Effects Of Turbulence Research Articles

Are turbulence effects on droplet collision–coalescence a key to understanding observed rain formation in clouds?

Rain formation is a critical factor governing the lifecycle and radiative forcing of clouds and therefore it is a key element of weather and climate. Cloud microphysics-turbulence interactions occur across a wide range of scales and are challenging to represent in atmospheric models with limited resolution. Based on past experiments and idealized numerical simulations, it has been postulated that cloud turbulence accelerates rain formation by enhancing drop collision-coalescence. We provide substantial evidence for significant impacts of turbulence on the evolution of cloud droplet size distributions and rain formation by comparing high-resolution observations of cumulus congestus clouds with state-of-the-art large-eddy simulations coupled with a Lagrangian particle-based microphysics scheme. Turbulent coalescence must be included in the model to accurately represent the observed drop size distributions, especially for drizzle drop sizes at lower heights in the cloud. Turbulence causes earlier rain formation and greater rain accumulation compared to simulations with gravitational coalescence only. The observed rain size distribution tail just above cloud base follows a power law scaling that deviates from theoretical scalings considering either a purely gravitation collision kernel or a turbulent kernel neglecting droplet inertial effects, providing additional evidence for turbulent coalescence in clouds. In contrast, large aerosols acting as cloud condensation nuclei ("giant CCN") do not significantly impact rain formation owing to their long timescale to reach equilibrium wet size relative to the lifetime of rising cumulus thermals. Overall, turbulent drop coalescence exerts a dominant influence on rain initiation in warm cumulus clouds, with limited impacts of giant CCN.

Breakthrough Underwater Physical Environment Limitations on Optical Information Representations: An Overview and Suggestions

Underwater optics have seen a notable surge of interest in recent years, emerging as a critical medium for conveying information crucial to underwater resource exploration, autonomous underwater vehicle navigation, etc. The intricate dynamics of underwater optical transmission, influenced by factors such as the absorption by the water and scattering by multiple particles, present considerable challenges. One of the most critical issues is that the optical information representation methods fail to take into account the impact of the underwater physical environment. We conducted a comprehensive review and analysis of recent advancements in underwater optical transmission laws and models. We summarized and analyzed relevant research on the effects of underwater particles and turbulence on light and analyzed the polarization effects in various environments. Then, the roles of various types of underwater optical propagation models were analyzed. Although optical models in complex environments are still mostly based on Monte Carlo methods, many underwater optical propagation mechanisms have been revealed and can promote the impacts of optical information expression. We delved into the cutting-edge research findings across three key domains: the enhancement of underwater optical image quality, the 3D reconstruction from monocular images, and the underwater wireless optical communication, examining the pivotal role played by light transmission laws and models in these areas. Drawing upon our extensive experience in underwater optics, including underwater optical sensor development and experiments, we identified and underscored future directions in this field. We advocate for the necessity of further advancements in the comprehension of underwater optical laws and physical models, emphasizing the importance of their expanded application in underwater optical information representations. Deeper exploration into these areas is not only warranted but essential for pushing the boundaries of current underwater optical technologies and unlocking new potential for their application in underwater optical sensor developments, underwater exploration, environmental monitoring, and beyond.

Accurate estimate of the ESPRESSO fibre-injection losses inferred from integrated field-stabilization images

ABSTRACT Ground-based astronomy is unavoidably subject to the adverse effect of atmospheric turbulence, a.k.a. the seeing, which blurs the images and limits the achievable spatial resolution. For spectroscopic observations, it leads to slit or fibre-injection losses, since not all photons distributed over the extended seeing disc can be captured. These losses might have a very substantial impact on the overall efficiency of a spectrograph and are naturally highly variable. Assessing the fibre-injection losses requires accurate information about the image quality (IQ) delivered by the telescope to the instrument over the course of the observations, which, however, is often not directly available. ESPRESSO provides acquisition and field-stabilization images attached to the science data and thus offers the opportunity for a post-processing analysis. Here, we present a novel method to infer the IQ profile and fibre-injection losses from the integrated field-stabilization images, utilizing the spill-over light that does not get injected into the fibre. We validate these measurements against the IQ observed in the acquisition images and determine that our method delivers unbiased estimates with a scatter of 0.11 arcsec for the FWHM of the profile and $15~{{\ \rm per\ cent}}$ in terms of fibre-injection losses. This compares favourably to the estimates derived from either the differential image motion monitor or the telescope guide probe sensors and therefore represents a valuable tool to characterize the instrument efficiency and to correct raw spectra for fibre-injection losses.

