Search Results (221)

Aluminium alloy 6082 is widely used in the automotive and aerospace industries due to its high strength-to-weight ratio. However, its structural integrity can sometimes be affected by an early fatigue failure. This study investigates the fatigue performance of extruded 6082-T6 samples through a series of fatigue tests conducted at varying stress levels. The material showed significant variability under identical fatigue conditions, suggesting the presence of microstructural defects. Scanning electron microscopy with energy-dispersive spectroscopy (SEM/EDS) and scanning transmission electron microscopy (S/TEM) were used to identify the nature and location of the defects and evaluate the underlying mechanisms influencing the fatigue performance. Computer tomography (CT) also confirmed the presence of oxide inclusions on the fracture surface and near the edges of the samples. These oxide inclusions are distributed throughout the material heterogeneously and in the form of broken oxide films, suggesting that they might have originated during the material’s early processing stages. These oxides acted as stress concentrators, initiating microcracks that led to catastrophic and unpredictable early failure, ultimately reducing the fatigue life of micro-oxide-containing samples. These results highlight the need for better casting control and improved post-processing techniques to minimise the effect of oxide presence in the final components, thus enhancing their fatigue life. Full article

With the extensive application of 3D-printed composites across multiple industries, the investigation into their structural reliability under complex loading conditions has become a critical research focus. This study comprehensively employs acoustic emission (AE) monitoring, digital image correlation (DIC) measurement, and micro-computed tomography (Micro-CT) visualization techniques to explore the progressive damage behavior of 3D-printed sandwich-structured composites reinforced with continuous carbon fiber sheets under three-point bending. Mechanical tests show that increasing the fiber content of face sheets from 10% to 20% enhances average bending strength by 56%, while low fiber content compromises stiffness and load-bearing capacity. AE analysis categorizes damage modes into matrix cracking (<50 kHz), debonding/delamination (50–150 kHz), and fiber breakage (>150 kHz) using k-means clustering algorithms. DIC measurement reveals significant structural deformation processes during damage progression. The AE-DIC-Micro-CT combination demonstrates an initial undamaged state, followed by damage initiation and propagation in the subsequent stages. This integrated approach provides an effective method for damage assessment, guiding the design and reliability improvement of 3D-printed composites. Full article

High-density component-induced metal artifacts in industrial computed tomography (CT) severely impair image quality and make further analysis more difficult. To suppress artifacts and improve image quality, this research suggests a practical approach that combines lightweight attention-enhanced super-resolution networks with Radon-domain artifact elimination. First, the original CT slices are subjected to bicubic interpolation, which enhances resolution and reduces sampling errors during transformation. The Radon transform, which detects and suppresses metal artifacts in the Radon domain, is then used to convert the interpolated pictures into sinograms. The artifact-suppressed sinograms are then reconstructed at better resolution using a lightweight Enhanced Deep Super-Resolution (EDSR) network with a channel attention mechanism, which consists of only one residual block. The inverse Radon transform is used to recreate the final CT images. An average peak signal-to-noise ratio (PSNR) of 40.39 dB and an average signal-to-noise ratio (SNR) of 29.75 dB, with an SNR improvement of 15.48 dB over the original artifact-laden images, show the success of the suggested strategy in experiments. This method offers a workable and effective way to improve image quality in industrial CT applications that involve intricate structures that incorporate metal. Full article

Since lightweight design and construction safety is a crucial element in different sectors of industry, the use of SMA wires in composites could improve the monitoring and adjustment of mechanical properties starting from the product development process through to field use. This work shows how embedded SMA wires can lead to a better understanding of applied forces to a composite structure made of GFRP laminates. To achieve this, different methods will be addressed. Besides mechanical testing of the GFRP-samples with embedded SMA wires, NDT-methods like active thermography, high-frequency ultrasonic testing, and computer tomography are used to detect the SMA wires, whereby thermography and computer tomography are best suited. In this study, the location and the amount of the applied force on GFRP composites with embedded SMA wires could be characterized with relative resistance changes. It is shown that SMA wires with a diameter of 250 µm are preferred to wires with a diameter of 100 µm due to production process and better performance under load (4N force plateau for 100 µm in contrast to 25N force plateau for 250 µm wires). Furthermore, Young’s modulus of the GFRP composites with embedded SMA wires was measured and is similar for various samples with 30.8 GPa on average. Full article

