Search Results (53)

Digital transformation is the process of using digital technologies for creating or modifying existing business processes and customer experience, leveraging cutting-edge technology to meet changing market needs. Disruptions like the COVID-19 pandemic, regional wars, and climate-driven natural disasters create consequential scenarios, e.g., global supply chain disruption creating further demand–supply mismatch for healthcare enterprises. According to KPMG’s 2021 Healthcare CEO Future Pulse, 97% of healthcare leaders reported that COVID-19 significantly accelerated the digital transformation agenda. Successful digital transformation initiatives, for example, digital twins for supply chains, augmented reality, the IoT, and cybersecurity technology initiatives implemented significantly enhanced resiliency in supply chain and manufacturing operations. However, according to another study conducted by Mckinsey & Company, 70% of digital transformation efforts for healthcare enterprises fail to meet their goals. Healthcare enterprises face unique challenges, such as complex regulatory environments, cultural resistance, workforce IT skills, and the need for data interoperability, which make digital transformation a challenging project. Therefore, this study explored potential barriers, enablers, disruption scenarios, and digital transformation use cases for healthcare enterprises. A structured literature review (SLR), followed by thematic content analysis, was conducted to inform the research objectives. A sample of sixty (n = 60) peer-reviewed journal articles were analyzed using research screening criteria and keywords aligned with research objectives. The key themes for digital transformation use cases identified in this study included information processing capability, workforce enablement, operational efficiency, and supply chain resilience. Collaborative leadership as a change agent, collaboration between information technology (IT) and operational technology (OT), and effective change management were identified as the key enablers for digital transformation of healthcare enterprises. This study will inform digital transformation leaders, researchers, and healthcare enterprises in the development of enterprise-level proactive strategies, business use cases, and roadmaps for digital transformation. Full article

Grain boundaries play a vital role in determining the mechanical and physical properties of metallic materials. Heat treatment (HT) is widely employed to modify the content and distribution of grain boundaries. However, achieving precise control by HT remains challenging due to the scale mismatch between heat transfer and microstructure evolution. Electric pulse treatment (EPT) offers a breakthrough in microstructure control, by unifying the scales of microstructure and heat generation through a local Joule heating effect, with significant acceleration to microstructure evolution through athermal effects. Those two aspects establish EPT as an effective approach to grain boundary regulation. Despite its advantages, the mechanisms underlying the thermal and athermal effects of EPT remain unclear. To this end, a study of the grain growth kinetics of a nickel-based superalloy with an inhomogeneous microstructure under EPT was carried out through experimental and theoretical approaches. Grain boundary migration behaviors in both coarse- and fine-grained regions were investigated, corresponding grain growth kinetics were established, and effects were validated via annealing twin evolution. The results reveal that EPT accelerates grain boundary migration more than HT, exhibiting a “target effect” where growth rates correlate with grain boundary density. The efficacy of EPT depends on the balance between enhanced grain boundary migration and a reduced treatment time. Full article

Introducing nano-twins into electrolytic copper foil is an effective method to enhance strength and toughness. While pulse electrodeposition enables the easier preparation of high-density nano-twin copper, large-scale industrial production mainly relies on direct current electrodeposition. Therefore, systematically studying the effects of electroplating parameters on the microstructure and mechanical properties of direct current electrodeposited copper foil is crucial. In this paper, we discuss the effects of pH value, C_CuSO4, and J_k on the microstructure and mechanical properties of electroplated copper foils at room temperature. The results show that copper foils exhibit stronger (220)_Cu preferred orientation on the M surface than on the S surface with changes in pH value, C_CuSO4, and J_k. When the pH value is 2.5, the C_CuSO4 is between 70 and 90 g/L, and the J_k is within the range of 70–90 mA/cm², the prepared copper foil has better compactness and no obvious pinhole-like defects. Particularly, the copper foil electroplated with a pH value of 2.5, a C_CuSO4 of 80 g/L, and a J_k of 80 mA/cm² consists of equiaxed and columnar grains, featuring small grain size, uniform distribution, and a dense structure, resulting in excellent mechanical properties. Full article

Pulsed detonation–plasma technology (PDT) is a surface-modification technology used in an atmospheric environment, where plasma, a detonation impact and thermal conditions are combined and have an effect on the material’s surface. In this study, annealed 65Mn steel was selected to further study the principle of PDT modification. The results show that the modified layer with fine grains was divided into an infiltration layer with a large amount of non-uniformly distributed granular CW₃ carbides and a heat-affected layer below the infiltration layer after PDT treatment. However, a higher amount of acicular martensite and a lower amount of austenite was achieved in the modified layer, containing a large number of small-angle grain boundaries, dislocations, and twin grains. After the PDT treatment, the hardness of the modified layer, heat-affected layer, and substrate was 980 HV, 856.2 HV, and 250 HV, respectively. The mass loss of the sample before and after PDT treatment was 21.1 mg and 12.4 mg, respectively. The hardness and wear resistance of the modified layer were greatly improved compared with the substrate because of the combined effect of the solid-phase transformation, element infiltration, and distortion. Full article

