Numerical Simulation Of Physical Processes Research Articles

Numerical calculation of the operating parameters of the ION engine for satellite correction

The article provides a description of methods for numerical simulation of physical processes occurring in an electric jet engine. A method for estimating the ionization of the working fluid based on drift-diffusion equations is presented. The possibility of calculating the neutralization coefficient to prevent erosion of an engine with an original design based on a system of nested electrodes is shown. The article describes the sequence of creating a computer model of an ion engine and the main methods of numerical analysis of the dynamics of charged particles.

A statistical bias correction technique for global climate model predicted near-surface temperature in India using the generalized regression neural network

Abstract Global climate models (GCMs) developed by the numerical simulation of physical processes in the atmosphere, ocean, and land are useful tools for climate prediction studies. However, these models involve parameterizations and assumptions for the simulation of complex phenomena, which lead to random and structural errors called biases. So, the GCM outputs need to be bias-corrected with respect to observed data before applying these model outputs for future climate prediction. This study develops a statistical bias correction approach using a four-layer feedforward radial basis neural network – a generalized regression neural network (GRNN) to reduce the biases of the near-surface temperature data in the Indian mainland. The input to the network is the CNRM-CM5 model output gridded data of near-surface temperature for the period 1951–2005, and the target to the model used for bias correcting the input data is the gridded near-surface temperature developed by the Indian Meteorological Department for the same period. Results show that the trained GRNN model can improve the inherent biases of the GCM output with significant accuracy, and a good correlation is seen between the test statistics of observed and bias-corrected data for both the training and testing period. The trained GRNN model developed is then used for bias correction of CNRM-CM5 modelled projected near-surface temperature for 2006–2100 corresponding to the RCP4.5 and RCP8.5 emission scenarios. It is observed that the model can adapt well to the nature of unseen future temperature data and correct the biases of future data, assuming quasi-stationarity of future temperature data for both emission scenarios. The model captures the seasonal variation in near-surface temperature over the Indian mainland, having diverse topography appreciably, and this is evident from the bias-corrected output.

Fundamentally New Composite Materials of Fast Reactors Made on the Basis of Nanotechnology

The main goal of the work is to identify the advantages of fast reactors when using nanotechnology in the manufacture of core materials. The research methods are based on the adaptation of known technologies (including powder metallurgy) to the design of fast reactors and on the numerical simulation of physical processes carried out using computer programs for the analysis of emergency conditions of fast reactors (including anticipated transient without scram - ATWS). The results of the research show that the use of structural materials based on steels hardened by nanooxides in combination with fundamentally new types of fuel based on composite materials can significantly improve the safety of nuclear technics. Sintered mixtures of ceramic microgranules (oxide, nitride) and nanoadditives of metallic beryllium or uranium are considered as nuclear fuel. Such composite nuclear fuel improves reactor safety and power. The following types of composite fuel were analyzed: mixed oxide with additives of a beryllium or uranium nanopowder, mixed mononitride with additives of a beryllium or uranium nanopowder. Most preferably, a ceramic-metal pellet fuel based on mononitride microgranules and uranium metal nanopowder. The use of such fuel (with a volume fraction of metallic uranium up to 20%) significantly increases the safety of the reactor, combining the advantages of metal and ceramics and completely neutralizing their disadvantages. The proposed materials are of practical importance in the development of new concepts of nuclear technics, in the transition to large-scale nuclear power and high-power reactors. The use of a new cermet-based composite fuel increases the power of the reactor and significantly increases the safety of the reactor.

DETERMINATION OF THE IMPEDANCE OF A HONEYCOMB RESONATOR BY DEAN’S METHOD AND DIRECT METHOD IN A COMPUTATIONAL EXPERIMENT WITH GRAZING INCIDENCE OF WAVES

The article considers the determination of the impedance of the acoustic liner sample on the basis of numerical simulation of physical processes in a honeycomb resonator with a grazing incidence of sound waves. The computational domain is the test section of a grazing incidence impedance tube with an acoustic liner sample. The liner sample is a single honeycomb resonator with a depth of 14 mm and an open area percent of 4.2%. Numerical simulation is performed based on the direct solution of the non-stationary compressible Navier-Stokes equations in a three-dimensional formulation. The pressure-time and velocity-time signals are recorded in the numerical simulation and processed by Dean's method and the direct method (from the ratio of acoustic pressure to normal acoustic velocity). The comparison of impedances obtained by the two methods demonstrates a good agreement with each other.

