Search Results (4,150)

This study numerically investigates the flow characteristics of submerged impinging jets at a standoff distance of H/d = 3. The computational analysis is performed utilizing large eddy simulation (LES) alongside the one-equation Wray-Agarwal and the two-equation SST k-ω and RNG k-ε turbulence models. The current work emphasizes the hydrodynamic structures developing in the unconfined jet region and the variations in flow behavior at the stagnation zone across a range of impact angles (θ ≤ 90°) at Re (Reynolds number) = 23,400. Compared with PIV data, the Wray-Agarwal model accurately predicts the free-jet flow, whereas the RNG k-ε model excels in the wall-jet region. As the impingement angle increases, the pressure distribution calculated by the LES method gradually approaches the experimental results. When the impinging angle θ = 90°, LES has high prediction accuracy in both regions. In general, under the grid scheme used in this study, RNG k-ε can make a more accurate prediction of the average characteristics of the submerged impinging jet flow field. Full article

The multi-finger robotic hand offers great potential for precise control due to its high degrees of freedom. Yet, manipulating objects forms a closed-chain kinematic system, which compounds the dimensionality and computational complexity of trajectory tracking. To tackle this challenge, and inspired by the widespread application of the zeroing neurodynamics (ZND) in robotic control, this study proposes a novel direct-discrete robust neurodynamics (DDRN) algorithm. The proposed algorithm advances the ZND methodology by employing a direct discretization design strategy. This strategy is crucial for two reasons. First, it fits naturally with the discrete-time nature of digital systems, enabling practical implementation. Second, it enhances precision by avoiding the integration errors inherent in continuous-to-discrete transformations. By simultaneously integrating this direct discretization with explicit noise suppression mechanisms, the DDRN algorithm efficiently solves the high-dimensional tracking problem formulated as a constrained time-varying quadratic programming (CTVQP) problem. Theoretical analyses demonstrate that under various noise environments, the steady-state residuals (SSRs) achieve global convergence, guaranteeing the algorithm’s strong robustness and high accuracy. Furthermore, comprehensive numerical simulations substantiate its superior performance. Practically, this DDRN algorithm enables more reliable and precise real-time control of dexterous robotic hands, with potential benefits for advanced manufacturing, prosthetic hands, and automated assembly where accurate trajectory tracking under sensor noise is critical. Full article

Plant extracts are widely used as natural pesticides, cosmetic ingredients, and in pharmaceutical applications. However, their poor water solubility and stability limit their usability. Lipid nanoparticles (LNPs) offer an effective encapsulation strategy to overcome these challenges. This study demonstrates the encapsulation of three representative substances from these industries: quercetin as a pesticide, irones as a cosmetic ingredient, and nucleic acids for pharmaceutical use. Ultrasonic treatment was used for the encapsulation of quercetin and irones, and a concept for continuous encapsulation in a plug flow reactor was proposed for process intensification. Inline multi-angle light scattering and dynamic light scattering measurements proved effective for real-time monitoring and enabled the replacement of traditional batch measurements. In the pharmaceutical area, mRNA-based therapies require LNP encapsulation to prevent nucleic acid degradation. Plant-based β-sitosterol was used as an alternative helper lipid to cholesterol, resulting in an average particle diameter of 72 nm and an encapsulation efficiency of 91%, comparable to commercial formulations such as the Comirnaty vaccine. Furthermore, a novel process model based on population balances was developed to simulate the entire manufacturing process, from rapid mixing in a T-mixer to particle stabilization via buffer exchange during diafiltration. By applying a quantitative and distinctive model validation workflow, the model was shown to be as accurate and precise as the experimental data, enabling its use as a digital twin for autonomous continuous operation. In summary, this study contributes to reducing the facility footprint and cost of goods through the implementation of continuous processing and model-based control. This approach improves productivity by 20% and reduces process time by a factor of two. Full article

