Search Results (1,797)

The core objective of Active Vibration and Noise Control (AVNC) is to enhance system performance by generating real-time counter-phase signals of equal amplitude to cancel out vibration and noise interference from mechanical or structural systems. As the demand for low-noise, low-vibration environments grows in fields such as new energy vehicles (NEVs), aerospace, and high-precision manufacturing, traditional AVNC methods—which rely on precise linear models and have poor adaptability to nonlinear and time-varying conditions—struggle to meet the dynamic requirements of complex engineering scenarios. However, with advancements in artificial intelligence (AI) technology, AI-driven Active Vibration and Noise Control (AI-AVNC) technology has garnered significant attention from both industry and academia. Based on a thorough investigation into the state-of-the-art AI-AVNC methods, this survey has made the following contributions: (1) Introducing the theoretical foundations of AVNC and its historical development; (2) Classifying existing AI-AVNC methods from the perspective of control strategies; (3) Analyzing engineering applications of AI-AVNC; (4) Discussing current technical challenges and future development trends of AI-AVNC. Full article

Electromagnetic interference (EMI) represents a growing challenge in the modern era, as electronic systems and wireless technologies become increasingly integrated into daily life. This review provides a comprehensive overview of EMI, beginning with its historical evolution over centuries, from early power transmission systems and industrial machinery to today’s complex environment shaped by IoT, 5G, smart devices, and autonomous technologies. The diverse sources of EMI and their wide-ranging effects are examined, including disruptions in electrical and medical devices, ecological impacts on wildlife, and potential risks to human health. Beyond its technical and societal implications, the economic dimension of EMI is explored, highlighting the rapid expansion of the global shielding materials market and its forecasted growth driven by telecommunications, automotive, aerospace, and healthcare sectors. Preventative strategies against EMI are discussed, with particular emphasis on the role of advanced materials. Carbon-based nanomaterials—such as graphene, carbon nanotubes, and carbon foams—are presented as promising solutions owing to their exceptional conductivity, mechanical strength, tunable structure, and environmental sustainability. By uniting perspectives on EMI’s origins, consequences, market dynamics, and mitigation strategies, this work underscores the urgent need for scalable, high-performance, and eco-friendly shielding approaches. Special attention is given to recent advances in carbon-based nanomaterials, which are poised to play a transformative role in ensuring the safety, reliability, and sustainability of future electronic technologies. Full article

Pultrusion is a manufacturing process used to produce fiber-reinforced polymer composites with excellent mechanical, thermal, and chemical properties. The resulting materials are lightweight, durable, and corrosion-resistant, making them valuable in aerospace, automotive, construction, and energy sectors. However, conventional thermoset composites remain difficult to recycle due to their infusible and insoluble cross-linked structure. This review explores integrating vitrimer technology a novel class of recyclable thermosets with dynamic covalent adaptive networks into the pultrusion process. As only limited studies have directly reported vitrimer pultrusion to date, this review provides a forward-looking perspective, highlighting fundamental principles, challenges, and opportunities that can guide future development of recyclable high-performance composites. Vitrimers combine the mechanical strength (tensile strength and modulus) of thermosets with the reprocessability and reshaping of thermoplastics through dynamic bond exchange mechanisms. These polymers offer high-temperature reprocessability, self-healing, and closed-loop recyclability, where recycling efficiency can be evaluated by the recovery yield retention of mechanical properties and reuse cycles meeting the demand for sustainable manufacturing. Key aspects discussed include resin formulation, fiber impregnation, curing cycles, and die design for vitrimer systems. The temperature-dependent bond exchange reactions present challenges in achieving optimal curing and strong fiber–matrix adhesion. Recent studies indicate that vitrimer-based composites can maintain structural integrity while enabling recycling and repair, with mechanical performance such as flexural and tensile strength comparable to conventional composites. Incorporating vitrimer materials into pultrusion could enable high-performance, lightweight products for a circular economy. The remaining challenges include optimizing curing kinetics, improving interfacial adhesion, and scaling production for widespread industrial adoption. Full article