Quantum key distribution (QKD) is a cornerstone of secure communication in the quantum era, yet most existing protocols are designed for point-to-point transmission, limiting their scalability in networked environments. In this work, we introduce Loop-Back QKD, a novel QKD protocol that supports both two-party linear configurations and scalable multiuser ring topologies. By leveraging a structured turn-based mechanism and bidirectional pulse propagation, the protocol enables efficient key distribution while reducing the quantum bit error rate (QBER) through a multi-pulse approach. Unlike trusted-node QKD networks, Loop-Back QKD eliminates intermediate-node vulnerabilities, as secret keys are never processed by intermediate nodes. Furthermore, unlike Measurement-Device-Independent (MDI-QKD) and Twin-Field QKD (TF-QKD), which require complex entanglement-based setups, Loop-Back QKD relies solely on direct polarization transformations, reducing vulnerability to side-channel attacks and practical implementation challenges. Additionally, our analysis indicates that multi-pulse Loop-Back QKD can tolerate higher QBER thresholds. However, this increased robustness comes at the cost of a lower key rate efficiency compared to standard QKD schemes. This design choice enhances its robustness against real-world adversarial threats, making it a strong candidate for secure multiuser communication in local and metropolitan-scale quantum networks. Full article

In high-capacity and short-reach applications, double-sideband self-coherent detection (DSB-SCD) has garnered significant attention due to its ability to recover optical fields of DSB signals without requiring a local oscillator. However, DSB-SCD is fundamentally constrained by the non-ideal receiver transfer function, necessitating a guard band between the carrier and signal. While the conventional twin-single-sideband (twin-SSB) modulation scheme addresses this requirement, it incurs substantial implementation complexity. In this paper, we propose a spectrum inversion-based double-sideband (SI-DSB) modulation scheme, where spectral inversion shifts the DSB signal to the high-frequency region, creating a guard band around the zero frequency. After photodetector detection, baseband signal recovery is achieved through subsequent spectral inversion. Compared with the twin-SSB modulation scheme, this approach significantly reduces DSP complexity. The simulation exploration two modulation formats of pulse–amplitude modulation and quadrature-amplitude modulation, demonstrating a comparable system performance between SI-DSB and twin-SSB modulation schemes. We also illustrate the parameter optimization process for the SI-DSB modulation scheme, including carrier-to-signal power ratio and guard band. Furthermore, validation with three FADD receivers further demonstrates the superior performance of the proposed SI-DSB modulation in DSB-SCD systems. Full article

Zircaloy-4 is extensively used in nuclear reactors as fuel element cladding and core structural material. However, the safety concerns post-Fukushima underscore the need for further enhancing its high-temperature and high-pressure water-side corrosion resistance. Therefore, this study aimed to investigate the effects of high-current pulsed electron beam (HCPEB) irradiation on the microstructures and corrosion resistance of Zircaloy-4, with the goal of improving its performance in nuclear applications. Results showed that after irradiation, the cross-section of the sample could be divided into three distinct layers: the outermost melted layer (approximately 4.80 μm), the intermediate heat-affected zone, and the bottom normal matrix. Large numbers of twin martensites were induced within the melted layer, which became finer with increasing irradiation times. Additionally, plenty of ultrafine/nanoscale grains were observed on the surface of the sample pulsed 25 times. Zr(Fe, Cr)₂ second-phase particles (SPPs) were dissolved throughout the modified layer and Fe and Cr elements were uniformly distributed under the action of HCPEB. As a result, the corrosion resistance of the sample pulsed 25 times was significantly improved compared to the initial one. Research results confirmed that HCPEB irradiation is an effective method in improving the service life of Zircaloy-4 under extreme environmental conditions. Full article