Комбинированный алгоритм вычисления расстояния со знаком для задач численного моделирования физических процессов и визуализации движения твердых тел

Комбинированный алгоритм вычисления расстояния со знаком для задач численного моделирования физических процессов и визуализации движения твердых тел

DETERMINATION OF ACOUSTIC CHARACTERISTICS OF THE DOUBLE-LAYER HONEYCOMB LINER BASED ON NUMERICAL SIMULATION

For the first time, the acoustic characteristics of a full-scale double-layer sample of acoustic liner were determined by numerical simulation of physical processes in an normal incident interferometer. The double-layer liner sample consisted of 14 honeycomb cells and 70 perforation holes. The dimensions of the honeycomb cells and perforation holes correspond to the acoustic liners used in the ducts of aircraft engines. Numerical simulation was carried out based on solution of the unsteady Navier-Stokes equations in three-dimensional formulation. A high degree of agreement of the acoustic characteristics obtained by numerical simulation with experiment was noted.

Numerical Simulation of the Operation of a Wide-Aperture Electron Gun with a Grid Plasma Emitter and Beam Output into the Atmosphere

Numerical simulation of physical processes in the electron-optical system of a DUET accelerator was carried out using the ERA-DD code. The calculations were made on adaptive quasi-structured grids developed by the authors. A mathematical model for the emission plasma surface deformable when solving the problem is proposed. In this model, the problem is considered in a two-dimensional axisymmetric approximation and the front of the electron entrance to the computational domain is represented as a set of circular arcs connected by necks. In order to increase the accuracy of the calculations, it is proposed to divide the multi-scale extended domain into two subdomains and alternately solve self-consistent problems in the subdomains using the Schwarz alternating method. The beams are simulated by the method of current tubes, and the electric field potential is calculated by the finite volume method. The obtained characteristics of the beam are compared with experimental data. It is shown that for the operating parameters of the beam source, its losses on the accelerator components are minimal and can be caused primarily by the imperfect alignment of the holes in the mask and the support grid, as well as by deviations of electron beams generated by the structures located on the periphery of the emission electrode.

DETERMINATION OF ACOUSTIC CHARACTERISTICS OF FULL-SCALE SAMPLE OF SINGLE LAYERED HONEYCOMB LINER BASED ON NUMERICAL SIMULATION

The acoustic characteristics of a full-scale sample of an actual single-layer liner are determined by numerical simulation of physical processes in normal incidence interferometer. Numerical simulation is performed based on solving the unsteady Navier-Stokes equations with allowance for compressibility in three-dimensional statement. It is noted the good agreement of the acoustic characteristics of the liner sample obtained in numerical simulation and in experiment. It is shown that conducting numerical simulation on single cell sample of the liner also gives results that are in good agreement with the experiment. It allows predicting the acoustic characteristics of samples of locally reacting liners with a more complex geometry in further.

О численной модели физических процессов в высокотемпературных сверхпроводниках

О численной модели физических процессов в высокотемпературных сверхпроводниках

Scale and Boundary Effects on the Effective Elastic Properties of 2‐D and 3‐D Non‐REV Heterogeneous Porous Media

AbstractA digital 3‐D representation of a heterogeneous medium can be used as an input to physics‐based numerical methods to obtain an estimate of the effective physical properties of the composite, such as transport, electrical, and elastic properties. These properties can then be used to simplify large‐scale numerical simulations of physical processes by considering the constitutive equations of the heterogeneous composite as if it was a homogenous continuum. By definition, effective physical properties do not depend on the boundary conditions applied to a medium during an experiment. In finite‐sized media, computing effective properties for a medium may not be feasible due to the boundary effects on the computed parameters. Through numerical experiments, we developed a methodology to minimize the boundary effects by considering a subdomain within a sample onto which the experiment was performed. Specifically, we analyzed the boundary effects on the computed elastic properties of 2‐D and 3‐D subdomains located within a digitized sample of a Berea sandstone and a compacted random pack of identical spherical particles. As the parent sample size increases while the size of the subdomain remains fixed, the elastic properties of the latter converge to constant values. These values correspond to the effective elastic values of the subsample, though they depend on the immediate region surrounding the subdomain. In addition, we propose a method to relate the effective elastic properties of rock samples to another microstructural parameter to be used in prediction of elastic properties of other samples having the same type and geological conditions.