Three-Dimensional Numerical Simulation of a Two-Phase Supercritical Open Channel Junction Flow

This study investigates the computational fluid dynamics (CFD) modeling of supercritical open channel junction flow using two different turbulence models: k-ω shear stress transport (SST) and k-ω SST scale-adaptive simulation (SAS), in conjunction with Volume of Fluid (VOF) and mixture multiphase models. The efficacy of these models in predicting the intricate free surface fluctuation and free surface elevation in a supercritical junction is evaluated through a comprehensive analysis of time-averaged free surface data obtained from CFD simulations and Light Detection and Ranging (LIDAR) measurements. The dimensionless Reynolds (Re) and Froude (Fr) numbers of the investigated scenario were Fr = 9 and Re = 5.1 × 104 for the main channel, and Fr = 6 and Re = 3.3 × 104 for the side channel. The results of the analysis demonstrated a satisfactory level of agreement with the experimental data. However, certain limitations associated with both CFD and LIDAR were identified. Specifically, the CFD performance was limited by the model’s incapacity to consider small-scale turbulent effects and to model air bubbles smaller than the cell size while the LIDAR measurements were limited by instrument range, inability to provide insight into what is happening below the water surface, and blind spots. Nonetheless, the k-ω SST turbulent model with the VOF multiphase model most closely matched the LIDAR results.

Computational Fluid Dynamics Modelling of the Temperature Distribution in Power Plant's Cooling Canal

Seawater used as a heat exchanger in the coal-fired power plant condenser system has a higher water temperature than the natural temperature of seawater. There was an increase in the temperature of the waters around the coal-fired power plant due to the discharge of boiling water reaching 6.50C. According to the regulations in force in Indonesia, the hot water temperature at the water discharge outlet should not be more than 20C of the natural temperature of seawater. The purpose of this study is to predict the pattern of temperature decrease in the temperature of the boiling water along the cooling line. The method used to predict temperature drop patterns along the cooling line uses a 3-dimensional CFD (Computational Fluid Dynamics) modelling approach with the Ansys Fluent 2023 RI application. The K-Epsilon turbulence model was chosen to describe the effect of flow turbulence on temperature changes. The modelling results were validated by comparing the actual measurements of the water temperature field data representing along the cooling line. The results showed that the performance of reducing the temperature of the water increased when passing through the cascade aeration downstream of the channel. The flow of water along the channel tends to be on the lower side, and downstream, the flow is on the left–middle side. The error calculation using MAPE resulted in 9.49%.

Investigation on particle slug flow using large eddy simulation combined a particle kinetic energy model

In this study, an investigation on particle hydrodynamic behaviors of gas-particle slug flow is modeled and numerically simulated. A novelty particle kinetic energy model at subgrid-scale level is developed to consider the effect of gas turbulence on particle movement and a four-way coupling approach is combined. Anisotropic particle dispersions and the multiphase interactions is revealed by using a second-order moment turbulence model and large eddy simulation is performed to solve the Euler-Euler two-fluid transport equations, Predictions are well agreed with the experimental data and reported results by discrete particle model built-in the multiphase flow model with interphase exchanges code. Bubble motions have great effects on the particle dynamics due to bubble entrainment. Flow patterns of particle circulation are generated between higher and lower concentrations. The largest frequency of power spectrum density at center of top surface is approximately 4.5 times larger than that of wall region. Bubblelike granular temperatures are much larger than smaller-scale particle granular temperature. At the top surface, maximum value of vertical bubblelike Reynolds stress is found at x/W = 0.28, it is 4.0 times larger than that of the lateral x-direction. In addition, the mean values, and the standard deviation of SGS particle kinetic energy at center are both approximately 3.5 times larger than those of z = 10.0 cm. For particle shear stress at middle section, maximum ratios of mean value and standard deviation at central regions to those of walls reach up to 8.0 and 11.0.

