Space-time correlations in turbulent Rayleigh–Bnard convection

The recent development of the elliptic model （He, et al. Phy. Rev. E, 2006）, which predicts that the space-time correlation function Cu（r, r） in a turbulent flow has a scaling form Cu（rE, 0） with re being a combined space-time separa- tion involving spatial separation r and time delay T, has stimulated considerable experimental efforts aimed at testing the model in various turbulent flows. In this paper, we review some recent experimental investigations of the space-time correlation function in turbulent Rayleigh-Benard convection. The experiments conducted at different representative locations in the convection cell confirmed the predictions of the elliptic model for the velocity field and passive scalar field, such as local temperature and shadowgraph images. The understanding of the functional form of Cu（r, v） has a wide variety of applications in the analysis of experimental and numerical data and in the study of the statistical properties of small-scale turbulence. A few examples are discussed in the review.

Parameterized thermal model of a mixed mantle convection

Simple parameterized models, either whole mantle convection or layered mantleconvection, cannot explain the tectonic characteristics of the Earth's evolution history, therefore a mixed mantle convection model has been carried out in this paper. We introduce a time-dependent parameter F, which denotes the ratio betWeen the mantle material involved in whole mantle convection and the material of the entire mantle, and introduce a local Rayleigh number Raloc as well as two critical numbers Ra1 and Ra2. These parameters are used to describe the stability of the phase boundary between the upper and lower mantle. The result shows that the mixed mantle convection model is able to simulate the episodic tectonic evolution of the Earth.

Atmospheric Convection Model Based Digital Confidentiality Scheme

Nonlinear dynamics is a fascinating area that is intensely affecting a wide range of different disciplines of science and technology globally.The combination of different innovative topics of information security and high-speed computing has added new visions into the behavior of complex nonlinear dynamical systems which uncovered amazing results even in the least difficult nonlinearmodels.The generation of complex actions froma very simple dynamical method has a strong relation with information security.The protection of digital content is one of the inescapable concerns of the digitally advanced world.Today,information plays an important role in everyday life and affects the surroundings rapidly.These digital contents consist of text,images,audio,and videos,respectively.Due to the vast usage of digital images in the number of social and web applications,its security is one of the biggest issues.In this work,we have offered an innovative image encryption technique based on present criteria of confusion and diffusion.The designed scheme comprises two major nonlinear dynamical systems.We have employed discrete fractional chaotic iterative maps to add confusion capability in our suggested algorithm and continuous chaotic Lorenz system.We have verified our offered scheme by using statistical analysis.The investigations under the statistical tests suggested that our proposed technique is quite reasonable for the security of digital data.

Characteristics of convection and overshooting in RGB and AGB stars

Based on the turbulent convection model （TCM） of Li ＆ Yang, we have studied the characteristics of turbulent convection in the envelopes of 2 and 5M⊙ stars at the red giant branch and asymptotic giant branch phases. The TCM has been successfully applied over the entire convective envelopes, including the convective unstable zone and the overshooting regions. We find that the convective motions become progressively stronger when the stellar models are located farther up along the Hayashi line. In the convective unstable zone, we find that the turbulent correlations are proportional to functions of a common factor （V - V^d）T, which explains similar distributions in those correlations. For the TCM we find that if the obtained stellar temperature structure is close to that of the mixing length theory （MLT）, the convective motion will have a much larger velocity and thus be more violent. However, if the turbulent velocity is adjusted to be close to that of the MLT, the superadiabatic convection zone would be much more extended inward, which would lead to a lower effective temperature of the stellar model. For the overshooting distance, we find that the e-folding lengths of the turbulent kinetic energy k in both the top and bottom overshooting regions decrease as the stellar model is progressively located farther up along the Hayashi line, but both the extents of the decrease are not obvious. The overshooting distances of the turbulent correlation /u＇rT＂ are almost the same for the different stellar models with the same set of TCM parameters. For the decay modes of the kinetic energy k, we find that they are very similar for different stellar models based on the same set of TCM parameters, and there is a nearly linear relationship between lg k and In P for different stellar models. When Cs or α increases while the other parameters are fixed, the obtained linearly decaying distance will become longer.

