Turbulent Conditions Research Articles

Generation of inflow turbulence using an improved synthetic eddy method

The generation of turbulent inflow conditions is a key issue in large eddy simulation (LES) or direct numerical simulation (DNS). In this paper, an improved synthetic eddy method (SEM) is proposed to generate inflow turbulence for LES and DNS. The improvements about SEM focus on the eddy radius and eddy distributions. First, the eddy radius is improved to reduce the nonphysical vortex structure on the wall caused by overestimation of the radius. Second, a sampling method using Gaussian distribution is proposed to improve the distribution of eddies, which accurately captures the randomness of turbulent structure size and is close to the actual flow field. The improved method is applied to the direct numerical simulation of the supersonic turbulent boundary layer at Mach 2.7 and the 24° compression ramp. Results indicate that the predictions yielded by the improved method are in good agreement with both DNS and experimental data. Compared to the original method, the improved method exhibits a more rapid recovery of the friction coefficient and effectively shortens the development distances. The improved SEM has enhanced the efficiency and accuracy of generating inlet turbulence, which can provide inlet turbulence boundary conditions for LES and DNS.

Real-time adaptive optics for high-power laser beam correction in the strong turbulence

A combined adaptive optical system designed to correct the wavefront of light radiation distorted by the influence of strong atmospheric turbulence is presented. The system consists of a beam position stabilizer and a fast adaptive optical system operating in real time. Stabilization of the beam position is carried out by two electronically controlled tilt mirrors. The control loop includes two quadrant sensors and an FPGA (field-programmable gate array) that closes the feedback loop. Using information received from Shack-Hartmann wavefront sensor, a bimorph-based adaptive mirror, controlled by another FPGA, is able to compensate for wavefront aberrations for up to 23-th Zernike polynomial in real time. The system was tested under the laboratory turbulence conditions created by a fan heater. The bandwidth of the artificial turbulence in the experiments did not exceed 100 Hz, which corresponds to the average statistical state of the real atmosphere. Results of the correction of the wave front distorted by the artificial turbulence are presented. It is shown that when only a bimorph corrector is used, the value of wavefront tilt angles increases. This presents a certain problem, since a significant part of the turbulence energy falls on the wave front tilts. To address this problem, it is proposed additionally using a system for stabilizing the position of the light beam.

A bidirectional free space optical link for last-mile terrestrial access links employing a novel wavelength shift keying technique

In this study, we propose a novel wavelength shift keying (WSK) technique that is combined with the conventional intensity modulation scheme for the transmission of point-to-point bidirectional data at the rate of 10 Gbps in each direction. We observe that WSK technique has not been investigated for implementation in point-to-point free space optical (FSO) links. Therefore, to the best of our knowledge, our study is the first one to perform this investigation. Our proposed link uses WSK in the downlink direction while we re-use the optical carriers for the transmission of uplink data. The use of WSK in the downlink direction enables us to perform balanced detection at the receiver, resulting in 3 dB improvement in receiver sensitivity compared to simple direct detection. We present bit error rate (BER) results for the signals transmitted in both the directions under different turbulence conditions and FSO link lengths. It was observed that the downlink signals generally perform better compared to the uplink due to the use of balanced detection and higher intensity fluctuations induced over the re-used optical carrier transmitted in the uplink direction.Please check and confirm that all the author names (given name, family name) and initials are correctly identified. The author names and initials are CORRECT.

Modeling the settling and resuspension of microplastics in rivers: Effect of particle properties and flow conditions

Microplastics have numerous different shapes, affecting the fate and transport of these particles in the environment. However, theoretical models generally assume microplastics to be spherical. This study aims to develop a modeling approach that incorporates the shapes of microplastics to investigate the vertical transport of microplastics in rivers and simulate the effect of particle and flow characteristics on settling and resuspension. To achieve these aims, a mechanistic model was developed utilizing the mass-balance and hydrodynamic equations. Scenario analysis was implemented assigning different values to model parameters, such as bed shear stress, shape factor and particle size to simulate the effect of flow patterns and particle properties. The model outcomes revealed that the residence time of microplastics in the water column was longest in medium bed shear stress, whilst it was shortest in low bed shear stress. This suggests that the influence of turbulence is not unidirectional; it can both increase and decrease microplastic concentrations and residence time in the water column. According to the scenario analysis, the settling flux of microplastics was the highest for near-spherical particles and increased with the size of the particles, as well as with increasing bed shear stress. However, the resuspension of particles was primarily influenced by increasing bed shear stress, but the ranking of resuspension flux values for different shaped and sized microplastics exhibited alterations with changing flow patterns. Turbulent conditions predominantly influenced the resuspension of near-spheres and large microplastics. On the contrary, the settling of fibers and small microplastics were significantly influenced by changing flow patterns, whereas near-spheres and largest particles were least affected. The model results were sensitive to changes in shape factor developed for this model, therefore this parameter should be improved in future studies.

