Explore the vast range of titles available.

This research paper investigates the applicability and scalability of the Rotor Control Equivalent Turbulence Input models for multi-rotor vehicles. Initially, a Rotor Control Equivalent Turbulence Input model is developed for an isolated rotor using rotor RPM as the input and the rotor hub-load coefficient as the output. Subsequently, the model is applied to multi-rotor vehicle example to show that the effect of turbulence on vehicle response can be replicated using the Rotor Control Equivalent Turbulence Input models. This study further incorporates rotor collective deflections, which could be used in multi-rotor vehicles, to develop a collective input model. Additionally, the effect of altering rotor parameters on the Rotor Control Equivalent Turbulence Input model is studied and presented. The results demonstrate that the Rotor Control Equivalent Turbulence Input model effectively captures the turbulence-induced behaviors in multi-rotor vehicles, offering a generalizable and scalable framework for use to replicate the effect of turbulence in multi-rotor vehicles.

Large-eddy simulations (LESs) with various constant wind, wave, and surface destabilizing surface buoyancy flux forcing are conducted, with a focus on assessing the impact of Langmuir turbulence on the entrainment buoyancy flux at the base of the ocean surface boundary layer. An estimate of the entrainment buoyancy flux scaling is made to best fit the LES results. The presence of Stokes drift forcing and the resulting Langmuir turbulence enhances the entrainment rate significantly under weak surface destabilizing buoyancy flux conditions, that is, weakly convective turbulence. In contrast, Langmuir turbulence effects are moderate when convective turbulence is dominant and appear to be additive rather than multiplicative to the convection-induced mixing. The parameterized unresolved velocity scale in the K -profile parameterization (KPP) is modified to adhere to the new scaling law of the entrainment buoyancy flux and account for the effects of Langmuir turbulence. This modification is targeted on common situations in a climate model where either Langmuir turbulence or convection is important and may overestimate the entrainment when both are weak. Nevertheless, the modified KPP is tested in a global climate model and generally outperforms those tested in previous studies. Improvements in the simulated mixed layer depth are found, especially in the Southern Ocean in austral summer.

Future quantum communication infrastructures will rely on both terrestrial and space-based links integrating high-performance optical systems engineered for this purpose. In space-based downlinks in particular, the loss budget and the variations in the signal propagation due to atmospheric turbulence effects impose a careful optimization of the coupling of light in single-mode fibers required for interfacing with the receiving stations and the ground networks. In this work, we perform a comprehensive study of the role of adaptive optics (AO) in this optimization, focusing on realistic baseline configurations of prepare-and-measure quantum key distribution, with both discrete and continuous-variable encoding, and including finite-size effects. Our analysis uses existing experimental turbulence datasets at both day and night time to model the coupled signal statistics following a wavefront distortion correction with AO, and allows us to estimate the secret key rate for a range of critical parameters, such as turbulence strength, satellite altitude and ground telescope diameter. The results we derive illustrate the interest of adopting advanced AO techniques in several practical configurations.

A numerical analysis method for wind-induced response of structures is presented which is based on the pseudo-excitation method to significantly reduce the computational complexity while preserving accuracy. Original pseudo-excitation method was developed suitable for adoption by combining an effective computational fluid dynamic method which can be used to replace wind tunnel tests when finding important aerodynamic parameters. Two problems investigated are gust responses of a composite wing and buffeting vibration responses of the Tsing Ma Bridge. Atmospheric turbulence effects are modeled by either k–ω shear stress transport or detached eddy simulation. The power spectral responses and variances of the wing are computed by employing the Dryden atmospheric turbulence spectrum and the computed values of the local stress standard deviation of the Tsing Ma Bridge are compared with experimental values. The simulation results demonstrate that the proposed method can provide highly efficient numerical analysis of two kinds of wind-induced responses of structures and hence has significant benefits for wind-induced vibration engineering.

