Search Results (111)

A provenance-audited load transfer and structural screening workflow is presented for a 28 g, 25 Hz hummingbird-inspired mechanism. A saved unsteady vortex lattice case is linked to Autodesk Inventor load curves and motion load-informed static studies. The Curve_Example_90 record describes a 90 mm semi-span wing under prescribed 25 Hz kinematics. Its cycle 3–4 phasewise vector RMS difference is 0.0466 N (53.1% of the final-cycle vector RMS), so the latest complete cycle supports deterministic export rather than aerodynamic convergence. Positive-span panel forces were summed, transformed into Inventor axes, and interpolated without amplitude scaling; the maximum exported resultant is 0.17599 N. A normalized 16-position index map is declared between saved aerodynamic time and Inventor report time, but the retained files do not prove an encoder-defined absolute stroke-phase origin. All 96 intended component–phase records are identity-qualified. The aluminium 6061 maxima are 14.82 MPa for the force bar, 6.98 MPa for the wing-link bar, and 0.0134 MPa for the motion bar. Corrected PLA properties are serialized in the latest force bar link and wing bar reports, while the rotation pin report retains obsolete material metadata. Solution timestamps, displacements, and safety factors further show that the polymer export mixes refreshed and cached states, so polymer capacity is withheld. The common three-pass adaptive mesh setting improves within-study refinement but is not an independent mesh convergence study. The study is an empirical-to-numerical hypothesis check and design fault screen, not an aerodynamic or structural optimisation campaign; mesh-converged capacity, synchronized force/deformation validation, and print-calibrated material claims remain outside its evidence boundary. Full article

An understanding of vortex formation in stirred tank reactors is of great importance, as in some processes, vortices are necessary for a chemical reaction to take place at all or to be accelerated, whilst in other processes, vortex formation is undesirable and can cause high mechanical stresses on the stirrer shaft, sealing and motor drive unit, or may cause undesirable surface aeration or foaming. To gain a better understanding of vortex formation, various baffle systems with different geometries are being experimentally investigated concerning power consumption and the resulting vortices on a single-stage Rushton turbine setup. The shapes of the resulting vortices are described mathematically in terms of vortex depth, width and volume, and the stirring systems prone to vortex formation are simulated using a CFD model based on the Lattice Boltzmann method. The CFD data obtained are compared, validated and verified against the experimental results in order to ultimately be able to fully describe, model and predict vortex formation through simulation. Furthermore, based on the detailed CFD data, vortex formation can be directly correlated with the swirl number, offering a mechanistic characterization method for the vortex shape in various mixing vessel configurations. Full article

In the present work, an alternative methodology was developed for the rapid prediction of pressure distributions over wings of low-speed aircraft. A hybrid neural network architecture, named “MARTHA” (Model for Airloads Reconstruction using a Trained Hybrid Architecture), was presented, which is composed of a Multilayer Perceptron and the decoder of an Autoencoder. Three compact representation models—Principal Component Analysis (PCA), Autoencoder (AE), and Variational Autoencoder (VAE)—were systematically evaluated to determine the optimal dimensionality reduction architecture; the AE was selected based on its superior reconstruction accuracy and training stability. The main feature of MARTHA is that it provides predictions of the differential pressure coefficient field in the form of monochrome images, where the pixel intensity directly represents the normalized pressure value. One of the main objectives of developing MARTHA was to create a rapid surrogate model that can approximate vortex lattice method (VLM) simulations in preliminary design and optimization tasks, particularly when thousands of wing configurations need to be evaluated. The key feature of the proposed model is its ability to predict the pressure distribution for trapezoidal wings of various geometries 10¹–10⁴ times faster than numerical models, while maintaining accuracy (R² = 0.9998). The data obtained are presented in a convenient format for their further use in CAE systems of strength analysis. To assess the practical utility of the proposed model, implementation cases were carried out using the finite element software ANSYS 18.2 for three wing configurations not present in the training dataset. The pressure fields predicted by MARTHA were mapped onto the wing meshes, and linear static structural analyses were performed. The obtained Von Mises stress distributions showed good agreement with the corresponding distributions obtained using numerical models. Full article