Additive manufacturing has emerged as a powerful approach for producing architected materials with tailored mechanical properties and enhanced energy absorption capabilities. By enabling precise control over geometry, relative density, and hierarchical topology, additive manufacturing facilitates the design of lightweight cellular structures with superior crashworthiness compared to conventional energy-absorbing materials. This review provides a comprehensive overview of recent advances in additively manufactured energy-absorbing structures, with particular emphasis on the interplay between structural architecture, fabrication technologies, and mechanical performance. Key additive manufacturing processes, including fused deposition modeling, stereolithography, selective laser sintering, and multi-jet fusion, are evaluated in terms of their fabrication capabilities, material compatibility, and inherent limitations. Special attention is given to the mechanical behavior of representative architectures, including two-dimensional cellular structures, three-dimensional lattice geometries, sandwich systems, and emerging four-dimensional programmable materials. Depending on topology and material system, additively manufactured lattices can achieve specific energy absorption values exceeding 20–40 J g⁻¹, significantly outperforming many conventional foams. Finally, current challenges, such as process-induced defects, anisotropic mechanical behavior, and the lack of standardized testing methodologies, are discussed, along with future research directions, including multi-material printing, functionally graded architectures, and adaptive metamaterials for next-generation impact mitigation systems. Full article

Pelvic organ prolapse (POP) is a common benign gynecological disorder that substantially affects quality of life, particularly in aging female populations. Current management strategies, including standardized vaginal pessaries and synthetic surgical meshes, are often limited by poor anatomical adaptability, mechanical mismatch with native pelvic tissues, and long-term safety concerns. These limitations have driven increasing interest in personalized and biomechanically compatible therapeutic solutions. Three-dimensional (3D) printing, also known as additive manufacturing, has emerged as a promising bioengineering technology to address these unmet clinical needs. By enabling layer-by-layer fabrication directly from digital models, 3D printing allows for precise control over device geometry, mechanical properties, and material composition, facilitating patient-specific design. This narrative review summarizes recent progress in 3D printing for POP management across three major application domains: (i) next-generation meshes based on biodegradable polymers, elastomeric materials, natural biomaterials, and hydrogel systems; (ii) customized vaginal pessaries tailored to individual pelvic anatomy using imaging-assisted workflows; and (iii) imaging-based pelvic models and prototype devices for surgical planning, education, and exploratory assessment. Overall, existing studies demonstrate that 3D printing enables improved biomechanical compatibility, enhanced tissue integration, and multifunctional device design, including drug delivery capability. Although current evidence is largely pre-clinical or based on pilot studies, additive manufacturing holds strong potential to advance POP management toward safer, personalized, and functionally optimized clinical solutions. Full article

Sapphire, with excellent optical properties and high hardness, has become a key hard and brittle material component in extreme environments like aviation equipment and infrared detection systems. Its processing quality directly determines the performance of various equipment systems. To address processing defects, technologies such as multi-wire cutting, magnetorheological polishing, chemical mechanical polishing, femtosecond laser processing, and ion beam etching have been developed and studied to improve the surface quality of sapphire components. This paper focuses on key technologies, including sapphire’s nano-scale surface morphology control, intrinsic nano-surface atomic-level defect control, and combined process systems for precision and shape control. These technologies lay the foundation for sapphire components’ process chain manufacturing to achieve high-precision shape and surface quality control. Full article

This work presents an experimental aerodynamic study of a Mars rover model, aimed at characterizing its flow behavior under Martian environmental conditions. Due to the extremely low Reynolds numbers associated with Mars’ thin atmosphere, the experiments were conducted using a scaled model of the rover manufactured via additive techniques. The study first focuses on understanding how the geometry of the rover influences the overall flow field, identifying key aerodynamic features such as separation zones, vortical structures, and flow reattachment regions driven by the complexity of the vehicle. A comprehensive investigation of the flow around the model was performed using both a hydrodynamic towing tank with dye injection for qualitative visualization, and particle image velocimetry (PIV) for quantitative flow field analysis in wind tunnel tests. After the general flow characterization, a more detailed local analysis was conducted using laser Doppler anemometry (LDA). This phase of the study targeted precise velocity measurements at specific locations corresponding to the MEDA (Mars Environmental Dynamics Analyzer) wind sensors onboard the rover. Quantitative results indicate that the central body induces a local flow acceleration of 20% to 40% relative to the free stream while severe turbulence was recorded in specific angular sectors, with velocity fluctuations reaching up to 120% for Sensor 1 and 90% for Sensor 2. Full article

Minimally invasive surgery (MIS) has transformed modern surgical operations by reducing pain, trauma, scarring and recovery time for the patient. However, precision, stability and accuracy continue to limit surgical performance. Robots can exhibit better precision and stability than humans and have the potential to improve MIS results. This work presents the design and development of a patented 3R1T parallel robot for MIS. The mechanism incorporates a coaxial spherical parallel architecture enabling three rotational degrees of freedom, combined with a remotely actuated translational fourth degree of freedom, therefore reducing the weight of the moving structure, decreasing inertial forces and increasing the system accuracy. The kinematic design is analyzed to achieve the required workspace, motor torque requirements are calculated, and a control system with integrated inverse kinematics is developed. A prototype was manufactured, and preliminary experiments were conducted to evaluate the orientation repeatability of the robot. Results demonstrated a repeatability of ±22.86 μm, commensurate with typical MIS constraints. This suggests that the proposed robot offers potential improvements in precision and control for minimally invasive surgical procedures, over traditional manual methods. Full article

