Search Results (44)

The Kuroshio Current’s flow velocity imposes exacting requirements on underwater vehicle propulsive systems. Ecological preservation necessitates low-noise propeller designs to mitigate operational disturbances. As technological evolution advances toward greater intelligence and system integration, intelligent unmanned systems are positioning themselves as a critical frontier in marine innovation. In recent years, the global research community has increased its efforts towards the development of high-maneuverability underwater vehicles. However, propeller design optimization ignores the key balance between acoustic performance and hydrodynamic efficiency, as well as the appropriate speed threshold for blade rotation. In order to solve this problem, the propeller design of the NACA 65A010 airfoil is optimized by using OpenProp v3.3.4 and XFlow 2022 software, aiming at innovating the propulsion system of shallow water agile submersibles. The study presents an integrated design framework combining lattice Boltzmann method (LBM) simulations synergized with fully Lagrangian-LES modeling, implementing rotational speed thresholds to detect cavitation inception, followed by advanced acoustic propagation analysis. Through rigorous comparative assessment of hydrodynamic metrics, we establish an optimization protocol for propeller selection tailored to littoral zone operational demands. Studies have shown that increasing the number of propeller blades can reduce the single-blade load and delay cavitation, but too many blades will aggravate the complexity of the flow field, resulting in reduced efficiency and noise rebound. It is concluded that the propeller with five blades, a diameter of 234 mm, and a speed of 500 RPM exhibits the best performance. Under these conditions, the water efficiency is 69.01%, and the noise is the lowest, which basically realizes the balance between hydrodynamic efficiency and acoustic performance. This paradigm-shifting research carries substantial implications for next-generation marine vehicles, particularly in optimizing operational stealth and energy efficiency through intelligent propulsion architecture. Full article

Unmanned aerial vehicles (UAVs), commonly known as drones, offer unprecedented flexibility for complex missions such as area surveillance, search and rescue, and cooperative inspection. This paper presents a unified evaluation framework for the comparison of centralized and distributed task allocation algorithms specifically tailored to multi-UAV operations. We first contextualize the classical assignment problem (AP) under UAV mission constraints, including the flight time, propulsion energy capacity, and communication range, and evaluate optimal one-to-one solvers including the Hungarian algorithm, the Bertsekas $ϵ$-auction algorithm, and a minimum cost maximum flow formulation. To reflect the dynamic, uncertain environments that UAV fleets encounter, we extend our analysis to distributed multi-UAV task allocation (MUTA) methods. In particular, we examine the consensus-based bundle algorithm (CBBA) and a distributed auction 2-opt refinement strategy, both of which iteratively negotiate task bundles across UAVs to accommodate real-time task arrivals and intermittent connectivity. Finally, we outline how reinforcement learning (RL) can be incorporated to learn adaptive policies that balance energy efficiency and mission success under varying wind conditions and obstacle fields. Through simulations incorporating UAV-specific cost models and communication topologies, we assess each algorithm’s mission completion time, total energy expenditure, communication overhead, and resilience to UAV failures. Our results highlight the trade-off between strict optimality, which is suitable for small fleets in static scenarios, and scalable, robust coordination, necessary for large, dynamic multi-UAV deployments. Full article

This paper aims to analyze the performance of a tilt-rotor fixed-wing RPAS (Remotely Piloted Aircraft System) using a segmented approach, focusing on a nominal mission for SAR (Search and Rescue) applications. The study employs optimization techniques tailored to each segment to meet power consumption requirements, and the results highlight the accuracy of the physical characterization, which incorporates nonlinear propulsive and aerodynamic models derived from wind tunnel test campaigns. Critical segments for this nominal mission, such as the vertical take off or the transition from vertical to horizontal flight regimes, are addressed to fully understand the performance response of the aircraft. The proposed framework integrates experimental models into trajectory optimization procedures for each segment, enabling a realistic and modular analysis of energy use and aerodynamic performance. This approach provides valuable insights for both flight control design and future sizing iterations of convertible UAVs (Uncrewed Aerial Vehicles). Full article