Coherent vortices alter flapping-foil energy harvesting, but wake-generated vortex properties and timing are coupled to upstream-body kinematics. We use two-dimensional immersed boundary–lattice Boltzmann simulations of a prescribed heaving–pitching NACA0015 foil at $Re=1100$. An independently prescribed Taylor vortex allows nominal encounter phase, body-fixed offset, diameter, and intensity to be varied at fixed kinematics. Production-grid ${\overline{C}}_P$ is within $0.10\%$ of the fine-grid result; the fine-grid diffusion test gives a maximum full-field velocity $L_2$ error of $0.0690\%$ against the analytical solution over $0\le t^{*}\le 4$. For the reference vortex with a pivot-centered nominal target ($D/c=v_{\theta m}/U_{\infty }=1$), nominal-encounter-aligned mean power coefficients of $0.747$, $0.862$, and $0.987$ occur at ${\psi }_e=0.10$, $0.40$, and $0.60$, respectively, compared with $0.832$ without gusts. These define the power-reducing (PR), near-baseline (NB), and power-enhancing (PE) cases. Within the sampled ranges, diameter is associated mainly with disturbance reach and duration, intensity with loading magnitude, and offset with spatial overlap and interaction timing. Power variations are consistent with the timing of vortex-modified loading relative to prescribed foil motion. In three same-sign, once-per-cycle sequences, the PR–NB–PE ordering persists despite residual-wake interactions, with sustained mean power coefficients of $0.763$, $0.916$, and $0.965$, respectively. Nominal encounter phase and foil placement should be considered jointly for repeatable or predictable vortex passages. Full article

Panel-based aeroelasticity models are commonly used to conduct mid-fidelity aeroelastic analysis. The unsteady vortex lattice method (UVLM) in particular is used when non-linear aerodynamic corrections are needed, for example by utilizing the $\alpha$-convergence method. While this method is well tested for non-linear corrections in high-Reynolds transonic flows for both steady and unsteady cases, its effectiveness has not been well researched in unsteady low-Reynolds flows. This paper tests the effectiveness of the $\alpha$-convergence method in this regime by comparing modeling results with original wind tunnel test results. In the steady aeroelastic displacement tests, the aerodynamic non-linearity improved the modeling results significantly, with an error under $\pm 10\%$ at all tested angles of attack, compared to a maximum error of $-30.8\%$ for the aerodynamically linear models. In the flutter test case, the aerodynamic non-linearity had less of an impact, with structural non-linearity being more important in this case. However, the maximum flutter speed error for the aerodynamically non-linear model was still lower, at $-14.4\%$, compared to $+19.6\%$ for the aerodynamically linear model. Full article

The lubrication performance of high-speed transmission systems directly affects mechanical power consumption and operational reliability. During high-speed oil-stirring lubrication, strong gas–liquid interfacial shear, liquid-film deformation, droplet splashing, and oil-mist transport generate an unsteady multiphase turbulent flow field. Conventional continuum-based numerical methods often face difficulties in resolving interface breakup and transient turbulent dissipation under high-speed rotational excitation. To address this problem, this study develops a coupled Lattice Boltzmann–Large Eddy Simulation (LBM–LES) method for oil–air two-phase flow in a high-speed oil-stirring lubrication system. The D3Q27 discrete velocity model, cumulant collision operator, WALE subgrid-scale model, free-surface tracking, and local grid refinement are integrated to analyze free-surface deformation, oil-mist evolution, and power-loss characteristics. Taking a notched toothless oil-stirring disk as the reference configuration, the effects of oil immersion depth and disk topology on gas–liquid phase distribution, oil-mist coverage, power consumption, and vortex-induced energy dissipation are investigated. The results indicate that oil immersion depth has a nonlinear influence on lubrication performance and power loss. Among the investigated cases, an immersion depth of 20 mm provides a favorable balance between upper-region oil-mist coverage and lower-region oil-pool stability. At this depth, the notched disk exhibits directional oil delivery and relatively low power consumption, whereas the double-rhombus structure expands the oil-mist coverage but increases the average power consumption to approximately 175 W. These findings provide numerical support for balancing oil-mist coverage, mechanical power consumption, and disk topology design in high-speed transmission lubrication systems. Full article

The distributed electric propulsion (DEP) system offers significant potential for enhancing aerodynamic efficiency, reducing emissions, and enabling innovative aerodynamic configurations. However, the strong coupling between propeller slipstream effects and wing structural dynamics presents new challenges for aeroelastic analysis. To address this issue, this paper proposes an aeroelastic modeling approach tailored for DEP systems that systematically accounts for the effects induced by propeller slipstreams. Specifically, the induced velocity generated by the propeller slipstreams is computed using a slipstream tube model and incorporated into the unsteady aerodynamic modeling via the unsteady vortex lattice method. Under appropriate assumptions, a state-space formulation of the unsteady aerodynamic forces is derived, while the wing structural dynamics are represented using the finite element method. After establishing the subsystem models, a complete aeroelastic model of the DEP system is assembled based on the input–output relationships among the subsystems. Nonlinear simulations are conducted using this integrated model. The results demonstrate the potential of distributed propellers for suppressing wing vibrations and alleviating structural loads. Full article

