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Статті в журналах з теми "Multiscale flow"

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Sindeev, S. V., S. V. Frolov, D. Liepsch, and A. Balasso. "MODELING OF FLOW ALTERATIONS INDUCED BY FLOW-DIVERTER USING MULTISCALE MODEL OF HEMODYNAMICS." Vestnik Tambovskogo gosudarstvennogo tehnicheskogo universiteta 23, no. 1 (2017): 025–32. http://dx.doi.org/10.17277/vestnik.2017.01.pp.025-032.

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Koumoutsakos, Petros. "MULTISCALE FLOW SIMULATIONS USING PARTICLES." Annual Review of Fluid Mechanics 37, no. 1 (January 2005): 457–87. http://dx.doi.org/10.1146/annurev.fluid.37.061903.175753.

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SHENG, MAO, GENSHENG LI, SHOUCENG TIAN, ZHONGWEI HUANG, and LIQIANG CHEN. "A FRACTAL PERMEABILITY MODEL FOR SHALE MATRIX WITH MULTI-SCALE POROUS STRUCTURE." Fractals 24, no. 01 (March 2016): 1650002. http://dx.doi.org/10.1142/s0218348x1650002x.

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Nanopore structure and its multiscale feature significantly affect the shale-gas permeability. This paper employs fractal theory to build a shale-gas permeability model, particularly considering the effects of multiscale flow within a multiscale pore space. Contrary to previous studies which assume a bundle of capillary tubes with equal size, in this research, this model reflects various flow regimes that occur in multiscale pores and takes the measured pore-size distribution into account. The flow regime within different scales is individually determined by the Knudsen number. The gas permeability is an integral value of individual permeabilities contributed from pores of different scales. Through comparing the results of five shale samples, it is confirmed that the gas permeability varies with the pore-size distribution of the samples, even though their intrinsic permeabilities are the same. Due to consideration of multiscale flow, the change of gas permeability with pore pressure becomes more complex. Consequently, it is necessary to cover the effects of multiscale flow while determining shale-gas permeability.
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Zhou, Hui, and Hamdi A. Tchelepi. "Operator-Based Multiscale Method for Compressible Flow." SPE Journal 13, no. 02 (June 1, 2008): 267–73. http://dx.doi.org/10.2118/106254-pa.

