Time-averaged Field Research Articles

Evaluating impedance boundary conditions to model interfacial dynamics in acoustofluidics

We present a numerical study to investigate the efficacy of impedance boundary conditions in capturing the interfacial dynamics of a particle subjected to an acoustic field and study the concomitant time-averaged acoustic streaming and radiation force fields. While impedance boundary conditions have been utilized to represent fluid–solid interface in acoustofluidics, such models assume the solid material to be locally reactive to the acoustic waves. However, there is a limited understanding of when this assumption holds true, raising concerns about the suitability of impedance boundary conditions. Here, we systematically investigate the applicability of impedance boundary conditions by comparing the predictions of an impedance boundary approach against a fully coupled fluid–solid model. We contrast the oscillation profiles of the fluid–solid interface predicted by the two models. We consider different scatterer materials to identify the extent to which the differences in interfacial dynamics impact the time-averaged fields and highlight the divergence within the predictions of the two models. Our findings indicate that, although impedance boundary conditions can yield qualitatively similar results to the full model in certain situations, the predictions from the two models generally differ both qualitatively and quantitatively. These results underscore the importance of exercising caution when applying these boundary conditions to model general acoustofluidic systems.

Reconstruction Of Time-Averaged 3D Pressure Fields In The Wake Of An Ahmed Body With Pressure From PIV

In this contribution, we present and compare time-averaged pressure fields reconstructed from scanned stereoscopic 2D3C-PIV data and volumetric 3D-PTV data (Shake-The-Box) with classic pointwise surface pressure tap measurements. Measurements were conducted in the near-wake region of an one-quarter scaled Ahmed body (Ahmed 1984) with 25° slant angle at height-based Reynolds numbers of Re = 5.06 · 10^4 and 1.13 · 10^5, respectively, i.e. free-stream velocities of 10.5 m/s and 23.5 m/s. The measurements are a continuation of previous measurements (Gericke et al. 2023, Ladwig et al. 2023) with a focus on the more complex flow topology concerning the wake flow structure. Measurements were conducted in a low-speed wind tunnel of Göttinger design with a semi-closed test section at Bochum University of Applied Sciences. The investigated flow field in the near wake region is dominantly characterized by a strongly three-dimensional flow field based on a mutually influenced vortex system in the wake, which challenges the utilized pressure reconstruction algorithm based on the Reynolds-averaged Navier-Stokes equations. The present study addresses challenges in pressure reconstruction due to the presence of highly transient rotational and shearing flow in the context of a practical application. The results show good agreement between reconstructed PIV/PTV-based pressure fields and reference pressure measurements using classic wall pressure measurements. The global characteristics of the pressure distributions are correctly reproduced. The agreement is particularly good in areas of unidirectional flow and local smaller velocity gradients. In shear zones as well as separation and, e.g., recirculation areas, larger deviations are clearly visible, as the velocity gradients present near the surface are not sufficiently captured at all.

Self-similarity of obliquely impinging jet heat flux fields in a range of Mach numbers from 0.1 to 1.0

This study reveals self-similarity (Mach-number-invariance) of the normalized time-averaged surface heat flux fields measured using temperature sensitive paint (TSP) in an obliquely impinging jet in a range of the nozzle exit Mach numbers from 0.1 to 1.0. Further, this self-similarity is also found in the normalized root-mean-square (RMS) fields of the heat flux fluctuation and the normalized skin friction fields extracted from the surface temperature and heat flux fields. To elucidate the origin of this self-similarity, a semi-empirical model is proposed for the maximum surface temperature difference used for normalization, indicating that the Mach number effect on the impinging jet heat transfer is mainly represented by the recovery temperature at the impingement point.

The palaeomagnetic field recorded in Eyjafjarðardalur basalts (2.6–8.0 Ma), Iceland: are inclination-shallowing corrections necessary in time-averaged field analysis?