Effect of supercritical CO2 on carbonates: Savonnières sample case study

ABSTRACTCO2 geosequestration is an efficient way to reduce greenhouse gas emissions into the atmosphere. Carbonate rock formations are one of the possible targets for CO2 sequestration due to their relative abundance and ability to serve as a natural trapping reservoir. The injected supercritical CO2 can change properties of the reservoir rocks such as porosity, permeability, tortuosity, and specific surface area due to dissolution and precipitation processes. This, in turn, affects the reservoir characteristics, i.e., their elastic properties, storage capacity, stability, etc.The tremendous progresses made recently in both microcomputed X‐ray tomography and high‐performance computing make numerical simulation of physical processes on actual rock microstructures feasible. However, carbonate rocks with their extremely complex microstructure and the presence of microporosity that is below the resolution of microcomputed X‐ray tomography scanners require novel, quite specific image processing and numerical simulation approaches.In the current work, we studied the effects of supercritical CO2 injection on microstructure and elastic properties of a Savonnières limestone. We used microtomographic images of two Savonnières samples, i.e., one in its natural state and one after injection and residence of supercritical CO2. A statistical analysis of the microtomographic images showed that the injection of supercritical CO2 led to an increase in porosity and changes of the microstructure, i.e., increase of the average volume of individual pores and decrease in the total number of pores. The CO2 injection/residence also led to an increase in the mean radii of pore throats, an increase in the length of pore network segments, and made the orientation distribution of mesopores more isotropic. Numerical simulations showed that elastic moduli for the sample subjected to supercritical CO2 injection/residence are lower than those for the intact sample.

On scientific inference in geophysics and the use of numerical simulations for scientific investigations

AbstractScientific knowledge is acquired in geophysics generally without the benefit of controlled experiments. In this paper, we discuss how scientific inference based on observations occurs in geophysical contexts. We develop a specific approach that uses approximate simultaneity of proposed cause and effect phenomena to infer causality. The approach applies equally well to effect phenomena that follow the cause with a known time delay. We find that, in general, establishing a causal relationship between two phenomena based on simultaneity requires knowledge of how often simultaneity of these phenomena occurs in the absence of causality. We then extend the discussion to using numerical simulations in the scientific inference process. Numerical simulations of physical processes, because they can simulate the values of observations, are often used to infer what physical processes are occurring in nature. We discuss agreement between model output and observations as a basis for inferring the physical processes underlying the observations. We find that an important factor to consider, which we here call the “confusion factor,” is how often it may occur that insufficient model representations of the physical processes nevertheless lead to agreement between model computations and observations. We suggest that models of intermediate or low complexity may have a significant role to play when using geophysical simulations to reach scientific conclusions.

Method for Stochastic Inverse Modeling of Fault Geometry and Connectivity Using Flow Data

This paper focuses on fault-related uncertainties in the subsurface, which can significantly affect the numerical simulation of physical processes. Our goal is to use dynamic data and process-based simulation to update structural uncertainty in a Bayesian inverse approach. We propose a stochastic fault model where the number and features of faults are made variable. In particular, this model samples uncertainties about connectivity between the faults. The stochastic three dimensional fault model is integrated within a stochastic inversion scheme in order to reduce uncertainties about fault characteristics and fault zone layout, by minimizing the mismatch between observed and simulated data. The stochastic fault model uses a priori information such as fault orientation, location, size and sinuosity, to sample both geometrical and topological uncertainties with realistic fault descriptions. Each fault object is parameterized by the random vector used to simulate fault features. Then, during inversion, the random vector of the current model is stochastically perturbed, producing a new parameter vector used as input by the stochastic fault model to produce a new model. Even if the topology varies from one model to another, the algorithm produces correlated models so that their flow responses evolve quite smoothly. The methodology is applicable in general and illustrated on a synthetic two-phase flow example. A first set of models is generated to sample the prior uncertainty space. Then models minimizing reference water-saturation data misfit are used as seeds to generate continuous Monte Carlo Markov Chains (MCMC) of models with discrete states. Posterior models reduce uncertainties about fault position, while the topology varies from one model to another. A second example highlights the interest of the parameterization when interpreted data are available, by perturbing geological scenarios and falsifying those that do not match two-phase flow observations.

Estimation problems for a class of impulsive systems

AbstractThis paper deals with on‐line identification of continuous‐time systems subject to impulsive terms. Using a distribution framework, a scheme is proposed in order to annihilate singular terms in differential equations representing a class of impulsive systems. As a result, an online estimation of unknown parameters is provided, regardless of the switching times or the impulse rules. Numerical simulations of physical processes with noisy data are illustrating our methodology and results. Copyright © 2010 John Wiley & Sons, Ltd.