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Summary Multiscale methods have been developed for accurate and efficient numerical solution of flow problems in large-scale heterogeneous reservoirs. A scalable and extendible Operator-Based Multiscale Method (OBMM) is described here. OBMM is cast as a general algebraic framework. It is natural and convenient to incorporate more physics in OBMM for multiscale computation. In OBMM, two operators are constructed: prolongation and restriction. The prolongation operator is constructed by assembling the multiscale basis functions. The specific form of the restriction operator depends on the coarse-scale discretization formulation (e.g., finitevolume or finite-element). The coarse-scale pressure equation is obtained algebraically by applying the prolongation and restriction operators to the fine-scale flow equations. Solving the coarse-scale equation results in a high-quality coarse-scale pressure. The finescale pressure can be reconstructed by applying the prolongation operator to the coarse-scale pressure. A conservative fine-scale velocity field is then reconstructed to solve the transport (saturation) equation. We describe the OBMM approach for multiscale modeling of compressible multiphase flow. We show that extension from incompressible to compressible flows is straightforward. No special treatment for compressibility is required. The efficiency of multiscale formulations over standard fine-scale methods is retained by OBMM. The accuracy of OBMM is demonstrated using several numerical examples including a challenging depletion problem in a strongly heterogeneous permeability field (SPE 10). Introduction The accuracy of simulating subsurface flow relies strongly on the detailed geologic description of the porous formation. Formation properties such as porosity and permeability typically vary over many scales. As a result, it is not unusual for a detailed geologic description to require 107-108 grid cells. However, this level of resolution is far beyond the computational capability of state-of-the-art reservoir simulators (106 grid cells). Moreover, in many applications, large numbers of reservoir simulations are performed (e.g., history matching, sensitivity analysis and stochastic simulation). Thus, it is necessary to have an efficient and accurate computational method to study these highly detailed models. Multiscale formulations are very promising due to their ability to resolve fine-scale information accurately without direct solution of the global fine-scale equations. Recently, there has been increasing interest in multiscale methods. Hou and Wu (1997) proposed a multiscale finite-element method (MsFEM) that captures the fine-scale information by constructing special basis functions within each element. However, the reconstructed fine-scale velocity is not conservative. Later, Chen and Hou (2003) proposed a conservative mixed finite-element multiscale method. Another multiscale mixed finite element method was presented by Arbogast (2002) and Arbogast and Bryant (2002). Numerical Green functions were used to resolve the fine-scale information, which are then coupled with coarse-scale operators to obtain the global solution. Aarnes (2004) proposed a modified mixed finite-element method, which constructs special basis functions sensitive to the nature of the elliptic problem. Chen et al. (2003) developed a local-global upscaling method by extracting local boundary conditions from a global solution, and then constructing coarse-scale system from local solutions. All these methods considered incompressible flow in heterogeneous porous media where the pressure equation is elliptic. A multiscale finite-volume method (MsFVM) was proposed by Jenny et al. (2003, 2004, 2006) for heterogeneous elliptic problems. They employed two sets of basis functions--dual and primal. The dual basis functions are identical to those of Hou and Wu (1997), while the primal basis functions are obtained by solving local elliptic problems with Neumann boundary conditions calculated from the dual basis functions. Existing multiscale methods (Aarnes 2004; Arbogast 2002; Chen and Hou 2003; Hou and Wu 1997; Jenny et al. 2003) deal with the incompressible flow problem only. However, compressibility will be significant if a gas phase is present. Gas has a large compressibility, which is a strong function of pressure. Therefore, there can be significant spatial compressibility variations in the reservoir, and this is a challenge for multiscale modeling. Very recently, Lunati and Jenny (2006) considered compressible multiphase flow in the framework of MsFVM. They proposed three models to account for the effects of compressibility. Using those models, compressibility effects were represented in the coarse-scale equations and the reconstructed fine-scale fluxes according to the magnitude of compressibility. Motivated to construct a flexible algebraic multiscale framework that can deal with compressible multiphase flow in highly detailed heterogeneous models, we developed an operator-based multiscale method (OBMM). The OBMM algorithm is composed of four steps:constructing the prolongation and restriction operators,assembling and solving the coarse-scale pressure equations,reconstructing the fine-scale pressure and velocity fields, andsolving the fine-scale transport equations. OBMM is a general algebraic multiscale framework for compressible multiphase flow. This algebraic framework can also be extended naturally from structured to unstructured grid. Moreover, the OBMM approach may be used to employ multiscale solution strategies in existing simulators with a relatively small investment.
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Liu, Zhongqiu. "Numerical Modeling of Metallurgical Processes: Continuous Casting and Electroslag Remelting." Metals 12, no. 5 (April 27, 2022): 746. http://dx.doi.org/10.3390/met12050746.

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Zhou, H., S. H. H. Lee, and H. A. A. Tchelepi. "Multiscale Finite-Volume Formulation for the Saturation Equations." SPE Journal 17, no. 01 (December 12, 2011): 198–211. http://dx.doi.org/10.2118/119183-pa.

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Summary Recent advances in multiscale methods have shown great promise in modeling multiphase flow in highly detailed heterogeneous domains. Existing multiscale methods, however, solve for the flow field (pressure and total velocity) only. Once the fine-scale flow field is reconstructed, the saturation equations are solved on the fine scale. With the efficiency in dealing with the flow equations greatly improved by multiscale formulations, solving the saturation equations on the fine scale becomes the relatively more expensive part. In this paper, we describe an adaptive multiscale finite-volume (MSFV) formulation for nonlinear transport (saturation) equations. A general algebraic multiscale formulation consistent with the operator-based framework proposed by Zhou and Tchelepi (SPE Journal, June 2008, pages 267–273) is presented. Thus, the flow and transport equations are solved in a unified multiscale framework. Two types of multiscale operators—namely, restriction and prolongation—are used to construct the multiscale saturation solution. The restriction operator is defined as the sum of the fine-scale transport equations in a coarse gridblock. Three adaptive prolongation operators are defined according to the local saturation history at a particular coarse block. The three operators have different computational complexities, and they are used adaptively in the course of a simulation run. When properly used, they yield excellent computational efficiency while preserving accuracy. This adaptive multiscale formulation has been tested using several challenging problems with strong heterogeneity, large buoyancy effects, and changes in the well operating conditions (e.g., switching injectors and producers during simulation). The results demonstrate that adaptive multiscale transport calculations are in excellent agreement with fine-scale reference solutions, but at a much lower computational cost.
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Cui, Zhanyou, Gaoli Chen, Bing Liu та Deguang Li. "A Multiscale Symbolic Dynamic Entropy Analysis of Traffic Flow". Journal of Advanced Transportation 2022 (30 березня 2022): 1–10. http://dx.doi.org/10.1155/2022/8389229.