SUMMARY The geocentric axial dipole (GAD) hypothesis is key to many palaeomagnetic applications, for example plate-tectonic reconstructions; however, the validity of this hypothesis at high latitudes is not fully resolved. To address this, in this paper we determined the palaeomagnetic directional data of 156 lava units in Eyjafjarðardalur, Iceland, with the aim of determining the validity of the GAD hypothesis at high latitudes using time-averaged field (TAF) analysis. In addition to the palaeomagnetic directional data, we constructed an age model for the sequences using new 40Ar/39Ar dates, magnetostratigraphy and field data. The sequence age range is 2.6–8.0 Ma. We show that the mean virtual geomagnetic pole (VGP) for our data does not agree with the GAD theory at 95 per cent confidence, when only the standard tilt and tectonic corrections are made; however, when inclination-shallowing processes are accounted for, for example thermoremanence (TRM) anisotropy and refraction effects, the mean VGP can align with GAD at 95 per cent confidence. These inclination-shallowing processes are shown to reduce the inclination by up to 14° for some of the basaltic units. Applying the inclination-shallowing correction also reduces VGP dispersion to levels that agree with global model predictions. We propose that much of the scatter within the palaeomagnetic directional databases are due to inclination-shallowing process effects, which become more important as the natural remanent magnetization (NRM) intensity is high, for example >2 A m−1. We propose that inclination-shallowing processes can be identified and corrected for by examining the NRM intensity and dispersion.

WindSeer: real-time volumetric wind prediction over complex terrain aboard a small uncrewed aerial vehicle

Real-time high-resolution wind predictions are beneficial for various applications including safe crewed and uncrewed aviation. Current weather models require too much compute and lack the necessary predictive capabilities as they are valid only at the scale of multiple kilometers and hours – much lower spatial and temporal resolutions than these applications require. Our work demonstrates the ability to predict low-altitude time-averaged wind fields in real time on limited-compute devices, from only sparse measurement data. We train a deep neural network-based model, WindSeer, using only synthetic data from computational fluid dynamics simulations and show that it can successfully predict real wind fields over terrain with known topography from just a few noisy and spatially clustered wind measurements. WindSeer can generate accurate predictions at different resolutions and domain sizes on previously unseen topography without retraining. We demonstrate that the model successfully predicts historical wind data collected by weather stations and wind measured by drones during flight.

Numerical Study on the Precipitation Concentration over the Western Coast of Sumatra Island

Abstract Large amounts of tropical precipitation have been observed as significantly concentrated over the western coast of Sumatra Island. In the present study, we used a cloud-resolving model to perform 14-day numerical simulations and reproduce the distinctive precipitation distributions over western Sumatra Island and adjacent areas. The control experiment, in which the warmer sea surface temperature (SST) near the coast was incorporated and the terminal velocity and effective radius of ice clouds were parameterized to be temperature dependent, adequately reproduced the precipitation concentration as well as the diurnal cycles of precipitation. We then used the column-integrated frozen moist static energy budget equation, which is virtually equivalent to the column-integrated moisture budget equation under the weak temperature gradient assumption, to formulate sensitivity experiments focusing on the effects of coastal SST and upper-level ice clouds. Analysis of the time-averaged fields revealed that the column-integrated moisture and precipitation in the coast were significantly reduced when a cooler coastal SST or larger ice cloud particle size was assumed. Based on the comparison of the sensitivity experiments and in situ observations, we speculate that ice clouds, which are exported from inland convection that is strictly regulated by solar radiation, promote the accumulation of moisture in the coastal region by mitigating radiative cooling. Together with the moisture and heat supplied by the warm ocean surface, they contribute to the large amounts of precipitation here.

Contribution of the wind and Loop Current eddies to the circulation in the western Gulf of Mexico

