Understanding how ambient wind shear influences the transport of microdroplets is crucial for assessing airborne infection risks in realistic outdoor environments, where shear and turbulence are unavoidable yet often oversimplified. In this study, we perform direct numerical simulations of tiny particles transported in homogeneous shear turbulence across a range of shear Reynolds numbers (Rez) from which we reveal pronounced anisotropic transmission characteristics. First, particle trajectories exhibit a transition from ballistic to diffusive behavior in the lateral directions, while streamwise transport remains ballistic due to mean shear advection. The probability density function of particle displacements exhibits a universal collapse when normalized by time-dependent mean and standard deviation, indicating robust statistical self-similarity. Detailed scaling analysis shows that the standard deviation along the lateral direction grows linearly before transitioning to √(t) scaling. In contrast, along streamwise direction, the standard deviation of displacement follows t2 scaling initially and transitions to a superdiffusive scaling t3/2, consistently across all Rez. The shear-induced enhancement of particle transmission can be understood by analyzing statistical moments. Based on these insights, we develop a simplified infection risk model using a well-mixed, joint-Gaussian assumption. The model captures essential features of anisotropic particle transmission under shear. It predicts that higher Rez enhances downstream transport and accelerates dilution, it also shortens spread time, leading to a larger but less concentrated infectious zone. These findings highlight the critical role of wind shear in modulating airborne disease transmission and underscore the need to incorporate realistic flow conditions into public health risk assessments beyond classical uniform-wind assumptions.
Wrinkling patterns across length scales are widely observed in film-substrate biological systems, and play an important role in maintaining essential bio-functions. Prestrain induced by heterogeneous growth is ubiquitous in living systems, especially in layered soft biological tissues. Here, we comprehensively investigate the influence of prestrain on the growth-induced wrinkling instability and post-buckling evolution of the film-substrate biological systems, through quantitative swelling experiments, theoretical analysis, and numerical simulations. Both experimental observation and theoretical analysis demonstrate that not only the wrinkling pattern but also the post-buckling amplitude can be prescribed by manipulating prestrain. The larger the prestrain value, the deeper the growth-induced wrinkles. Besides, the quantitative wrinkling experiments are in excellent agreement with our theoretical predictions across various conditions. The phase diagram for bifurcation type shows that the supercritical and subcritical bifurcations occur only depending on the normalized thickness and modulus. Both experimental and numerical results reveal that further growth/compression could trigger a secondary bifurcation of the emerging wrinkling patterns and lead to a period-doubling morphology in the film-substrate systems. This study not only deepens our understanding of the morphogenesis and evolution of some film-substrate biological tissues and organs, but also paves a promising way for the fabrication of morphology-related functional surfaces.
This paper presents a modeling approach for the rigid-elastic coupling flutter of flying-wing aircraft with ground effect taken into account. The paper begins with the formulation of a set of nonlinear coupled dynamic equations using Lagrange equations in terms of quasi-coordinates, with structural dynamics represented by the nodal coordinates of a finite element model and aerodynamic loads expressed through aerodynamic derivative matrices. These matrices are solvable from the unsteady vortex lattice method combined with the step response method, while the ground effect comes from mirror-image vortices. The linearization of the nonlinear dynamic equations enables the analysis of static aeroelastic trim and rigid-elastic coupling flutter for aircraft with ground effect. Numerical simulations of a flexible flying-wing aircraft indicate that the ground effect increases the frequency gap between the short-period mode and the first symmetric bending mode, thereby weakening rigid-elastic coupling and delaying the onset of flutter. From an energy-transfer perspective, ground effect reduces the net positive aerodynamic work associated with elastic bending, despite preserving the phase condition for aerodynamic excitation. Overall, the proposed method provides an effective framework for aeroelastic analysis of flexible aircraft operating near the ground and offers new insights into how ground effect modifies flutter characteristics.