Blind and robust estimation of adaptive optics point spread function and diffuse halo with sharp-edged objects

Context. Initially designed to detect and characterise exoplanets, extreme adaptive optics (AO) systems open a new window onto the Solar System by resolving its small bodies. Nonetheless, their study remains limited by the accuracy of the knowledge of the AO-corrected point spread function (AO-PSF) that degrades their image and produces a bright halo, potentially hiding faint moons in their close vicinity. Aims. To overcome the random nature of AO-PSFs, I aim to develop a method that blindly recovers the PSF and its faint structured extensions directly into the data of interest, without any prior on the instrument or the object’s shape. The objectives are both to deconvolve the object and to properly estimate and remove its surrounding halo to highlight potential faint companions. Methods. My method first estimated the PSF core via a parametric model fit, under the assumption of a sharp-edged flat object. Then, the resolved object and the PSF extensions were alternatively deconvolved with a robust method, insensitive to model outliers, such as cosmic rays or unresolved moons. Finally, the complex halo produced by the AO system was modelled and removed from the data. Results. The method is validated on realistic simulations with an on-sky AO-PSF from the SPHERE/ZIMPOL instrument. On real data, the proposed blind deconvolution algorithm strongly improves the image sharpness and retrieves details on the surface of asteroids. In addition, their moons are visible in all tested epochs despite important variability in turbulence conditions. Conclusions. My method shows the feasibility of retrieving the complex features of AO-PSFs directly from the data of interest. It paves the way towards more precise studies of asteroid surfaces and the discovery and characterisation of Solar System moons in archival data or with future instruments on extremely large telescopes with ever more complex AO-PSFs.

A novel GM-APD array-based heterodyne imaging detection system supports large array multi-pixel parallel target motion state image detection

Existing laser active imaging detection methods are limited by the detection mechanism, which can only capture the intensity image and distance image of the target, and lack practical detection solutions for acquiring images of the target motion state characteristics (non-macroscopic centroid motion, such as rotation, rolling, and other motion characteristics around the centroid). In this paper, a detection method using Geiger mode avalanche photodiode (GM-APD) array detector for heterodyne imaging to obtain images of the target motion state is proposed. An innovative method based on photon counting time interval calculation (PCTIC) is proposed to obtain the Doppler frequency shift of the target echo for each GM-APD pixel, which effectively eliminates useless data unrelated to the signal. With limited data storage and processing speed, the heterodyne imaging performance has been effectively improved to achieve high-precision heterodyne imaging detection of very weak target echoes and to support heterodyne imaging detection of large arrays with more image pixels in parallel. Experiments show that the method can achieve video-level detection at an imaging resolution of 32×32, and with a paucity of echo photons (detection probability of echo is 0.0032), a millimetre-level velocimetry measurement error can be achieved by accumulating only 6 echo photons per image element. The system also shows good resistance to turbulence interference, with target motion state characteristics detected based on velocity images remaining virtually unaffected under turbulence conditions caused by strong flames. This advancement is crucial for target detection in complex working environments such as smart manufacturing and autonomous driving.

Robust detection of a rotational Doppler shift with randomly fluctuated light.

The complex external environment, such as obstruction and turbulence, poses significant limitations on the applications of rotational Doppler detection. The active manipulation of randomly fluctuated light has been proven effective in mitigating external environmental perturbations. Here, as an example, a partially coherent source with petal-like focal (or far) field distribution is constructed specifically for detecting rotational Doppler frequency shifts. The experiment involved conducting rotational Doppler detection under obstruction or turbulence conditions, and the results are compared with the fully coherent counterpart. The results demonstrate that the use of a partially coherent source can address the frequency-shift broadening problem due to the obstruction-induced beam information loss and mitigate it due to the turbulence-induced beam misalignment. These advantages make the proposed approach applicable to velocity metrology in complex environments.

