Numerical Evaluation of Two k-εTurbulence Model for Predicting Flow and Solidification in Continuous Casting Slab

A steady three-dimensional fluid flow and solidification model was built based on CFD software by high-Reynolds-number and Lam-Bremhorst low-Reynolds-number k-ε model.During the simulation,the fixed-grid enthalpy-porosity technique was used to represent the solidification,and Darcy law was adopted to simulate the flow in mushy region.The prediction for steel flow and solidification was evaluated by the comparison of two turbulence models.It is found that both Lam-Bremhorst low-Reynolds-number and high-Reynolds-number k-ε models predict the same trend of the steel flow and temperature distribution.However,due to the effect of turbulent flow on heat transfer,the low-Reynolds-number turbulence model predicts longer penetration depth of molten steel in sub-mold region,less shell growth and higher shell surface temperature at the narrow face compared with standard k-ε model.

An assessment of k-εturbulence models for gas distribution analysis

This paper presents the gas distribution analysis by injecting air fountain into the containment and simulations with the HYDRAGON code. Turbulence models of standard k-ε(SKE), re-normalization group k-ε(RNG) and a realizable k-ε(RLZ) are used to assess the effects on the gas distribution analysis during a severe accident in a nuclear power plant. By comparing with experimental data,the simulation results of the RNG and SKE turbulence models agree well with the experimental data on the prediction of dimensionless density distributions. The results illustrate that the turbulence model choice had a small effect on the simulation results, particularly the region near to the air fountain source.

Mapping Network-Coordinated Stacked Gated Recurrent Units for Turbulence Prediction

Accurately predicting fluid forces acting on the sur-face of a structure is crucial in engineering design.However,this task becomes particularly challenging in turbulent flow,due to the complex and irregular changes in the flow field.In this study,we propose a novel deep learning method,named mapping net-work-coordinated stacked gated recurrent units(MSU),for pre-dicting pressure on a circular cylinder from velocity data.Specifi-cally,our coordinated learning strategy is designed to extract the most critical velocity point for prediction,a process that has not been explored before.In our experiments,MSU extracts one point from a velocity field containing 121 points and utilizes this point to accurately predict 100 pressure points on the cylinder.This method significantly reduces the workload of data measure-ment in practical engineering applications.Our experimental results demonstrate that MSU predictions are highly similar to the real turbulent data in both spatio-temporal and individual aspects.Furthermore,the comparison results show that MSU predicts more precise results,even outperforming models that use all velocity field points.Compared with state-of-the-art methods,MSU has an average improvement of more than 45%in various indicators such as root mean square error(RMSE).Through comprehensive and authoritative physical verification,we estab-lished that MSU’s prediction results closely align with pressure field data obtained in real turbulence fields.This confirmation underscores the considerable potential of MSU for practical applications in real engineering scenarios.The code is available at https://github.com/zhangzm0128/MSU.

基于Alt-Geohash编码的k-匿名位置隐私保护方案

在对享受基于位置服务(LBS)用户进行位置隐私保护时,传统k-匿名技术在执行匿名操作时没有全面考虑时间开销和位置背景信息。针对上述问题,提出了一种基于Alt-Geohash编码的k-匿名位置隐私保护方案(k-anonymous location privacy protection scheme based on Alt-Geohash coding,KLPPS-AGC)。首先,通过位置泛化和Alt-Geohash编码技术实现对历史数据的快速检索;其次,根据历史查询概率筛选出能与用户构建高位置熵的位置;再次,利用海伦公式改善匿名集的位置分散度;最后,构建安全匿名集实现对用户的位置隐私保护。实验证明,该方案拥有较低的时间开销和较高的隐私性。

Effects of aeration induced turbulence on colonial morphology and microcystin release of the bloom-forming cyanoabcterium Microcystis

Aeration induced turbulence was considered as an important measure to control the occurrence of cyanobacterial blooms in many lakes.Different aeration intensities were set for the culture of Microcystis aeruginosa based on the formation of Microcystis colony at high iron concentrations.The turbulent dissipation rate was calculated using a computational fluid dynamics(CFD)model to evaluate the intensity of turbulence.The effects of turbulence on the formation of Microcystis colony and the release of microcystin were analyzed.Results show that turbulence produced by aeration promoted the growth of Microcystis compared to that in stagnant water.Low intensity turbulence(4×10^(-8)-1×10^(-7) m2/s3)promoted the formation of Microcystis colonies,but high intensity turbulence(1.28×10^(-6)-1.8×10^(-5) m^(2)/s^(3))did not.The increase in the number of cells per colony was slower than that in total biomass,indicating that the low intensity turbulence induced colony formation via cell division,while the high level turbulence disaggregated colonies formed by both cell division and cell adhesion.Low aeration intensity induced more production of reactive oxygen species(ROS)and malondialdehyde(MDA)in the cells of Microcystis than those in high aeration intensity.In addition,the content of microcystin(MC)-LR in the cells was positively correlated with turbulence intensity,showing that turbulence affected not only the growth and aggregation of Microcystis colonies but also their toxin production.These findings provide a better understanding of the cyanobacterial bloom formation mechanisms and help to propose feasible methods to prevent the formation of Microcystis colonies in a natural environment.