Industries are leveraging the wire laser-beam-directed energy deposition (DED-LB) additive manufacturing (AM) process to manufacture and repair high-quality, defect-free, and cost-effective parts. However, expensive, non-easily accessible, and complex metrology equipment is needed to quantify part-related performance metrics such as cross-sectional dimensional accuracy and intrinsic defects. This information is necessary for establishing the operating process window and for the quality characterization of the part. Therefore, this work presents a methodology that combines information captured from a vision-based monitoring system with the output of Computed Tomography (CT) towards the knowledge generation and process optimization of wire DED-LB. The design of experiments as well as the interpretation of the results are achieved by employing Nested ANOVA where the dependency of cross-sectional stability on the laser power parameter is demonstrated, enabling, at the same time, the understanding of unstructured datasets where multiple parameters vary at different levels. Finally, this work can be the pillar for adopting new production and part requirements while also giving directions about the effect of control strategies on the part quality. Full article

Non-destructive testing (NDT) methods are critical for evaluating the structural integrity of and detecting defects in composite materials across industries such as aerospace and renewable energy. This review examines the recent trends and successful implementations of NDT approaches for composite materials, focusing on articles published between 2015 and 2025. A systematic literature review identified 120 relevant articles, highlighting techniques such as ultrasonic testing (UT), acoustic emission testing (AET), thermography (TR), radiographic testing (RT), eddy current testing (ECT), infrared thermography (IRT), X-ray computed tomography (XCT), and digital radiography testing (DRT). These methods effectively detect defects such as debonding, delamination, and voids in fiber-reinforced polymer (FRP) composites. The selection of NDT approaches depends on the material properties, defect types, and testing conditions. Although each technique has advantages and limitations, combining multiple NDT methods enhances the quality assessment of composite materials. This review provides insights into the capabilities and limitations of various NDT techniques and suggests future research directions for combining NDT methods to improve quality control in composite material manufacturing. Future trends include adopting multimodal NDT systems, integrating digital twin and Industry 4.0 technologies, utilizing embedded and wireless structural health monitoring, and applying artificial intelligence for automated defect interpretation. These advancements are promising for transforming NDT into an intelligent, predictive, and integrated quality assurance system. Full article

This study presents the development of a sustainable composite material by incorporating by-products from the cork industry into acrylonitrile butadiene styrene (ABS), with the aim of reducing the environmental impact of plastic composites while maintaining their performance. ABS, a petroleum-based polymer, was used as the matrix, and maleic anhydride (MAH) with dicumyl peroxide (DCP) served as a compatibilizing system to improve interfacial adhesion with cork microparticles. Composites were prepared with 10% w/w cork in various particle sizes and characterized via FTIR, X-ray computed tomography, SEM, mechanical testing, and thermal analysis. The best performing formulation (CPC-125) showed a reduction of only ~16% in tensile modulus and ~7% in tensile strength compared with ABS-g-MAH, with a more pronounced decrease in strain at break (3.23% vs. 17.47%) due to the cork’s inherent rigidity. Thermogravimetric and calorimetric analysis confirmed that thermal stability and processing temperatures remained largely unaffected. These results demonstrate the feasibility of incorporating cork microparticles as a bio-based reinforcing filler in ABS composites, offering a promising strategy to reduce the use of virgin plastics in applications compatible with conventional injection molding. Full article

Background: Lithium is an essential commodity; however, its mining and processing can expose miners to airborne contaminants such as inhalable dust, respirable dust and respirable crystalline silica. These exposures may adversely affect respiratory health. To protect the health of miners, exposure assessment and control activities are required, followed by respiratory health monitoring to assess the effect of exposure on respiratory health. This study aimed to investigate the relationship between workgroup exposure to airborne contaminants and respiratory health. To determine group exposure levels, exposure data was collected at the group level, which limits individual-level inference, followed by health monitoring. Methods: Industry health monitoring data were collected from miners in three surface lithium mines in Western Australia for the period between October 2023 and October 2024. Miners from Management Administration & Technical, Crusher/Dry/Wet Plant, and Laboratory Operations participated in a pulmonary function test, completed a health and exposure questionnaire and underwent a low dose high-resolution computed tomography. Multivariable linear and logistic regression models were fitted to identify factors associated with lung function and respiratory symptoms. Results: Older age, smoking and pre-existing respiratory conditions were correlated with poor respiratory airflow. The odds of having a respiratory obstruction or restriction were significantly higher by 3.942 and 2.165 times respectively, for miners who were 40 years old or above, and those who had existing diagnosed respiratory medical conditions. The risk of coughing among current smokers was more than four times higher compared to non-smokers. In addition, working in Crushing and Processing was significantly associated with the risk of experiencing respiratory symptoms compared to working in Management Administration & Technical and Laboratory Operations. Conclusions: The study demonstrated that respiratory health was influenced by non-work-related risk factors. Based on these results, it is recommended that health promotion programs be developed and implemented to empower miners to cease smoking and to manage non-work-related respiratory conditions. Full article