Cancer remains a primary global health challenge, accounting for millions of new cases and significant mortality annually. Although doxorubicin (DOX) is a fundamental anthracycline used for various malignancies, its therapeutic index is severely limited by poor selectivity, systemic toxicity, and dose-dependent cardiotoxicity. To address these issues, Janus nanoparticles (JNPs) have emerged as a promising bifunctional platform characterized by a structural asymmetry that allows for the independent functionalization of each hemisphere. This review examines primary fabrication routes—such as masking, microfluidics, self-assembly, and phase separation—and their specific applications in DOX delivery. The anisotropic architecture of JNPs enables a “separate rooms” concept, allowing for the co-delivery of incompatible drugs while facilitating multi-stimuli-responsive release mechanisms triggered by pH, enzymes, or NIR light. Furthermore, JNPs have demonstrated enhanced tumor accumulation and reduced systemic toxicity compared to conventional isotropic carriers. Recent developments even highlight the use of autonomous nanomotors to improve therapeutic delivery while minimizing premature leakage. However, clinical translation is currently hindered by manufacturing complexity, high equipment costs, scalability issues, and a lack of standardized reporting in the literature. Ultimately, JNPs represent a sophisticated frontier in precision oncology, though robust manufacturing processes and characterization protocols are required for future medical adoption. Full article

Ensuring the structural integrity and service reliability of railway wheels has become a key challenge in modern manufacturing and maintenance strategies within the railway sector. In this context, Eddy Current (EC)-based Non-Destructive Testing (NDT) provides an automated and efficient approach for detecting surface and near-surface defects, while reducing inspection time and operator dependency compared to conventional manual methods. This study presents the integration of an EC inspection system into a precision lathe, enabling in-machining evaluation during wheel turning. Experimental validation was conducted on wheels with artificial defects, yielding high signal-to-noise ratios and enabling reliable defect characterization. Furthermore, computationally efficient and easily deployable machine learning algorithms were developed to enable automatic defect detection, localization, and size estimation. The results confirm the feasibility of in-machine EC inspection during machining operations, enabling early defect detection and contributing to safer, more efficient, and higher-quality manufacturing processes in the railway sector. Full article

This review systematically analyzes the technological progress, structural characteristics, and performance disparities among various diamond grinding wheel bond systems, aiming to establish a unified performance evaluation framework. This framework clarifies material selection criteria and highlights promising research directions. Eight prevalent bond systems are encompassed: resin, metal, ceramic, brazing, electroplating, composite, additive manufacturing, and glass-ceramics. A comparative analysis of these systems is conducted across multiple dimensions. Key evaluation metrics primarily include bond strength, thermal stability, self-sharpening capability, thermal conductivity, and formability. Considerable variations in these indicators are observed across the different bonding agents. Each system presents distinct advantages alongside inherent limitations. Within the constructed multi-metric framework, glass-ceramic bonding agents demonstrate high comprehensive potential in critical aspects such as bond strength and thermal stability, underscoring their research value as a novel high-performance bond system. Current primary challenges focus on the regulation of crystallization kinetics, the design of interfacial reaction layers, and multiscale performance prediction. Future research may advance along several paths. Synergistic design of material composition and microstructure is essential, while in-depth investigation into multiphysics coupling mechanisms remains necessary. Furthermore, data-driven material optimization methods are poised to unlock new possibilities for bond development. These approaches are expected to facilitate the precise design and application of high-performance diamond grinding wheel bonds. Full article