Cryogenic propellant sloshing presents significant challenges in aerospace systems, inducing vehicle instability, structural fatigue, energy losses, and complex thermal management issues. This review synthesizes experimental, analytical, and numerical advances with an emphasis on energy dissipation and conversion efficiency in propellant storage and transfer. Recent developments in computational fluid dynamics (CFD) and AI-driven digital-twin frameworks are critically examined alongside the influences of tank materials, baffle configurations, and operating conditions. Unlike conventional fluids, cryogenic propellants in microgravity and within composite overwrapped pressure vessels (COPVs) exhibit unique thermodynamic and dynamic couplings that remain only partially characterized. Prior reviews have typically treated these factors in isolation; here, they are unified through an integrated perspective linking cryogenic thermo-physics, reduced-gravity hydrodynamics, and fluid–structure interactions. Persistent research limitations are identified in the areas of data availability, model validation, and thermo-mechanical coupling fidelity, underscoring the need for scalable multi-physics approaches. This review’s contribution lies in consolidating these interdisciplinary domains while outlining a roadmap toward experimentally validated, AI-augmented digital-twin architectures for improved energy efficiency, reliability, and propellant stability in next-generation aerospace missions. Full article

Micro-combustion-powered thermoelectric generators (μ-CPTEGs) combine the high energy density of hydrocarbons with solid-state conversion, offering compact and refuelable power for long-endurance electronics. Such characteristics make μ-CPTEGs particularly promising for aerospace systems, where conventional batteries face serious limitations. Their achievable performance hinges on how a swirl-stabilized flame transfers heat into the hot ends of thermoelectric modules. This study uses a conjugate CFD framework coupled with a lumped parameter model to examine how input power and equivalence ratio shape the flame/flow structure, temperature fields, and hot-end heating in a swirl combustor-powered TEG. Three-dimensional numerical simulations were performed for the swirl combustor-powered TEG, varying the input power from 1269 to 1854 W and the equivalence ratio from φ = 0.6 to 1.1. Results indicate that the combustor exit forms a robust “annular jet with central recirculation” structure that organizes a V-shaped region of high modeled heat release responsible for flame stabilization and preheating. At φ = 1.0, increasing Q_in from 1269 to 1854 W strengthens the V-shaped hot band and warms the wall-attached recirculation. Heating penetrates deeper into the finned cavity, and the central-plane peak temperature rises from 2281 to 2339 K (≈2.5%). Consistent with these field changes, the lower TEM pair near the outlet heats more strongly than the upper module (517 K to 629 K vs. 451 K to 543 K); the inter-row gap widens from 66 K to 86 K, and the incremental temperature gains taper at the highest power, while the axial organization of the field remains essentially unchanged. At fixed Q_in = 1854 W, raising φ from 0.6 to 1.0 compacts and retracts the reaction band toward the exit and weakens axial penetration; the main-zone temperature increases up to φ = 0.9 and then declines for richer mixtures (peak 2482 K at φ = 0.9 to 2289 K at φ = 1.1), cooling the fin section due to reduced transport, thereby identifying φ = 0.9 as the operating point that best balances axial penetration against dilution/convective-cooling losses and maximizes the TEM hot-end temperature at the fixed power. Full article

Magnesium alloys, characterized by high specific strength and low density, have high potential for applications in transportation and aerospace. Nevertheless, ensuring the reliable joining of thin-walled components remains a major technical challenge. This study examines how rotational speed affects the microstructure and mechanical properties of friction stir welded AZ61 magnesium alloy hollow profiles (3 mm thick), with particular focus on the underlying mechanisms. The results show that higher rotational speed during friction stir welding promotes dynamic recrystallization and weakens the basal texture. It also affects microstructural homogeneity, where an optimal rotational speed produces a relatively uniform hybrid microstructure consisting of refined recrystallized and un-recrystallized regions. This balance enhances both texture strengthening and microstructural optimization. The weld joint fabricated at a rotational speed of 1500 rpm showed the best overall mechanical properties, with ultimate tensile strength, yield strength, and elongation reaching peak values of 286.7 MPa, 154.7 MPa, and 9.7%, respectively. At this speed, the average grain size in the weld nugget zone was 4.92 μm, and the volume fraction of second-phase particles was 0.67%. This study establishes a critical process foundation for the reliable joining of thin-walled magnesium alloy structures. The optimized parameters serve as valuable guidelines for engineering applications in lightweight transportation equipment and aerospace manufacturing. Full article

Aluminum alloy surface microstructures possess functional characteristics such as hydrophilicity/hydrophobicity and anti-icing and have important applications in fields such as aerospace and power systems. In order to improve the filling quality of the microstructure and verify the anti-icing property of the microstructure, this work develops a scheme for achieving large-area hot embossing of anti-icing functional microstructures based on a multi-arc ion-plating mold. Compared with conventional steel, the hardness of the PVD-coated steel increases by 44.7%, the friction coefficient decreases by 66.2%, and the wear resistance is significantly enhanced. The PVD-coated punch-assisted embossing could significantly improve filling properties. While the embossing temperature is 300 °C, the PVD-coated punch-assisted embossing can ensure the complete filling of the micro-array channels. In contrast, under-filling defects occur in conventional hot embossing. Then, a large-area micro-channel specimen of 100 cm² was precisely formed without warping, and the average surface roughness Ra was better than 0.8 µm. The maximum freezing fraction of the micro-array channel was reduced by about 53.2% compared with the planar, and the complete freezing time was delayed by 193.3%. The main reason is that the air layer trapped by the hydrophobic structures hinders heat loss at the solid–liquid interface. Full article