Prospects for the development of national logistics under sanctions

The article examines the theoretical background and practical experience of creating a logistics startup in the context of the national logistics infrastructure. The purpose of this scientific article is to develop a system of recommendations for implementing a logistics startup in conditions of economic turbulence. The relevance of the stated topic is due to the fact that due to international instability of economic relations, a significant part of the logistics export and import channels have collapsed, which requires entrepreneurial initiative to create new supply channels taking into account current foreign economic realities. At the same time, in the current conditions, the problems of the Russian logistics system related to its lack of self–sufficiency and the presence of certain links, the existence of which is necessary to ensure its integrity, have become urgent. In particular, these links are represented by structures providing container transportation, structures authorized to carry out international insurance and technology companies used in organizing navigation and dispatch processes. The high probability that Russia will be cut off from global logistics processes for a long time indicates that there are unfilled niches in the country for the creation of domestic logistics start–ups, which requires the implementation of logistics start–ups on conditions other than standard market ones.

Stability, thermophysical properties, forced convective heat transfer, entropy minimization and exergy performance of a novel hybrid nanofluid: Experimental study

This research explores how incorporating graphene oxide (GO) into red mud (RM) creates a superior nanomaterial for heat transfer applications. RM's inherent stability and thermal conductivity (TC), stemming from its metal oxide composition, are further amplified by this hybrid nano-composite. The study primarily investigates the thermal performance of water-based RM mono nanofluid and hybrid RM + GO (50:50) nanofluids (HNFs) at nanoparticle concentrations of 0.1–0.75 vol%. An experimental setup consisting of a copper tube under turbulent flow conditions with a constant heat flux and a bulk fluid temperature of 60 °C was used to test the performance of HNF. Various techniques are used to characterize the nanoparticles (NPs), and evaluate the thermophysical properties of nanofluids. The experimental data reveal that the heat transfer coefficient (HTC) increases with higher inlet fluid velocity and nanoparticle concentrations. Notably, the HNF demonstrates a significant improvement of 47.2 % in Nusselt number (Nu) and a 13.6 % rise in pressure drop (Δp) compared to base fluid, at 0.75 vol%. The least entropy generation number (EGN) is obtained for the HNF (0.0049) compared to the RM NF (0.00583) at a concentration of 0.75 vol%. The exergy efficiency improves with an increase in concentration and Reynolds number (Re). Additionally, the study identifies the performance index (PI) of NFs and modelled correlations for estimating the Nu and friction factor (f) within the investigated concentration range.

Study on Design Method of Diversion Pier in Channel Entrance Area with Complex Flow Characteristics

The entrance area is the main way for ships to enter and exit the approach channel. During the navigation period, the approach channel, the entrance area and the connecting section should avoid turbulence, whirlpool and other bad flow conditions. When conditions are limited and cannot be avoided, engineering or non-engineering measures should be taken to make it harmless to ensure the efficiency and safety of shipping. Aiming at improving the navigation safety effect of the estuary area, this paper analyzes the effect of improvement measures under the actual navigable flow condition by establishing the flow information fitting model and the prediction model of diversion pier setting, and provides the design method and basis for the installation of diversion pier in the estuary area to be predicted. It enriches the model base and knowledge base of the channel entrance area with complex flow characteristics, which has important practical significance and engineering value for shipping safety and waterway management.

Numerical Investigation of Thermal Performance of Minichannels with Transversely Patterned Non-Slip and Superhydrophobic Surfaces in Turbulent Flow Conditions

Numerical Investigation of Thermal Performance of Minichannels with Transversely Patterned Non-Slip and Superhydrophobic Surfaces in Turbulent Flow Conditions

Deep reinforcement learning finds a new strategy for vortex-induced vibration control

As a promising machine learning method for active flow control (AFC), deep reinforcement learning (DRL) has been successfully applied in various scenarios, such as the drag reduction for stationary cylinders under both laminar and weakly turbulent conditions. However, current applications of DRL in AFC still suffer from drawbacks including excessive sensor usage, unclear search paths and insufficient robustness tests. In this study, we aim to tackle these issues by applying DRL-guided self-rotation to suppress the vortex-induced vibration (VIV) of a circular cylinder under the lock-in condition. With a state space consisting only of the acceleration, velocity and displacement of the cylinder, the DRL agent learns an effective control strategy that successfully suppresses the VIV amplitude by $99.6\,\%$ . Through systematic comparisons between different combinations of sensory-motor cues as well as sensitivity analysis, we identify three distinct stages of the search path related to the flow physics, in which the DRL agent adjusts the amplitude, frequency and phase lag of the actions. Under the deterministic control, only a little forcing is required to maintain the control performance, and the VIV frequency is only slightly affected, showing that the present control strategy is distinct from those utilizing the lock-on effect. Through dynamic mode decomposition analysis, we observe that the growth rates of the dominant modes in the controlled case all become negative, indicating that DRL remarkably enhances the system stability. Furthermore, tests involving various Reynolds numbers and upstream perturbations confirm that the learned control strategy is robust. Finally, the present study shows that DRL is capable of controlling VIV with a very small number of sensors, making it effective, efficient, interpretable and robust. We anticipate that DRL could provide a general framework for AFC and a deeper understanding of the underlying physics.

