Relative dispersion with finite inertial ranges

Relative dispersion experiments are often analysed using theoretical predictions from two- and three-dimensional turbulence. These apply to infinite inertial ranges, assuming the same dispersive behaviour over all scales. With finite inertial ranges, the metrics are less conclusive. We examine this using pair separation probability density functions (PDFs), obtained by integrating a Fokker–Planck equation with different diffusivity profiles. We consider time-based metrics, such as the relative dispersion, and separation-based metrics, such as the finite scale Lyapunov exponent (FSLE). As the latter cannot be calculated from a PDF, we introduce a new measure, the cumulative inverse separation time (CIST), which can. This behaves like the FSLE, but advantageously has analytical solutions in the inertial ranges. This allows the establishment of consistency between the time- and space-based metrics, something which has been lacking previously. We focus on three dispersion regimes: non-local spreading (as in a two-dimensional enstrophy inertial range), Richardson dispersion (as in an energy inertial range) and diffusion (for uncorrelated pair motion). The time-based metrics are more successful with non-local dispersion, as the corresponding PDF applies from the initial time. Richardson dispersion is barely observed, because the self-similar PDF applies only asymptotically in time. In contrast, the separation-based CIST correctly captures the dependencies, even with a short (one decade) inertial range, and is superior to the traditional FSLE at large scales. Nevertheless, it is advantageous to use all measures together, to seek consistent indications of the dispersion.

Technical note: Interpretation of field observations of point-source methane plume using observation-driven large-eddy simulations

This study demonstrates the ability of large-eddy simulation (LES) forced by a large-scale model to reproduce plume dispersion in an actual field campaign. Our aim is to bring together field observations taken under non-ideal conditions and LES to show that this combination can help to derive point source strengths from sparse observations. We prepared a one-day case study based on data collected near an oil well during the ROMEO campaign (ROmanian Methane Emissions from Oil and gas) that took place in October 2019. We set up our LES using boundary conditions derived from the meteorological reanalysis ERA5 and released a point source in line with the configuration in the field. The weather conditions produced by the LES show close agreement with field observations, although the observed wind field showed complex features due to the absence of synoptic forcing. In order to align the plume direction with field observations, we created a second simulation experiment with manipulated wind fields. The estimated source strengths using the LES plume agrees well with the emitted artificial tracer gas plume, indicating the suitability of LES to infer source strengths from observations under complex conditions. To further harvest the added value of LES, higher order statistical moments of the simulated plume were analysed. Here, we found good agreement with plumes from previous LES and laboratory experiments in channel flows. We derived a length scale of plume mixing from the boundary layer height, the mean wind speed and convective velocity scale. It was demonstrated that this length scale represents the distance from the source at which the predominant plume behaviour transfers from meandering dispersion to relative dispersion.

Electrochemical Determination of Capsaicinoids Content in Soy Sauce and Pot-Roast Meat Products Based on Glassy Carbon Electrode Modified with Β-Cyclodextrin/Carboxylated Multi-Wall Carbon Nanotubes

The rapid quantification of capsaicinoids content is very important for the standardization of pungent taste degree and flavor control of soy sauce and pot-roast meat products. To rapidly quantify the capsaicinoids content in soy sauce and pot-roast meat products, an electrochemical sensor based on β-cyclodextrin/carboxylated multi-wall carbon nanotubes was constructed and the adsorptive stripping voltammetry method was used to enrich samples in this study. The results showed that the excellent performance of the established electrochemical sensor was mostly because β-cyclodextrin caused the relative dispersion of carboxylated multi-wall carbon nanotubes on the glassy carbon electrode surface. Capsaicin and dihydrocapsaicin had similar electrochemical behavior, so the proposed method could determine the total content of capsaicinoids. The linearity of capsaicinoids content was from 0.5 to 100 μmol/L and the detection limit was 0.27 μmol/L. The recovery rates of different capsaicinoids content were between 83.20% and 136.26%, indicating the proposed sensor could realize trace detection of capsaicinoids content in sauce and pot-roast meat products. This work provides a research basis for pungent taste degree standardization and flavor control in the food industry.

Impact of entrainment-mixing and turbulent fluctuations on droplet size distributions in a cumulus cloud: An investigation using Lagrangian microphysics with a sub-grid-scale model