Surface coating materials have many applications in various sectors, such as aerospace, medical technology, packaging, and construction, due to their unique properties, including self-healing, corrosion resistance, and protection from external factors. Their use not only enhances the durability and lifespan of surfaces but also their functionality and esthetic value. These coatings can be effective barriers against moisture, oxygen, chemicals, and the growth of microorganisms, which makes them indispensable in industries where reliability and safety are paramount. In the aerospace sector, they provide protection at extreme temperatures and limit component wear. Special coatings in biomedicine improve implant compatibility and prevent bacterial adhesion. In packaging, they extend the shelf life of products, while in construction they prevent the degradation of structural elements. This review article examines the major categories of these materials, as well as their advantages and limitations, and demonstrates a comparative evaluation of their use in certain applications. Full article

This article presents the technology of automated placement of an injection molding gate based on a parametric optimization algorithm with technological constraints consideration. The algorithm is based on the modification of the genetic algorithm using the criterion of maximum equivalent stresses on the weld line as an optimization criterion. The proposed software’s modular structure combines the authors’ modules that implement a new optimization algorithm with the ANSYS 2022R1 and Moldflow calculation kernels called via API interfaces. This structure provides an opportunity to implement developed technology to solve industrial problems using standard mesh generation tools and complex geometric models due to the flexibility of modules and computing kernel scalability. The consideration of the technological constraints allows us to reduce the population size and optimization problem solution computational time to 1.9 times. The developed algorithms are used to solve the gate location optimization problem using the example of an aerospace bracket made of short-reinforced composite material with a nonzero genus surface and a weld line. The use of the proposed technology made it possible to increase the strength of the studied structure by two times. Full article

Flange bolts are vital fasteners in civil, mechanical, and aerospace structures, where preload stability directly affects overall safety. Conventional methods for bolt loosening detection often suffer from missed detections, weak feature representation, and insufficient cross-scale fusion under complex backgrounds. This paper presents an integrated detection and angle estimation framework using a lightweight deep learning detection network. A MobileViT backbone is employed to balance local texture with global context. In the spatial pyramid pooling stage, large separable convolutional kernels are combined with a channel and spatial attention mechanism to highlight discriminative features while suppressing noise. Together with content-aware upsampling and bidirectional multi-scale feature fusion, the network achieves high accuracy in detecting small and low-contrast targets while maintaining real-time performance. For angle estimation, the framework adopts an efficient training-free pipeline consisting of oriented FAST and rotated BRIEF feature detection, approximate nearest neighbor matching, and robust sample consensus fitting. This approach reliably removes false correspondences and extracts stable rotation components, maintaining success rates between 85% and 93% with an average error close to one degree, even under reflection, blur, or moderate viewpoint changes. Experimental validation demonstrates strong stability in detection and angular estimation under varying illumination and texture conditions, with a favorable balance between computational efficiency and practical applicability. This study provides a practical, intelligent, and deployable solution for bolt loosening detection, supporting the safe operation of large-scale equipment and infrastructure. Full article

This study investigates the fatigue performance of 3D-printed metal shafts fabricated via Wire Arc Additive Manufacturing (WAAM) with stacked steel ring substrates under rotating bending (ISO 1143:2021). A Taguchi L25 orthogonal array was used to analyze five process parameters: ring diameter, current intensity, torch speed, ring thickness, and contact tip to workpiece distance (CTWD). Analysis of Variance (ANOVA) identified ring diameter as the dominant factor, significantly enhancing fatigue life at 14.0 mm by reducing stress concentrations. Current intensity (125 A) and torch speed (550 mm/min) further improve weld quality and microstructure, while ring thickness (1.0 mm) and CTWD (1.5 mm) have minor effects. A linear regression model (R² = 0.9603) accurately predicts fatigue life, with optimal settings yielding 299,730 cycles. The stacked-ring configuration enables intricate structures like cooling channels, ideal for aerospace and automotive applications. The 3.5% unexplained variance suggests parameter interactions, warranting further investigation into shielding gas effects and multiaxial loading to broaden material and loading applicability. Full article