Properties of focused Laguerre–Gaussian beam propagating in anisotropic ocean turbulence

We analyze the properties of a focused Laguerre–Gaussian(LG)beam propagating through anisotropic ocean turbulence based on the Huygens–Fresnel principle.Under the Rytov approximation theory,we derive the analytical formula of the channel capacity of the focused LG beam in the anisotropic ocean turbulence,and analyze the relationship between the capacity and the light source parameters as well as the turbulent ocean parameters.It is found that the focusing mirror can greatly enhance the channel capacity of the system at the geometric focal plane in oceanic turbulence.The results also demonstrate that the communication link can obtain high channel capacity by adopting longer beam wavelength,greater initial beam waist radius,and larger number of transmission channels.Further,the capacity of the system increases with the decrease of the mean squared temperature dissipation rate,temperature-salinity contribution ratio and turbulence outer scale factor,and with the increase of the kinetic energy dissipation rate per unit mass of fluid,turbulence inner scale factor and anisotropy factor.Compared to a Hankel–Bessel beam with diffraction-free characteristics and unfocused LG beam,the focused LG beam shows superior anti-turbulence interference properties,which provide a theoretical reference for research and development of underwater optical communication links using focused LG beams.

Detection of Turbulence Anomalies Using a Symbolic Classifier Algorithm in Airborne Quick Access Record(QAR)Data Analysis

As the risks associated with air turbulence are intensified by climate change and the growth of the aviation industry,it has become imperative to monitor and mitigate these threats to ensure civil aviation safety.The eddy dissipation rate(EDR)has been established as the standard metric for quantifying turbulence in civil aviation.This study aims to explore a universally applicable symbolic classification approach based on genetic programming to detect turbulence anomalies using quick access recorder(QAR)data.The detection of atmospheric turbulence is approached as an anomaly detection problem.Comparative evaluations demonstrate that this approach performs on par with direct EDR calculation methods in identifying turbulence events.Moreover,comparisons with alternative machine learning techniques indicate that the proposed technique is the optimal methodology currently available.In summary,the use of symbolic classification via genetic programming enables accurate turbulence detection from QAR data,comparable to that with established EDR approaches and surpassing that achieved with machine learning algorithms.This finding highlights the potential of integrating symbolic classifiers into turbulence monitoring systems to enhance civil aviation safety amidst rising environmental and operational hazards.

Numerical prediction of inner turbulent flow in conical diffuser by using a new five-point scheme and DLR k-ε turbulence model

The internal turbulent flow in conical diffuser is a very complicated adverse pressure gradient flow.DLR k-ε turbulence model was adopted to study it.The every terms of the Laplace operator in DLR k-ε turbulence model and pressure Poisson equation were discretized by upwind difference scheme.A new full implicit difference scheme of 5-point was constructed by using finite volume method and finite difference method.A large sparse matrix with five diagonals was formed and was stored by three arrays of one dimension in a compressed mode.General iterative methods do not work wel1 with large sparse matrix.With algebraic multigrid method(AMG),linear algebraic system of equations was solved and the precision was set at 10-6.The computation results were compared with the experimental results.The results show that the computation results have a good agreement with the experiment data.The precision of computational results and numerical simulation efficiency are greatly improved.

Numerical simulation of a combined oxidation ditch flow using 3D k-ε turbulence model

The standard three dimensional（3D） k-ε turbulence model was applied to simulate the flow field of a small scale combined oxidation ditch. The moving mesh approach was used to model the rotor of the ditch. Comparison of the computed and the measured data is acceptable. A vertical reverse flow zone in the ditch was found, and it played a very important role in the ditch flow behavior. The flow pattern in the ditch is discussed in detail, and approaches are suggested to improve the hydrodynamic performance in the ditch.

REVISED k-ε TURBULENCE MODEL IN ELECTROMAGNETIC CONTINUOUS CASTING OF MELT

The research is motivated by the ongoing the electromagnetic continuous casting of molten metal. The revised k-ε model considering the effect of magnetic field application was derived. The specific model equations for the electromagnetic braking were used to calculate the velocity distribution in the continuous casting mold of steel. The results show that the revised k-ε model considering the effect of magnetic field application tends to suppress the production of turbulence and difference between the conventional and revised k-e model is small.