The segregation of brittle Laves phases remains a critical bottleneck limiting the performance of additive manufacturing (AM) nickel-based superalloys. While its evolution is governed by complex transient physical fields within the melt pool, a quantitative kinetic correlation between processing parameters and microstructural features is currently lacking. In this study, a high-fidelity multiphysics numerical model was developed to establish a cross-scale mapping logic of “Process-Physical Field-Microstructure” by dissecting the global distribution of temperature gradient (G) and solidification rate (R) along the quasi-steady-state melt pool boundary. It is revealed that increasing the scanning speed synergistically enhances R while compressing G. Beyond driving a transition from oriented columnar dendrites to refined mixed-dendritic structures, this shift effectively blocks the continuous enrichment channels of Nb and Mo elements by compressing the “kinetic time window” for solute redistribution. Consequently, the morphology of the Laves phase is forced to evolve from a continuous interconnected chain-like network into dispersed isolated particles. This research clarifies the kinetic essence of microstructural evolution under non-equilibrium solidification, providing critical physical criteria for the precise intervention of deleterious phases and the regulation of microstructural consistency in high-performance AM components. Full article

Servo electric cylinders have been widely adopted in high-performance linear drive applications such as aerospace systems, robotic servo systems, medical equipment, advanced manufacturing, precision testing, and high-end equipment due to their advantages, including high cleanliness, compact structure, high transmission efficiency, and ease of achieving precise control. However, under complex operating conditions, system performance is influenced not only by control strategies but also closely related to factors such as friction, clearance, transmission flexibility, structural vibrations, and modeling accuracy. This paper reviews mainstream control strategies and dynamic simulation methods for servo electric cylinders, providing structured analysis and systematic evaluation of representative research. In terms of control strategies, key approaches, including classical PID control, robust nonlinear control, intelligent and learning-based control, and active disturbance rejection control, are discussed, with comparative analysis of their characteristics and limitations in tracking accuracy, robustness, adaptability, and engineering feasibility. Regarding dynamic modeling and simulation, methods such as multibody dynamics, finite element analysis, rigid-flexible coupling, and multi-domain collaborative simulation are reviewed, examining their applicability in nonlinear mechanism characterization, local structural response assessment, and high-fidelity system modeling. Current research indicates that servo cylinder control is evolving from single-method improvements toward integrated and composite approaches, while dynamic modeling has progressed from low-order simplified analyses to system-level, multi-level, and high-fidelity descriptions. Existing studies still face challenges, including insufficient unified evaluation criteria, inadequate cross-method comparisons, and insufficient integration between control design and high-fidelity models. Future research should focus on enhancing control-model co-design, experimental validation under complex conditions, and system-level optimization oriented toward intelligent and high-reliability systems. Full article

Age-related macular degeneration (AMD) is the most common cause of blindness and vision impairment in individuals over 60 years of age in the United States (US). Despite this, current treatment options have limitations related to drug efficacy and durability. Gene therapy provides a potential solution by providing a more durable and longer- acting treatment option that can decrease treatment burden and improve long-term visual outcomes. This review presents the current treatment approaches, routes of administration, and vectors being investigated for gene therapy delivery in AMD. It also provides an update on the ongoing gene therapy clinical trials for dry and wet AMD. As these therapies advance into later-stage clinical trials, ophthalmologists need to be mindful of the many challenges pertaining to gene therapy delivery, including safety, limitations related to immunogenicity, long-term ocular and systemic side effects, and potential barriers to drug manufacturing and access. Continued efforts are required to improve precision, safety, and efficacy, including identifying the safest and most effective vectors and delivery routes, and minimizing potential adverse effects. In addition, guidelines need to be established to guide appropriate patient selection before gene therapy can be integrated into clinical practice. Full article

The structural integrity of bogie frames is a critical factor in the safety and reliability of railway rolling stock, requiring advanced assessment methods to handle complex, multi-axial stress states. This research presents a robust numerical framework for the preliminary fatigue evaluation of a metro bogie frame, integrating high-fidelity Finite Element Analysis (FEA) with the Findley multi-axial fatigue criterion. The methodology overcomes the limitations of traditional uniaxial verification methods by employing a localized critical plane approach, implemented through a proprietary computational code. The investigation simulates a realistic operational scenario by superimposing a static vertical load of 15 tons per side with dynamic components derived from on-track accelerometric data. This integrated loading condition enables a precise reproduction of the “rotating” stress states typically encountered in service. Global structural analysis identified critical transverse welded joints as high-stress concentration zones, which were then subjected to a detailed multi-axial investigation. By correlating the extracted stress tensors with the resistance category included in the reference standard, over a regulatory life of 10 million cycles, a maximum cumulative damage index of 0.4602 was recorded. The results demonstrate that while the frame possesses adequate structural reserves, nearly half of its fatigue life is consumed in localized nodes. This methodology provides a reliable and computationally efficient tool for the structural health monitoring and development of innovative railway geometries, offering a superior predictive capability that remains scarcely utilized by major rolling stock manufacturers. Full article