流体力学：开放获取

We present an overview of the lattice Boltzmann method (LBM), a parallel and efficient algorithm for simulating single-phase and multiphase fluid flows and for incorporating additional physical complexities. The LBM is especially useful for modeling complicated boundary conditions and multiphase interfaces. Recent extensions of this method are described, including simulations of fluid turbulence, suspension flows, and reaction diffusion systems.

Lattice Boltzmann method (LBM) is a methodology based on the microscopic particle models and mesoscopic kinetic equations. According to Kadanoff (1986), it has been found that macroscopic behavior of a fluid system is generally not very sensitive to the underlying microscopic particle behavior if only collective macroscopic flow behavior is of interest. The fundamental idea behind the LBM is to construct simplified kinetic models that incorporate only the essential physics of microscopic or mesoscopic processes so that the macroscopic averaged properties obey the desired macroscopic equations. This subsequently avoids the use of the full Boltzmann equation, and one also avoids following each particle as in molecular dynamics simulations.

LBM is based on a particle representation, the principal focus remains in the averaged macroscopic behavior. The kinetic nature of the LBM introduces three important features that distinguish this methodology from other numerical methods. Firstly, the convection operator of the LBM in the velocity phase is linear. The inherent simple convection when combined with the collision operator allows the recovery of the nonlinear macroscopic advection through multiscale expansions. Secondly, the incompressible Navier–Stokes equations can be obtained in the nearly incompressible limit of the LBM. The pressure is calculated directly from the equation of state in contrast to satisfying Poisson's equation with velocity strains acting as sources. Thirdly, the LBM utilizes the minimum set of velocities in the phase space. Because only one or two speeds and a few moving directions are required, the transformation relating the microscopic distribution function and macroscopic quantities is greatly simplified and consists of simple arithmetic calculations.

Microfluidic devices for manipulating fluids square measure widespread and finding uses in several scientific and industrial contexts. Their style usually needs uncommon geometries and therefore the interaction of multiple physical effects like pressure gradients, electrokinetics, and capillary action. These circumstances cause attention-grabbing variants of well-studied fluid ever-changing issues and a few new fluid responses. We offer an outline of flows in microdevices with specialize in electrokinetics, compounding and dispersion, and point in time flows. We tend to highlight topics vital for the outline of the fluid dynamics: driving forces, geometry, and therefore the chemical characteristics of surfaces.

The use of pipes and channels to convey fluids in an organized manner is essentially as old as the living world, since living systems have veins and arteries to transport water, air, gas, etc. The use of channels for the transport and mixing of gases and liquids is part of the industrial and civil infrastructure of our society and so, not surprisingly, many aspects of the dynamics of flow in channels are well understood. At the larger scales (e.g. length scales and typical speeds) of many common flows, the inertia of the motion is most relevant to the dynamics, and in this case turbulence is the rule: such flows are irregular, stochastic, dominated by fluctuations, and often require statistical ideas, correlations or large-scale numerical computation to quantify (if that is even possible). The recent explosion of interest in fluid flows, and so their active manipulation and management, in micro- and nano-environments has turned attention to dynamics wherever viscous effects, which may be thought of, as a primary approximation, as resistance influences interior to the fluid, area unit most significant: such flows area unit regular, consistent, and customarily stratified, that makes elaborate management doable at tiny length scales. In several cases comparatively easy quantitative estimates of necessary flow parameters.

In mechanics it is generally important to speak in terms of the stress or force/area. The term fluid refers to either a liquid or a gas, or more generally any material that flows (the specialist might say “deforms continuously”) in response to tangential stresses. It is best to think first about the flow of a single phase fluid in a channel. . The most common way to create such a flow is to apply a pressure difference across the two ends of the channel: the ensuing flow speed, or rate (volume per time), generally varies linearly with the applied pressure distinction, a minimum of at low enough flow speeds or Reynolds numbers, that could be a dimensionless parameter introduced below. This flow is also accustomed transport some chemical species or suspended particles.

A viscous solvent streamline flow is changed by the addition of a small quantity of long compound molecules, leading to a chaotic flow known as elastic turbulence (ET). ET is attributed to compound stretching, that generates elastic stress and its back reaction on the flow. Its properties area unit analogous to those ascertained in fluid mechanics turbulence, though the formal similarity doesn't imply a similarity in physical mechanisms underlining these two sorts of random motion. Here we have a tendency to review the applied mathematics and spectral properties and also the spacial structure of the rate field, the applied mathematics and spectral properties of pressure fluctuations, and scaling of the friction issue of ET in wall-bounded and boundless flow geometries, as ascertained in experiments and numerical simulations and delineate by theory for a good vary of management parameters and compound concentrations.

A systematic experimental investigation of the onset, development, and statistical and scaling properties of elastic turbulence in a curvilinear micro-channel of a dilute solution of a high molecular weight polymer is presented. By measurements of time series of high spatial resolution flow fields performed over a time 320 times longer than the average relaxation, we show that the transition to elastic turbulence occurs via an imperfect bifurcation. Slightly above the onset of the primary elastic instability, rare events manifested through a local deceleration of the flow are observed.