Influence of the Turbulence Effect on the Rainfall Scavenging Coefficient

Influence of the Turbulence Effect on the Rainfall Scavenging Coefficient

Comprehensive Analysis of Pressure Drop Phenomena in Rotating Packed Bed Distillation: An In-Depth Investigation.

A rotating packed bed (RPB) is an innovative intensification technology that improves its separation capabilities in high-gravity conditions. This process increases efficiency with smaller equipment size and footprint than conventional packed columns. Although significant advancements have been made regarding RPBs, most studies only focused on single or dual rotor configurations in addressing dry pressure drop. Hence, multiple rotor systems in industrial settings can enhance economic efficiency by minimizing the necessity for numerous RPBs. This study investigated the pressure drops and holdup in a three-stage rotor-based RPB under actual process conditions using natural gas as the feed. A novel pressure drop correlation was introduced based on the nitrogen removal process from the natural gas in continuous RPB distillation operations. Consequently, the correlation between centrifugal acceleration, turbulent, and momentum effects demonstrated remarkable accuracy within ±15%. This outcome also highlighted the importance of meticulous design considerations in RPB-based applications due to the complex correlation between centrifugal forces, liquid holdup, and gas flow rates. The reflux feed ratio, liquid holdup, rotating speed, and F-factor effects were examined to comprehend the RPB distillation process. Overall, the correlations between the critical parameters offered crucial insights to prevent process upsets (such as flooding), contributing to advancing RPBs in practical industrial settings.

Atmospheric turbulence recognition with deep learning models for sinusoidal hyperbolic hollow Gaussian beams-based free-space optical communication links

The integration of artificial intelligence technology to improve the performance of free-space optical communication (FSO) systems has received increasing interest. This study aims to propose a novel approach based on deep learning techniques for detecting turbulence-induced distortion levels in FSO communication links. The deep learning-based models improved and fine-tuned in this work are trained using a dataset containing the intensity profiles of Sinusoidal hyperbolic hollow Gaussian beams (ShHGBs). The intensity profiles included in the dataset are the ones of ShHGBs propagating for 6 km under the influence of six different atmospheric turbulence strengths. This study presents deep learning-based Resnet-50, EfficientNet, MobileNetV2, DenseNet121 and Improved+MobileNetV2 approaches for turbulence-induced disturbance detection and experimental evaluation results. In order to compare the experimental results, an evaluation is made by considering the accuracy, precision, recall, and f1-score criteria. As a result of the experimental evaluation, the average values for accuracy, precision, recall and F-score with the best performance of the improved method are given; average accuracy 0.8919, average precision 0.8933, average recall 0.8955 and average F-score 0.8944. The obtained results have immense potential to address the challenges associated with the turbulence effects on the performance of FSO systems.

CREATIVE AND PURE IMITATION UNDER ENVIRONMENTAL TURBULENCE: EVIDENCE FROM AN EMERGING ECONOMY

Due to the significance of imitation in business success and economic growth, there is an increasing interest of scholars in exploring different dimensions of imitation, illuminating the ‘black box’ of imitation. Given the increasingly turbulent nature of business environments, this study aims to investigate creative and pure imitation-based competitive strategies and their performance under different levels of environmental turbulence. A theoretical framework was tested using a sample of manufacturing firms in Vietnam. The results revealed that creative imitation is positively associated with sustained competitive advantage, while the impact of pure imitation on sustained competitive advantage is negligible. Furthermore, environmental turbulence affects both creative and pure imitation, with only creative imitation mediating the effects of environmental turbulence on sustained competitive advantage. Lastly, environmental turbulence amplifies the effect of pure imitation on sustained competitive advantage, while it has minimal moderating effects on the relationship between creative imitation and sustained competitive advantage. This study contributes to the literature by being the first to examine the effect of environmental turbulence on the performance of both creative and pure imitation strategies.