As an innovative underwater propulsion technology, the rim-driven thruster (RDT) has garnered increasing attention due to its advantages over conventional diesel or gas turbine propulsion systems, including reduced noise, higher efficiency, and a compact structure. However, traditional hull–engine–propeller matching theories are not directly applicable to RDTs because of their unique shaftless and ducted characteristics. Based on conventional hull–engine–propeller matching theory and propeller design methodology, this study proposes a novel hull–engine–propeller matching approach tailored specifically to RDTs. The method enables rapid matching by using open-water characteristics for hull–engine–propeller matching. In the absence of open-water test data for shaftless propellers, key parameters derived from ducted propeller tests are used for matching based on open-water characteristics to design the shaftless propeller. The propeller is then optimized through computational fluid dynamics (CFD) simulations to achieve the required thrust performance, effectively enabling an equivalent replacement. The proposed method provides a practical framework for selecting and designing RDTs, improves overall propulsion efficiency, and offers specific guidelines for determining optimal motor design parameters. Full article

Composite solid propellants, which serve as the core energetic materials in aerospace and military propulsion systems, necessitate tailored enhancement of their mechanical properties to ensure operational safety and stability. A critical challenge involves elucidating the interfacial interactions among the multiple propellant components (≥6 components, including the polymer binder HTPB, curing agent IPDI, oxidizer particles AP/Al, bonding agents MAPO/T313, plasticizer DOS, etc.) and their influence on crosslinked network formation. In this study, we propose an integrated computational framework that combines coarse-grained simulations with reactive force fields to investigate these complex interactions at the molecular level. Our approach successfully elucidates the two-step reaction mechanism propagating along the AP interface in multicomponent propellants, comprising interfacial self-polymerization of bonding agents followed by the participation of curing agents in crosslinked network formation. Furthermore, we assess the mechanical performance through tensile simulations, systematically investigating both defect formation near the interface and the influence of key parameters, including the self-polymerization time, HTPB chain length, and IPDI content. Our results indicate that the rational selection of parameters enables the optimization of mechanical properties (e.g., ~20% synchronous improvement in tensile modulus and strength, achieved by selecting a side-chain ratio of 20%, a DOS molar ratio of 2.5%, a MAPO:T313 ratio of 1:2, a self-polymerization MAPO time of 260 ns, etc.). Overall, this study provides molecular-level insights into the structure–property relationships of composite propellants and offers a valuable computational framework for guided formulation optimization in propellant manufacturing. Full article

Bioinspired morphing offers a powerful route to higher aerodynamic and hydrodynamic efficiency. Birds reposition feathers, bats extend compliant membrane wings, and fish modulate fin stiffness, tailoring lift, drag, and thrust in real time. To capture these advantages, engineers are developing airfoils, rotor blades, and hydrofoils that actively change shape, reducing drag, improving maneuverability, and harvesting energy from unsteady flows. This review surveys over 296 studies, with primary emphasis on literature published between 2015 and 2025, distilling four biological archetypes—avian wing morphing, bat-wing elasticity, fish-fin compliance, and tubercled marine flippers—and tracing their translation into morphing aircraft, ornithopters, rotorcraft, unmanned aerial vehicles, and tidal or wave-energy converters. We compare experimental demonstrations and numerical simulations, identify consensus performance gains (up to 30% increase in lift-to-drag ratio, 4 dB noise reduction, and 15% boost in propulsive or power-capture efficiency), and analyze materials, actuation, control strategies, certification, and durability as the main barriers to deployment. Advances in multifunctional composites, electroactive polymers, and model-based adaptive control have moved prototypes from laboratory proof-of-concept toward field testing. Continued collaboration among biology, materials science, control engineering, and fluid dynamics is essential to unlock robust, scalable morphing technologies that meet future efficiency and sustainability targets. Full article

One of the challenges of our age is climate change and the ways in which it affects the Earth’s global ecosystem. To face the problems linked to such an issue, the international community has defined actions aimed at the reduction in greenhouse gas emissions in several sectors, including the aviation industry, which has been requested to mitigate its environmental impact. Conventional aircraft propulsion systems depend on fossil fuels, significantly contributing to global carbon emissions. For this reason, innovative propulsion technologies are needed to reduce aviation’s impact on the environment. Electric propulsion has emerged as a promising solution among the several innovative technologies introduced to face climate change challenges. It offers, in fact, a pathway to more sustainable air travel by eliminating direct greenhouse gas emissions, enhancing energy efficiency. Unfortunately, integrating electric motors into aircraft is currently a big challenge, primarily due to thermal management-related issues. Efficient heat dissipation is crucial to maintain optimal performance, reliability, and safety of the electric motor, but aeronautic applications are highly demanding in terms of power, so ad hoc Thermal Management Systems (TMSs) must be developed. The present paper explores the design and optimization of a TMS tailored for a megawatt electric motor in aviation, suitable for regional aircraft (~80 pax). The proposed system relies on coolant oil injected through a hollow shaft and radial tubes to directly reach hot spots and ensure effective heat distribution inside the permanent magnet cavity. The goal of this paper is to demonstrate how advanced TMS strategies can enhance operational efficiency and extend the lifespan of electric motors for aeronautic applications. The effectiveness of the radial tube configuration is assessed by means of advanced Computational Fluid Dynamics (CFD) analysis with the aim of verifying that the proposed design is able to maintain system thermal stability and prevent its overheating. Full article