Flapping-wing flight offers a promising solution for aerial mobility in low-density environments such as the Martian atmosphere, where conventional rotorcraft faces significant performance constraints. However, the coupled aerodynamic and structural mechanisms governing lift generation at low Reynolds numbers remain insufficiently understood. This study investigates the aeroelastic and unsteady aerodynamic behaviour of a bio-inspired flapping wing using an integrated experimental–numerical framework. High-speed imaging is employed to extract representative wing kinematics, including flapping frequency, stroke amplitude, and rotational motion. A geometrically scaled wing model is developed based on Reynolds number similitude and analysed using finite element methods to characterise its dynamic response. Aeroelastic behaviour is evaluated through modal transient simulations, while aerodynamic performance is assessed using both vortex-lattice modelling and computational fluid dynamics. The results show strong coupling between bending and torsional modes, with the structural response highly dependent on excitation frequency relative to the natural modes. Near-resonant conditions lead to amplified deformation and distinct phase relationships, while aerodynamic simulations reveal vortex-dominated lift generation. These findings provide a physics-based framework for the design and analysis of flapping-wing systems operating in low-Reynolds-number and low-density flight regimes. Full article

The mechanism by which fish enhance hydrodynamic performance through collective swimming is a research hotspot in the field of underwater bionic robots. This study employs the Immersed Boundary-Lattice Boltzmann Method (IB-LBM) to conduct numerical simulations on a two-dimensional, single-degree-of-freedom (1-DOF) autonomous propulsion bionic fish swarm. It systematically investigates the effects of swarm size and inter-individual spacing on swimming speed and cost of transport (CoT) under two typical configurations: series and parallel arrangements. Findings reveal that hydrodynamic benefits are highly dependent on the spatiotemporal evolution of flow field structures. In the series configuration, an optimal spacing range of 1.5 L to 2.0 L exists within the school, where the “wake capture” effect is pronounced. Trailing fish achieve a maximum speed increase of approximately 41.1% while significantly reducing energy consumption. However, as spacing increases to 2.5 L, the cooperative gain for front and middle-row individuals rapidly diminishes, and the lead fish even experiences significant performance loss. Uniquely, the trailing fish in the four-fish formation exhibits distinct flow field reorganization and performance recovery at the 4.5 L trailing position. In the parallel formation, the “channel effect” and “blocking effect” of the fluid dominate. The study identifies 0.4 L laterally as the critical instability spacing under the investigated kinematic regime, where strong destructive interference causes a sharp deterioration in individual swimming performance. Additionally, the parallel formation exhibits pronounced positional differentiation. Central individuals, constrained by dual lateral flow fields, experience restricted lateral wake expansion and accelerated energy dissipation, resulting in significantly weaker escape capabilities from low-speed conditions compared to marginal individuals. The vortex-dynamic mechanism revealed herein provides theoretical foundations for formation control in multi-fish biomimetic cooperative systems. Full article

Introduction: Lattice Radiation Therapy (LRT) is an evolving spatially fractionated radiation therapy (SFRT) technique that delivers heterogeneous dose distributions to large and radioresistant tumors. The literature highlights LRT’s potential for effective tumor debulking, palliation, and immune modulation. Effective LRT planning is crucial for maximizing tumor control while minimizing toxicity to organs at risk (OARs). The process involves defining the size, spacing, and arrangement of high-dose vortexes within the GTV. Traditionally, this has been a manual and time-consuming process, prone to inter-planner variability in vortex placement. Recent research has focused on developing automated or semi-automated tools to address these challenges, enhancing planning standardization. We aimed to systematically review for the first time the available scientific evidence of automated planning tools of vortexes for Lattice Radiotherapy and to assess the efficacy of such tools for standardizing Lattice Radiotherapy delivery. Methods: A systematic review of available studies in PubMed, Web of Science, and Scopus, including the terms “Lattice radiation therapy and (automated or optimized)”. Only LRT clinical planning reports published in English and with access to the full accepted text were considered eligible. This study was conducted in accordance with the PRISMA guidelines and was registered on the PROSPERO platform (CRD420251108024). Results: A total of 82 articles were found. Twenty articles fulfilled all inclusion criteria. Automated treatment planning tools have significantly improved the efficiency, consistency, and scalability of LRT planning, addressing limitations of manual planning. In conclusion, LRT should be planned to use automated tools to improve wide clinical standardization and implementation. Full article

