques, coupled with the surge in data processing capabilities, has revolutionized the anatomical modeling of the bronchial tree. The limitations and challenges in both mathematical and image-based modeling are discussed, along with their applications. The foundation of image-based modeling is discussed, and recent segmentation strategies from CT and MRI scans and their clinical implications are also examined. By providing a chronological review of these models, this work offers insights into the evolution and potential future of airway geometry modeling, setting the stage for advancements in diagnosing and treating lung diseases. This review offers a novel perspective by highlighting how advancements in imaging techniques and data processing capabilities have significantly enhanced the accuracy and applicability of airway geometry models in both clinical and research settings. These advancements provide unique opportunities for developing patient-specific models. Full article

Objective: The aim of the present study is to identify a more reliable reference point in three-dimensional cephalometric analysis to replace the Porion point used in two-dimensional analysis, enhancing the accuracy of assessments. Methods: The methodology assessed potential alternative landmarks for three-dimensional cephalometric analysis. Utilizing a segmenting technique, anatomical landmarks were accurately pinpointed from the external acoustic meatus of 26 Cone Beam Computed Tomography (CBCT) scans. These landmarks were chosen for their clear and unambiguous detectability. To assess reproducibility, each landmark was replicated twice with a one-week interval by a master’s student. Reproducibility was quantitatively evaluated by analyzing the absolute difference per axis. Results: Five possible candidate landmarks were identified: the most anterior, posterior, superior, and inferior points of the external acoustic meatus (EAM) and a notch delineating the epitympanic recess. The reproducibility of pinpointing these landmarks ranged from 0.56 mm to 2.2 mm. The absolute mean differences between measurements were 0.46 mm (SD 0.75) for the most anterior point, 0.36 mm (SD 0.44) for the most posterior point, 0.25 mm (SD 0.26) for the most superior point, 1.11 mm (SD 1.03) for the most inferior point, and 0.78 mm (SD 0.57) for the epitympanic notch. Conclusions: The most superior point of the EAM might successfully replace the Porion as an anatomical reference. Full article

Over the past decade, significant research has focused on detecting abnormalities in metal laser powder bed fusion (L-PBF) additive manufacturing. Effective online monitoring systems are crucial for enhancing process stability, repeatability, and the quality of final components. Therefore, the development of in situ detection mechanisms has become essential for metal L-PBF systems, making efficient closed-loop control strategies to adjust process parameters in real time vital. This paper presents an overview of current in situ monitoring systems used in metal L-PBF, complemented by ex situ characterizations. It discusses in situ techniques employed in L-PBF and evaluates the applicability of commercial systems. The review covers optical, thermal, acoustic, and X-ray in situ methods, along with destructive and non-destructive ex situ methods like optical, Archimedes, and X-ray characterization techniques. Each technique is analyzed based on the sensor used for defect detection and the type or size of defects. Optical in situ monitoring primarily identifies large defects from powder bed abnormalities, while thermal methods detect defects as small as 100 µm and keyholes. Thermal in situ detection techniques are notable for their applicability to commercial devices and efficacy in detecting subsurface defects. Computed tomography scanning excels in locating porosity in 3D space with high accuracy. This study also explores the advantages of multi-sensor in situ techniques, such as combining optical and thermal sensors, and concludes by addressing current research needs and potential applications of multi-sensor systems. Full article

Even though the influence of the printing direction on the mechanical properties of 3D-printed samples by fused filament fabrication is established in the literature, very little is known about mechanical and electrical coupling. In this study, electrically conductive polylactic acid filled with carbon black particles undergoes monotonic and repeated progressive tensile loading to better understand the influence of the printing direction on the electro-mechanical properties of three-dimensional-printed samples. The objective is to analyse the electro-mechanical behaviour of this composite for its potential application as an actuator. The classical laminate theory is also applied to evaluate the relevance of this theory in predicting the mechanical characteristics of this material. In addition, a comprehensive damage analysis is performed using acoustic emission, infrared thermography, scanning electron microscopy, and X-ray microcomputed tomography imaging. Results show that the degradation of the mechanical and electrical properties is highly influenced by the printing direction. The appearance and development of crazes in 0° filaments are highlighted and quantified. The conclusions drawn by this study underline the interest in using longitudinal and unidirectional printing directions to improve the conductive path within the samples. Furthermore, the evolution of the resistance throughout the experiments emphasizes the need to control the implemented voltage in the design of future electro-thermally triggered actuators. Full article