In response to the future demand for efficient and simplified high-lift configuration in civil aircraft, this study numerically investigates flow control on a swept-back multi-element wing using synthetic jets. To elucidate the differences in control mechanisms between two-dimensional and three-dimensional flows, we focus on the crossflow effect on the flow control mechanism by comparing the results on straight and swept wing configurations. The results show that the crossflow effect plays a crucial role in flow control. The swept wing achieves a lift gain of 10.7
The unique riverbed profiles and bending reaches of the more than 2000-year-old Dujiangyan Irrigation System (DIS) guarantee relatively stable water supply to the Chengdu Plain, China, with minimal sediment. Similarly, the human aorta buffers the cardiac-induced pulsatile flow through Windkessel effect and reduces the thrombus transport to cerebral vessels through swirling effect of blood flow. This study employs computational simulations and in vitro experiments to analyze the shared hydrodynamic principles between both systems. A three-dimensional (3D) model of the Inner River of DIS was constructed based on data obtained with large-scale prototype observation system. In parallel, 3D aorta models were reconstructed based on medical images, incorporating lumped parameter models as boundary conditions. Both flow pulsatility and helicity-dependent mass transport (sediment in DIS vs. thrombus in aorta) were quantitatively compared. The results have, for the first time, confirmed the amazing similarities in flow characteristics between the DIS and human aorta. The findings provide novel insights for advancing aortic disease therapies and endovascular device design, while opening new perspectives for addressing challenges in flood and sediment management.
Predicting and understanding quench in high-temperature superconducting (HTS) materials pose significant challenges due to strong nonlinearity from extreme multifield coupling at cryogenic temperatures, as well the phase transition from the superconducting state to the normal one. Accurately determining the occurrence and location of a quench in HTS tapes, triggered by thermal disturbances, is crucial for advancing superconducting applications, as it requires solving a complex inversion problem. This study develops a deep learning framework to solve this inverse problem for predicting quench phenomena in YBCO tapes. We first construct a coupled forward model based on thermoelastic quench theory to simulate the quench onset and generate a high-fidelity dataset. A convolutional neural network is then designed to directly map temperature and strain distributions to the characteristics of the thermal disturbance, including its location, average power, and duration. The model, trained solely on physics-based simulation data, achieves exceptional performance with a mean relative error of less than 3
The vibration issues in various mechanical equipment and architectural structures have gradually developed into two directions: vibration control and vibration utilization. Developing better engineering structures and system models is a crucial step in realizing vibration control and utilization. A novel magnet-array quasi-zero stiffness energy-harvesting vibration isolator (MQZS EVI) is proposed; it mainly consists of three parallel negative stiffness mechanisms (NSMs), three series-connected electromagnetic shunt damping, and three parallel spring positive stiffness mechanisms. Firstly, the magnetic force analytical model of the electromagnetic NSM is established using the filament method and the finite element method. Structural parameter optimization analysis is then conducted for the NSM. Secondly, the dynamic equations of the MQZS EVI system are formulated. The vibration isolation performance and energy-harvesting characteristics of the MQZS EVI system are evaluated using the harmonic balance method and the pseudo-arc length continuation method. Finally, a prototype is manufactured and tested. The experimental results demonstrate that the MQZS EVI system can effectively isolate ultra-low-frequency vibrations while simultaneously capturing energy from low-frequency vibrations.
Heterogeneous thin films inherently exhibit directional adhesion, where the peeling force increases when peeled in the soft-to-stiff direction and decreases when peeled in the opposite direction compared to their homogeneous counterparts. This unique property offers a basis for designing smart adhesion systems requiring both strong attachment and easy detachment. However, heterogeneous thin films with sharp interfaces suffer from poor adhesion stability and robustness. The maximum peeling force is highly sensitive to the cohesive zone between the thin film and substrate, reducing adhesion robustness. Moreover, a sudden big drop in peeling force happens immediately after the sharp interface, reflecting its poor adhesion stability. Inspired by the gradient designs in adhesive microstructures of beetles and geckos, we propose a bioinspired gradient-interface design for the heterogeneous thin films. A theoretical model is developed to describe the peeling behavior of the gradient-interface heterogeneous thin films. Our results show that gradient interfaces maintain the directional adhesion property while significantly mitigating the impact of cohesive zones on the maximum peeling force, thus enhancing adhesion robustness. With analogy to the redundant design in engineering, three indices are introduced to quantitatively characterize the adhesion strength and stability of practical interest: the half-peak peeling force, the half-peak peeling-zone length, and the half-peak fracture energy. Comparative analysis reveals that the optimal gradient magnitude depends on the gradient form and interface energy. This study uncovers the mechanisms behind robust and stable directional adhesion with gradient-interface heterogeneous thin films and provides valuable insights for the design of smart adhesion systems with strong attachment and easy detachment.