The roles of the Loop Current (LC) and associated eddies in driving the circulation of the Gulf of Mexico (GoM) have been investigated for several decades from different perspectives. Nevertheless, a clear understanding of the relative contributions of the wind forcing and the Loop Current eddies (LCEs) to the GoM circulation and variability remain lacking. In this study, the roles of these two factors in sustaining the less well-known western GoM upper-layer (~1000 m) circulation are investigated with two numerical experiments using the HYbrid Coordinate Ocean Model (HYCOM). First, we examine the relative contributions of the wind and LCEs in setting the mean circulation in the western GOM. We then perform a vorticity balance to analyze the relative importance of the physical processes, including the wind stress, involved in sustaining the western GoM circulation. The results show that the wind stress contributes to a mean anticyclonic circulation in the central and northwestern Gulf, while in the southwestern subregion both wind and LCEs combine to induce a cyclonic circulation, highlighting the role of wind stress curl and topographic confinement. The vorticity balance analysis conducted in the upper layer of the western basin shows that planetary vorticity and stretching are primarily responsible for the balance in time scales longer than weeks, and their co-variability are good indicators of LCEs entering the central and northwestern subregions. However, the southwestern subregion is primarily driven by vortex stretching. Mean advection of vorticity and planetary vorticity are also contributors to the time-averaged vorticity field. Since the wind stress is distributed over the upper layer of the GoM, direct input of vorticity in the regional vorticity balance is negligible, but it does play a role through the vortex stretching term. The results also suggest that wind forcing acts to produce larger, faster moving, and longer-lived anticyclonic eddies that impact the western Gulf and modulate the circulation over monthly timescales.

Predicting Concentration Fluctuations of Locally Emitted Air Pollutants in Urban-like Geometry Using Deep Learning

The accurate quantification of concentration fluctuations is crucial when evaluating the exposure to toxic, infectious, reactive, flammable, or explosive substances, as well as for the estimation of odor nuisance. However, in the field of Computational Fluid Dynamics (CFD), the industry currently relies predominantly on steady-state RANS turbulence models for simulating near-field pollutant dispersion, which are only capable of producing the time-averaged concentration field. This paper presents a regression relationship for calculating the standard deviation of the local concentration based on the mean concentration and the downstream distance from a point source, over a city-like surface, in the case of the wind direction perpendicular to the streets. The desired peak values and other statistical characteristics can be predicted by assuming a gamma distribution which is fitted based on the average and standard deviation. To obtain the regression function, a deep neural network model was used. The model was trained using time-resolved concentration data obtained from wind tunnel experiments. The validation results show that the concentration fluctuations predicted by the DNN-based model are in satisfactory agreement with the measurement data in terms of the skewness, the kurtosis, the median, and the peak concentrations. Furthermore, the present paper suggests a workflow for estimating the concentration fluctuations based on RANS CFD results, as well as recommendations for generating further training data for specific applications.

MHD in a Cylindrical Shearing Box. II. Intermittent Bursts and Substructures in MRI Turbulence

By performing ideal magnetohydrodynamical (MHD) simulations with weak vertical magnetic fields in unstratified cylindrical shearing boxes with modified boundary treatment, we investigate MHD turbulence excited by magnetorotational instability. The cylindrical simulation exhibits extremely large temporal variation in the magnetic activity compared with the simulation in a normal Cartesian shearing box, although the time-averaged field strengths are comparable in the cylindrical and Cartesian setups. Detailed analysis of the terms describing magnetic energy evolution with “triangle diagrams” surprisingly reveals that in the cylindrical simulation the compression of toroidal magnetic field is unexpectedly as important as the winding due to differential rotation in amplifying magnetic fields and triggering intermittent magnetic bursts, which are not seen in the Cartesian simulation. The importance of the compressible amplification is also true for a cylindrical simulation with tiny curvature; the evolution of magnetic fields in the nearly Cartesian shearing box simulation is fundamentally different from that in the exact Cartesian counterpart. The radial gradient of epicyclic frequency, κ, which cannot be considered in the normal Cartesian shearing box model, is the cause of this fundamental difference. An additional consequence of the spatial variation of κ is continuous and ubiquitous formation of narrow high-density (low-density) and weak-field (strong-field) localized structures; seeds of these ring gap structures are created by the compressible effect and subsequently amplified and maintained under the marginally unstable condition regarding “viscous-type” instability.

