Showing papers on "Discretization published in 2002"

The immersed boundary method

Abstract: This paper is concerned with the mathematical structure of the immersed boundary (IB) method, which is intended for the computer simulation of fluid–structure interaction, especially in biological fluid dynamics. The IB formulation of such problems, derived here from the principle of least action, involves both Eulerian and Lagrangian variables, linked by the Dirac delta function. Spatial discretization of the IB equations is based on a fixed Cartesian mesh for the Eulerian variables, and a moving curvilinear mesh for the Lagrangian variables. The two types of variables are linked by interaction equations that involve a smoothed approximation to the Dirac delta function. Eulerian/Lagrangian identities govern the transfer of data from one mesh to the other. Temporal discretization is by a second-order Runge–Kutta method. Current and future research directions are pointed out, and applications of the IB method are briefly discussed. Introduction The immersed boundary (IB) method was introduced to study flow patterns around heart valves and has evolved into a generally useful method for problems of fluid–structure interaction. The IB method is both a mathematical formulation and a numerical scheme. The mathematical formulation employs a mixture of Eulerian and Lagrangian variables. These are related by interaction equations in which the Dirac delta function plays a prominent role. In the numerical scheme motivated by the IB formulation, the Eulerian variables are defined on a fixed Cartesian mesh, and the Lagrangian variables are defined on a curvilinear mesh that moves freely through the fixed Cartesian mesh without being constrained to adapt to it in any way at all.

Efficient Inverse Modeling of Barotropic Ocean Tides

Abstract: A computationally efficient relocatable system for generalized inverse (GI) modeling of barotropic ocean tides is described. The GI penalty functional is minimized using a representer method, which requires repeated solution of the forward and adjoint linearized shallow water equations (SWEs). To make representer computations efficient, the SWEs are solved in the frequency domain by factoring the coefficient matrix for a finite-difference discretization of the second-order wave equation in elevation. Once this matrix is factored representers can be calculated rapidly. By retaining the first-order SWE system (defined in terms of both elevations and currents) in the definition of the discretized GI penalty functional, complete generality in the choice of dynamical error covariances is retained. This allows rational assumptions about errors in the SWE, with soft momentum balance constraints (e.g., to account for inaccurate parameterization of dissipation), but holds mass conservation constraints. Wh...

Computational Contact Mechanics

Abstract: Preface. Introduction. Introduction to Contact Mechanics. Continuum Solid Mechanics and Weak Forms. Contact Kinematics. Constitutive Equations for Contact Interfaces. Contact Boundary Value Problem and Weak Form. Discretization of the Continuum. Discretization, Small Deformation Contact. Discretization, Large Deformation Contact. Solution Algorithms. Thermo--mechanical Contact. Beam Contact. Adaptive Finite Element Methods for Contact Problems. Computation of Critical Points with Contact Constraints. Appendix A: Gauss Integration Rules. Appendix B: Convective Coordinates. Appendix C: Parameter Identification for Friction Materials. References. Index.

Discretization: An Enabling Technique

Abstract: Discrete values have important roles in data mining and knowledge discovery They are about intervals of numbers which are more concise to represent and specify, easier to use and comprehend as they are closer to a knowledge-level representation than continuous values Many studies show induction tasks can benefit from discretization: rules with discrete values are normally shorter and more understandable and discretization can lead to improved predictive accuracy Furthermore, many induction algorithms found in the literature require discrete features All these prompt researchers and practitioners to discretize continuous features before or during a machine learning or data mining task There are numerous discretization methods available in the literature It is time for us to examine these seemingly different methods for discretization and find out how different they really are, what are the key components of a discretization process, how we can improve the current level of research for new development as well as the use of existing methods This paper aims at a systematic study of discretization methods with their history of development, effect on classification, and trade-off between speed and accuracy Contributions of this paper are an abstract description summarizing existing discretization methods, a hierarchical framework to categorize the existing methods and pave the way for further development, concise discussions of representative discretization methods, extensive experiments and their analysis, and some guidelines as to how to choose a discretization method under various circumstances We also identify some issues yet to solve and future research for discretization

Diffusion Kernels on Graphs and Other Discrete Input Spaces

Abstract: The application of kernel-based learning algorithms has, so far, largely been confined to realvalued data and a few special data types, such as strings In this paper we propose a general method of constructing natural families of kernels over discrete structures, based on the matrix exponentiation idea In particular, we focus on generating kernels on graphs, for which we propose a special class of exponential kernels called diffusion kernels, which are based on the heat equation and can be regarded as the discretization of the familiar Gaussian kernel of Euclidean space