A K-εTWO-EQUATION TURBULENCE MODEL FOR THE SOLID-LIQUID TWO-PHASE FLOWS

A two-equation turbulence model has been dereloped for predicting two-phase flow the two equations describe the conserration of turbulence kinetic energy and dissipation rate of that energy for the incompressible carrier fluid in a two-phase flow The continuity, the momentum, K and εequations are modeled. In this model,the solid-liquid slip veloeites, the particle-particte interactions and the interactions between two phases are considered,The sandy water pipe turbulent flows are sueeessfuly predicted by this turbulince model.

Robust autofocusing propagation in turbulence

Turbulence in complex environments such as the atmosphere and biological media has always been a great challenge to the application of beam propagation in optical communication, optical trapping and manipulation. To overcome this challenge, this study comprehensively investigates the robust propagation of traditional Gaussian and autofocusing beams in turbulent environments. In order to select stable beams that exhibit high intensity and high field gradient at the focal position in complex environments, Kolmogorov turbulence theory is used to simulate the propagation of beams in atmospheric turbulence based on the multi-phase screen method. We systematically analyze the intensity fluctuations, the variation of the coherence factor and the change in the scintillation index with propagation distance. The analysis reveals that the intensity fluctuations of autofocusing beams are significantly smaller than those of Gaussian beams, and the coherence of autofocusing beams is better than that of Gaussian beams under turbulence. Moreover, autofocusing beams exhibit less oscillation than Gaussian beams, indicating that autofocusing beams propagate in complex environments with less distortion and intensity fluctuation. Overall, this work clearly demonstrates that autofocusing beams exhibit higher stability in propagation compared with Gaussian beams, showing great promise for applications such as optical trapping and manipulation in complex environments.

Baseline design of the KunLun Turbulence Profiler instrument

Adaptive optics systems are the most powerful tools to counteract the image blurring caused by atmospheric turbulence,allowing ground-based telescopes to capture high-resolution images.A critical parameter influencing adaptive optics system performance is the atmospheric refractive index structure constant,C_(n)^(2),which characterizes the intensity of atmospheric optical turbulence as a function of altitude.Given its simplicity,the lunar scintillometer is the preferred method for detecting atmospheric turbulence in challenging environments like Dome A in Antarctica,where sites are still in the developmental stages and local environmental conditions are extremely harsh.However,optimizing the performance of such instruments requires carefully determining the baseline configuration of photon sensors according to each site's specific optical turbulence profile characteristics.This study uses a Monte Carlo method to identify the optimal configuration for the KunLun Turbulence Profiler(KLTP),an instrument comparable to the lunar scintillometer,developed for use at Dome A.Simulations conducted using the obtained optimal baseline configuration recovered three different model optical turbulence profiles,demonstrating the effectiveness of our method in obtaining an optimal baseline configuration.Our approach can be easily applied to baseline design for similar turbulence profilers at other sites.

J-TEXT achievements in turbulence and transport in support of future device/reactor

Following the reconstruction of the TEXT tokamak at Huazhong University of Science and Technology in China, renamed as J-TEXT, a plethora of experimental and theoretical investigations has been conducted to elucidate the intricacies of turbulent transport within the tokamak configuration. These endeavors encompass not only the J-TEXT device's experimental advancements but also delve into critical issues pertinent to the optimization of future fusion devices and reactors. The research includes topics on the suppression of turbulence, flow drive and damping, density limit, non-local transport, intrinsic toroidal flow, turbulence and flow with magnetic islands, turbulent transport in the stochastic layer, and turbulence and zonal flow with energetic particles or helium ash. Several important achievements have been made in the last few years, which will be further elaborated upon in this comprehensive review.

First results of turbulence investigation on Globus-M2 using radial correlation Doppler reflectometry

The first results of investigation of the turbulence structure using Doppler backscattering(DBS)on the Globus-M2 tokamak are presented.A one-channel DBS system with a variable probing frequency within the 18–26 GHz range was installed to investigate the edge plasma at normalized minor radiiρ=0.9–1.1.Radial correlation Doppler reflectometry was used to study the changes in turbulence eddies after the LH transition.Correlation analysis was applied to the phase derivative of complex in-phase and quadrature(IQ)signals of the DBS diagnostic as it contains information about the poloidal plasma rotation velocity.In L-mode,the radial correlation length L_(r)is estimated to be 3 cm and after transition to H-mode reduces to approximately 2 cm.Gyrokinetic modelling in a linear local approximation using code GENE indicates that the instability with positive growth rate at the normalized minor radiusρ=0.75 in L-mode and H-mode on Globus-M2 was the ion temperature gradient(ITG)mode.