Fast and reliable aerodynamic predictions are crucial in the early phases of aircraft design, where a quick assessment of various configurations is required. In this context, the Vortex Lattice Method (VLM) is widely adopted due to its computational efficiency; however, its predictive accuracy is highly sensitive to panel discretization strategies, which are often determined heuristically. This study proposes a bio-inspired optimization framework for VLM panel discretization and evaluates it through a systematic case study on a representative wing geometry. A grid-convergence analysis was initially carried out to ensure solution independence across various spanwise-to-chordwise panel ratios. Subsequently, a novel Hybrid Response Surface Methodology (HRSM), integrating Box–Behnken and Central Composite experimental designs, was employed to enable a more comprehensive exploration of the factor space while quantifying the effects of clustering parameters at the leading-edge, trailing-edge, root, and tip regions of the wing. The HRSM dataset was further utilized to train Ensemble Machine-Learning surrogate models, which were coupled with bio-inspired Crayfish and Aquila optimization algorithms, alongside a classical Genetic Algorithm (GA) as a performance benchmark, to identify the optimal discretization strategy and to enable a comparative assessment of their convergence behavior and robustness against the numerical noise of the ensemble-based landscape. Compared to base (i.e., uniform) panel distribution, the optimally clustered discretization enhanced overall aerodynamic prediction accuracy by approximately 33%, particularly at low angles of attack, while maintaining robust performance at higher angles. Both algorithms converged to similar minima; however, the Aquila algorithm achieved higher solution consistency, whereas the Crayfish algorithm exhibited greater dispersion despite faster convergence, revealing a multimodal optimization landscape. The variance decomposition revealed that trailing-edge clustering dominated aerodynamic accuracy at low angles of attack, contributing up to 90% of the total variance, whereas tip clustering became increasingly influential at higher angles, exceeding 30%, highlighting the need for adaptive discretization strategies to ensure reliable VLM-based aerodynamic analyses. Full article

Recently, continuous improvements in aircraft manoeuvrability and fuel consumption reduction have led researchers to investigate additional wing configurations based on morphing concepts. Morphing is also a potential solution for noise level reduction and may therefore represent an additional benefit. The advantages of morph-type schemes over traditional control surfaces during specific manoeuvres become a key parameter in the preliminary design stage. In this work, three types of airfoil morphing applied to a typical basic wing are considered and analysed: leading-edge morphing, trailing-edge morphing, and rib twist. The aerodynamic performance of each configuration is evaluated through a numerical procedure combining a panel method and a vortex lattice method. Drag reduction in morphed versus conventional wings under identical flight conditions is quantified, allowing the identification of the most efficient configuration. The analyses consider both roll manoeuvres and high-lift flight phases by evaluating changes in design parameters—such as chord-wise hinge positions, span-wise morph distribution, and morphing angles—which are compared and discussed. For the rolling manoeuvre, increasing the span-wise morphing region improves drag reduction, but not by more than 5%. When shifting the hinge position from 60% to 80% of the chord, similar drag reduction levels can be achieved, although the required morph angle differs under the same conditions. The effect of different drag components is also assessed, showing that the induced drag component is predominant for low aspect ratio wings, whereas parasite drag becomes significant at higher aspect ratios. Optimal geometrical configurations are presented and discussed for both manoeuvres. For the rolling, hinge positions yielding typical rolling moment coefficients (i.e., −0.05, −0.06, and −0.08) lie between 65% and 75% of the chord, with span-wise morphing ranges 40% < y_rib < 60% producing drag reduction up to 40% compared with a conventional wing. For the high-lift conditions, configurations between 65% < x_hinge < 80% and 50% < y_rib < 90% allow a drag reduction which can go up to 60%. Another beneficial effect is also observed for the yawing moment coefficient C_n with a reduction of more than 20% for larger aileron surfaces. Full article