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The complexity analysis of traffic flow is important for understanding the property of traffic system. Being good at analyzing the regularity and complexity, multiscale SamEn has attracted much attention and many methods have been proposed for complexity analysis of traffic flow. However, there may exist discontinuity of the calculated entropy value which makes the regularity of the traffic system difficult to understand. The phenomenon occurs due to an inappropriate selection of the parameter r in the multiscale SamEn. Moreover, it is difficult to select an appropriate r for the accurate evaluation of the complexity, which limits the application of multiscale entropy for traffic flow analysis. To solve this problem, a new entropy-based method, multiscale symbolic dynamic entropy, for evaluating the traffic system is proposed here. To verify the effectiveness of the proposed method, traffic data collected from stations in different cities are preprocessed by the proposed method. Both results of two cases show that the weekend patterns and weekday patterns are effectively distinguished using the proposed method, respectively. Specifically, compared with the traditional methods including multiscale SamEn and the multiscale modified SamEn, the complexity of the corresponding traffic system can be better evaluated without considering the selection of r, which demonstrates the effectiveness of the proposed method.
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Bazilevs, Yuri, Kenji Takizawa, and Tayfun E. Tezduyar. "Computational analysis methods for complex unsteady flow problems." Mathematical Models and Methods in Applied Sciences 29, no. 05 (May 2019): 825–38. http://dx.doi.org/10.1142/s0218202519020020.

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In this lead paper of the special issue, we provide a brief summary of the stabilized and multiscale methods in fluid dynamics. We highlight the key features of the stabilized and multiscale scale methods, and variational methods in general, that make these approaches well suited for computational analysis of complex, unsteady flows encountered in modern science and engineering applications. We mainly focus on the recent developments. We discuss application of the variational multiscale (VMS) methods to fluid dynamics problems involving computational challenges associated with high-Reynolds-number flows, wall-bounded turbulent flows, flows on moving domains including subdomains in relative motion, fluid–structure interaction (FSI), and complex-fluid flows with FSI.
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Mäkipere, Krista, and Piroz Zamankhan. "Simulation of Fiber Suspensions—A Multiscale Approach." Journal of Fluids Engineering 129, no. 4 (August 18, 2006): 446–56. http://dx.doi.org/10.1115/1.2567952.

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The present effort is the development of a multiscale modeling, simulation methodology for investigating complex phenomena arising from flowing fiber suspensions. The present approach is capable of coupling behaviors from the Kolmogorov turbulence scale through the full-scale system in which a fiber suspension is flowing. Here the key aspect is adaptive hierarchical modeling. Numerical results are presented for which focus is on fiber floc formation and destruction by hydrodynamic forces in turbulent flows. Specific consideration was given to dynamic simulations of viscoelastic fibers in which the fluid flow is predicted by a method that is a hybrid between direct numerical simulations and large eddy simulation techniques and fluid fibrous structure interactions will be taken into account. Dynamics of simple fiber networks in a shearing flow of water in a channel flow illustrate that the shear-induced bending of the fiber network is enhanced near the walls. Fiber-fiber interaction in straight ducts is also investigated and results show that deformations would be expected during the collision when the surfaces of flocs will be at contact. Smaller velocity magnitudes of the separated fibers compare to the velocity before collision implies the occurrence of an inelastic collision. In addition because of separation of vortices, interference flows around two flocs become very complicated. The results obtained may elucidate the physics behind the breakup of a fiber floc, opening the possibility for developing a meaningful numerical model of the fiber flow at the continuum level where an Eulerian multiphase flow model can be developed for industrial use.
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Lorenz, Eric, and Alfons G. Hoekstra. "Heterogeneous Multiscale Simulations of Suspension Flow." Multiscale Modeling & Simulation 9, no. 4 (October 2011): 1301–26. http://dx.doi.org/10.1137/100818522.