Geometric Properties of the Icosahedral-Hexagonal Grid on the Two-Sphere

An icosahedral-hexagonal grid on the two-sphere is created by dividing the faces of an icosahedron and projecting the vertices onto the sphere. This grid and its Voronoi tessellation have several desirable features for numerical simulations of physical processes on the sphere. While several methods to construct the icosahedral grid mesh have been proposed over the past decades, and empirical data have been collected to understand and help improve the grid, rarely have analytical analyses been done to investigate the basic geometric properties of the grid. In this paper, we present an analytical analysis of several geometric properties of the icosahedral grids based on two basic constructions: recursive and nonrecursive construction. We point out that these geometric properties can be improved with modified construction procedures. We demonstrate how these improvements impact the numerical integration of PDEs over the sphere.

Sparse matrix operations on several multi-core architectures

This paper compares various contemporary multicore-based microprocessor architectures from different vendors with different memory interconnects regarding performance, speedup, and parallel efficiency. Sparse matrix decomposition is used as a benchmark application. The example matrix used in the experiments comes from an electrical engineering application, where numerical simulation of physical processes plays an important role in the design of industrial products. Within this context, thread-to-core pinning and cache optimization are two important aspects which are investigated in more detail.

Adaptive Algebraic Multigrid

Efficient numerical simulation of physical processes is constrained by our ability to solve the resulting linear systems, prompting substantial research into the development of multiscale iterative methods capable of solving these linear systems with an optimal amount of effort. Overcoming the limitations of geometric multigrid methods to simple geometries and differential equations, algebraic multigrid methods construct the multigrid hierarchy based only on the given matrix. While this allows for efficient black-box solution of the linear systems associated with discretizations of many elliptic differential equations, it also results in a lack of robustness due to unsatisfied assumptions made on the near null spaces of these matrices. This paper introduces an extension to algebraic multigrid methods that removes the need to make such assumptions by utilizing an adaptive process. Emphasis is on the principles that guide the adaptivity and their application to algebraic multigrid solution of certain symmetric positive-definite linear systems.

Color interpolation algorithms in visualizing results of numerical simulations.

The paper addresses the application of graphical replenishment (GR) color interpolation algorithms for visualizing numerical simulation of physical processes in order to enhance the information density of the graphic interpretation of these processes. The GR algorithms presented here may be successfully applied to two- and three-dimensional grids, and grids of various structures.

Numerical models of Plinian eruption columns and pyroclastic flows

Numerical simulations of physical processes governing the large‐scale dynamics of Plinian eruption columns reveal conditions contributing to column collapse and emplacement of pyroclastic flows. The simulations are based on numerical solution of the time‐dependent, two‐phase, compressible Navier‐Stokes equations for jets in a gravitational field. This modeling effort is directed toward studying the steady discharge phase of eruptions in contrast to our previous models of the initial, unsteady blast phase. Analysis of 51 eruption models covers a wide range of vent exit pressures, inertial and buoyancy driving forces, and coupling of energy and momentum between gas and pyroclasts. Consideration of three dimensionless groups (Richardson and Rouse numbers and thermogravitational parameter) facilitates this analysis and defines conditions leading to column collapse. For eruptions with similar particle size characteristics, exit pressure ratios are also very important in determining column behavior; column behavior is much more sensitive to exit pressure ratio than to the density ratio between the column and the atmosphere. Model eruption columns with exit pressures exceeding atmospheric pressure have diamond‐shaped patterns at their bases with internal dynamics that correspond closely to observations of overpressured jets in laboratory experiments. Collapsing fountains form pyroclastic flows that consist of low‐concentration fronts, relatively thick heads, vortex development along the top surfaces, and rising clouds of buoyant ash. The presence of coarse‐grained proximal deposits primarily reflects tephra size sorting within the eruption column before collapse, as opposed to that which occurs during lateral transport of the material in pyroclastic flows. The dynamics and particle behavior in the proximal zone around collapsing eruption columns is examined; the modeling indicates that flow within a few kilometers of a vent will be at its highest particle concentration relative to other parts of the flow field.

Bottom Smoothing to Prevent Numerical Instability

Numerical simulation of sediment transport and the changes in plan form of the shoreline near coastal structures may produce results where the bottom slope exceeds the maximum slope which would be expected to occur on the real (prototype) shoreline. This may cause instability in the numerical solution and prevent an accurate simulation of the transport processes. A numerical subroutine has been developed to redistribute the sediment at pints where the numerically produced bottom slope exceeds the maximum expected slope. This subroutine has no dependence on time. The smoothing is accomplished numerically after the completion of one or more iterations of time-dependent, numerical simulation of physical processes, e.g., sediment transport associated with wave action or currents. It should be noted that the smoothing subroutine will smooth any input data to reach a maximum slope between points, even random numbers. This subroutine should not be used as a substitute for good simulation of the physical processes, but may be used to smooth errors resulting from the inexact nature of numerical modeling.