Analyzing 3D fields of refractive index, emission and temperature in spray-flame nanoparticle synthesis via tomographic imaging using multi-simultaneous measurements (TIMes)

Turbulent spray flames issuing from the SpraySyn 2.0 burner were investigated in the present work by means of tomographic imaging using multi-simultaneous measurements (TIMes). This small-scale standard burner is designed to study flame-spray synthesis of tailored nanoparticle systems. The applied measurement technique combined background-oriented schlieren tomography, computed tomography of light emission and two-color tomographic salt emission thermometry to reveal single-shot and time-averaged 3D fields of refractive index (linked to temperature, pressure and species concentration), CH* chemiluminescence (flame front indicator), SrOH emission from synthesized trace amount of Sr(NO3)2 dissolved in the liquid precursor solution (marker of the hot spray-flame products), and temperature of the hot spray-flame products, respectively. The salt emission thermometry technique was extended to tomographic measurements for the first time. Its implementation was based on the voxel-wise intensity ratio of reconstructed thermally-excited SrOH signals at two different regions in the visible spectrum that was converted to temperature using a single calibration curve based on multi-line OH planar laser-induced fluorescence measurements. The cost-effective setup for TIMes was composed of 43 machine-vision cameras equipped with bandpass spectrum filters, an innovative continuous semi-circular background pattern and LED light sources. The combined reconstructed fields provided information on the 3D flame structure in detail, showing the interaction between the flame front and spray stream, and the hot temperature regions. Spray-flame features were quantitatively analyzed, namely temperature, height, width, 3D tilt angle, and spreading half-angle of the flame plume. The temperature measurements proved to be robust against variations in the fuel/oxidizer equivalence ratio for the four investigated operating conditions. The spray flame issuing from the SpraySyn 2.0 burner at the standard operating condition was more stable than that in the previous burner generation, although more asymmetric near the nozzle exit and tilted, which might still cause heterogeneity of the synthesized nanoparticle system.

Assessment of cavitation erosion risk by Eulerian–Lagrangian multiscale modeling

Cavitation erosion in fluid machineries is a complicated physicochemical and instantaneous process, leading to material loss and reduced efficiency. As the cavitation and the consequent erosion are difficult to be measured and modeled, the present work aims to incorporate an improved energy balance approach into a new Eulerian–Lagrangian multiscale model for addressing the risk of cavitation erosion. The volume of fluid (VOF) and discrete bubble model (DBM) are coupled by a transforming algorithm to develop the multiscale cavitation model. With using the large eddy simulation (LES) approach, the multiscale cavitation features including the morphological evolution of large-cavities and characteristics of microbubbles are well reproduced. To assess the cavitation erosion, a modified aggressive indicator using a modified moving time-averaged pressure field as the driving pressure is proposed to consider the evolution of local pressure and vapor volume fraction. Furthermore, the erosion powers produced from large cavities and microbubbles are completely taken into account. The results show that the VOF-DBM multiscale model can better simulate the cavitation features around a twisted hydrofoil including the secondary shedding and the horse-shoe vapor structure, compared with the VOF method using the same mesh resolution. From the results of discrete bubbles, it is found that the primary shedding leads to the rapid growth of the number of discrete bubbles, which decreases during the transportation of the bubble cloud generated from the primary shedding. By taking the collapsing power of discrete bubbles into account, the prediction of cavitation erosion distribution is quite consistent with the experimental one, whereas the VOF method fails to predict the erosion region near the trailing edge.

Interaction effect of adjacent pores on plasma generation inside pores of porous catalysts

A study on the influence of pore characteristics on the microdischarge plasma inside pores of catalyst is important for understanding plasma catalysis mechanism. This article focuses on the effect of pore interaction on plasma production in pores including electron density, electron temperature, and total ion density, etc. These parameters are calculated by solving the electron energy density conservation equation, electron convection diffusion equation, heavy species conservation equation and Poisson equation. The numerical simulation results show that the distribution of electron density, electron temperature and electric field in and near a pore is apparently affected by the adjacent pore, namely, the time-averaged electron density, total ion density and ionization rate in a pore increase with the pore spacing in the range of 8–150 μm because the loss of electrons to the wall due to the adjacent pore decreases with the increasing pore spacing, but there is an opposite law for the time-averaged electron temperature and electric field in a pore; moreover, the pore spacing presents more apparent effect on the plasma generation in a smaller pore and at higher applied voltage, indicating stronger interactions between pores at these conditions. The simulation results show that the pore characteristics of porous catalysts including pore spacing and pore diameter may affect the degradation of pollutants in plasma catalysis processes. The study is important for understanding the plasma catalysis mechanisms, especially the influence mechanism of pore interaction on microdischarge in porous catalysts.