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Дисертації з теми "Multiscale flow"

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Rycroft, Christopher Harley. "Multiscale modeling in granular flow." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/41557.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 2007.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 245-254).
Granular materials are common in everyday experience, but have long-resisted a complete theoretical description. Here, we consider the regime of slow, dense granular flow, for which there is no general model, representing a considerable hurdle to industry, where grains and powders must frequently be manipulated. Much of the complexity of modeling granular materials stems from the discreteness of the constituent particles, and a key theme of this work has been the connection of the microscopic particle motion to a bulk continuum description. This led to development of the "spot model", which provides a microscopic mechanism for particle rearrangement in dense granular flow, by breaking down the motion into correlated group displacements on a mesoscopic length scale. The spot model can be used as the basis of a multiscale simulation technique which can accurately reproduce the flow in a large-scale discrete element simulation of granular drainage, at a fraction of the computational cost. In addition, the simulation can also successfully track microscopic packing signatures, making it one of the first models of a flowing random packing. To extend to situations other than drainage ultimately requires a treatment of material properties, such as stress and strain-rate, but these quantities are difficult to define in a granular packing, due to strong heterogeneities at the level of a single particle. However, they can be successfully interpreted at the mesoscopic spot scale, and this information can be used to directly test some commonly-used hypotheses in modeling granular materials, providing insight into formulating a general theory.
by Christopher Harley Rycroft.
Ph.D.
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Kumar, Mayank Ph D. Massachusetts Institute of Technology. "Multiscale CFD simulations of entrained flow gasification." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/69495.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references.
The design of entrained flow gasifiers and their operation has largely been an experience based enterprise. Most, if not all, industrial scale gasifiers were designed before it was practical to apply CFD models. Moreover, gasification CFD models developed over the years may have lacked accuracy or have not been tested over a wide range of operating conditions, gasifier geometries and feedstock compositions. One reason behind this shortcoming is the failure to incorporate detailed physics and chemistry of the coupled non-linear phenomena occurring during solid fuel gasification. In order to accurately predict some of the overall metrics of gasifier performance, like fuel conversion and syngas composition, we need to first gain confidence in the sub-models of the various physical and chemical processes in the gasifier. Moreover, in a multiphysics problem like gasification modeling, one needs to balance the effort expended in any one submodel with its effect on the accuracy of predicting some key output parameters. Focusing on these considerations, a multiscale CFD gasification model is constructed in this work with special emphasis on the development and validation of key submodels including turbulence, particle turbulent dispersion and char consumption models. The integrated model is validated with experimental data from various pilot-scale and laboratory-scale gasifier designs, further building confidence in the predictive capability of the model. Finally, the validated model is applied to ascertain the impact of changing the values of key operating parameters on the performance of the MHI and GE gasifiers. The model is demonstrated to provide useful quantitative estimates of the expected gain or loss in overall carbon conversion when critical operating parameters such as feedstock grinding size, gasifier mass throughput and pressure are varied.
by Mayank Kumar.
Ph.D.
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Basu, Debashis. "Hybrid Methodologies for Multiscale Separated Turbulent Flow Simulations." University of Cincinnati / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1147362291.

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Hauge, Vera Louise. "Multiscale Methods and Flow-based Gridding for Flow and Transport In Porous Media." Doctoral thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for matematiske fag, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-12132.

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The topic of this thesis is fast and accurate simulation techniques used for simulations of flow and transport in porous media, in particular petroleum reservoirs. Fast and accurate simulation techniques are becoming increasingly important for reservoir management and development, as the geological models increase in size and level of detail and require more computational resources to be utilized. The multiscale framework is a promising approach to facilitate simulation of detailed geological models. In contrast to traditional upscaling approaches, the multiscale methods have the detailed geological models present at all times. The work in this thesis includes development of a multiscale-multiphysics method for naturally fractured reservoirs and a new coarsening strategy for geological models to facilitate fast and accurate transport simulations in a multiscale framework. In addition, the work comprises an application of the multiscale framework for flow and transport simulation for rate optimization loops. The coarsening strategy generates flow-based transport grids and is based on amalgamating cells from a fine model, typically the geological model, according to an indicator function. The research indicates a great potential for flexibility and scalability suitable for multi-fidelity simulators
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Lamponi, Daniele. "One dimensional and multiscale models for blood flow circulation /." [S.l.] : [s.n.], 2004. http://library.epfl.ch/theses/?nr=3006.

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Moragues, Ginard Margarida. "Variational multiscale stabilization and local preconditioning for compressible flow." Doctoral thesis, Universitat Politècnica de Catalunya, 2016. http://hdl.handle.net/10803/384841.