Linear and nonlinear structural mechanics

Abstract: Preface. 1. Introduction. 1.1 Structural Elements. 1.2 Nonlinearities. 1.3 Composite Materials. 1.4 Damping. 1.5 Dynamic Characteristics of Linear Discrete Systems. 1.6 Dynamic Characteristics of Nonlinear Discrete Systems 1.7 Analyses of Linear Continuous Systems. 1.8 Analyses of Nonlinear Continuous Systems. 2. Elasticity. 2.1 Principles of Dynamics. 2.2 Strain--Displacement Relations. 2.3 Transformation of Strains and Stresses. 2.4 Stress--Strain Relations. 2.5 Governing Equations. 3. Strings and Cables. 3.1 Modeling of Taut Strings. 3.2 Reduction of String Model to Two Equations. 3.3 Nonlinear Response of Strings. 3.4 Modeling of Cables. 3.5 Reduction of Cable Model to Two Equations. 3.6 Natural Frequencies and Modes of Cables. 3.7 Discretization of the Cable Equations. 3.8 Single--Mode Response with Direct Approach. 3.9 Single--Mode Response with Discretization Approach. 3.10 Extensional Bars. 4. Beams. 4.1 Introduction. 4.2 Linear Euler--Bernoulli Beam Theory. 4.3 Linear Shear--Deformable Beam Theories. 4.4 Mathematics for Nonlinear Modeling. 4.5 Nonlinear 2--D Euler--Bernoulli Beam Theory. 4.6 Nonlinear 3--D Euler--Bernoulli Beam Theory. 4.7 Nonlinear 3--D Curved Beam Theory Accounting for Warpings. 5. Dynamics of Beams. 5.1 Parametrically Excited Cantilever Beams. 5.2 Transversely Excited Cantilever Beams. 5.3 Clamped--Clamped Buckled Beams. 5.4 Microbeams. 6. Surface Analysis. 6.1 Initial Curvatures. 6.2 Inplane Strains and Deformed Curvatures. 6.3 Orthogonal Virtual Rotations. 6.4 Variation of Curvatures. 6.5 Local Displacements and Jaumann Strains. 7. Plates. 7.1 Introduction. 7.2 Linear Classical Plate Theory. 7.3 Linear Shear--Deformable Plate Theories. 7.4 Nonlinear Classical Plate Theory. 7.5 Nonlinear Modeling of Rectangular Surfaces. 7.6 General Nonlinear Classical Plate Theory. 7.7 Nonlinear Shear--Deformable Plate Theory. 7.8 Nonlinear Layerwise Shear--Deformable Plate Theory. 8. Dynamics of Plates. 8.1 Linear Vibrations of Rectangular Plates. 8.2 Linear Vibrations of Membranes. 8.3 Linear Vibrations of Circular and Annular Plates. 8.4 Nonlinear Vibrations of Circular and Annular Plates. 8.5 Nonlinear Vibrations of Rotating Disks. 8.6 Nonlinear Vibrations of Near--Square Plates. 8.7 Micropumps. 8.8 Thermally Loaded Plates. 9. Shells. 9.1 Introduction. 9.2 Linear Classical Shell Theory. 9.3 Linear Shear--Deformable Shell Theories. 9.4 Nonlinear Classical Theory for Double--Curved Shells. 9.5 Nonlinear Shear--Deformable Theories for Circular Cylindrical Shells. 9.6 Nonlinear Layerwise Shear--Deformable Shell Theory. 9.7 Nonlinear Dynamics of Infinitely Long Circular Cylindrical Shells. 9.8 Nonlinear Dynamics of Axisymmetric Motion of Closed Spherical Shells. Bibliography. Subject Index.