A Two-plume Convective Model for Precipitation Extremes

In the study of diagnosing climate simulations and understanding the dynamics of precipitation extremes,it is an essential step to adopt a simple model to relate water vapor condensation and precipitation,which occur at cloudmicrophysical and convective scales,to large-scale variables.Several simple models have been proposed;however,improvement is still needed in both their accuracy and/or the physical basis.Here,we propose a two-plume convective model that takes into account the subgrid inhomogeneity of precipitation extremes.The convective model has three components,i.e.,cloud condensation,rain evaporation,and environmental descent,and is built upon the zero-buoyancy approximation and guidance from the high-resolution reanalysis.Evaluated against the CMIP5 climate simulations,the convective model shows large improvements in reproducing precipitation extremes compared to previously proposed models.Thus,the two-plume convective model better captures the main physical processes and serves as a useful diagnostic tool for precipitation extremes.

Temperature field model in surface grinding: a comparative assessment

Grinding is a crucial process in machining workpieces because it plays a vital role in achieving the desired precision and surface quality.However,a significant technical challenge in grinding is the potential increase in temperature due to high specific energy,which can lead to surface thermal damage.Therefore,ensuring control over the surface integrity of workpieces during grinding becomes a critical concern.This necessitates the development of temperature field models that consider various parameters,such as workpiece materials,grinding wheels,grinding parameters,cooling methods,and media,to guide industrial production.This study thoroughly analyzes and summarizes grinding temperature field models.First,the theory of the grinding temperature field is investigated,classifying it into traditional models based on a continuous belt heat source and those based on a discrete heat source,depending on whether the heat source is uniform and continuous.Through this examination,a more accurate grinding temperature model that closely aligns with practical grinding conditions is derived.Subsequently,various grinding thermal models are summarized,including models for the heat source distribution,energy distribution proportional coefficient,and convective heat transfer coefficient.Through comprehensive research,the most widely recognized,utilized,and accurate model for each category is identified.The application of these grinding thermal models is reviewed,shedding light on the governing laws that dictate the influence of the heat source distribution,heat distribution,and convective heat transfer in the grinding arc zone on the grinding temperature field.Finally,considering the current issues in the field of grinding temperature,potential future research directions are proposed.The aim of this study is to provide theoretical guidance and technical support for predicting workpiece temperature and improving surface integrity.

Finite element simulation of three-dimensional temperature field in underwater welding

Mathematical models of three-dimensional temperature fields in underwater welding with moving heat sources are built. Double ellipsoid Gauss model is proposed as heat sources models. Several factors which affect the temperature fields of underwater welding are analyzed. Water has little influence on thermal efftciency. Water convection coefftcient varies with the temperature difference between the water and the workpiece , and water convection makes molten pool freeze quickly. With the increase of water depth, the dimensions of heat sources model should be reduced as arc shrinks. Finite element technology is used to solve mathematical models. ANSYS software is used as finite element tool, and ANSYS Parametric Design Language is used to develop subprograms for loading the moving heat sources and the various convection coefftcients. Experiment results show that computational results by using double ellipsoid Gauss heat sources model accord well with the experimental results.

Ensemble Cloud Model Application in Simulating the Catastrophic Heavy Rainfall Event

An attempt has been made in the present research to simulate a deadly flash-flood event over the City of Skopje,Macedonia on 6 August 2016.A cloud model ensemble forecast method is developed to simulate a super-cell storm’s initiation and evolutionary features.Sounding data are generated using an ensemble approach,that utilizes a triple-nested WRF model.A three-dimensional(3-D)convective cloud model(CCM)with a very fine horizontal grid resolution of 250-m is initialized,using the initial representative sounding data,derived from the WRF 1-km forecast outputs.CCM is configured and run with an open lateral boundary conditions LBC,allowing explicit simulation of convective scale processes.This preliminary study showed that the ensemble approach has some advantages in the generation of the initial data and the model initialization.The applied method minimizes the uncertainties and provides a more qualitative-quantitative assessment of super-cell storm initiation,cell structure,evolutionary properties,and intensity.A high-resolution 3-D run is capable to resolve detailed aspects of convection,including high-intensity convective precipitation.The results are significant not only from the aspect of the cloud model’s ability to provide a qualitative-quantitative assessment of intense precipitation but also for a deeper understanding of the essence of storm development,its vortex dynamics,and the meaning of micro-physical processes for the production and release of large amounts of precipitation that were the cause of the catastrophic flood in an urban area.After a series of experiments and verification,such a system could be a reliable tool in weather services for very short-range forecasting(now-casting)and early warning of weather disasters.