Analytical wind turbine wake models are widely used to predict the wake velocity deficit. In these models, the wake growth rate is a key parameter specified mainly with empirical formulations. In this study, a new physics-based model is proposed and validated to predict the wake expansion downstream of a turbine based on the incoming ambient turbulence and turbine operating conditions. The new model utilises Taylor diffusion theory, the Gaussian wake model, turbulent mixing layer theory and the analogy between wind turbine wake expansion and scalar diffusion. These components ensure that the model conserves mass and momentum in the far wake and accounts for the ambient turbulence and turbine-induced turbulence effects on the wake expansion. To account for the turbulence relevant scales that contribute to the wake expansion, the model uses the root-mean-square of the low-pass filtered radial velocity component. A simplified version that only requires the unfiltered velocity standard deviation and turbulence integral scale is also proposed. In addition, a new relation for the near-wake length is derived. The model performance is validated using large-eddy simulation data of a wind turbine wake under neutral atmospheric conditions with a wide range of incoming turbulence levels. The results show that the proposed model yields reasonable predictions of the wake width, maximum velocity deficit and near-wake length. In the case with a relatively low incoming streamwise turbulence intensity of 0.05, the ambient and turbine-induced terms in the model contribute almost equally to the wake width, rendering them both crucial for reasonable wake predictions.

Linear non-modal analyses are performed to study the mechanism of how deformable free surfaces influence very-large-scale motions (VLSMs) in turbulent open channel flows. The mean velocity and eddy viscosity profiles obtained from direct numerical simulations are used in the generalised Orr–Sommerfeld and Squire equations to represent background turbulence effects. Solutions of surface-wave eigenmodes and shear eigenmodes are obtained. The results indicate that at high Froude numbers, free surfaces enhance the maximum transient growth rate of VLSMs through surface-wave eigenmodes. We then analyse the energy budget equation to reveal the underlying mechanism. For streamwise-uniform motions, the energy growth rate is enhanced by an energy production term associated with the correlation between the streamwise velocity, which is generated by the lifting-up effect of streamwise vortices composed of shear eigenmodes, and the vertical velocity, which is induced by a spanwise standing wave composed of surface-wave eigenmodes. For streamwise-varying motions, the energy growth rate is enhanced by a standing wave moving with a pair of vortices that travel at a speed approximately equal to the projection of the mean surface velocity along the wavenumber vector direction. Finally, an analytical expression of the energy production term is derived to provide the initial conditions for the maximum transient growth and explain the weak free-surface effect observed at large spanwise wavenumbers and low Froude numbers. The results demonstrate a linear non-modal mechanism in interactions between free surfaces and VLSMs in open channel flows.

Compared to fiber continuous-variable quantum key distribution (CVQKD), atmospheric link offers the possibility of a broader geographical coverage and more flexible transmission. However, there are many negative features of the atmospheric channel that will reduce the achievable secret key rate, such as beam extinction and a variety of turbulence effects. Here we show how these factors affect performance of CVQKD, by considering our newly derived key rate formulas for fading channels, which involves detection imperfections, thus form a transmission model for CVQKD. This model can help evaluate the feasibility of experiment scheme in practical applications. We found that performance deterioration of horizontal link within the boundary layer is primarily caused by transmittance fluctuations (including beam wandering, broadening, deformation, and scintillation), while transmittance change due to pulse broadening under weak turbulence is negligible. Besides, we also found that communication interruptions can also cause a perceptible key rate reduction when the transmission distance is longer, while phase excess noise due to arrival time fluctuations requires new compensation techniques to reduce it to a negligible level. Furthermore, it is found that performing homodyne detection enables longer transmission distances, whereas heterodyne allows higher achievable key rate over short distances.

This paper aims to investigate and quantify the turbulence effect on droplet collision efficiency and explore the broadening mechanism of the droplet size distribution (DSD) in cumulus clouds. The sophisticated model employed in this study individually traces droplet motions affected by gravity, droplet disturbance flows, and turbulence in a Lagrangian frame. Direct numerical simulation (DNS) techniques are implemented to resolve the small-scale turbulence. Collision statistics for cloud droplets of radii between 5 and 25 μm at five different turbulence dissipation rates (20–500 cm 2 s −3 ) are computed and compared with pure-gravity cases. The results show that the turbulence enhancement of collision efficiency highly depends on the r ratio (defined as the radius ratio of collected and collector droplets r/ R) but is less sensitive to the size of the collector droplet investigated in this study. Particularly, the enhancement is strongest among comparable-sized collisions, indicating that turbulence can significantly broaden the narrow DSD resulting from condensational growth. Finally, DNS experiments of droplet growth by collision–coalescence in turbulence are performed for the first time in the literature to further illustrate this hypothesis and to monitor the appearance of drizzle in the early rain-formation stage. By comparing the resulting DSDs at different turbulence intensities, it is found that broadening is most pronounced when turbulence is strongest and similar-sized collisions account for 21%–24% of total collisions in turbulent cases compared with only 9% in the gravitational case.