Galerkin Proper Orthogonal Decomposition Methods for a General Equation in Fluid Dynamics

Abstract: Error estimates for Galerkin proper orthogonal decomposition (POD) methods for nonlinear parabolic systems arising in fluid dynamics are proved For the time integration the backward Euler scheme is considered The asymptotic estimates involve the singular values of the POD snapshot set and the grid-structure of the time discretization as well as the snapshot locations

A New Class of Optimal High-Order Strong-Stability-Preserving Time Discretization Methods

Abstract: Strong-stability-preserving (SSP) time discretization methods have a nonlinear stability property that makes them particularly suitable for the integration of hyperbolic conservation laws where discontinuous behavior is present. Optimal SSP schemes have been previously found for methods of order 1, 2, and 3, where the number of stages s equals the order p. An optimal low-storage SSP scheme with s=p=3 is also known. In this paper, we present a new class of optimal high-order SSP and low-storage SSP Runge--Kutta schemes with s>p. We find that these schemes are ultimately more efficient than the known schemes with s=p because the increase in the allowable time step more than offsets the added computational expense per step. We demonstrate these efficiencies on a set of scalar conservation laws.

Semi‐discretization method for delayed systems

Abstract: SUMMARY The paper presents an ecient numerical method for the stability analysis of linear delayed systems. The method is based on a special kind of discretization technique with respect to the past eect only. The resulting approximate system is delayed and also time periodic, but still, it can be transformed analytically into a high-dimensional linear discrete system. The method is applied to determine the stability charts of the Mathieu equation with continuous time delay. Copyright ? 2002 John Wiley & Sons, Ltd.

Non-planar 3d crack growth by the extended finite element and level sets- part ii: level set update

Abstract: We present a level set method for treating the growth of non-planar three-dimensional cracks.The crack is defined by two almost-orthogonal level sets (signed distance functions). One of them describes the crack as a two-dimensional surface in a three-dimensional space, and the second is used to describe the one-dimensional crack front, which is the intersection of the two level sets. A Hamilton–Jacobi equation is used to update the level sets. A velocity extension is developed that preserves the old crack surface and can accurately generate the growing surface. The technique is coupled with the extended finite element method which approximates the displacement field with a discontinuous partition of unity. This displacement field is constructed directly in terms of the level sets, so the discretization by finite elements requires no explicit representation of the crack surface. Numerical experiments show the robustness of the method, both in accuracy and in treating cracks with significant changes in topology. Copyright © 2002 John Wiley & Sons, Ltd.

Discretization schemes for fractional-order differentiators and integrators

Abstract: For fractional-order differentiator s/sup r/ where r is a real number, its discretization is a key step in digital implementation. Two discretization methods are presented. The first scheme is a direct recursive discretization of the Tustin operator. The second one is a direct discretization method using the Al-Alaoui operator via continued fraction expansion (CFE). The approximate discretization is minimum phase and stable. Detailed discretization procedures and short MATLAB scripts are given. Examples are included for illustration.

Computational micro-to-macro transitions of discretized microstructures undergoing small strains

Abstract: The paper investigates algorithms for the computation of homogenized stresses and overall tangent moduli of microstructures undergoing small strains. Typically, these microstructures define representative volumes of nonlinear heterogeneous materials such as inelastic composites, polycrystalline aggregates or particle assemblies. We consider a priori given discretized microstructures, without focusing on details of specific discretization techniques in space and time. The key contribution of the paper is the construction of a family of algorithms and matrix representations of the overall properties of discretized microstructures. It is shown that the overall stresses and tangent moduli of a typical microstructure may exclusively be defined in terms of discrete forces and stiffness properties on the boundary. We focus on deformation-driven microstructures, where the overall macroscopic deformation is controlled. In this context, three classical types of boundary conditions are investigated: (i) linear displacements, (ii) constant tractions and (iii) periodic displacements and antiperiodic tractions. Incorporated by the Lagrangian multiplier method, these constraints generate three classes of algorithms for the computation of equilibrium states and the overall properties of microstructures. The proposed algorithms and matrix representations of the overall properties are formally independent of the interior spatial structure and the local constitutive response of the microstructure and are therefore applicable to a broad class of model problems. We demonstrate their performance for some representative model problems including elastic–plastic deformations of composite materials.

Simulating quantum transport in nanoscale transistors: Real versus mode-space approaches

Abstract: In this article, we present a computationally efficient, two-dimensional quantum mechanical simulation scheme for modeling electron transport in thin body, fully depleted, n-channel, silicon-on-insulator transistors in the ballistic limit. The proposed simulation scheme, which solves the nonequilibrium Green’s function equations self-consistently with Poisson’s equation, is based on an expansion of the active device Hamiltonian in decoupled mode space. Simulation results from this method are benchmarked against solutions from a rigorous two-dimensional discretization of the device Hamiltonian in real space. While doing so, the inherent approximations, regime of validity and the computational efficiency of the mode-space solution are highlighted and discussed. Additionally, quantum boundary conditions are rigorously derived and the effects of strong off-equilibrium transport are examined. This article shows that the decoupled mode-space solution is an efficient and accurate simulation method for modeling e...