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This thesis is about the stabilization of the numerical solution of the Euler and Navier- Stokes equations of compressible flow. When simulating numerically the flow equations, if no stabilization is added, the solution presents non-physical (but numerical) oscillations. For this reason the stabilization of partial differential equations and of the fluid dynamics equations is of great importance. In the framework of the so-called variational multiscale stabilization, we present here a stabilization method for compressible flow. The method assessment is done first of all on a batch of academical examples for different Mach numbers, for viscous and inviscid, steady and transient flow. Afterwards the method is applied to atmospheric flow simulations. To this end we solve the Euler equations for dry and moist atmospheric flow. In the presence of moisture a set of transport equations for water species should be solved as well. This domain of application is a real challenge from the stabilization point of view because the correct amount of stabilization must be added in order to preserve the physical properties of the atmospheric flow. At this point, in order to even improve our method, we turn towards local preconditioning. Local preconditiong permits to reduce the stiffness problems that present the flow equations and cause a bad and slow convergence to the solution. With this purpose in mind we combine our stabilization method with local preconditioning and present a stabilization method for the preconditioned Navier-Stokes equations of compressible flow, that we call P-VMS. This method is tested over several examples at different Mach numbers and proves a significant improvement not only in the convergence to the solution but also in the accuracy and robustness of the method. Finally, the benefits of P-VMS are theoretically assessed using Fourier stability analysis. As a result of this analysis a modification on the computation of the time step is done even improving the convergence of the method.
Aquesta tesi tracta sobre l'estabilització de la solució numèrica de les equacions d'Euler i Navier-Stokes de flux compressible. Quan es simulen numèricament les equacions que governen els fluids, si no s'afegeix cap estabilització, la solució presenta oscil·lacions no físiques sinó numèriques. Per aquest motiu l'estabilització de les equacions en derivades parcials i de les equacions de la mecànica de fluids és de gran importància. Dins del marc de l'anomenada estabilització de multiescales variacionals, presentem aquí un mètode d'estabilització per flux compressible. L'evaluació del mètode es realitza primer en varis exemples acadèmics per diferents nombres de Mach, per flux viscós, inviscid, estacionari i transitori. Després el mètode s'aplica a simulacions de flux atmosfèric. Per això, resolem les equacions d'Euler per flux atmosfèric sec i humit. En presència d'humitat, també s'ha de resoldre un grup d'equacions de transport d'espècies d'aigua. Aquest domini d'aplicació representa un desafiament des del punt de vista de l'estabilització, donat que s'ha d'afegir la quantitat adequada d'estabilització per tal de preservar les propietats físiques del flux atmosfèric. Arribat aquest punt, per tal de millorar el nostre mètode, ens interessem pels precondicionadors locals. Els precondicionadors locals permeten reduir els problemes de rigidesa que presenten les equacions dels fluids i que són causa d'una pitjor i més lenta convergència cap a la solució. Amb aquest propòsit en ment, combinem el nostre mètode d'estabilització amb els precondicionadors locals i presentem un mètode d'estabilització per les equacions de Navier-Stokes de flux compressible, anomenem aquest màtode P-VMS. Aquest mètode es evaluat per mitjà de varis exemples per diferents nombres de Mach i demostra una millora sustancial no només pel que fa la convergència cap a la solució, sinó també en la precisió i robusteza del mètode. Finalment els beneficis del P-VMS es demostren teòricament a través de l'anàlisi d'estabilitat de Fourier. Com a resultat d'aquest anàlisi, sorgeix una modificació en el càlcul del pas de temps que millora un cop més la convergència del mètode
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Hellman, Fredrik. "Multiscale and multilevel methods for porous media flow problems." Licentiate thesis, Uppsala universitet, Avdelningen för beräkningsvetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-262276.

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We consider two problems encountered in simulation of fluid flow through porous media. In macroscopic models based on Darcy's law, the permeability field appears as data. The first problem is that the permeability field generally is not entirely known. We consider forward propagation of uncertainty from the permeability field to a quantity of interest. We focus on computing p-quantiles and failure probabilities of the quantity of interest. We propose and analyze improved standard and multilevel Monte Carlo methods that use computable error bounds for the quantity of interest. We show that substantial reductions in computational costs are possible by the proposed approaches. The second problem is fine scale variations of the permeability field. The permeability often varies on a scale much smaller than that of the computational domain. For standard discretization methods, these fine scale variations need to be resolved by the mesh for the methods to yield accurate solutions. We analyze and prove convergence of a multiscale method based on the Raviart–Thomas finite element. In this approach, a low-dimensional multiscale space based on a coarse mesh is constructed from a set of independent fine scale patch problems. The low-dimensional space can be used to yield accurate solutions without resolving the fine scale.
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Dub, Francois-Xavier. "A locally conservative variational multiscale method for the simulation of porous media flow with multiscale source terms." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/44874.