Convection–Diffusion Model for the Prediction of Anthropogenically-Initiated Wildfire Ignition

A spatial interaction model to predict anthropogenically-initiated accidental and incendiary wildfire ignition probability is developed using fluid flow analogies for human movement patterns. Urban areas with large populations are identified as the sites of global influencing factors, and are modeled as the gravity term. The transportation corridors are identified as local influencing factors, and are modeled using fluid flow analogy as diffusion and convection terms. The model is implemented in ArcGIS, and applied for the prediction of wildfire hazard distribution in southeastern Mississippi. The model shows87 % correlation with historic data in the winter season,whereas the previously developed gravity model shows only 75 % correlation. The normalized error for convection–diffusion model predictions is about 5 % in the winter season, whereas the gravity model shows an error of 7 %.The proposed model is robust as it couples a multi-criteria behavioral pattern within a single dynamic equation to enhance predictive capability. At the same time, the proposed model is more costly than the gravity model as it requires evaluation of distance from intermodal transportation corridors, transportation corridor density, and traffic volume maps. Nonetheless, the model is developed in a modular fashion, such that either global or local terms can be neglected if required.

CLOUD-RESOLVING MODELING OF CONVECTIVE PROCESSES

Recent decades have witnessed the rapid development of cloud-system resolving models （CRM）, which are now capable of simulating cloud systems and accompanying interactions on scales up to global, albeit in the latter application small- scale convection （cumulus） remains unresolved. The implication of such a truncation is not understood. The CRM approach has its roots in non-hydrostatic cloud models developed a generation ago for simulating individual cumulonimbus in integrations lasting about an hour Advances in computer capacity enable CRMs to be run with progressively larger computational domains and be integrated for weeks or months,

A new stationary droplet evaporation model and its validation

The liquid droplet evaporation character is important for not only combustion chamber design process but also high-accuracy spray combustion simulation. In this paper, the suspended droplets＇ evaporation character was measured in a quiescent high-temperature environment by micro high-speed camera system. The gasoline and kerosene experimental results are consistent with the reference data. Methanol, common kerosene and aviation kerosene droplet evaporation characteristics, as well as their evaporation rate changing with temperature, were obtained. The evaporation rate experimental data were compared with the prediction result of Ranz-Marshall boiling temperature model（RMB）, Ranz-Marshall low-temperature model（RML）, drift flux model（DFM）, mass analogy model（MAM）, and stagnant film model（SFM）. The disparity between the experimental data and the model prediction results was mainly caused by the neglect of the natural convection effect, which was never introduced into the droplet evaporation concept. A new droplet evaporation model with consideration of natural convection buoyancy force effect was proposed in this paper. Under the experimental conditions in this paper, the calculation results of the new droplet evaporation model were agreed with the experimental data for kerosene, methanol and other fuels, with less than 20% relative deviations. The relative deviations between the new evaporation model predictions for kerosene and the experimental data from the references were within 10%.

Approximating Stationary Statistical Properties

It is well-known that physical laws for large chaotic dynamical systems are revealed statistically.Many times these statistical properties of the system must be approximated numerically.The main contribution of this manuscript is to provide simple and natural criterions on numerical methods (temporal and spatial discretization) that are able to capture the stationary statistical properties of the underlying dissipative chaotic dynamical systems asymptotically.The result on temporal approximation is a recent finding of the author,and the result on spatial approximation is a new one.Applications to the infinite Prandtl number model for convection and the barotropic quasi-geostrophic model are also discussed.