Objective: Trauma is a leading cause of enophthalmos, typically resulting from an increase in the volume of the bony orbit. The general consensus is that post-traumatic primary deformity repair should aim to restore the premorbid volume, shape, and cosmesis of the orbitozygomatic complex (OZC). This study aims to utilise novel three-dimensional (3D) printed patient-specific moulds to intraoperatively fabricate enophthalmos wedges and onlays using polymethylmethacrylate (PMMA) bone cement to reconstruct the OZC. Methods: A total of seven patients underwent digital surgical planning using Freeform software to virtually correct orbitozygomatic complex deformities guided by a design algorithm. Three-dimensionally printed nylon patient-specific moulds were used intraoperatively to fabricate enophthalmos wedges and/or onlays using an industry-standard PMMA bone cement. Clinical examination and application of the proposed design algorithm determined that enophthalmos wedges were indicated for four patients, with one also requiring an onlay; and periorbital onlays were required for the three remaining patients. Results: Hertel exophthalmometry at a mean follow-up of 19.1 months demonstrated good outcomes in the correction of post-traumatic enophthalmos and hypoglobus and with patients reporting good subjective cosmetic results. Patients 5 and 7 had follow-up three-dimensional computed tomography (3D-CT) to confirm correct placement. Conclusion: The use of patient-specific PMMA wedges and onlays, fabricated intraoperatively with the aid of 3D-printed moulds, offers a reliable and effective approach for correcting post-traumatic enophthalmos and hypoglobus. This method allows for the restoration of orbital volume and anatomical contours, addressing both functional and aesthetic concerns. Our results demonstrate that this technique yields favourable outcomes. Full article

High-performance discontinuous carbon-fiber-reinforced thermoplastics (CFRTPs) offer promising manufacturing flexibility and recyclability for advanced composite applications. However, their mechanical performance and reliability strongly depend on the internal fiber architecture, which is largely determined by the molding process. In this study, three distinct compression molding approaches—CFRTP sheet molding compounds (SMCs), bulk molding compounds (BMCs), and free-edge molding compounds (FMCs)—were systematically evaluated to investigate how processing parameters affect fiber orientation, tape deformation, and impregnation quality. X-ray micro-computed tomography (XCT) was employed to visualize and quantify the internal structures of each material, focusing on the visualization and quantification of in-plane and out-of-plane fiber alignment and other internal structure features. The results indicate that CFRTP-SMC retains largely intact tape layers and achieves better impregnation, leading to more uniform and predictable internal geometry. Although CFRTP-BMC exhibits greater tape deformation and splitting due to increased flow, its simpler molding process and better tolerance for tape shape distortion suggest potential advantages for recycled applications. In contrast, CFRTP-FMC shows significant tape fragmentation and poor impregnation, particularly near free edges. These findings underscore the critical role of a controlled molding process in achieving a consistent internal structure for these materials for the first time. This study highlights the utility of advanced XCT methods for optimizing process design and advancing the use of high-performance discontinuous CFRTP in industry. Full article

Temporomandibular joint replacement is a critical intervention for severe temporomandibular joint disorders, enhancing pain levels, jaw function and overall quality of life. In this study, we compare two finite element method-based simulation workflows from both academic and industrial perspectives, focusing on a patient-specific case involving a custom-made temporomandibular joint prosthesis. Using computed tomography data and computer-aided design data, we generated different 3D models and performed mechanical testing, including wear and static compression tests. Our results indicate that the academic workflow, which is retrospective, purely image-based and applied post-operatively, produced peak stress values within 9–20% of those obtained from the industrial workflow. The industrial workflow is prospective, pre-operative, computer-aided design-based and guided by stringent regulatory standards and approval protocols. Observed differences between workflows were attributed primarily to distinct modelling assumptions, simplifications and constraints inherent in each method. To explicitly quantify these differences, multiple additional models were generated within the academic workflow using partial data from the industrial process, revealing specific sources of variation in stress distribution and implant performance. The findings underscore the potential of patient-specific simulations not only to refine temporomandibular joint prosthesis design and enhance patient outcomes, but also to highlight the interplay between academic research methodologies and industrial standards in the development of medical devices. Full article