Effect of gas turbulence in quartz-enhanced photoacoustic spectroscopy: A comprehensive flow field analysis

Here we present a computational and experimental fluid dynamics study for the characterization of the flow field within the gas chamber of a Quartz-Enhanced Photoacoustic Spectroscopy (QEPAS) sensor, at different flow rates at the inlet of the chamber. The transition from laminar to turbulent regime is ruled both by the inlet flow conditions and dimension of the gas chamber. The study shows how the distribution of the flow field in the chamber can influence the QEPAS sensor sensitivity, at different operating pressures. When turbulences and eddies are generated within the gas chamber, the efficiency of photoacoustic generation is significantly altered.

Conjugate heat transfer analysis of helium–xenon gas mixture in tight rod bundles

Helium-xenon gas mixture (He-Xe) and tight rod bundles are widely used in gas-cooled space nuclear reactors. However, few studies have been conducted on the effects of pitch-to-diameter ratio (P/D) on thermal–hydraulic characteristics while considering conjugate heat transfer. This paper numerically investigated He-Xe heat transfer in a fuel-gas gap-cladding-coolant structure of tight rod bundles. The numerical model is validated using experimental data and the maximum error of wall temperature is less than 5 %. The results show that conjugate heat transfer significantly affects the heat transfer. The heat transfer coefficient without conjugate heat transfer is only 8.85 % of that with conjugate heat transfer in the quasi-triangular pipe. The decrease in P/D enhances the convective heat transfer and causes larger pressure drops. A new performance evaluation criterion (PEC) is presented considering the effects of heat transfer, pressure drop and volume. PEC first increases and then decreases with the increase in P/D and the best comprehensive performance occurs at P/D = 1.113. The analysis of the temperature difference in the viscous sublayer (y+ < 5) shows that the decrease in P/D enhances the turbulent effect of He-Xe and reduces the thickness of the viscous sublayer, resulting in the heat transfer enhancement. This study contributes to the optimal design of advanced space reactors.

Thermo-Fluid–Structural Coupled Analysis of a Mechanical Seal in Extended Loss of AC Power of a Reactor Coolant Pump

We proposed a numerical method to investigate the thermo-fluid–structural coupled characteristics of a mechanical seal of a reactor coolant pump (RCP), especially during extended loss of AC power (ELAP) operation. We developed a finite element program for the general Reynolds equation, including the turbulence effect to calculate the pressure, opening force, and leakage rate of fluid lubricant and the two-dimensional energy equation to calculate the temperature distribution of the fluid lubricant. We verified the accuracy of the developed program by comparing the simulated temperature distribution and leakage rate of this study with those of previous research. Heat conduction and elastic deformation due to pressure and temperature changes at the seal structure were analyzed using an ANSYS program. The results showed that temperature more significantly affected the elastic deformation of the seal structure near clearance than pressure both under normal and ELAP operating conditions. High temperature and pressure of the coolant under ELAP operating conditions deform the seal structure, resulting in a much smaller clearance of the fluid film than normal operating condition. However, even with a small clearance under ELAP operation, the leakage rate slightly increases due to the high internal pressure of the coolant. This research will contribute to the development of robust mechanical seals for RCPs by accurately predicting the characteristics of mechanical seals, especially when the RCP is operating under ELAP.