Vapor concentration and bimodal distributions of turbulent fluctuations in cavitating flow around a hydrofoil

The article presents results of a statistical analysis of the original PIV data for the cavitating flow around the 2D symmetric hydrofoil mimicking a guide vane of a Francis turbine which were previously reported in Timoshevskiy et al. (2020). We employ the procedure of statistical vector filtration (Heinz et al., 2004) to eliminate vector outliers from the measured velocity fields, which allows us to retrieve genuine spatial distributions of higher-order statistical moments of velocity fluctuations, and the method of vapor phase detection (Pervunin et al., 2021) to extract time-averaged fields of vapor in the cavitating flow. The spatial distributions of the probability of vapor phase occurrence allowed us to unambiguously distinguish the extension of the flow area occupied by the dispersed phase (cavitation) together with the time-averaged concentration of the vapor phase in the three characteristic regimes of the cavitating flow as well as different features of cavitation evolution, including the location and length of an attached cavity and the place of detachments of cloud cavities in the case of unsteady cloud cavitation. The development of cavitation is also reflected in the fields of higher-order statistical moments of turbulent fluctuations by the example of coefficients of asymmetry and excess. With a transition to unsteady cloud cavitation, the distribution of velocity fluctuations transforms, taking a nonequilibrium shape, with an increase in magnitudes of the asymmetry and excess coefficients over a significant flow area. In a region of the attached cavity, around the place of formation of vapor clouds and downstream, where the cloud cavities are carried away by the flow, the distribution of velocity fluctuations becomes bimodal. Through visual inspection of the raw PIV images, realizations related to two characteristic phases of the cavity oscillation cycle were extracted, providing quasi-phase-averaged data. As a result, the bimodal shape of the distributions in certain areas of the unsteady cavitating flow was demonstrated to be most probably linked with periodic detachments and downstream advection of the vapor clouds as the predominant fundamental process determining the flow structure and dynamics.

Optimizing the trench shaped film cooling design

In this numerical study an optimized trench film cooling design is determined using a Bayesian algorithm and neural network trained RANS model. Three objective functions were considered, the area-averaged film cooling efficiency, spatial standard deviation of film cooling efficiency and hot gas ingestion into the trench. Nine geometrical design parameters were varied to allow for a 3D trench shape and to find an optimal trench design based on the initial parametrization of the trench. Jet-engine like inflow boundary conditions with respect to turbulence intensity and length scales were applied. The investigated momentum ratios (I) were 1 and 8 at a main flow Reynolds number (ReD) of 2500. For each design the steady state Reynolds Averaged Navier-Stokes (RANS) equations were solved using the commercial Computational Fluid Dynamics (CFD) code Ansys Fluent V2022 R1. The turbulence model coefficients of the generalized k−ω (GEKO) model were tuned to approximate the time-averaged 3D temperature field from a predictive Large Eddy Simulation (LES) and trained by a neural network to improve the prediction capability. The tuned GEKO model shows improved agreement with experimental data of a literature case compared to the standard GEKO model. With this tuned RANS model optimized trench designs are found and validated by additional LES’s. The optimized designs include angled side walls to improve former trench designs, particularly in mitigating hot gas entrainment into the trench, which could be omitted almost entirely.

Machine learning and sensitivity analysis for predicting nasal drug delivery for targeted deposition

Targeted nasal drug delivery can provide improved efficacy for drug formulations to be delivered at high efficacy rates. Some parameters that influence drug delivery have a dependency on the patient’s technique of administration and the spray device itself. When the different parameters, each having a specific range of values are combined, the combinatory permutations for studying its effects on particle deposition become large.In this study, we combine six input spray parameters (the spray half-cone angle, the mean spray exit velocity, the breakup length from the nozzle exit, the diameter of the nozzle spray device, the particle size, and the sagittal angle of the spray) with a range of values to produce 384 combinations of spray characteristics. This was repeated for three inhalation flow rates of 20, 40, and 60 L/min.To reduce the computational costs of a full transient Large Eddy Simulation flow field, we create a time-averaged frozen field and perform the time integration of particle trajectories through the flow field to determine the particle deposition in four anatomical regions of the nasal cavity (anterior, middle, olfactory and posterior) for each of the 384 spray field.A sensitivity analysis determined the significance of each input variable on the deposition. It was found the particle size distribution significantly affected deposition in the olfactory and posterior regions, while the spray device insertion angle was significant for deposition in the anterior and middle regions.Five machine learning models were evaluated based on 384 cases and it was found that despite the small sample dataset the simulation data was sufficient to provide accurate machine-learning predictions.

