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=== <span style="color:#0000FF"> Introduction </span>=== | === <span style="color:#0000FF"> Introduction </span>=== | ||
− | The numerical solution of convection-diffusion transport problems arises in many important applications in science and engineering. These problems occur in many applications such as in the transport of air and ground water pollutants, oil reservoir flow, in the modeling of semiconductors, and so forth | + | The numerical solution of convection-diffusion transport problems arises in many important applications in science and engineering. These problems occur in many applications such as in the transport of air and ground water pollutants, oil reservoir flow, in the modeling of semiconductors, and so forth. |
Theory | Theory |
Revision as of 14:21, 16 July 2013
Contents |
Introduction
The numerical solution of convection-diffusion transport problems arises in many important applications in science and engineering. These problems occur in many applications such as in the transport of air and ground water pollutants, oil reservoir flow, in the modeling of semiconductors, and so forth.
Theory
Under the assumption of incompressibility, the governing equations are given by
(1)
(2)
In the context of mass difussion within a fluid, (1) is is the mass conservation equation and (2) is a contitutive law proposed by Fourier. The notation is standard: ρ is the density, C the heat capacity, κ the thermal conductivity, T is the temperature, v is the velocity field and q is the diffusive flux per unit fluid density.
Remark: systen can be decoupled since we can plug (2) into (1) and solve the
scalar equation
(3)
Problem statement
Let us consider the transport by convection and diffusion in an open set Ω (d=2 or 3) \ with piecewise smooth boundary Γ, such that . The unit outward normal vector to Γ is denoted n. The convection-diffusion initial-boundary value problem can be stated as follows: given a divergence-free velocity field a, the diffusion tensor κ and adequate initial and boundary conditions, find T : such that
(4)
T(x,0) = T_{0}(x)onΩ
Space discretization method Multiplying Eq.(4) by a test function W and intehrating on the whole domain Ω the equation reads
(5)
Integratin by parts the right term of Eq.(5) leads to
(6)
Finite element discretization
The temperature is discretized in the standard finite element method manner as (7) where N_{i} are the nodal shape functions. Substituting the finite element approximation (7) into the variational equation () and choosing a Galerling formulation (W_{i} = N_{i}) leads to the following equation:
(7)
Time discretization method Consider a first-order BDF (that is, the Euler implicit scheme)
or a second-order BDF
Computational Structural Mechanics module
Introduction
Examples showing the class of problems that the code can solve (2-4 examples)
Description of the underlying theory and schematic list of the problems this application can solve.
The Computational Structural Mechanics module (CSM) is....
Application Structure
Analysis Type
The available solutions strategies are:
- Static
- Dynamic
- Relaxed dynamic
With this module you can solve both linear and non linear problems. In case of non linear problems several methods are available:
- Newton-Raphson
- Newton Raphson with line search
- Arch lenght
Different solvers are availables (LINK TO SOLVER SECTION!!!!)
Elements
- Frame Elements:
- Euler-Bernoulli beam short explanation
- Crisfield truss short explanation
- 2D elements
- Linear triangular element:
- Shell elements:
- Isotropic shell: (change the name with the usual one!!!!)
- Ansotropic shell: (change the name with the usual one!!!!)
- EBST shell: (change the name with the usual one!!!!)
- Membrane element:
- Solid elements:
- Linear tetrahedral element:
Dimension | Element Type | Kratos name | Geometry | Nonlinearity | Material Type |
---|---|---|---|---|---|
1D | Frame | LinearBeamElement | Line | Isotropic | |
1D | Truss | CrisfieldTrussElement | Line | Large Displacement | Isotropic |
2D | Solid | TotalLagrangian | 2D Geometries | Large Displacement | Isotropic |
3D | Solid | TotalLagrangian | 3D Geometries | Large Displacement | Isotropic |
Shell | ShellIsotropic | 3D Triangle | Large Displacement | Isotropic | |
Shell | ShellAnisotropic | 3D Triangle | Large Displacement | Orthotropic |
Boundary Conditions
Boundary conditions can be set fixing displacements and rotations degrees of freedom.
Loads
- Self weight
- Punctual force
- Moment
- Face pressure (sign convenction!!!!)
- Distributed load
Constitutive laws
The following constitutive laws are available:
- Linear elastic:
- ...
HPC
The code can be run in shared or distributed memory:
- OpenMP:
- MPI:
Problem parameters
...
Others relevand aspects
...
Benchmarking
Here validation and verification examples should be inserted
Tutorials
Contact people
Akcnowledgements
Convection Diffusion module
Introduction
The numerical solution of convection-diffusion transport problems arises in many important applications in science and engineering. These problems occur in many applications such as in the transport of air and ground water pollutants, oil reservoir flow, in the modeling of semiconductors, and so forth. This paper describes the Convection Diffusion Applications for solving this equation.
Theory
Under the assumption of incompressibility, the governing equations are given by
(1)
(2)
In the context of mass difussion within a fluid, (1) is is the mass conservation equation and (2) is a contitutive law proposed by Fourier. The notation is standard: ρ is the density, C the heat capacity, κ the thermal conductivity, T is the temperature, v is the velocity field and q is the diffusive flux per unit fluid density.
Remark: systen can be decoupled since we can plug (2) into (1) and solve the
scalar equation
(3)
Problem statement
Let us consider the transport by convection and diffusion in an open set Ω (d=2 or 3) \ with piecewise smooth boundary Γ, such that . The unit outward normal vector to Γ is denoted n. The convection-diffusion initial-boundary value problem can be stated as follows: given a divergence-free velocity field a, the diffusion tensor κ and adequate initial and boundary conditions, find T : such that
(4)
T(x,0) = T_{0}(x)onΩ
Space discretization method Multiplying Eq.(4) by a test function W and intehrating on the whole domain Ω the equation reads
(5)
Integratin by parts the right term of Eq.(5) leads to
(6)
Finite element discretization
The temperature is discretized in the standard finite element method manner as (7) where N_{i} are the nodal shape functions. Substituting the finite element approximation (7) into the variational equation () and choosing a Galerling formulation (W_{i} = N_{i}) leads to the following equation:
(7)
Time discretization method Consider a first-order BDF (that is, the Euler implicit scheme)
or a second-order BDF
Structure
Analysis type
The available solution strategy is:
Dynamic
With this module you can solve both linear and non linear problems.
Kinematical approaches
Eulerian and Lagrangian approach are available in order to solve the equation.
Solution strategies
Elements
Linear triangular elements in 2D and linear tetrahedra elements in 3D. Both elements are stabilized with OSS.
ConvDiff2D
ConvDiff3D
Boundary conditions
Dirichlet boundary condition:
Neumann boundary conditions:
Initial conditions
Initial condition in temperature can be set.
HPC
The code can be run in shared or distributed memory:
- OpenMP:
- MPI:
Problem parameters
The parameters involved in this problem are:
ρ : Density
C :heat capacity
κ: thermal conductivity
v : velocity field
q: diffusive flux per unit fluid density.
T a: ambient temperature.
σ: Stefen Boltzmann constant
e: emissivity
h: convection coefficient