The health and stability of trees are essential information for the safety of people and property in urban greenery, parks or along roads. The stability of the trees is linked to root stability but essentially also to trunk decay. Currently used internal tree stem decay assessment methods, such as tomography and penetrometry, are reliable but usually time-consuming and unsuitable for large-scale surveys. Therefore, a new method based on close-range remotely sensed data, specifically close-range photogrammetry and iPhone LiDAR, was tested to detect decayed standing tree trunks automatically. The proposed study used the PointNet deep learning algorithm for 3D data classification. It was verified in three different datasets consisting of pure coniferous trees, pure deciduous trees, and mixed data to eliminate the influence of the detectable symptoms for each group and species itself. The mean achieved validation accuracies of the models were 65.5% for Coniferous trees, 58.4% for Deciduous trees and 57.7% for Mixed data classification. The accuracies indicate promising data, which can be either used by practitioners for preliminary surveys or for other researchers to acquire more input data and create more robust classification models. Full article

Sound reception was investigated in the Yangtze finless porpoise (Neophocaena phocaenoides asiaeorientalis) at its most sensitive frequency. The computed tomography scanning, sound speed, and density results were used to develop a three-dimensional numerical model of the porpoise sound-reception system. The acoustic fields showed that sounds can reach the ear complexes from various pathways, with distinct receptivity peaks on the forward, left, and right sides. Reception peaks were identified on the ipsilateral sides of the respective ears and found on the opposite side of the ear complexes. These opposite maxima corresponded to subsidiary hearing pathways in the whole head, especially the lower head, suggesting the complexity of the sound-reception mechanism in the porpoise. The main and subsidiary sound-reception pathways likely render the whole head a spatial receptor. The low-speed and -density mandibular fats, compared to other acoustic structures, are significant energy enhancers for strengthening forward sound reception. Based on the porpoise reception model, a biomimetic receptor was developed to achieve directional reception, and in parallel to the mandibular fats, the silicon material of low speed and density can significantly improve forward reception. This bioinspired and biomimetic model can bridge the gap between animal sonar and artificial sound control systems, which presents potential to be exploited in manmade sonar. Full article

Acoustics is a field with significant application in wood science and technology for the classification and grading, through non-destructive tests, of a large variety of products from standing trees to building structural elements and musical instruments. In this review article the following aspects are treated: (1) The theoretical background related to acoustical characterization of wood as an orthotropic material. We refer to the wave propagation in anisotropic media, to the wood anatomic structure and propagation phenomena, to the velocity of ultrasonic waves and the elastic constants of an orthotropic solid. The acoustic methods for the determination of the elastic constants of wood range from the low frequency domain to the ultrasonic domain using direct contact techniques or ultrasonic spectroscopy. (2) The acoustic and ultrasonic methods for quality assessment of trees, logs, lumber and structural timber products. Scattering-based techniques and ultrasonic tomography are used for quality assessment of standing trees and green logs. The methods are based on scanning stress waves using dry-point-contact ultrasound or air-coupled ultrasound and are discussed for quality assessment of structural composite timber products and for delamination detection in wood-based composite boards. (3) The high-power ultrasound as a field with important potential for industrial applications such as wood drying and other applications. (4) The methods for the characterization of acoustical properties of the wood species used for musical instrument manufacturing, wood anisotropy, the quality of wood for musical instruments and the factors of influence related to the environmental conditions, the natural aging of wood and the effects of long-term loading by static or dynamic regimes on wood properties. Today, the acoustics of wood is a branch of wood science with huge applications in industry. Full article

The use of fibre-reinforced plastics (FRPs) in various industrial applications continues to increase thanks to their good strength-to-weight ratio and impact resistance, as well as the high strength that provides engineers with advanced options for the design of modern structures subjected to a variety of out-of-plane impacts. An assessment of the damage morphology under such conditions using non-destructive techniques could provide useful data for material design and optimisation. This study investigated the damage mechanism and energy-absorption characteristics of E-glass laminates and sandwich structures with GFRP face sheets with PVC cores under quasi-static indentation with conical, square, and hemispherical indenters. An acoustic emission (AE) technique, coupled with a k-means++ pattern-recognition algorithm, was employed to identify the dominant microscopic and macroscopic damage mechanisms. Additionally, a post-mortem damage assessment was performed with X-ray micro computed tomography and scanning electron microscopy to validate the identified clusters. It was found that the specific energy absorption after impact with the square and hemispherical indenters of the GFRP sandwich and the plain laminate differed significantly, by 19.29% and 43.33%, respectively, while a minimal difference of 3.5% was recorded for the conical indenter. Additionally, the results obtained with the clustering technique applied to the acoustic emission signals detected the main damaged modes, such as matrix cracking, fibre/matrix debonding, delamination, the debonding of face sheets/core, and core failure. The results therefore could provide a methodology for the optimisation and prediction of damage for the health monitoring of composites. Full article