Meta-analysis of a large bedload transport rate dataset

The estimation of bedload transport, a type of coarse fluvial sediment motion, is challenging because of higher-order, complex, and time-variable environmental processes. Still, models for calculating bedload transport mostly rely on semi-empirical formulae derived from time-averaged laboratory flume or field measurements and involve cross-section averaging of hydro-environmental parameters. Additionally, many models assume infinite, constant availability of sediment, which is unrealistic in natural environments. While most published models yield excellent results on the dataset they were trained on, they may be significantly inaccurate when applied to other cases. Also, more recent formulae relying on considerable amounts of data still lead to high calculation uncertainty. While the importance of short-term dynamics, for example, driven by turbulence, for bedload transport is well known, this study investigates the relevance of time-variable processes at monthly to seasonal scales. Our analysis of a large dataset and remote sensing data shows evidence for seasonal variability in measurements of bedload transport rates and challenges the validity of Gaussian statistics for interpolating bedload transport models. Measured bedload transport rates were smaller when snowmelt was taking place and when no glacier was present in the catchment, and were best represented by extreme value distributions. By controlling for biases from measurement devices, geomorphic patterns, and the presence of an upstream dam, we show that steady, constant at-a-station hydraulics only explain a limited share of the variance in the measurements. Ultimately, a model for estimating bedload transport rates should consider the temporal variability of processes across all scales, from turbulence to climate.

Palaeosecular variation in Northern Patagonia recorded by 0–5 Ma Caviahue–Copahue lava flows

SUMMARY Palaeosecular variation (PSV) determinations and studies of the geometry of the Earth’s main magnetic field provide important information about the field evolution, and to constrain numerical geodynamo models. Palaeomagnetic directional data from lava flows over the last few million years is of particular interest because the regional and global tectonic effects are minimal. However, the distribution of this type of palaeomagnetic data is uneven where the Southern Hemisphere is the destitute side. Therefore, the better knowledge of the geomagnetic field behaviour depends on the increased availability of high-quality data, especially in the Southern Hemisphere. A PSV and the time-averaged field (TAF) study was then performed in 0–5 Ma lava flows from the Caviahue–Copahue Volcanic Complex located in Northern Patagonia, Argentina (37°0′S, 71°10′W). The magnetic mineralogy of lava flows was investigated through thermomagnetic susceptibility curves, isothermal remanent magnetization (IRM) acquisition curves, hysteresis loops and first-order reversal curves (FORCs). Samples are essentially comprised of titanomagnetite with different Ti contents and magnetic domain structures typical of vortex state particles. A total of 50 volcanic sites were sampled, which provided 42 reliable palaeomagnetic site-mean directions after alternating field and thermal demagnetization. From these 42 sites, 36 are of normal and 6 are of reversed polarity. The mean direction from normal (reversed) sites is D = 356.2°, I = −50.1°, α95 = 4.0° and N = 36 (D = 176.5°, I = 59.5°, α95 = 14.1° and N = 6). Using only site-level data with the precision parameter k ≥ 100, we obtain 26 palaeomagnetic sites for PSV and TAF investigations in the study region. The filtered data set has a mean direction (D = 354.4°, I = −53.2° and α95 = 5.1°) close to the expected direction for a geocentric axial dipole (GAD) field (IGAD = −57.3°). The palaeopole (Plat = 84.4°, Plon = 229.1° and A95 = 5.7°) coincides with the Earth’s spin axis within the 95 per cent confidence interval. Virtual geomagnetic pole scatter ($S_{B} = {15.8^{18.9}_{11.8}}^{\circ }$) and the inclination anomaly ($\Delta I = 4.1_{-1.0}^{{9.2}^{\circ }}$) are both consistent at the 95 per cent confidence level with recent PSV and TAF models, respectively. Our results support the presence of small non-dipole field contributions (<3 per cent) superimposed on the GAD term, as reported by South American studies at mid southern latitudes.