In the era of sleek, super slender suspension bridges, facing the issue of stability against dynamic wind actions represents an increasingly complex challenge. Despite the significant progress over the last decades, the impact of atmospheric turbulence on bridge stability remains partially not understood, evoking the need for innovative research approaches. This study aims to address a gap in current research by investigating the random flutter stability associated with variations in the angle of attack due to turbulence, which has not formally been addressed yet. The present investigation employs the 2D rational function approximation model to express self-excited forces in a turbulent flow. The application of this type of models to bridge dynamics yields a viscoelastic coupled dynamic system characterized by memory effects and driven by broad-band long-time-scale noise, described here by a linear homogeneous time-variant differential equation, which shows apparent nonlinear features, and which has rarely been matter of research. Utilizing a Monte Carlo methodology, this work innovates in applying the largest Lyapunov exponent (LE) and the moment Lyapunov exponents (MLE) to study bridge random flutter stability. The calculation of LE and MLE under diverse turbulent wind conditions uncovers lower flutter stability than without turbulence effects. In most cases, sample and low-order p -th moment stability thresholds closely align with the bridge dynamic response pattern; therefore, the flutter critical wind speed is unequivocal. However, under certain turbulence scenarios, it is necessary to resort to MLE for a complete description of stability, evoking some additional consideration of which statistical moments should be considered for the engineering assessment of the flutter limit. Finally, this work provides a qualitative insight into the instability mechanisms by approximating the random parametric excitation with a sinusoidal gust and evaluating the time-periodic system stability via Floquet theory.

Snow avalanche‐induced air‐blasts are capable of breaking trees, damaging buildings and causing fatalities. Predicting their destructive properties is an essential part of snow avalanche hazard mitigation. Here, we propose a depth‐averaged model that involves turbulent fluctuations to simulate the air‐blast dynamics. The turbulent energy of the air‐blast arises from that of dust‐mixed air transferred from the avalanche core, shearing work in the cloud and entrained air, and is exploited to improve the air entrainment and drag relationships. We further present a unique data set of air blast‐induced tree breakage, providing type, status, diameter and falling direction of the measured trees. Through case studies of two artificially released avalanches with measured powder heights and three natural avalanches with tree‐breakage information, we test the model and investigate the turbulence effect on air‐blast dynamics. The proposed model and tree‐breakage data set quantify the air‐blast destructiveness and can be applied for avalanche hazard assessment. Plain Language Summary Snow avalanche‐induced air‐blasts are common natural hazards in high‐altitude regions. They are fully turbulent mixtures of ice dust and gases capable of causing damage and human fatalities far beyond the avalanche deposits, representing a major threat to societies in avalanche‐prone environments. In this study, we propose a robust numerical model that accounts for the turbulent fluctuations to simulate the air‐blast dynamics. An unprecedented data set of air blast‐induced tree breakage in three natural snow avalanches is further presented. Using five case studies in Switzerland, of which two artificial avalanches and three natural avalanches with tree‐breakage data, we test the model and investigate the impact of turbulence on air‐blast dynamics. Results suggest great performances of the proposed model in calculating the air‐blast height, impact area and dynamic pressure. Turbulent fluctuations play an important role in the travel resistance and air entrainment of the air‐blast, and can magnify the maximum pressure several times larger than the mean value. The new air‐blast hazard model gives promising perspectives for estimations of snow avalanche hazards, and the tree‐breakage data set can serve as a calibration basis for future more accurate numerical avalanche models. Key Points An unprecedented tree breakage data set is presented to quantify the magnitude and reach of the air‐blast generated by three snow avalanches The forest destruction is simulated with a depth‐averaged avalanche model to calculate the pressures induced by snow avalanche air‐blasts Turbulence can magnify the air‐blast pressure several times larger than the mean value, acting at frequencies near the tree frequencies