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Анотація:
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2008.
Includes bibliographical references (p. 75-78).
Multiscale phenomena are ubiquitous to flow and transport in porous media. They manifest themselves through at least the following three facets: (1) effective parameters in the governing equations are scale dependent; (2) some features of the flow (especially sharp fronts and boundary layers) cannot be resolved on practical computational grids; and (3) dominant physical processes may be different at different scales. Numerical methods should therefore reflect the multiscale character of the solution. We concentrate on the development of simulation techniques that account for the heterogeneity present in realistic reservoirs, and have the ability to solve for coupled pressure-saturation problems (on coarse grids). We present a variational multiscale mixed finite element method for the solution of Darcy flow in porous media, in which both the permeability field and the source term display a multiscale character. The formulation is based on a multiscale split of the solution into coarse and subgrid scales. This decomposition is invoked in a variational setting that leads to a rigorous definition of a (global) coarse problem and a set of (local) subgrid problems. One of the key issues for the success of the method is the proper definition of the boundary conditions for the localization of the subgrid problems. We identify a weak compatibility condition that allows for subgrid communication across element interfaces, something that turns out to be essential for obtaining high-quality solutions. We also remove the singularities due to concentrated sources from the coarse-scale problem by introducing additional multiscale basis functions, based on a decomposition of fine-scale source terms into coarse and deviatoric components.
(cont.) The method is locally conservative and employs a low-order approximation of pressure and velocity at both scales. We illustrate the performance of the method on several synthetic cases, and conclude that the method is able to capture the global and local flow patterns accurately.
by Francois-Xavier Dub.
S.M.
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Gravemeier, Volker. "The variational multiscale method for laminar and turbulent incompressible flow." [S.l. : s.n.], 2003. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB11051842.

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Xu, Mingtian, and 許明田. "Multiscale transport of mass, momentum and energy." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B3124497X.

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Книги з теми "Multiscale flow"

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Abdol-Hamid, Khaled Sayed. Multiscale turbulence effects in supersonic jets exhausting into still air. Hampton, Va: Langley Research Center, 1987.

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Li, Jun. Multiscale and Multiphysics Flow Simulations of Using the Boltzmann Equation. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-26466-6.

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Panasenko, Grigory, and Konstantin Pileckas. Multiscale Analysis of Viscous Flows in Thin Tube Structures. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-54630-3.

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Zhao, T. S., and Ao Xu. Multiscale Modelling and Simulation of Flow Batteries. Elsevier Science & Technology Books, 2022.

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Zhao, T. S., and Ao Xu. Multiscale Modelling and Simulation of Flow Batteries. Elsevier Science & Technology, 2023.

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Multiscale Thermal Transport in Energy Systems. Nova Science Publishers, Incorporated, 2016.

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7

Li, Jun. Multiscale and Multiphysics Flow Simulations of Using the Boltzmann Equation: Applications to Porous Media and MEMS. Springer, 2019.

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Li, Jun. Multiscale and Multiphysics Flow Simulations of Using the Boltzmann Equation: Applications to Porous Media and MEMS. Springer International Publishing AG, 2020.

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9

Verma, Mahendra K. Energy Transfers in Fluid Flows: Multiscale and Spectral Perspectives. Cambridge University Press, 2019.

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Pileckas, Konstantinas. Multiscale Analysis of Viscous Flows in Thin Tube Structures. Springer Basel AG, 2024.

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Частини книг з теми "Multiscale flow"

1

Florack, Luc. "Multiscale Optic Flow." In Computational Imaging and Vision, 175–203. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-015-8845-4_6.

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Li, Jun. "Multiscale LBM Simulations." In Multiscale and Multiphysics Flow Simulations of Using the Boltzmann Equation, 119–62. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26466-6_4.

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Kassinos, S. C., J. H. Walther, E. Kotsalis, and P. Koumoutsakos. "Flow of Aqueous Solutions in Carbon Nanotubes." In Multiscale Modelling and Simulation, 215–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18756-8_16.

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Vassilicos, John Christos. "Fractal/Multiscale Wake Generators." In Fractal Flow Design: How to Design Bespoke Turbulence and Why, 157–63. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33310-6_5.

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Kayumov, Rashit A., and Farid R. Shakirzyanov. "Large Deflections and Stability of Low-Angle Arches and Panels During Creep Flow." In Multiscale Solid Mechanics, 237–48. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54928-2_18.