Proton acceleration in plasma turbulence driven by high-energy lepton jets

The interaction of high energy lepton jets composed of electrons and positrons with background electron–proton plasma is investigated numerically based upon particle-in-cell simulation,focusing on the acceleration processes of background protons due to the development of electromagnetic turbulence.Such interaction may be found in the universe when energetic lepton jets propagate in the interstellar media.When such a jet is injected into the background plasma,theWeibel instability is excited quickly,which leads to the development of plasma turbulence into the nonlinear stage.The turbulent electric and magnetic fields accelerate plasma particles via the Fermi II type acceleration,where the maximum energy of both electrons and protons can be accelerated to much higher than that of the incident jet particles.Because of background plasma acceleration,a collisionless electrostatic shock wave is formed,where some pre-accelerated protons are further accelerated when passing through the shock wave front.Dependence of proton acceleration on the beam-plasma density ratio and beam energy is investigated.For a given background plasma density,the maximum proton energy generally increases both with the density and kinetic energy of the injected jet.Moreover,for a homogeneous background plasma,the proton acceleration via both turbulent fields and collisionless shocks is found to be significant.In the case of an inhomogeneous plasma,the proton acceleration in the plasma turbulence is dominant.Our studies illustrate a scenario where protons from background plasma can be accelerated successively by the turbulent fields and collisionless shocks.

Scaling Laws Behind Penetrative Turbulence:History and Perspectives

An unstably stratified flow entering into a stably stratified flow is referred to as penetrative convection,which is crucial to many physical processes and has been thought of as a key factor for extreme weather conditions.Past theoretical,numerical,and experimental studies on penetrative convection are reviewed,along with field studies providing insights into turbulence modeling.The physical factors that initiate penetrative convection,including internal heat sources,nonlinear constitutive relationships,centrifugal forces and other complicated factors are summarized.Cutting-edge methods for understanding transport mechanisms and statistical properties of penetrative turbulence are also documented,e.g.,the variational approach and quasilinear approach,which derive scaling laws embedded in penetrative turbulence.Exploring these scaling laws in penetrative convection can improve our understanding of large-scale geophysical and astrophysical motions.To better the model of penetrative turbulence towards a practical situation,new directions,e.g.,penetrative convection in spheres,and radiation-forced convection,are proposed.

An improved TDE technique for derivation of 2D turbulence structures based on GPI data in toroidal plasma

This paper reports an improved time-delay estimation(TDE)technique for the derivation of turbulence structures based on gas-puff imaging data.The improved TDE technique,integrating an inverse timing search and hierarchical strategy,offers superior accuracy in calculating turbulent velocity field maps and analyzing blob dynamics,which has the power to obtain the radial profiles of equilibrium poloidal velocity,blob size and its radial velocity,even the fluctuation analysis,such as geodesic acoustic modes and quasi-coherent mode,etc.This improved technique could provide important 2D information for the study of edge turbulence and blob dynamics,advancing the understanding of edge turbulence physics in fusion plasmas.

Numerical analysis of turbulent mixed convection air flow in inclined plane channel with k-εtype turbulence model

Numerical study on turbulent mixed convection in inclined plane channels,from 15° to 90° (vertical),was carried out to examine the effect of inclination on fluid flow and heat transfer distributions.The turbulent air flows upward or downward into the duct with one wall heated from bottom.Calculation results with several kinds of k-εtype turbulence models were used to compare the experimental data with those in literatures to determine suitable model.The dependents of Nusselt number on the inclination angle of both the buoyancy-aided and buoyancy-opposed flow are discussed.

Performance of physical-informed neural network (PINN) for the key parameter inference in Langmuir turbulence parameterization scheme

The Stokes production coefficient(E_(6))constitutes a critical parameter within the Mellor-Yamada type(MY-type)Langmuir turbulence(LT)parameterization schemes,significantly affecting the simulation of turbulent kinetic energy,turbulent length scale,and vertical diffusivity coefficient for turbulent kinetic energy in the upper ocean.However,the accurate determination of its value remains a pressing scientific challenge.This study adopted an innovative approach by leveraging deep learning technology to address this challenge of inferring the E_(6).Through the integration of the information of the turbulent length scale equation into a physical-informed neural network(PINN),we achieved an accurate and physically meaningful inference of E_(6).Multiple cases were examined to assess the feasibility of PINN in this task,revealing that under optimal settings,the average mean squared error of the E_(6) inference was only 0.01,attesting to the effectiveness of PINN.The optimal hyperparameter combination was identified using the Tanh activation function,along with a spatiotemporal sampling interval of 1 s and 0.1 m.This resulted in a substantial reduction in the average bias of the E_(6) inference,ranging from O(10^(1))to O(10^(2))times compared with other combinations.This study underscores the potential application of PINN in intricate marine environments,offering a novel and efficient method for optimizing MY-type LT parameterization schemes.