The purpose of this review paper is to show the possibilities of carbonate reservoir characterization using well logging and laboratory measurements. Attention was focused on standard and new methods of well logging acquisition and interpretation including laboratory experiments to show a part of the history of carbonate rock investigations as hydrocarbon or water reservoirs. Brief information on the geology, mineralogy and petrography of carbonate rocks was delivered. Reservoir properties, i.e., porosity (including fracturing), permeability, and saturation, were defined to emphasize the specific features of carbonates, such as fractures, and vugs. Examples of methodologies were selected from the commonly used laboratory techniques (thin sections examination, mercury and helium porosimetry, X-ray diffraction—XRD) combined with the standard well logs (bulk density—RHOB, neutron porosity—NPHI, sonic slowness—DT, and deep resistivity—Rd) to show the methods that have been used since the very beginning of the scientific and engineering studies of carbonates. Novelty in well logging, i.e., resistivity and acoustic imaging, nuclear magnetic resonance–NMR, dipole shear sonic imaging–DSI, and a spectral neutron-gamma log-geochemical device–GLT combined with modern laboratory investigations (NMR laboratory experiments, scanning electron microscopy SEM), showed how continuous information on mineral composition, porosity and saturation could be obtained and juxtaposed with very detailed laboratory data. Computed X-ray tomography (CT) enabling the 2D and 3D analyses of pores and fractures was presented as a quantitative methodology, effective in pore space characterization, revealing rock filtration abilities. Deep learning and artificial intelligence were used for joining various types of data. It was shown that thanks to new computational technologies original data from very small samples (micro scale), extensively describing the flow ability of the reservoir, could be extended to mezzo scale (core samples) and macro scale (well log images). Selected examples from the published papers illustrated the review. References cited in the text, together with the issues included in them, were the rich source of the practical knowledge processed These were checked by the authors and could be used in other projects. Full article

We report the case of a 51-year-old woman with multiple otologic and vestibular symptoms. She presented with two different types of tinnitus in her right ear, vertigo, and fluctuating aural symptoms in the left ear. She also complained of disequilibrium; chronic headache; hyperhidrosis; amenorrhea; insomnia; broadened hands and feet; and widened, thickened, and stubby fingers. The patient underwent careful collection of medical history, otomiscroscopy, pure tone audiometry, tympanometry, reflex threshold measurements, vestibular assessments, blood tests, magnetic resonance imaging (MRI), and cone beam computed tomography (CBTC) of the head. The audiogram showed: (1) a mild low-to-mid frequency conductive hearing loss, and a sharply sloping sensorineural hearing loss above 4000 Hz in the right ear; (2) a mild low-frequency sensorineural hearing loss in the left ear. MRI with 3D FLAIR sequences detected an acoustic neuroma (7.4 mm × 5.2 mm) in the middle-third of the right internal auditory canal, a pituitary macroadenoma (13 mm × 10 mm × 10 mm) and left saccular hydrops. The CBCT scan documented an outbreak of otosclerosis (3 mm) around the fissula ante fenestram in the right ear. Therefore, acoustic neuroma (right ear), growth hormone-secreting macroadenoma of the pituitary gland, Menière’s disease (left ear), and otosclerosis (right ear) were diagnosed/strongly suspected. A watch-and-wait strategy was adopted for acoustic neuroma and otosclerosis, while transsphenoidal surgery was successfully performed to remove the pituitary macroadenoma. This case report confirms that multiple otologic disorders can occur simultaneously in the same patient, requiring prompt audiological and imaging evaluations. Full article

Geophysical detection techniques are important methods in marine gas hydrate exploration and monitoring, because the small-scale distribution of hydrates has a large impact on the wave velocity. The acoustic response characteristics of hydrate micro-distributions have strong significance for monitoring the hydrate dissociation process. In this paper, experiments simulating the hydrate dissociation process were carried out in a self-developed experimental device combining X-ray computed tomography (X-CT) scanning and ultrasonic detection, which allowed the acoustic wave characteristics and X-CT scanning results to be simultaneously obtained during the hydrate dissociation process. This study found that the hydrate dissociation stage is divided into three stages. The hydrate begins to dissociate at spots where it comes into touch with sand particles early in the dissociation process. The main factor affecting the acoustic wave velocity of hydrates in this stage is changes in the microscopic distribution of hydrate. In the middle stage, a large amount of hydrate decomposes, and the main factor affecting the acoustic wave velocity of hydrate in this stage is the change in hydrate content. In the later stage of hydrate dissociation, the hydrate distribution pattern consists mainly of the pore-filling type, and the hydrate micro-distribution at this stage is the main factor affecting the acoustic wave velocity. This study will be of great significance for understanding the microscopic control mechanism of hydrate reservoir geophysical exploration. Full article