Entrainment-mixing and turbulent fluctuations critically impact cloud droplet size distributions (DSDs) in cumulus clouds. This problem is investigated via a new sophisticated modeling framework using the CM1 LES model and a Lagrangian cloud microphysics scheme – the “super-droplet method” (SDM) – coupled with sub-grid-scale (SGS) schemes for particle transport and supersaturation fluctuations. This modeling framework is used to simulate a cumulus congestus cloud. Average DSDs in different cloud regions show broadening from entrainment and secondary cloud droplet activation (activation above the cloud base). DSD width increases with increasing entrainment-induced dilution as expected from past work, except in the most diluted cloud regions. The new modeling framework with SGS transport and supersaturation fluctuations allows a more sophisticated treatment of secondary activation compared to previous studies. In these simulations, it contributes about 25%of the cloud droplet population and impacts DSDs in two contrastingways: narrowing in extremely diluted regions and broadening in relatively less diluted. SGS supersaturation fluctuations contribute significantly to an increase in DSD width via condensation growth and evaporation. Mixing of super-droplets from SGS velocity fluctuations also broadens DSDs. The relative dispersion (ratio of DSD dispersion and mean radius) negatively correlates with grid-scale vertical velocity in updrafts, but is positively correlated in downdrafts. The latter is from droplet activation driven by positive SGS supersaturation fluctuations in grid-mean subsaturated conditions. Finally, the sensitivity to model grid length is evaluated. The SGS schemes have greater influence as the grid length is increased, and they partially compensate for the reduced model resolution.

Large Eddy Simulation of Microphysics and Influencing Factors in Shallow Convective Clouds

A flight of shallow convective clouds during the SCMS95 (Small Cumulus Microphysics Study 1995) observation project is simulated by the large eddy simulation (LES) version of the Weather Research and Forecasting Model (WRF-LES) with spectral bin microphysics (SBM). This study focuses on relative dispersion of cloud droplet size distributions, since its influencing factors are still unclear. After validation of the simulation by aircraft observations, the factors affecting relative dispersion are analyzed. It is found that the relationships between relative dispersion and vertical velocity, and between relative dispersion and adiabatic fraction are both negative. Furthermore, the negative relationships are relatively weak near the cloud base, strengthen with the increasing height first and then weaken again, which is related to the interplays among activation, condensation and evaporation for different vertical velocity and entrainment conditions. The results will be helpful to improve parameterizations related to relative dispersion (e.g., autoconversion and effective radius) in large-scale models.

Sensitive dependence of trajectories on tracer seeding positions – coherent structures in German Bight backward drift simulations

Backward drift simulations can aid the interpretation of in situ monitoring data. In some cases, however, trajectories are very sensitive to even small changes in the tracer release position. A corresponding spread of backward simulations implies attraction in the forward passage of time and, hence, uncertainty about the probed water body's origin. This study examines surface drift simulations in the German Bight (North Sea). Lines across which drift behaviour changes non-smoothly are obtained as ridges in the fields of the finite-time Lyapunov exponent (FTLE), a parameter used in dynamical systems theory to identify Lagrangian coherent structures (LCSs). Results closely resemble those obtained considering two-particle relative dispersion. It is argued that simulated FTLE fields might be used in support of the interpretation of monitoring data, indicating when simulations of backward trajectories are unreliable because of their high sensitivity to tracer seeding positions.

Hybrid Domain Evaluation PTS with Adaptive Selection Methods for PAPR Reduction

Partial transmit sequence (PTS) technique is a fairly suitable scheme to mitigate the high peak-to-average power ratio (PAPR) problem inherent in 5G multicarrier system-especially considering high-order QAM modulation design. However, the high computational complexity level and the speed of the convergence for optimizing the phases of the transmitting signal restricts this technique in practical applications. In this paper, a low-complexity frequency domain evaluated PTS (F-PTS) based on spacing multi-objective (SMO) processing algorithm is proposed to reduce the PAPR values. The PAPR performance are accurately predicted in terms of modifying relative dispersion in the frequency domain. As a result, the complexity of searching the optimal phase factors and IFFT computing is simplified. Moreover, frequency domain and time domain evaluating PTS (FTD-PTS) is employed to search the optimal solution within reasonable complexity. Simulation results verify that the F-PTS scheme can obtain well secondary peaks with lower computational complexity, and the FTD-PTS scheme effectively reduces PAPR with a faster convergence speed.

High birefringence and broadband dispersion compensation photonic crystal fiber

We propose a perfectly square lattice photonic crystal fiber (PCF) which shows high birefringence and negative dispersion. To set up high asymmetry in the core, dual line imperfection is considered where the fill fraction ratio and defect air hole diameter exhibit significant impact on dispersion and birefringence. Numerical analyses of guiding properties of the proposed PCF are done using finite element method with perfectly matched layer boundary condition from 1.2 to 1.8 μm wavelength. The optimized square lattice PCF presents high birefringence of 2.48 × 10−2 and dispersion of −777.66 (ps/nm.km) at 1.55 μm wavelength. In addition, the proposed PCF offers ultra-low confinement and insertion loss at 1.55 μm wavelength. Moreover, −0.45 (ps/nm2.km) dispersion slope and 0.0045 nm−1 relative dispersion slope are observed at 1.55 μm wavelength. Additionally, the proposed PCF maintains dispersion and birefringence variation of ±30 (ps/nm.km) and ±0.00001 between 1.5 and 1.6 μm wavelength ranges, respectively. Furthermore, the proposed PCF shows high quality factor and low bit error rate at 10 dBm input power. We believe the proposed square lattice PCF can be deployed in wavelength division multiplexing based optical fiber transmission system for wide-band dispersion compensation.