This review summarizes the mechanical properties of key ocular structures (cornea, sclera, lens, and vitreous) and systematically evaluates the measurement techniques and data discrepancies. We review here experimental methods for ocular injury loading and three types of injury models: isolated eyeball model, orbit-eyeball model, and head-eyeball model. The construction of numerical ocular models and their application in simulation experiments are analyzed. Based on experimental and simulation results, for blunt eye injuries, the severity of the impact and the resulting damage are influenced by factors such as the mass of the impacting object, its velocity at the time of impact, and the contact area with the eye. For instance, larger masses, higher velocities, and smaller contact areas tend to cause more severe injuries, often extending to the posterior segment of the eye. Therefore, we categorized impactors into less than orbit (LOI) and greater than orbit (GOI), examining their distinct deformation patterns and injury characteristics during loading. For explosive impacts, we analyzed the shockwave propagation path and pressure distribution across structures to elucidate the corresponding injury mechanisms. We further established an eye injury assessment index based on speed and overpressure. The eye rupture thresholds for LOI and GOI are set at 60 and 30 m/s respectively; for shock wave loading, when the overpressure exceeds 0.25 MPa, it will cause relatively severe damage, while when the overpressure is greater than 0.6 MPa, it may lead to severe injuries such as eye rupture. Additionally, recommendations for optimizing measurement, experimental, and simulation methods are provided for future research.
The novelty of this work lies in the analysis of dovetail, rectangular, and trapezoidal porous fins under dehumidification conditions using the differential transformation method (DTM), where condensation effects and latent heat release are explicitly incorporated to capture realistic thermal behaviour. In this study, the thermal performance and efficiency of aluminium and copper fins with these profiles are investigated by formulating the governing nonlinear ordinary differential equation incorporating Darcy’s law for porous media. The equation is solved analytically using DTM to obtain accurate solutions for temperature distribution and efficiency variations across different fin geometries and materials. The results reveal that fin with a higher taper ratio exhibit reduced temperature and efficiency due to increased thermal resistance and limited conduction at the base, while higher relative humidity decreases the performance as excess surface moisture suppresses the driving gradient for condensation-induced latent heat release. Among the profiles, the dovetail fin demonstrates good performance owing to its larger effective surface area and improved heat retention, the trapezoidal fin exhibits the lowest performance due to higher thermal resistance, and the rectangular fin displays intermediate characteristics. Copper fin with superior thermal conductivity enhances heat retention and efficiency, while aluminium fin offers advantages in lightweight design and corrosion resistance. These findings highlight the combined role of geometry, material, and dehumidification in governing fin performance and provide practical guidelines for designing efficient heat exchangers and thermal management systems.
During vehicle operation, road-induced vertical vibrations excite coupled whole-body dynamic responses in occupants, resulting in ergonomic concerns such as motion-induced fatigue and diminished comfort. This study develops lumped parameter models with multiple degrees of freedom to systematically investigate the formation mechanism of coupling responses in seated humans under vertical excitation, thereby overcoming the limitations of conventional single-axis models. Three stiffness and damping distribution patterns (Models A, B, and C) are proposed based on biomechanical characteristics. Parameter identification demonstrates that the linear dynamic properties of the torso (Model B) predominantly govern the frequency-domain characteristics of the coupling response. Moreover, an enhanced model (Model D) is introduced, for the first time, to quantitatively analyze the effect of a natural forward-leaning posture (head α1=9.0°, upper torso α2=15.1°) on coupling vibrations in a seated position. Frequency-domain analysis indicates that the human body exhibits globally coordinated motion below 3.5 Hz, whereas local organ resonances prevail above 6 Hz. Simulations reveal that a 15° backrest support angle can reduce fore-and-aft seat-to-head transmissibility by 87.2
Accurate and efficient estimation of structural failure probability often requires balancing predictive accuracy with computational cost, particularly when high-fidelity models are involved. To address this challenge, this study develops an adaptive ensemble of surrogates with approximate upper bound function (AES-AUBF) for reliability analysis. The proposed framework integrates multiple polynomial chaos Kriging (PCK) surrogates through a novel weighting scheme, enabling dynamic adjustment of model importance according to both global accuracy and local predictive uncertainty. An approximate upper bound function (AUBF) is introduced within a Bayesian active learning framework to guide the sequential selection of new informative samples, effectively reducing epistemic uncertainty in failure probability estimation. Furthermore, a reward-based learning function allocation strategy is proposed to adaptively select the most effective learning function from a portfolio, while a parallel enrichment mechanism accelerates convergence by adding multiple samples per iteration. A hybrid error-based stopping criterion ensures termination at an optimal balance between accuracy and efficiency. Three numerical examples, including a nonlinear oscillator, a multi-branch series system, and the fatigue reliability assessment of a monopile-supported offshore wind turbine, are employed to investigate the performance of AES-AUBF. Results show that AES-AUBF achieves accuracy comparable to direct Monte Carlo simulation while significantly reducing the number of function evaluations. The proposed framework provides a flexible and efficient tool for reliability analysis, and its modular structure allows seamless integration with dimension-reduction and advanced simulation techniques for future extension to high-dimensional or rare-event problems.