By measurements of the abstraction distributions and statistics of the second invariant of the speed of strain tensor, we have a tendency to show that the most prediction of the speculation concerning the saturation of root mean sq. of fluctuations of the rate gradients is qualitatively verified though quantitative agreement couldn't be found. A scientific analysis of the statistics of the fluctuations of flow fields in terms of abstraction and temporal correlations, power spectra, and chance distributions is conferred. The scaling properties of structure functions of the increments of the rate gradients square measure mentioned. Our experimental findings entail additional developments of the speculation of elastic turbulence in delimited flow channels.

Many synthetic fluids, still as some natural fluids, show complicated rheological behavior during which viscoelasticity may be a relevant fluid property. Over the last forty years, machine physics (CR), the appliance of machine fluid dynamics (CFD) to fluids with non-Newtonian physics, has developed into a mature discipline, that at the same time helps to grasp a good vary of physical phenomena whereas conjointly providing helpful tools for engineering style. Metallic element refers to flow simulations with fluids that area unit delineated by non-Newtonian models, additional complicated than the generalized Newtonian fluid, since specific techniques to deal with the inherent numerical difficulties related to the complicated constituent equations area unit required albeit the simulations area unit geared toward a hydraulics perspective.

In the late 1970s, at a time once Newtonian CFD had already began to take place into competitor industrial merchandise, the big scatter of numerical results for a similar elastic non-Newtonian flow issues and therefore the corresponding conflicting physical interpretations of information, that were pretty much related to the shortage of accuracy and convergence difficulties succeeding from the questionable high–Weissenberg range drawback (HWNP), LED to the institution of a series of standard workshops that introduced correct benchmarks and centered analysis efforts within the field. The biyearly International Workshop on Numerical strategies in Non-Newtonian Flows started in 1979 in Rhode Island, USA, and had its nineteenth edition in 2019, in Peso prosecuting officer Régua, Portugal. The start of the 21st century saw vital progress in attempt the HWNP through a more robust understanding of its causes and therefore the succeeding development of varied acceptable numerical techniques. chromium |Cr| atomic range 24 metallic element metal might finally be employed in unknown territory within the Weissenberg range (Wi)–Reynolds number (Re) space, therefore changing into a lot of correct and trustworthy tool, only if the adequate essential equation is chosen for the actual fluid and flow below investigation.

The relevance of this last point should be emphasized. If we take for granted the description of structurally simple fluids as Newtonian, in all possible flows, the description of complex fluids is often incomplete, except for very limited simple flow kinematics. Therefore, numerical or analytical flow descriptions in many real flows will be qualitative at most. In this review, we do not address the difficulties associated with the proper rheological characterization of real fluids by adequate constitutive equations, an important area of research on its own; rather, we assume that the adopted model adequately describes the intended fluid properties. Therefore, the numerical methods discussed here are for constitutive equations at the same level of description as the equations governing the conservation of mass and momentum, i.e., at the continuum level, also called macroscopic-scale level. Nevertheless, at the end of this review, we provide some references for methods relying on mesoscopic-scale-level fluid descriptions.

An early textbook, written by Crochet et al. (1984), discussed numerical methods for viscoelastic fluid flows based on the finite-element method (FEM) and finitedifference method (FDM). The enormous progress over the following two decades was covered by Owens & Phillips (2002), but the finite-volume method (FVM) was not addressed in detail. The FVM is a relative latecomer to CR and its extension for viscoelastic fluids has been presented. But further developments and new computational tools have become available since then. Therefore, this review focuses essentially on the state of the art, leaning toward the FVM, while providing potential future lines of research in numerical methods and new applications in viscoelastic fluid flow simulations.

Land leveling is one of the most important steps in soil preparation and cultivation. Although land leveling with machines require considerable amount of energy, it delivers a suitable surface slope with minimal deterioration of the soil and damage to plants and other organisms in the soil. Notwithstanding, researchers during recent years have tried to reduce fossil fuel consumption and its deleterious side effects using new techniques such as; Artificial Neural Network (ANN), Imperialist Competitive Algorithm –ANN (ICA-ANN), and regression and Adaptive Neuro-Fuzzy Inference System (ANFIS) and Sensitivity Analysis that will lead to a noticeable improvement in the environment. In this research effects of various soil properties such as Embankment Volume, Soil Compressibility Factor, Specific Gravity, Moisture Content, Slope, Sand Percent, and Soil Swelling Indexing energy consumption were investigated. The study was consisted of 90 samples were collected from 3 different regions. The grid size was set 20 m in 20 m (20*20) from a farmland in Karaj province of Iran. The aim of this work was to determine best linear model Adaptive Neuro-Fuzzy Inference System(ANFIS) and Sensitivity Analysis in order to predict the energy consumption for land leveling. According to the results of Sensitivity Analysis, cant effect on energy consumption. Using adaptive neuro-fuzzy inference system for prediction of labor energy, fuel energy, total machinery cost, and total machinery energy can be successfully demonstrated.