RF-EMF Exposure near 5G NR Small Cells.

Of particular interest within fifth generation (5G) cellular networks are the typical levels of radiofrequency (RF) electromagnetic fields (EMFs) emitted by 'small cells', low-power base stations, which are installed such that both workers and members of the general public can come in close proximity with them. In this study, RF-EMF measurements were performed near two 5G New Radio (NR) base stations, one with an Advanced Antenna System (AAS) capable of beamforming and the other a traditional microcell. At various positions near the base stations, with distances ranging between 0.5 m and 100 m, both the worst-case and time-averaged field levels under maximized downlink traffic load were assessed. Moreover, from these measurements, estimates were made of the typical exposures for various cases involving users and non-users. Comparison to the maximum permissible exposure limits issued by the International Commission on Non-Ionizing Radiation Protection (ICNIRP) resulted in maximum exposure ratios of 0.15 (occupational, at 0.5 m) and 0.68 (general public, at 1.3 m). The exposure of non-users was potentially much lower, depending on the activity of other users serviced by the base station and its beamforming capabilities: 5 to 30 times lower in the case of an AAS base station compared to barely lower to 30 times lower for a traditional antenna.

Research on the flow characteristics of the bulk carrier wake field based on particle image velocimetry

The wake field has three-dimensional flow separation characteristics, affecting various ship performances. The research on the characteristics of the wake field can provide theoretical guidance for the formation of new ship design methods and provide an understanding of flow mechanisms for improving ship performance. To explore the flow mechanism of the wake field, particle image velocimetry was used to carry out the detailed flow measurement of bulk carriers. First, the experimental uncertainty and convergence are analyzed. Then, the spatial distribution characteristics of the time-averaged field, instantaneous field, and turbulent flow statistics are discussed in detail, and a criterion for discriminating turbulent anisotropy is proposed. The results show that the vortex structure significantly affects flow characteristics, and the axial velocity contours present a U-form distribution with prominent “hook-like” features. Compared with the time-averaged velocity field, the instantaneous velocity field is chaotic and has multiple additional vortex structures, and the velocity contours and streamlines have prominent non-smooth characteristics. The wake field has an apparent double vortex structure, and the aggregation of many small vortices forms the bilge vortex. The instantaneous rotation characteristics of vortices in the wake field are highly time-dependent and fluctuate with time. The turbulent kinetic energy, the root mean square of fluctuation velocity, and the Reynolds stress have a U-form distribution. The U-form region is concentrated in the area with a large gradient. The wake distribution is in a state of turbulent anisotropy, and the kinetic energy change layer and low kinetic energy region have a low turbulent anisotropy.

Three-Dimensional Turbulent Flow Characteristics Near the Leading Edge of a Longitudinal Structure in the Presence of an Inclined Channel Bank

The present work investigates turbulent flow structures and behavior near the leading edge of a longitudinal flow obstruction in an open channel with an inclined bank. A volumetric particle image velocimetry (VPIV) was employed to collect velocity data. The results indicate that a relatively moderate channel bank angle (θ=28∘) does not prevent the formation of a junction vortex (JV) system. Indeed, it is found that the JV system develops over the channel bank and extends to the leading edge of the flow obstruction. It is demonstrated that the main factor that strengthens the primary junction vortex (JV1) at the tip of the protrusion is the pronounced downward flow. The probability density functions (pdfs) of the velocity fluctuations specify that the JV1 oscillates aperiodically between the so-called zero-flow and back flow modes. This explains the amplification of TKE at its core. It is shown that the velocity difference between the peaks of the pdf increases from over the channel bank towards the tip of the flow obstruction. The aperiodic behavior of the JV1 is confirmed via the proper orthogonal decomposition (POD) technique. Specifically, it is demonstrated that the leading POD modes, associated with the JV system, contain lower energy content compared to periodic flows. The time-averaged vertical vorticity field verifies the presence of a tornado like vortex structure near the upstream face of the retaining wall. Finally, the results suggest that the largest bed shear stress values in the mean flow are located near the tip of the protrusion.