Computation of Multiphase Systems with Phase Field Models

Abstract: Phase field models offer a systematic physical approach for investigating complex multiphase systems behaviors such as near-critical interfacial phenomena, phase separation under shear, and microstructure evolution during solidification. However, because interfaces are replaced by thin transition regions (diffuse interfaces), phase field simulations require resolution of very thin layers to capture the physics of the problems studied. This demands robust numerical methods that can efficiently achieve high resolution and accuracy, especially in three dimensions. We present here an accurate and efficient numerical method to solve the coupled Cahn-Hilliard/Navier-Stokes system, known as Model H, that constitutes a phase field model for density-matched binary fluids with variable mobility and viscosity. The numerical method is a time-split scheme that combines a novel semi-implicit discretization for the convective Cahn-Hilliard equation with an innovative application of high-resolution schemes employed for direct numerical simulations of turbulence. This new semi-implicit discretization is simple but effective since it removes the stability constraint due to the nonlinearity of the Cahn-Hilliard equation at the same cost as that of an explicit scheme. It is derived from a discretization used for diffusive problems that we further enhance to efficiently solve flow problems with variable mobility and viscosity. Moreover, we solve the Navier-Stokes equations with a robust time-discretization of the projection method that guarantees better stability properties than those for Crank-Nicolson-based projection methods. For channel geometries, the method uses a spectral discretization in the streamwise and spanwise directions and a combination of spectral and high order compact finite difference discretizations in the wall normal direction. The capabilities of the method are demonstrated with several examples including phase separation with, and without, shear in two and three dimensions. The method effectively resolves interfacial layers of as few as three mesh points. The numerical examples show agreement with analytical solutions and scaling laws, where available, and the 3D simulations, in the presence of shear, reveal rich and complex structures, including strings.

Large-Eddy Simulation on Curvilinear Grids Using Compact Differencing and Filtering Schemes

Abstract: This work investigates the application of a high-order finite difference method for compressible large-eddy simulations on stretched, curvilinear and dynamic meshes. The solver utilizes 4th and 6th-order compact-differencing schemes for the spatial discretization, coupled with both explicit and implicit time-marching methods. Up to 10th order, Pade-type low-pass spatial filter operators are also incorporated to eliminate the spurious high-frequency modes which inevitably arise due to the lack of inherent dissipation in the spatial scheme. The solution procedure is evaluated for the case of decaying compressible isotropic turbulence and turbulent channel flow. The compact/filtering approach is found to be superior to standard second and fourth-order centered, as well as third-order upwind-biased approximations. For the case of isotropic turbulence, better results are obtained with the compact/filtering method (without an added subgrid-scale model) than with the constant-coefficient and dynamic Smagorinsky models. This is attributed to the fact that the SGS models, unlike the optimized low-pass filter, exert dissipation over a wide range of wave numbers including on some of the resolved scales