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Vincent, Stéphane, Jean-Luc Estivalézes, and Ruben Scardovelli. "Multiscale Euler–Lagrange Coupling." In Small Scale Modeling and Simulation of Incompressible Turbulent Multi-Phase Flow, 263–91. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-09265-7_9.

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Bagchi, Prosenjit. "Large-Scale Simulation of Blood Flow in Microvessels." In Multiscale Modeling of Particle Interactions, 321–39. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9780470579831.ch11.

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Seoud, R. E. E., and J. C. Vassilicos. "Passive Multiscale Flow Control by Fractal Grids." In IUTAM Symposium on Flow Control and MEMS, 421–25. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6858-4_53.

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Buehler, Markus J., Farid F. Abraham, and Huajian Gao. "Stress and energy flow field near a rapidly propagating mode I crack." In Multiscale Modelling and Simulation, 143–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18756-8_10.

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Ewing, R. E., M. Espedal, and M. Celia. "Solution Methods for Multiscale Porous Media Flow." In Computational Methods in Water Resources X, 449–56. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-010-9204-3_55.

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Тези доповідей конференцій з теми "Multiscale flow"

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Ramakrishnan, Srinivas, and Samuel Collis. "Variational Multiscale Modeling for Turbulence Control." In 1st Flow Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2002. http://dx.doi.org/10.2514/6.2002-3280.

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Peña-Monferrer, C., J. L. Muñoz-Cobo, G. Monrós-Andreu, and S. Chiva. "Development of a multiscale solver with sphere partitioning tracking." In MULTIPHASE FLOW 2015. Southampton, UK: WIT Press, 2015. http://dx.doi.org/10.2495/mpf150221.

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Matsumoto, Yoichiro, and Kohei Okita. "Multiscale Analysis on Cavitating Flow." In 6th AIAA Theoretical Fluid Mechanics Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2011. http://dx.doi.org/10.2514/6.2011-4044.

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Grinberg, Leopold, Mingge Deng, Huan Lei, Joseph A. Insley, and George Em Karniadakis. "Multiscale simulations of blood-flow." In the 1st Conference of the Extreme Science and Engineering Discovery Environment. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2335755.2335829.

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Telea, Alexandru, and Robert Strzodka. "Multiscale image based flow visualization." In Electronic Imaging 2006, edited by Robert F. Erbacher, Jonathan C. Roberts, Matti T. Gröhn, and Katy Börner. SPIE, 2006. http://dx.doi.org/10.1117/12.640425.

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Challa, Sivakumar R., Richard Truesdell, Peter Vorobieff, Andrea Mammoli, Frank van Swol, Glaucio H. Paulino, Marek-Jerzy Pindera, et al. "Shear Flow on Super-Hydrophobic Surfaces." In MULTISCALE AND FUNCTIONALLY GRADED MATERIALS 2006. AIP, 2008. http://dx.doi.org/10.1063/1.2896904.

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Lie, K. A., S. Krogstad, and B. Skaflestad. "Mixed Multiscale Methods for Compressible Flow." In ECMOR XIII - 13th European Conference on the Mathematics of Oil Recovery. Netherlands: EAGE Publications BV, 2012. http://dx.doi.org/10.3997/2214-4609.20143240.

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Ding, Wei, Jinming Zhang, Hamed Setoodeh, Dirk Lucas, and Uwe Hampel. "Multiscale Approach for Boiling Flow Simulation." In 20th International Topical Meeting on Nuclear Reactor Thermal Hydraulics (NURETH-20). Illinois: American Nuclear Society, 2023. http://dx.doi.org/10.13182/nureth20-40132.

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Tao, Wen-Quan, and Ya-Ling He. "Multiscale Simulations of Heat Transfer and Fluid Flow Problems." In 2010 14th International Heat Transfer Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/ihtc14-23408.