Outboard Dynamic-inlet Waterjets (ODW) are axisymmetric units, powered by a self-contained pump, that, by processing a uniform undisturbed streamtube, can operate more efficiently than conventional marine propulsors. This feature also provides methodological convenience, enabling accurate numerical investigations of the system alone using 2D axisymmetric models. Leveraging this property, the present study bridges the gap on the design principles required to tailor ODW geometries across multiple operating conditions. Reynolds-Averaged Navier Stokes (RANS) equations are solved, including turbulence and cavitation models, to draw the propulsor’s characteristic maps and identify two relevant operating points, set by the combination of a specified pump rotational regime with an advancing velocity. Simulations for these in- and off-design conditions are systematically performed over a database of 512 randomly sampled geometric variants. The corresponding results show that optimised shapes improving the inlet Pressure Recovery (PR) and nacelle drag at cruise conditions result in beneficial outcomes also at take-off operations, where lip cavitation may occur. Thus, analysing together the off-design PR and the cruise net force underscores their conflicting behaviour. In fact, while nacelles shortened by $12\%$ can reduce overall drag and enhance nominal net thrust by $2\%$, designs featuring a $34\%$ wider capture area improve off-design PR by over $1.5\%$, albeit at the cost of compromised propulsive efficiency under any operating range. Full article

This study, set within the vast and varied research field of industrial Internet of Things (IoT) systems, proposes a methodology to address uncertainty quantification (UQ) issues in predictive maintenance (PdM) practices. At its core, this paper leverages the commercial modular aero-propulsion system simulation (CMAPSS) dataset to evaluate different artificial intelligence (AI) prognostic algorithms for remaining useful life (RUL) forecasting while supporting the estimation of a robust confidence interval (CI). The methodology primarily involves the comparison of statistical learning (SL), machine learning (ML), and deep learning (DL) techniques for each different scenario of the CMAPSS, evaluating the performances through a tailored metric, the S-score metric, and then benchmarking diverse conformal-based uncertainty estimation techniques, remarkably naive, weighted, and bootstrapping, offering a more suitable and reliable alternative to classical RUL prediction. The results obtained highlight the peculiarities and benefits of the conformal approach, despite probabilistic models favoring the adoption of complex models in cases where the operating conditions of the machine are multiple, and suggest the use of weighted conformal practices in non-exchangeability conditions while recommending bootstrapping alternatives for contexts with a more substantial presence of noise in the data. Full article

The proliferation of electric vehicle (EV) racing competitions, such as Formula electric vehicle (FEV) competitions, has intensified the quest for high-performance electric propulsion systems. High-speed permanent magnet synchronous motors (PMSMs) for FEVs necessitate an optimized control strategy that adeptly manages the complex interplay between electromagnetic torque production and minimal power loss, ensuring peak operational efficiency and performance stability across the full speed range. This paper delves into the optimization of high-speed PMSM, pivotal for its application in FEVs. It begins with a thorough overview of the FEV motor’s basic principles, followed by the derivation of a detailed mathematical model that lays the groundwork for subsequent analyses. Utilizing MATLAB/Simulink, a simulation model of the motor drive system was constructed. The proposed strategy synergizes the principles of maximum torque per ampere (MTPA) with the flux weakening control technique instead of conventional zero direct axis current (ZDAC), aiming to push the boundaries of motor performance while navigating the inherent limitations of high-speed operation. Covariance matrix adaptation evolution strategy (CMA-ES) was deployed to determine the optimal d-q axis current ratio achieving maximum operating torque without overdesign problems. The implementation of the optimized control strategy was rigorously tested on the simulation model, with subsequent validation conducted on a real test bench setup. The outcomes of the proposed technique reveal that the tailored control strategy significantly elevates motor torque performance by almost 22%, marking a pivotal advancement in the domain of high-speed PMSM. Full article