A Practical Guide to Boundary Element Methods with the Software Library BEMLIB

Abstract: LAPLACE'S EQUATION IN ONE DIMENSION Green's First and Second Identities and the Reciprocal Relation Green's Functions Boundary-Value Representation Boundary-Value Equation LAPLACE'S EQUATION IN TWO DIMENSIONS Green's First and Second Identities and the Reciprocal Relation Green's Functions Integral Representation Integral Equations Hypersingular Integrals Irrotational Flow Generalized Single- and Double-Layer Representations BOUNDARY-ELEMENT METHODS FOR LAPLACE'S EQUATION IN TWO DIMENSIONS Boundary Element Discretization . Discretization of the Integral Representation The Boundary-Element Collocation Method Isoparametric Cubic-Splines Discretization High-Order Collocation Methods Galerkin and Global Expansion Methods LAPLACE'S EQUATION IN THREE DIMENSIONS Green's First and Second Identities and the Reciprocal Relation Green's Functions Integral Representation Integral Equations Axisymmetric Fields in Axisymmetric Domains BOUNDARY-ELEMENT METHODS FOR LAPLACE'S EQUATION IN THREE DIMENSIONS Discretization Three-Node Flat Triangles Six-Node Curved Triangles High-Order Expansions INHOMOGENEOUS, NONLINEAR, AND TIME-DEPENDENT PROBLEMS Distributed Source and Domain Integrals Particular Solutions and Dual Reciprocity in One Dimension Particular Solutions and Dual Reciprocity in Two and Three Dimensions Convection - Diffusion Equation Time-Dependent Problems VISCOUS FLOW Governing Equations Stokes Flow Boundary Integral Equations in Two Dimensions Boundary-Integral Equations in Three Dimensions Boundary-Element Methods Interfacial Dynamics Unsteady, Navier-Stokes, and Non-Newtonian Flow BEMLIB USER GUIDE General Information Terms and Conditions Directory DIRECTORY: GRIDS grid_2d trgl DIRECTORY: LAPLACE lgf_2d lgf_3d lgf_ax flow_1d flow_1d 1p flow_2d body_2d body_ax tank_2d ldr_ 3d lnm_3d DIRECTORY: HELMHOLTZ flow_1d osc DIRECTORY: STOKES sgf_2d sgf_3d sgf_ax flow_2d prtcl_sw prtcl_2d prtcl_ax prtcl_3d APPENDIX A: MATHEMATICAL SUPPLEMENT APPENDIX B: GAUSS ELIMINATION AND LINEAR SOLVERS APPENDIX C: ELASTOSTATICS REFERENCES INDEX

An automated strategy for calculation of phase diagram sections and retrieval of rock properties as a function of physical conditions

Abstract: We formulate an algorithm for the calculation of stable phase relations of a system with constrained bulk composition as a function of its environmental variables. The basis of this algorithm is the approximate representation of the free energy composition surfaces of solution phases by inscribed polyhedra. This representation leads to discretization of high variance phase fields into a continuous mesh of smaller polygonal fields within which the composition and physical properties of the phases are uniquely determined. The resulting phase diagram sections are useful for understanding the phase relations of complex metamorphic systems and for applications in which it is necessary to establish the variations in rock properties such as density, seismic velocities and volatile-content through a metamorphic cycle. The algorithm has been implemented within a computer program that is general with respect to both the choice of variables and the number of components and phases possible in a system, and is independent of the structure of the equations of state used to describe the phases of the system.

Upscaling: a review

Abstract: Porous media have properties with heterogeneities on several length scales. It is possible to build digital models of such properties. However these can be so detailed that a computing machine of the same power as that used to build the property model is not able to solve the fluid flow equations using standard discretisation methods—storage is needed for workspace, and the discrete equations have to be solved in a reasonable time. This paper reviews averaging techniques, devised to simulate large scale features of solutions without necessarily solving all the fine scale equations. Copyright © 2002 John Wiley & Sons, Ltd.

Strain‐driven homogenization of inelastic microstructures and composites based on an incremental variational formulation

Abstract: The paper investigates computational procedures for the treatment of a homogenized macro-continuum with locally attached micro-structures of inelastic constituents undergoing small strains. The point of departure is a general internal variable formulation that determines the inelastic response of the constituents of a typical micro-structure as a generalized standard medium in terms of an energy storage and a dissipation function. Consistent with this type of inelasticity we develop a new incremental variational formulation of the local constitutive response where a quasi-hyperelastic micro-stress potential is obtained from a local minimization problem with respect to the internal variables. It is shown that this local minimization problem determines the internal state of the material for finite increments of time. We specify the local variational formulation for a setting of smooth single-surface inelasticity and discuss its numerical solution based on a time discretization of the internal variables. The existence of the quasi-hyperelastic stress potential allows the extension of homogenization approaches of elasticity to the incremental setting of inelasticity. Focusing on macro-strain-driven micro-structures, we develop a new incremental variational formulation of the global homogenization problem where a quasi-hyperelastic macro-stress potential is obtained from a global minimization problem with respect to the fine-scale displacement fluctuation field. It is shown that this global minimization problem determines the state of the micro-structure for finite increments of time. We consider three different settings of the global variational problem for prescribed linear displacements, periodic fluctuations and constant stresses on the boundary of the micro-structure and discuss their numerical solutions based on a spatial discretization of the fine-scale displacement fluctuation field. The performance of the proposed methods is demonstrated for the model problem of von Mises-type elasto-visco-plasticity of the constituents and applied to a comparative study of micro-to-macro transitions of inelastic composites. Copyright © 2002 John Wiley & Sons, Ltd.