STATISTICAL CHARACTERISTICS OF THE GEOPHYSICAL FIELDS DISTURBED BY WEATHER FRONTS

The Earth (internal spheres) — atmosphere — ionosphere — magnetosphere (EAIM) formation is a single integrated system with direct and reverse, positive and negative coupling, as well as with their combination. The high-energy sources of natural and anthropogenic origins activate coupling between the components of the EAIM. The effects that the sources of various physi- cal nature have on the EAIM system have been studied quite well, while the influence of the weather fronts and other powerful atmospheric sources on the EAIM system and its components has been studied only partly. The scientific objective of this study is to conduct a statistical analysis of variations in the basic parameters of the geophysical fields that accompany the movement of atmospheric fronts. The histograms have been constructed that show the atmospheric pressure difference, atmospheric tem- perature difference, duration of the action of the atmospheric front, and the rate of change in the pressure and temperature, as well as the histograms showing the distribution of variations in the atmospheric electric field, the atmospheric current density, and in the magnetic field. The analysis undertaken has shown that these parameters exhibit variations within a broad range of values. The mean values of these parameters are estimated to be 145 Pa, 6 °C, 70 min, 2.4 Pa/min, 0.23 °C/min, 3.2 kV/m, 63 nA/m2, and 20 nT, respectively. The analysis of the scatter diagrams shows that the correlation between the variation in physi- cal parameters is almost always absent. This means that a single governing parameter along the path of the atmospheric front does not exi st. A simplified analytical relation has been derived to estimate the perturbation in the electric field strength caused by the atmospheric front, which yields ~6–60 kV/m values that increase by an order of magnitude during thunderstorms. Under disturbed conditions, the atmospheric current density is shown to increase from 10 –12 A/m2 to 10–11—10–10 A/m 2. The fol- lowing three mechanisms of an increase in the magnetic induction under the influence of the atmospheric front are considered: the disturbances of the external current density, electromagnetic induction, and the magnetic effect of turbulence. All these mechanisms yield the value of the effect less than ~1 nT. Only the magnetic effect of the ionosphere can explain an increase of 10—70 nT in the magnetic field variations. The energetics of the pressure, temperature, electric, and magnetic fields has been estimated to be (~10 16—10 17 J, ~1013—1014 W), (~1018—1019 J, 1015—1016 W), (~109—1011 J, ~106—108 W), (~1010 — 10 11 J, 107—108 W), respectively. The following channels have been validated through which the components of the EAIM sys- tem couple under the action of atmospheric fronts: atmospheric pressure differences, ionospheric electron density differences, the generation of infrasound and gravity waves, the generation of electromagnetic waves by lightning flashes, and the perturba- tions in the global electric circuit.

Persistent mixed‐phase states in adiabatic cloud parcels under idealised conditions

AbstractBy assuming that liquid droplets and ice crystals within a computational grid box grow under the same conditions, mean‐field representations of mixed‐phase clouds in numerical models favour a quick cloud glaciation driven by the Wegener–Bergeron–Findeisen process. Consequently, maintenance of mixed‐phase states under the mean‐field approximation is conditioned to external dynamical forcing, such as sufficiently strong updraughts. In this work we go beyond the mean‐field representation and investigate the maintenance of mixed‐phase states in adiabatic (non‐entraining) cloud volumes by accounting for local variability in a particle's growth conditions in the turbulent cloud environment. This is done by using a Lagrangian microphysical scheme, where temperature and vapour mixing ratio are stochastic attributes attached to each cloud particle. Different dynamic scenarios show that microphysical variability and parametrised turbulence effects may significantly reduce cloud glaciation rates, resulting in much more resilient mixed‐phase states in idealised parcels containing non‐sedimenting and non‐aggregating cloud particles. We have stated a more refined criterion for the Wegener–Bergeron–Findeisen process activity in the bulk of a mixed‐phase cloud parcel (or computational grid box). This criterion is stated in terms of the conditional average supersaturations that are experienced by specific cloud particle types (liquid or ice), and not in terms of unconditional averages corresponding to parcel‐ or grid‐mean values of supersaturations. Formulation of a relation between conditional and unconditional average supersaturations poses an interesting closure problem in mixed‐phase cloud microphysics. Our stochastic microphysical model provides a Lagrangian closure to this problem and gives insights towards the development of a prognostic stochastic subgrid‐scale scheme for condensation/deposition in numerical models of mixed‐phase clouds.