Plasma-based control of hypersonic boundary layer transition has garnered considerable attention, yet its underlying mechanisms remain poorly understood. This study investigates the effects of plasma generated by surface arc discharge (SAD) actuators on a Mach 6 flat plate boundary layer, focusing on the evolution of instability modes. The SAD actuators are modeled as localized cylindrical heat sources, and their effects are analyzed using direct numerical simulation (DNS) and linear stability theory (LST). The results demonstrate that plasma-induced disturbances significantly modify the mean flow, altering the characteristics of instability modes. DNS confirms that small disturbances evolve linearly within plasma-modified flows. Notably, the second mode is suppressed, while the first mode is significantly amplified, consistent with LST predictions. This amplification of low-frequency disturbances may explain the experimentally observed promotion of transition by plasma, as these disturbances are known to dominate the transitional stage. Furthermore, while excitation frequency examined in this study has minimal impact on the amplitude evolution of instability modes, increased plasma energy substantially enhances disturbance energy, potentially accelerating the onset of transition.
Irregular wall pulsation is a distinctive feature of certain intracranial aneurysms (IAs) identified by four-dimensional computed tomography angiography (4D-CTA). While clinical studies have demonstrated the association of irregular pulsation with aneurysm instability or rupture, the underlying biomechanical mechanisms remain poorly understood. In this study, we utilized the coherent point drift algorithm combined with elastic theory and computational fluid dynamics to quantify biomechanical parameters of IAs with irregular pulsation based on 4D-CTA images. The methodology was applied to three patient-specific IAs with clinically confirmed irregular pulsation. Obtained results revealed that aneurysm wall regions with irregular pulsation generally displayed large wall displacement, which was either accompanied or not accompanied by high strain. Notably, large displacement or high strain could also be detected in some aneurysm wall regions without irregular pulsation, as well as in adjacent normal arteries. Hemodynamic simulations demonstrated the presence of low and oscillatory wall shear stress (WSS) in irregular pulsation regions. Comparisons between dynamic hemodynamic models (incorporating wall movement) and static hemodynamic models (with rigid walls) further revealed the role of irregular pulsation in amplifying WSS oscillation, which implies that the degradation of wall mechanics in aneurysm regions with irregular pulsation may interact with hemodynamic disturbance in a mutually reinforcing manner. In summary, the findings of our study suggest that quantifying biomechanical parameters in both the wall and sac of aneurysm may provide valuable insights for assessing the risk of IAs, particularly those exhibiting irregular pulsation.
Nonlinear energy sinks containing dry friction damping (DNES) hold significant potential in vibration control. To unveil DNES’s underlying mechanism and explore the vibration reduction effect, this study couples DNES with a typical Duffing system having quintic nonlinear stiffness under periodic excitations. Initially, the coupled DNES system’s dynamic model is formulated based on Newton’s laws. Subsequently, the system’s bifurcation behavior is examined using bifurcation theory and fast-slow analysis. Numerical simulations determine equilibrium points, thus clarifying the vibration reduction mechanism. Upon coupling DNES, the system experiences a Fold bifurcation marked by a rapid transition, where the motion trajectory is transformed from a large amplitude and high frequency vibration to a bursting oscillation of spiking state and quiescent state. This phenomenon occurs because the unstable equilibrium point stabilizes after DNES coupling, enhancing its attraction to the motion trajectory. Moreover, observations show that DNES vibration has a smaller amplitude than NES vibration, improving the vibration reduction effect’s stability. DNES exhibits a favorable vibration reduction effect, maintaining it even when the external excitation intensity increases.