Numerical simulations for the SAXO+ upgrade: Performance analysis of the adaptive optics system

SPHERE, operating at the VLT since 2014, is currently one of the high-contrast instruments with a higher performance. Its adaptive optics system, known as SAXO, will be upgraded to SAXO+, which features the addition of a second stage of adaptive optics. This stage will use a near-infrared pyramid wavefront sensor to record images of fainter exoplanets around redder stars. In this work, we compare the performance of SAXO and SAXO+. We look for the optimal values of the key system parameters of SAXO+ for various science cases and turbulence conditions. We performed numerical simulations using COMPASS, an end-to-end adaptive optics simulation tool. We simulated perfect coronagraph images of an on-axis point source, and we minimized the residual starlight intensity between 3 and $5\ / D$ as a performance criterion. The explored parameter space includes science cases (described by magnitude in G and J bands), turbulence conditions (seeing and coherence time), and key system parameters (first and second stage gains, first and second stage frequencies, pyramid modulation radius, pyramid modal gains optimization). In every science case and turbulence condition, SAXO+ reduces the residual starlight intensity inside the correction zone of the second stage by a factor of ten compared to SAXO. The optimal first stage gain is lower for SAXO+ than for SAXO alone. We quantified the gain in performance of SAXO+ when changing the second stage frequency from 2\,kHz to 3\,kHz, and we conclude that 2\,kHz may be sufficient for most realistic conditions. We give the optimal first stage gain as well as the first and second stage frequencies for every seeing, coherence time, and science case. Finally, we find that a $2\ WFS / D$ pyramid modulation radius is a good trade-off between performance and robustness against varying turbulence conditions. This study shows that the future SAXO+ system will outperform the current SAXO system in all studied cases.

Analysis of speckle-beacon size impact on wavefront sensing and closed-loop control in deep turbulence conditions

The impact of the laser beacon size on the performance of an ideal phase-conjugation-type adaptive optics (AO) system is analyzed using wave-optics-based numerical simulation. The analysis includes wavefront aberration sensing and closed-loop control for laser beam propagation both in vacuum and in distributed (volume) atmospheric turbulence with the beacon beam scattering off a flat extended target with Lambertian surface roughness. For mitigation of the impact of target-induced speckle effects on the performance of AO systems, speckle-average wavefront sensing and control approaches are introduced and analyzed. The results demonstrate that proposed speckle-average phase conjugation control algorithms enable partial mitigation of turbulence-induced aberrations in presence of strong speckle modulations.

Preferential Partitioning of Per- and Polyfluoroalkyl Substances (PFAS) and Dissolved Organic Matter in Freshwater Surface Microlayer and Natural Foam.

Per- and polyfluoroalkyl substances (PFAS) are surfactants that can accumulate in the surface microlayer (SML) and in natural foams, with potential elevated exposure for organisms at the water surface. However, the impact of water chemistry on PFAS accumulation in these matrices in freshwater systems is unknown. We quantified 36 PFAS in water, the SML, and natural foams from 43 rivers and lakes in Wisconsin, USA, alongside measurements of pH, cations, and dissolved organic carbon (DOC). PFAS partition to foams with concentration ranging 2300-328,200 ng/L in waters with 6-139 ng/L PFAS (sum of 36 analytes), corresponding to sodium-normalized enrichment factors ranging <50 to >7000. Similar enrichment is observed for DOC (∼70). PFAS partitioning to foams increases with increasing chain length and is positively correlated with [DOC]. Modest SML enrichment is observed for PFOS (1.4) and FOSA (2.4), while negligible enrichment is observed for other PFAS and DOC due to low specific surface area and turbulent conditions that inhibit surfactant accumulation. However, DOC composition in the SML is distinct from bulk water, as assessed using high-resolution mass spectrometry. This study demonstrates that natural foams in unimpacted and impacted waters can have elevated PFAS concentrations, whereas SML accumulation in surface waters is limited.

Lyapunov stability of suspension bridges in turbulent flow

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.