Heat and mass transfer performance analysis of a vertical tubular ammonia/water bubble absorber based on CFD modeling

Bubble absorbers are highly efficient in mass transfer processes, but their popularization is limited by the risks associated with too much ammonia charging. In order to reduce the ammonia charge, it is essential to optimize the heat and mass transfer performance in the absorber. Existing models provide in-depth analysis of bubble motion and morphology, but insufficient attention has been paid to the concentration distribution and interfacial heat and mass transfer resistance. In this study, a two-dimensional axisymmetric vertical tubular ammonia/water bubble absorber was modeled based on Fluent and phase equilibrium, absorption heat data based on Aspen was imported. The relative deviations were 9%, 0.45%, and 4.1% in terms of the completely absorbed height, the liquid phase ammonia mass fraction, and the outlet temperature, respectively. The results showed that the mass transfer deterioration point was at the gas column closure and the heat transfer deterioration point was at the gas column contraction. Variable parameter studies have shown that turbulence effects at the gas–liquid interface can lead to enhancement and deterioration of local heat and mass transfer, which in turn cause local oscillations in the concentration and temperature profiles. While increasing the interphase mass transfer driving force promotes the interphase mass transfer process, it hinders the diffusion mass transfer process within the liquid phase. This effect is particularly pronounced in the absence of intense cooling, leading to an increase in the complete absorbed height.

Effects of aerodynamic turbulator on efficiency improvement and heat transfer enhancement of the internal flow in a pipe

Effects of aerodynamic turbulator on efficiency improvement and heat transfer enhancement of the internal flow in a pipe

BPSK based MIMO with heterodyne detection for enhancing optical wireless communication performance under effect of atmospheric turbulence and pointing errors

BPSK based MIMO with heterodyne detection for enhancing optical wireless communication performance under effect of atmospheric turbulence and pointing errors

The Alfvén transition zone observed by the Parker Solar Probe in young solar wind – global properties and model comparisons

ABSTRACT The transition from subAlfvénic to superAlfvénic flow in the solar atmosphere is examined by means of Parker Solar Probe (PSP) measurements during solar encounters 8 to 14. Around 220 subAlfvénic periods with a duration ≥10 min are identified. The distribution of their durations, heliocentric distances, and Alfvén Mach number are analysed and compared with a global magnetohydrodynamic model of the solar corona and wind which includes turbulence effects. The results are consistent with a patchy and fragmented morphology, and suggestive of a turbulent Alfvén zone within which the transition from subAlfvénic to superAlfvénic flow occurs over an extended range of helioradii. These results inform and establish context for detailed analyses of subAlfvénic coronal plasma that are expected to emerge from PSP’s final mission phase, as well as for NASA’s planned PUNCH mission.

Fluid-to-fluid similarity and CFD predictions of surrogate fluid as a replacement for R11 refrigerant used in a subcooled flow boiling analysis: Validation against reference experimental data

In this study, we present the possibility of substituting the primary fluid Freon 11 (CCl3F, R11) used in the experimental thermohydraulic test facility which offers the advantage to obtain phase change at relatively low heat fluxes and pressure if compared to water working fluid. Nevertheless, R11 is a CFC (Chlorofluorocarbures) part of the gases that contribute to the degradation of the ozone layer.For this purpose, four working fluids (non-CFC) are judiciously selected to replace the R11, namely the R123, R134a, R143a and CO2, and this through multidimensional Computational Fluid Dynamics (CFD) modeling of steady state flow boiling phenomenon. The calculation model covers a wide range of mass fluxes (435 – 1443 kg/m2s) and heat fluxes (1.2– 36 W/cm2); it predicts the heat transfer rates and transitions points for each flow regime. In this research, the experiment's data were compared to the outcomes of Ansys-CFX computations, using a steady Reynolds-Averaged Navier-Stokes (Steady-RANS) model, to investigate the best replacement refrigerant for R11. The turbulence effects on the mean flow and near wall are taken into consideration using the Shear Stress Transport (SST k-ω) turbulence model. The results from the four fluids were transposed to their water equivalent and compared to those deduced from the experimentation and correlations available in the literature to select the appropriate substitution fluid. The results qualitative and quantitative for vertical and horizontal subcooled boiling flow at the CHF location show that, the most effective surrogate fluid is R123 (HCFC), is still widely used in the refrigeration and air-conditioning industry, then R134a (HFC), then R143a (HFC).