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Анотація:
Multiscale simulation is a rapidly evolving area of research that will have a great impact on computational mathematics and numerical modeling in engineering. In this keynote lecture following parts are included. First, what is multiscale problem. In the thermal and fluid science multiscale problems may be classified into two categories: multiscale process and multiscale system. By multiscale process we mean that the overall behavior is governed by processes occur at different length scales. By multiscale system we refer to a system that is characterized by a large variation in length scales. The cooling of an electronic system is such a typical multiscale system. Existing numerical methods for three geometric scales (macro, meso and micro) are briefly mentioned. In the second part the necessity of multiscale simulation is discussed. Examples are provided for multiscale process and multiscale system. In this lecture focus is put on the simulation of multiscale process. In the third section numerical approaches developed for the simulation of multiscale processes are presented. There are two types of simulation approaches. One is the usage of a general governing equation and solving the entire flow field involving a variation of several orders in characteristic geometric scale. The other is the so-called “solving regionally and coupling at the interfaces”. In this approach the processes at different length level is simulated by different numerical methods and then information is exchanged at the interfaces between different regions. The exchange of information should be conducted in a way that is physically meaningful, mathematically stable, and computationally efficient. The key point is the establishment of the reconstruction operator, which transforms the data of few variables of macroscopic computation to large amount of variables of microscale or mesoscale simulation. For different coupling cases the existing methods for such operators are briefly reviewed. In the fourth part, four numerical examples of multiscale simulation are presented: liquid flow in nanochannels with roughness by using MDS and FVM, flow and heat transfer in a micro nozzle by using DSMC in fluid and FVM in solid, flow past a cylinder and natural convection heat transfer in a square cavity by using coupled FVM and LBM. Finally, it is pointed out that we have a long way to go in order to have a successful full multiscale simulation for the complicated engineering problems as transport process in PEMFC and refrigerant condensation process on a enhanced surface. Further researches are highly required to establish robust and quick-convergent numerical solution approaches. Some further research needs are proposed.
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Laizet, Sylvain, and John Christos Vassilicos. "PASSIVE SCALAR STIRRING BY MULTISCALE-GENERATED TURBULENCE." In Seventh International Symposium on Turbulence and Shear Flow Phenomena. Connecticut: Begellhouse, 2011. http://dx.doi.org/10.1615/tsfp7.1120.

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Звіти організацій з теми "Multiscale flow"

1

Patnaik, Soumya S., Eugeniya Iskrenova-Ekiert, and Hui Wan. Multiscale Modeling of Multiphase Fluid Flow. Fort Belvoir, VA: Defense Technical Information Center, August 2016. http://dx.doi.org/10.21236/ad1016834.

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Richard W. Johnson. Dynamic Multiscale Averaging (DMA) of Turbulent Flow. Office of Scientific and Technical Information (OSTI), September 2012. http://dx.doi.org/10.2172/1057682.

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Hou, Thomas, Yalchin Efendiev, Hamdi Tchelepi, and Louis Durlofsky. Multiscale Simulation Framework for Coupled Fluid Flow and Mechanical Deformation. Office of Scientific and Technical Information (OSTI), May 2016. http://dx.doi.org/10.2172/1254120.

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Tchelepi, Hamdi. Multiscale Simulation Framework for Coupled Fluid Flow and Mechanical Deformation. Office of Scientific and Technical Information (OSTI), November 2014. http://dx.doi.org/10.2172/1164145.

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Holm, D. D., A. Aceves, J. S. Allen, M. Alber, R. Camassa, H. Cendra, S. Chen, et al. Self-Consistent Multiscale Theory of Internal Wave, Mean-Flow Interactions. Office of Scientific and Technical Information (OSTI), June 1999. http://dx.doi.org/10.2172/763237.

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Luettgen, Mark R., W. C. Karl, and Alan S. Willsky. Efficient Multiscale Regularization with Applications to the Computation of Optical Flow. Fort Belvoir, VA: Defense Technical Information Center, April 1993. http://dx.doi.org/10.21236/ada459986.

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Miller, Cass T., and William G. Gray. SISGR: Multiscale Modeling of Multiphase Flow, Transport, and Reactions in Porous Medium Systems. Office of Scientific and Technical Information (OSTI), February 2017. http://dx.doi.org/10.2172/1345027.

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Anh Bui, Nam Dinh, and Brian Williams. Validation and Calibration of Nuclear Thermal Hydraulics Multiscale Multiphysics Models - Subcooled Flow Boiling Study. Office of Scientific and Technical Information (OSTI), September 2013. http://dx.doi.org/10.2172/1110336.

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Yortsos, Y. C. Investigation of Multiscale and Multiphase Flow, Transport and Reaction in Heavy Oil Recovery Processes. Office of Scientific and Technical Information (OSTI), May 2001. http://dx.doi.org/10.2172/781148.

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Yortsos, Yanis C. Investigation of Multiscale and Multiphase Flow, Transport and Reaction in Heavy Oil Recovery Processes. Office of Scientific and Technical Information (OSTI), August 2001. http://dx.doi.org/10.2172/784112.

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