With the electrification of automotive powertrains, aerodynamic noise has emerged as the primary factor affecting vehicle comfort. This systematic review, adhering to PRISMA 2020 guidelines, bridges the gap between biological fluid mechanics and automotive engineering by synthesizing recent advances in aerodynamic mechanisms and bionic control strategies. Based on a comprehensive search of Web of Science, ScienceDirect, SAE Mobilus, and Google Scholar for the literature published between 2016 and 2025, 90 eligible studies were analyzed to provide a rigorous evidence-based synthesis. The review details complex flow phenomena, such as turbulent separation and vortex shedding across key regions like A-pillars and mirrors, drawing parallels to bio-inspired fluid–structure interactions. Numerical prediction methods, including large eddy simulation (LES), detached eddy simulation (DES), and lattice boltzmann method (LBM), are critically examined for their efficacy in resolving both conventional and bionic flow structures. A significant focus is placed on bio-inspired mitigation technologies, where quantitative findings demonstrate substantial noise suppression: specifically, the reviewed data shows that bionic riblet surfaces on tires can reduce noise levels by up to 5.18 dB, while beetle-head-inspired protuberances on exterior mirrors can achieve reductions of up to 10 dB. Finally, this work suggests future research directions in integrated fluid–acoustic–structural simulation frameworks and self-adaptive bionic systems, providing a robust reference for developing high-performance, low-noise vehicles inspired by natural organisms. Full article

During liquid drainage from intermediate vessels in various industrial processes such as continuous steel casting, aircraft fuel supply, and chemical separation, free-surface vortices commonly occur. The formation and evolution of these vortices not only entrain surface slag and gas, but also lead to deterioration of downstream product quality and abnormal equipment operation. The vortex evolution process exhibits notable three-dimensional unsteadiness, multi-scale turbulence, and dynamic gas–liquid interfacial changes, accompanied by strong coupling effects between temperature gradients and flow field structures. Traditional macroscopic numerical models show clear limitations in accurately capturing these complex physical mechanisms. To address these challenges, this study developed a mesoscopic numerical model for gas-liquid two-phase vortex flow based on the lattice Boltzmann method. The model systematically reveals the dynamic behavior during vortex evolution and the multi-field coupling mechanism with the temperature field while providing an in-depth analysis of how initial perturbation velocity regulates vortex intensity and stability. The results indicate that vortex evolution begins near the bottom drain outlet, with the tangential velocity distribution conforming to the theoretical Rankine vortex model. The vortex core velocity during the critical penetration stage is significantly higher than that during the initial depression stage. An increase in the initial perturbation velocity not only enhances vortex intensity and induces low-frequency oscillations of the vortex core but also markedly promotes the global convective heat transfer process. With regard to the temperature field, an increase in fluid temperature reduces the viscosity coefficient, thereby weakening viscous dissipation effects, which accelerates vortex development and prolongs drainage time. Meanwhile, the vortex structure—through the induction of Taylor vortices and a spiral pumping effect—drives shear mixing and radial thermal diffusion between fluid regions at different temperatures, leading to dynamic reconstruction and homogenization of the temperature field. The outcomes of this study not only provide a solid theoretical foundation for understanding the generation, evolution, and heat transfer mechanisms of vortices under industrial thermal conditions, but also offer clear engineering guidance for practical production-enabling optimized operational parameters to suppress vortices and enhance drainage efficiency. Full article

Due to the complexity of aerodynamic coupling between the duct and propeller, the overall design and optimization of ducted fans often require extensive experience and time. Meanwhile, traditional design methods based on Blade Element Momentum Theory, Lifting Surface Theory, Vortex Lattice Methods, and Panel Method usually exhibit certain deviations between their design results and actual outcomes. This is because these approaches struggle to accurately calculate the aerodynamic coupling effects between the duct and propeller, coupled with numerous simplifications inherent in the methods themselves. Considering the strong nonlinear coupling relationship between the duct and propeller, the Response Surface Method (RSM), which enables efficient and accurate analysis of multi-variable coupling effects, was selected for the parameter design and optimization of ducted fans. Computational Fluid Dynamics (CFD) was applied to evaluate the impact of design parameters on overall aerodynamic performance. This approach addresses the limitations of traditional methods, including low design accuracy, high computational cost, and insufficient multi–objective optimization capability. It explicitly models multi-parameter coupling and nonlinear effects using a small number of experimental points, combined with the Multi-Objective Genetic Algorithm (MOGA) to find the global optimum. Compared to the baseline duct fan, the optimized duct fan achieved a 9.6% increase in overall lift and a 9.5% improvement in lift efficiency. Full article