Implementation Of Optical Diagnostics For Study Of A Non-Canonical Hypersonic Geometry

The study of shock/boundary-layer interactions on a non-canonical hypersonic geometry involves physical complexities not found on the canonical investigations that dominate the literature. The present case examines a cone-slice-ramp, which combines an upstream asymmetric flow expansion with a downstream three-dimensional compression ramp. Optical diagnostics of the off-body flowfield are a necessary complement to surface instrumentation including high-frequency pressure sensors and Temperature Sensitive Paint (TSP). Focused Laser Differential Interferometry (FLDI) measured the flowfield distribution of second-mode instability waves responsible for transition. Filtered Rayleigh Scattering (FRS) was used for flow visualization of the separation region and unsteady shear layer. Velocimetry through the separation shear layer was provided by Femtosecond Laser Electronic Excitation Tagging (FLEET) whereas Coherent Anti-Stokes Raman Scattering (CARS) measured the thermal profiles through multiple flow features generated by the interaction. These flowfield diagnostics detail the alterations in the shock/boundary-layer interaction as the flow state moves from laminar to transitional to turbulent conditions, revealing behaviors absent from canonical flows.

The co-benefits of offshore wind under the UK Renewable Obligation scheme: Integrating sustainability in energy policy evaluation

Offshore wind energy is a key technology for decarbonising the UK electricity system. It also delivers significant socio-environmental co-benefits. Assessing these co-benefits is essential for energy policy under turbulent energy market conditions emerging in the wake of geopolitical unrest. This study focuses on assessing the co-benefits and costs associated with offshore wind electricity generation for the Renewable Obligation scheme in the UK, which although being phased out, currently supports more offshore wind generation in 2023 than its Contracts-for-Difference replacement scheme. Comparing offshore wind co-benefits with support scheme costs provides an objective evaluation of the scheme's success. Results indicate that reduced energy imports contribute to co-benefits of £5.9 ± 0.3bn and £4.9 ± 0.3bn in simple and flexible scenarios respectively. Emissions reductions lead to £4.4 ± 0.9bn in simple and £3.9 ± 0.8bn in flexible scenario. The employment benefits amounted £1 ± 0.2bn. The cost of the Renewable Obligation scheme amounted to £18.8 ± 3.8bn, indicating that the co-benefits can cover 60% and 52% of the policy costs, in simple and flexible scenarios, respectively. This analysis supports a case for monetising the wider co-benefits of energy technology implementation to support institutions and policy makers in the integration and evaluation of sustainability in energy policy in a way that goes beyond the electricity price.

Gas well deliverability: backpressure, Forchheimer, and numerical models

The Forchheimer and backpressure models are commonly employed to describe gas well deliverability and interpret multipoint well tests. While the Forchheimer model is regarded as more robust, the backpressure equation remains widely used. However, both models’ have unaddressed limitations, and it is unclear when their predictions diverge. This study investigates both models’ validity against numerical solutions of the diffusivity equation. Results show that the models’ accuracy depends on two dimensionless groups: the turbulence intensity ratio and the highest drawdown tested in a multipoint test. Only the Forchheimer model consistently yields flow rate errors below 10% when 25% of the reservoir pressure is tested, following industry guidelines, while the backpressure equation exhibits an average error of 30%. The backpressure equation is accurate under laminar or highly turbulent conditions but deteriorates in the transition between the two, diverging from the Forchheimer model. To mitigate the inadequacy of the backpressure model, testing pressure drawdowns as high as 40% of reservoir pressure is recommended.

HRM Algorithms: Moderating the Relationship between Chaotic Markets and Strategic Renewal

AbstractHRM algorithms can profoundly impact organizations in the digital economy era. In the face of turbulent and complex market conditions, strategic renewal is regarded as one of the most important organizational mechanisms for dealing with market uncertainty and a turbulent environment. However, the existing research remains elusive about the relationship between market‐level conditions and firm‐level strategic renewal. Our paper addresses this important gap by examining the potential enhancement of agile strategic renewal in high‐uncertainty environments through the implementation of HRM algorithms. Drawing on Chaos Theory, we argue that HRM algorithms have the potential to support the self‐organization capacity of a workforce, supporting better alignment with changing environments. Using covariance‐based structural equation modelling on a survey of over 500 Spanish firms, our findings provide partial support for the modelled hypotheses by showing that the use of HRM algorithms positively moderates the relationship between market turbulence and strategic renewal, but does not appear to moderate the relationship between market complexity and strategic renewal. The study contributes to our understanding of the importance of adopting internal business analytics systems to stimulate agility and align the workforce more effectively with changing environments, but also highlights their less substantive role in deciphering complex external factors.