Two-dimensional triaxially braided composites (2DTBCs) exhibit pronounced anisotropy and complex failure behavior under biaxial loading, where strain-path dependence and fiber coupling lead to nonlinear and asymmetric strength responses. To address the limitations of classical failure models, this study develops a refined mesoscale finite element framework that captures the progressive damage evolution and stress redistribution across interacting fiber systems. Simulations reveal a systematic transition in failure modes—from axial-dominated fracture to coupled axial-transverse damage and ultimately to shear-driven collapse in the bias tows—as strain ratios and axial loading modes vary. Based on these observations, a mechanism-informed, piecewise failure envelope is proposed, integrating a modified Tsai–Wu formulation in coupling regimes with a maximum strain criterion elsewhere. This hybrid approach improves predictive accuracy and enhances physical interpretability for multiaxial strength assessment in complex braided architectures.
To address the limitations of conventional structures in penetration resistance and deflection-based protection, based on the composite armor theory, we designed and fabricated a multilayer bi-directional composite corrugated structure with both anti-penetration and projectile deflection capabilities, and studied the effect of foam filling. A combined experimental and numerical approach was employed to systematically analyze the dynamic response of the structure under ballistic impacts at various positions and velocities. Key aspects such as ballistic limit, failure modes, deflection mechanisms, and energy absorption characteristics were investigated. Results showed that the ballistic resistance of the structure was significantly influenced by impact location, and the gradient thickness design effectively enhanced the deflection effect, increasing the maximum projectile deflection angle by up to 63.72
Stochastic optimal control studies the Markov control of Markov diffusion process. For a system driven by the fractional Gaussian noise (fGn), the system response is non-Markov process. Thus, stochastic optimal control methods cannot be directly applied to stochastic optimal control of multi-degree-of-freedom (MDOF) nonlinear system driven by fGn. In the present paper, it is pointed out that fGn can be approximated to wideband noise under certain condition and the stochastic optimal control method based on the stochastic averaging method (SAM) of quasi-Hamiltonian system driven by wideband noise and dynamical programming can then be applied. The study in the present paper focuses on minimizing the response of MDOF nonlinear systems driven by fGn. Firstly, a controlled and fGn-driven quasi integrable Hamiltonian system is considered. Under certain conditions, the SAM of quasi-Hamiltonian systems driven by wideband noise is applied to obtain the partially-averaged and controlled Itô stochastic differential equations (SDEs). Then, applying the dynamical programming principle to the partially-averaged and controlled Itô SDEs yields the Hamilton-Jacobi-Bellman (HJB) equation. Solving HJB equation yields the optimal control force. Substitute the obtained optimal control force into the partially-averaged and controlled Itô SDEs and complete averaging to obtain completely averaged and optimal controlled Itô SDEs. Finally, solve the associated reduced Fokker-Planck-Kolmogorov (FPK) equation to obtain the response of the optimal controlled system. The proposed method is verified by comparing the theoretical results with those from Monte Carlo simulation.
The time-/temperature-dependent viscoelasticity behaviors in polymer composites are due to the memory decay effects, inducing various interesting phenomena, including the shape memory effects, the morphology evolution in living of organisms, temperature-dependent fracture behaviors, and so forth. To model those behaviors, various constitutive models based convolutional integrals have been developed for capturing viscoelasticity. However, the more refined model introduced a greater number of parameters and made the parameter identification more intricate, hardening their applications. To solve this problem, we developed a viscoelastic constitutive artificial neural network (VCANN) for automated parameter identification. Following the recently developed physics-informed neural operator, the activation functions of the network architecture were chosen to incorporate the physical knowledge in the standard viscoelastic model within the continuum mechanics framework. This VCANN is equivalent to the viscoelastic model, mapping the input variables (time, temperature, and deformation histories) to the stress responses, and the network node weights are equivalent to the model parameters. Therefore, the parameter identification problems are equivalently transformed into the training problem of the VCANN. To validate the parameter identification by this VCANN, we used the finite element (FE) simulation method to generate datasets of the mechanical responses in polymer composites under different strain states (uniaxial tension and equibiaxial tension) and different loading history (monotonic stretching, relaxation, and step loading). Six training scenarios indicate that as the dataset incorporates more diverse material deformation features, the parameters identified by VCANN become more precise. The datasets should include both uniaxial and biaxial tensile data to achieve the decoupled identification of bulk modulus and shear modulus. Overall, this developed method could reduce the application threshold of the viscoelastic constitutive model by establishing a bridge between the results of experiments and the input of parameters in FE simulations.