The widespread adoption of arc additive manufacturing techniques across various industries has advanced the field of SS316L stainless steel manufacturing. It is crucial to acknowledge that different welding modes exert distinct influences on the forming and mechanical performance. This study analyzed the thermal input associated with four specific welding modes in LORCH MIG welding, clarifying the transition dynamics of molten droplets through waveform analysis and examining the resultant effects on microstructure and performance characteristics. The Pulse, Speed-Pulse-XT, and Twin-Pulse modes were found to induce spatter during the manufacturing process, consequently reducing molding efficiency in comparison to the SA-XT mode. Notably, the Twin-Pulse mode, characterized by double-pulse agitation, generated fish scale patterns along the lateral surfaces of the fabricated parts, promoting anisotropic grain growth. This microstructural refinement, compared to single-pulse samples with equivalent thermal input, resulted in enhanced mechanical properties. Nevertheless, the horizontal tensile strength of the three pulse modes was lower than the industrial standard for SA-XT mode and forging. In contrast, the SA-XT mode with an average hardness of 168.1 ± 6.9 HV and a tensile strength of 443.58 ± 5.7 MPa. Therefore, while three pulse modes offer certain microstructural advantages, the SA-XT mode demonstrates superior overall performance. Full article

Pulsed eddy current thermography can detect surface or subsurface defects in steel, but in the process of combining deep learning, it is expensive and inefficient to build a complete sample of defects due to the complexity of the actual industrial environment. Consequently, this study proposes a transfer learning method based on Twin-NMF and combines it with the SimAM attention mechanism to enhance the detection accuracy of the target domain task. First, to address the domain differences between the target domain task and the source domain samples, this study introduces a Twin-NMF transfer method. This approach reconstructs the feature space of both the source and target domains using twin non-negative matrix factorization and employs cosine similarity to measure the correlation between the features of these two domains. Secondly, this study integrates a parameter-free SimAM into the neck of the YOLOv8 model to enhance its capabilities in extracting and classifying steel surface defects, as well as to alleviate the precision collapse phenomenon associated with multi-scale defect recognition. The experimental results show that the proposed Twin-NMF model with SimAM improves the detection accuracy of steel surface defects. Taking NEU-DET and GC10-DET as source domains, respectively, in the ECTI dataset, mAP@0.5 reaches 99.3% and 99.2%, and the detection accuracy reaches 98% and 98.5%. Full article

According to the characteristics of the rotor system in an aero-engine and the vibrational test requirements of the aero-engine ground test, suitable vibration measurement sensors and test positions were selected. The vibration signals at the casings for the compressor and turbine of a twin-spool turbo-jet engine were collected under the states of maximum power and afterburning respectively, and the power spectrum analysis was carried out to determine the positions and causes of vibration. Furthermore, methods and preventive measures for eliminating vibration have been proposed. The results indicated that the main rotor vibration excited by mass imbalance in the twin-spool turbo-jet engine was significant. Rotor spindle misalignment or rotor radial stiffness unevenness also induced the vibration. The aerodynamic pulse vibration formed by the rotor blades of the first stage of the low pressure compressor was large, and rub induced vibration fault may occur at the turbine rotor seals. Based on the power spectrum analysis technology, the rotor system faults information including the type, position, and the degree can be quickly identified, and useful attempts and explorations have been made to reduce the vibration faults of the twin-spool turbo-jet engine. Full article

The relationship between acoustic parameters and the microstructure of a Cu30Zn brass plate subjected to plastic deformation was evaluated. The plate, previously annealed at 550 °C for 30 min, was cold rolled to reductions ranging from 10% to 70%. Linear ultrasonic measurements were performed on each of the nine specimens, corresponding to the nine different reductions, using the pulse-echo method to record the times of flight of longitudinal waves along the thickness axis. Subsequently, acoustic measurements were conducted to determine the nonlinear parameter $\beta$ through second harmonic generation. Microstructural analysis, carried out by X-ray diffraction, Vickers hardness testing, and optical microscopy, revealed an increase in deformation twins, reaching a maximum at 40% thickness reduction. At higher deformations, the microstructure showed the generation and proliferation of shear bands, coinciding with a decrease in the twinning structure and an increase in dislocation density. The longitudinal wave velocity exhibited a 0.9% decrease at 20% deformation, attributed to dislocations and initial twin formation, followed by a continuous increase up to 2% beyond this point, resulting from the combined effects of twinning and shear banding. The nonlinear parameter $\beta$ displayed a notable maximum, approximately one order of magnitude greater than its original value, at 40% deformation. This peak correlates with a roughly tenfold increase in twinning fault probability at the same deformation level. Full article