Wood drying is the most critical and energy-intensive process in the wood industry. However, the complex pore structure of wood significantly affects its thermal performance. Therefore, it is essential to study the relationship between the pore structure and the thermal properties of wood. In this study, X-ray-computed tomography (XCT) technology, combined with digital image processing (DIP) techniques, was used to visualize and characterize the three-dimensional structure of oak samples. Parameters such as porosity, pore size and distribution, and fractal dimensions were obtained to investigate their relationship with thermal conductivity. Subsequently, the thermal conductivities of the oak samples in the tangential, radial, and axial directions were simulated based on their three-dimensional structure. The simulation results were validated using the transient plane source method (TPS). The results showed that there were significant differences in porosity and pore size between earlywood and latewood, which in turn affect the correlation between fractal dimension and thermal conductivity. The higher the self-similarity of the wood structure is, the stronger the correlation between porosity and fractal dimension will be. Due to the limitations of CT resolution and threshold segmentation methods, there may be some axial deviations in the heat transfer simulation based on XCT. However, overall, this method provides a relatively accurate estimate of the effective thermal conductivity of oak wood. In addition, the pit structure and the research on heat conduction of wood-based multi-scale pore structures are of crucial importance to the study of heat conduction in wood. Full article

High-speed friction stir welding (HSFSW) has emerged as a promising technique for improving the manufacturing efficiency of aluminum alloy structures by enabling faster welding while maintaining the quality of welded joints. This study investigates the mechanical properties and microstructural characteristics of AA 7020-T651 aluminum alloy joints welded using a novel multi-pin tool at high feed rates ranging from 2500 to 6000 mm/min under a constant rotational speed of 4000 rpm. Defect-free welds were successfully fabricated, as confirmed by metallographic analysis and micro-computed tomography (µ-CT). The multi-pin tool facilitated consistent material flow and heat distribution, which contributed to reliable joint formation across all feed rates. At the highest feed rate, the tensile strength reached 76% of the base material. A consistent softening in the nugget zone (NZ) was observed, and electron backscatter diffraction (EBSD) analysis showed a more than 70% grain size reduction in this zone, averaging ~3 µm, due to dynamic recrystallization. These findings underscore the suitability of HSFSW with multi-pin tools for high-speed industrial applications, offering enhanced productivity without compromising structural integrity. Full article

Semi-continuous casting is an important method for the large-scale production of high-strength conductive copper-iron (Cu-Fe) alloys in the future. However, serious peeling defects were found on the surface of cold-rolled strips during industrial trials. Due to the multi-step complexity of the manufacturing process (from casting to final product), identifying the root cause of defect formation remains challenging. X-ray computed tomography (X-CT) was used to quantitatively characterize the pores and defects in the horizontal continuous casting Cu-Ni-Sn slab, the semi-continuous casting Cu-Fe alloy slab, and the hot-rolled slab of Cu-Fe, and the relationship between the defect characteristics and processes was analyzed. The results showed that the internal defect sphericity distribution of the Cu-Fe alloy slab after hot rolling was similar to that of the reference Cu-Ni-Sn slab. The main difference lies in the low sphericity range (<0.4). The volume of pore defects inside the Cu-Fe alloy after hot rolling was significantly larger than in the reference sample, with a 52-fold volume difference. This phenomenon may be the source of surface-peeling defects in the subsequent cold-rolling process. The occurrence of internal defects in the Cu-Fe alloy is related to both the composition characteristics and casting processes of the Cu-Fe alloy; on the other hand, it is also related to the hot-rolling process. Full article

With the depletion of high-grade iron ore resources, the efficient utilization of low-grade iron ore has become a critical demand in the steel industry. Due to its uniform particle size and chemical composition, pelletized iron ore significantly enhances both the utilization rate of iron ore and the efficiency of metallurgical processes. This paper presents a deep learning model based on ResUNet, which integrates three-dimensional CT images obtained through industrial computed tomography (ICT) to precisely segment hematite, liquid phase, and porosity. By incorporating residual connections and batch normalization, the model enhances both robustness and segmentation accuracy, achieving F1 scores of 98.37%, 95.10%, and 83.87% for the hematite, pores, and liquid phase, respectively, on the test set. Through 3D reconstruction and quantitative analysis, the volume fractions and fractal dimensions of each component were computed, revealing the impact of the spatial distribution of different components on the physical properties of the pellets. Systematic evaluation of model robustness demonstrated varying sensitivity to different CT artifacts, with the strongest resistance to beam hardening and highest sensitivity to Gaussian noise. Multi-scale resolution analysis revealed that segmentation quality and fractal dimension estimates exhibit phase-dependent responses to resolution changes, with the liquid phase being the most sensitive. Despite these dependencies, the relative complexity relationships among phases remained consistent across resolutions, supporting the reliability of our qualitative conclusions. The study demonstrates that the deep learning-based image segmentation method effectively captures microstructural details, reduces human error, and enhances automation, providing a scientific foundation for optimizing pellet quality and improving metallurgical performance. It holds considerable potential for industrial applications. Full article