This paper presents the design and experimental evaluation of a throttleable pintle-centrifugal injector system tailored for hybrid rocket engines, aimed at improving combustion efficiency and enabling precise throttling control. The novel injector system combines the principles of swirl injection and pintle-based throttling, offering fine adjustment of oxidizer flow rates to optimize combustion dynamics. Cold-flow experiments using deionized water were conducted to assess the injector’s performance across a range of flow rates and pintle strokes. Results demonstrate that the pintle stroke effectively regulates injection pressure drop and atomization characteristics, with significant improvements observed in spray cone angle and droplet size distribution. The injector system achieved a pressure drop variation ratio of 4.162 at a flow rate adjustment ratio of 6.841, indicating a strong capacity for deep throttling. These findings highlight the potential of the pintle-centrifugal injector to enhance the performance and adaptability of hybrid rocket motors, offering promising applications in modern aerospace propulsion systems. Full article

To address the challenges in controlling a Tunnel Boring Machine (TBM) equipped with a V-type propulsion system during excavation, a digging attitude control strategy based on a nonlinear controller is introduced. First, the mathematical models of the V-type propulsion hydraulic system and the propulsion system’s attitude are developed, followed by an analysis of the system’s nonlinearities and susceptibility to strong disturbances. Second, a nonlinear control strategy tailored to the propulsion system’s characteristics is devised to regulate the digging attitude of the V-TBM. Finally, the proposed nonlinear control strategy is validated through comprehensive simulations and experimental evaluations. Simulation results demonstrate that the proposed nonlinear control strategy outperforms traditional PID control in attitude regulation performance. Field experiments reveal that the TBM achieves an average horizontal error of less than 20 mm and a vertical error of less than 22 mm in circular curve boring. This validates the strategy’s effectiveness in enabling rapid tracking and adjustment of the tunnel boring axis, meeting the stringent demands of small-radius curved boring. Full article

The bacterial flagellum serves as a crucial propulsion apparatus for motility and chemotaxis. Bacteria employ complex swimming patterns to perform essential biological tasks. These patterns involve transitions between distinct swimming states, driven by flagellar motor rotation, filament polymorphism, and variations in flagellar arrangement and configuration. Over the past two decades, advancements in fluorescence staining technology applied to bacterial flagella have led to the discovery of diverse bacterial movement states and intricate swimming patterns. This review provides a comprehensive overview of nano-filament observation methodologies, swimming states, swimming patterns, and the physical mechanisms underlying chemotaxis. These novel insights and ongoing research have the potential to inspire the design of innovative active devices tailored for operation in low-Reynolds-number environments. Full article

Energetic ionic liquids (EILs) have various industrial applications because they release chemically stored energy under certain conditions. They can avoid some environmental problems caused by traditionally used toxic fuels. EILs, which are environmentally friendly and safer, are emerging as an alternative source for hypergolic bipropellant fuels. This review focuses on the crucial thermophysical properties of the EILs. The properties of imidazolium and triazolium-based ionic liquids (ILs) are discussed here. The thermophysical properties addressed, such as glass transition temperature, viscosity, and thermal stability, are critical for designing EILs to meet the need for sustainable energy solutions. Imidazolium-based ILs have tunable physical properties making them ideal for use in energy storage while triazolium-based ILs have thermal stability and energetic potential. As a result, it is important to understand and compile thermophysical properties so they can help researchers synthesize tailored compounds with desirable characteristics, advancing their application in energy storage and propulsion technologies. Full article

Objective: The purpose of this study was to investigate differences in countermovement jump (CMJ) force–time metrics between male and female youth basketball players. Methods: Twenty-two female and seventeen male basketball players (ages 12–16) performed CMJs on a portable force plate system (VALD Performance). The data collected were analyzed for differences in force–time characteristics, specifically during the concentric and eccentric phases of the CMJ. Results: The results showed no statistically significant differences in anthropometric characteristics between the sexes. However, male athletes demonstrated better performance in several force–time metrics during the concentric phase of the CMJ, including concentric impulse, peak velocity, and mean power, ultimately leading to higher vertical jump heights. Sex-specific differences in the eccentric phase were less pronounced, though males exhibited greater relative eccentric mean power. Conclusions: The findings suggest that male players tend to display greater force and power-producing capabilities during the propulsive (concentric) phase of the CMJ. These differences highlight the importance of tailoring training programs to address specific needs, particularly focusing on enhancing concentric force and power production in female basketball players. Full article