As typical examples of rotational rate sensors, microelectromechanical system (MEMS) gyroscopes have been widely applied as inertial devices in various fields, including national defense, aerospace, healthcare, etc. This review systematically summarizes research advancements in MEMS gyroscope structural forms and processing technologies, which are evaluated through performance indices. The review encompasses several areas. First, it outlines the modelling principles and processes of gyroscopes on the basis of the Coriolis force and resonance, establishing a theoretical foundation for MEMS gyroscope development. Second, it introduces and analyzes the latest research advances in MEMS gyroscope structures and corresponding processing technologies. On the basis of published research advances, this review categorically discusses multidisciplinary technology properties, statistical results, the existence of errors, and compensation methods. Additionally, it identifies challenges in MEMS gyroscope technologies through classification analysis. Full article

Accurate aircraft trajectory prediction is fundamental to air traffic management, operational safety, and intelligent aerospace systems. With the growing availability of flight data, deep learning has emerged as a powerful tool for modeling the spatiotemporal complexity of 4D trajectories. This paper presents a comprehensive review of deep learning-based approaches for aircraft trajectory prediction, focusing on their evolution, taxonomy, performance, and future directions. We classify existing models into five groups—RNN-based, attention-based, generative, graph-based, and hybrid and integrated models—and evaluate them using standardized metrics such as the RMSE, MAE, ADE, and FDE. Common datasets, including ADS-B and OpenSky, are summarized, along with the prevailing evaluation metrics. Beyond model comparison, we discuss real-world applications in anomaly detection, decision support, and real-time air traffic management, and highlight ongoing challenges such as data standardization, multimodal integration, uncertainty quantification, and self-supervised learning. This review provides a structured taxonomy and forward-looking perspectives, offering valuable insights for researchers and practitioners working to advance next-generation trajectory prediction technologies. Full article

The origin of life initiated an evolutionary continuum yielding biologically optimized systems capable of operating under extreme environmental constraints. Biomimetics, defined as the systematic abstraction and transfer of biological principles into engineering domains, has become a strategic design paradigm for addressing the multifactorial challenges of space systems. This study introduces two core contributions to formally establish the discipline of Aerospace Bionic Robotics (ABR): First, it elucidates the relevance of biologically derived functionalities such as autonomy, adaptability, and multifunctionality to enhance the efficiency of space robotic platforms operating in microgravity environments. Second, it proposed the BEAM-D (Biomimetic Engineering and Aerospace Mechatronics Design), a standard for the development of Aerospace Bionic Robotics. By integrating biological abstraction levels (morphological, functional, and behavioral) with engineering protocols including ISO, VDI, and NASA’s TRL, BEAM-D enables a structured design pathway encompassing subsystem specification, cyber–physical integration, in situ testing, and full-scale mission deployment. It is implemented through a modular BEAM-DX framework and reinforced by iterative BIOX design steps. This study thus establishes formalized bio-inspired design tools for advanced orbital and planetary robotic systems capable of sustained autonomous operations in deep space exploration scenarios. Full article

JP-10 (exo-tetrahydrodicyclopentadiene) is a high-energy-density hydrocarbon broadly used in advanced aerospace propulsion as a regenerative cooling fluid; in this study, we aimed to clarify how fuel pressure affects its thermal degradation (oxidative and pyrolytic) in near-isothermal flowing reactor. Experiments were performed under oxidative conditions (wall temperature 623.15 K, p = 0.708–6.816 MPa) and pyrolytic conditions (wall temperature 793.15 K, p = 2.706–7.165 MPa); carbon deposits were quantified by LECO analysis, oxidation activity was assessed by temperature-programmed oxidation (TPO), and morphology was performed by FESEM and EDS. Results show that oxidative coking is minimal (5.37–14.95 μg·cm²) and largely insensitive to pressure in the liquid phase (1.882–6.816 MPa), whereas at 0.708 MPa (gas/phase-change conditions), deposition increases, implicating phase and local heat-transfer effects. Under oxidative conditions, deposits are predominantly amorphous carbon with a disordered structure, formed at relatively low temperatures, with only a few fiber-like metal sulfides identified by EDS. In contrast, under pyrolysis conditions, the deposits are predominantly carbon nanotubes, exhibiting well-defined tubular morphology formed at elevated temperatures via metal-catalyzed growth. The pyrolysis coking yield is substantially higher (66.88–221.89 μg·cm⁻²) and increases with pressure. The findings imply that the pressure influences the coking of JP-10 via phase state under oxidative conditions and residence time under pyrolytic conditions, while basic morphologies of coke deposits remain similar; operationally, maintaining the working pressure higher than the saturated vapor pressure can mitigate oxidation coking associated with phase transitions, and minimizing residence time can mitigate pyrolytic coking. Full article