This paper proposes a novel welding process for ultrahigh-strength steel. The effects of welding parameters on the welding process and weld formation were studied to obtain the optimal parameter window. It was found that the metal transfer modes of solid wires were primarily determined by electrical parameters, while flux-cored wires consistently exhibited multiple droplets per pulse. The one droplet per pulse possessed better welding stability and weld formation, whereas the short-circuiting transfer or one droplet multiple pulses easily caused abnormal arc ignition that decreased welding stability, which could easily lead to a “sawtooth-shaped” weld formation or weld offset towards one side with more spatters. Thus, the electrical parameters corresponding to one droplet per pulse were identified as the optimal parameter window. Furthermore, the weld zone (WZ) was predominantly composed of AF, and the heat-affected zone (HAZ) primarily consisted of TM and LM. Consequently, the welded joint still exhibited excellent mechanical properties, particularly toughness, despite higher welding heat input. The average tensile strength reached 928 MPa, and the impact absorbed energy at −40 °C for the WZ and HAZ were 54 J and 126 J, respectively. In addition, the application of triple-wire welding for ultrahigh-strength steel (UHSS) demonstrated a significant enhancement in post-weld deposition rate, with increases of 106% and 38% compared to single-wire and twin-wire welding techniques, respectively. This process not only utilized flux-cored wire to enhance the mechanical properties of joints but also achieved high deposition rate welding. Full article

Aluminum–magnesium (Al–Mg) alloys, known for their lightweight properties, are extensively utilized and crucial in the advancement of wire and arc additive manufacturing (WAAM) for direct high-quality printing—a focal point in additive manufacturing research. This study employed 1.2 mm ER5356 welding wire as the raw material to fabricate two sets of 30-layer thin-walled structures. These sets were manufactured using two distinct welding modes, speed-twin pulse (STP) and twin pulse (TP). Comparative evaluations of the surface quality, microstructures, and mechanical properties of the two sets of samples indicated that both the STP and TP modes were suitable for the WAAM of Al–Mg alloys. Analyses of grain growth in the melt pools of both sample sets revealed a non-preferential grain orientation, with a mixed arrangement of equiaxed and columnar grains. The STP mode notably achieved a refined surface finish, a reduced grain size, and a slight increase in tensile strength compared to the TP mode. From the comparison of the tensile data at the bottom, middle, and top of the two groups of samples, the additive manufacturing process in the STP mode was more stable. Full article

Duplex stainless steels are materials with high performance under mechanical stress and stress corrosion in chloride ion environments. Despite being used in many new applications such as components for offshore drilling platforms as well as in the chemical and petrochemical industry, the automotive industry, etc., they face issues of wear and hardness that limit current applications and prevent the creation of new use opportunities. To address these shortcomings, it is proposed to develop a hardfacing process by a special welding technique using a universal TIG source adapted for manual welding with a pulsed current, and a manganese austenitic alloy electrode as filler material. The opportunity to deposit layers of manganese austenitic steel through welding creates advantages related to the possibility of achieving high mechanical characteristics of this steel exclusively in the working area of the part, while the substrate material will not undergo significant changes in chemical composition. As a result of the high strain hardening rate, assisted mainly by mechanical twinning, manganese austenitic alloys having a face-centered cubic crystal lattice (f.c.c) and low stacking fault energy (SFE = 20–40 mJ/m²) at room temperature, exhibit high wear resistance and exceptional toughness. Following cold deformation, the hardness of the deposited metal increases to 465 HV5–490 HV5. The microstructural characteristics were investigated through optical microscopy (OM), scanning electron microscopy (SEM), energy-dispersive X-ray analysis (EDX), X-ray diffraction (XRD), and Vickers hardness measurements (HV). The obtained results highlighted the feasibility of forming hard coatings on duplex stainless steel substrates. Full article

Ground-penetrating radar (GPR) is a non-invasive technology that uses electromagnetic pulses for subsurface exploration. In the railroad sector, it is crucial to assessing soil layers and infrastructure, offering insights into soil stratification and geological features and aiding in identifying subsurface hazards. However, the automation of radargram analysis is impeded by the lack of ground truth—accurate real-world data used to validate machine learning models—thus affecting the deployment of advanced algorithms. This study focuses on generating high-quality simulated data to address the shortage of real-world data in the context of object detection along railroad tracks and presents a fully automated pipeline that includes data generation, algorithm training, and validation using real-world data. By doing so, it paves the way for significantly easing the future task of object detection algorithms in the railway sector. A simulation environment, including the digital twin of a GPR antenna, was developed for artificial data generation. The process involves pre- and post-processing techniques to transform the three-dimensional data from the multichannel GPR system into two-dimensional datasets. This ensures minimal information loss and suitability for established two-dimensional object detection algorithms like the well-known YOLO (You Only Look Once) framework. Validation involved real-world measurements on a track with predefined buried objects. The entire pipeline, encompassing data generation, processing, training, and application, was automated for efficient algorithm testing and implementation. Artificial data show promise for better performance with increased training. Future AI and sensor advancements will enhance subsurface exploration, contributing to safer and more reliable railroad operations. Full article