Finite-Difference Techniques for Vectorized Fluid Dynamics Calculations

1981 ◽  
Keyword(s):  
Fluid Dynamics ◽  
Finite Difference ◽  
Finite Difference Techniques

Finite difference techniques for variable grids

1972 ◽  
Vol 2 (1-2) ◽  
pp. 17-29 ◽  
Author(s):  
Paul S. Jensen
Keyword(s):  
Finite Difference ◽  
Finite Difference Techniques

Calculation of the Quasi Three-Dimensional Flow in a Turbomachine Blade Row

1977 ◽  
Vol 99 (1) ◽  
pp. 53-62 ◽  
Author(s):  
Jean-Pierre Veuillot
Keyword(s):  
Finite Difference ◽  
Three Dimensional ◽  
Three Dimensional Flow ◽  
Through Flow ◽  
Blade Row ◽  
Time Marching ◽  
Space Discretization ◽  
Finite Volume Approach ◽  
Marching Method ◽  
Finite Difference Techniques

The equations of the through flow are obtained by an asymptotic theory valid when the blade pitch is small. An iterative method determines the meridian stream function, the circulation, and the density. The various equations are discretized in an orthogonal mesh and solved by classical finite difference techniques. The calculation of the steady transonic blade-to-blade flow is achieved by a time marching method using the MacCormack scheme. The space discretization is obtained either by a finite difference approach or by a finite volume approach. Numerical applications are presented.

Hybrid modeling of elastic‐wave propagation in two‐dimensional laterally inhomogeneous media

Geophysics ◽  
1987 ◽  
Vol 52 (6) ◽  
pp. 765-771 ◽  
Author(s):  
B. Kummer ◽  
A. Behle ◽  
F. Dorau
Keyword(s):  
Integral Equation ◽  
Wave Propagation ◽  
Finite Difference ◽  
Elastic Wave ◽  
Boundary Integral Equation ◽  
Integral Equation Method ◽  
Boundary Integral ◽  
Two Dimensional ◽  
Hybrid Scheme ◽  
Finite Difference Techniques

We have constructed a hybrid scheme for elastic‐wave propagation in two‐dimensional laterally inhomogeneous media. The algorithm is based on a combination of finite‐difference techniques and the boundary integral equation method. It involves a dedicated application of each of the two methods to specific domains of the model structure; finite‐difference techniques are applied to calculate a set of boundary values (wave field and stress field) in the vicinity of the heterogeneous domain. The continuation of the near‐field response is then calculated by means of the boundary integral equation method. In a numerical example, the hybrid method has been applied to calculate a plane‐wave response for an elastic lens embedded in a homogeneous environment. The example shows that the hybrid scheme enables more efficient modeling, with the same accuracy, than with pure finite‐difference calculations.

An Analytical Study of Cryosurgery in the Lung

1992 ◽  
Vol 114 (4) ◽  
pp. 467-472 ◽  
Author(s):  
J. C. Bischof ◽  
J. Bastacky ◽  
B. Rubinsky
Keyword(s):  
Finite Difference ◽  
Analytical Study ◽  
Outer Boundary ◽  
Temperature Profiles ◽  
One Dimensional ◽  
Thermal Phenomenon ◽  
Healthy Lung Tissue ◽  
Close Form ◽  
Finite Difference Techniques ◽  
Healthy Lung

The process of freezing in healthy lung tissue and in tumors in the lung during cryosurgery was modeled using one-dimensional close form techniques and finite difference techniques to determine the temperature profiles and the propagation of the freezing interface in the tissue. A thermal phenomenon was observed during freezing of lung tumors embedded in healthy tissue, (a) the freezing interface suddenly accelerates at the transition between the tumor and the healthy lung, (b) the frozen tumor temperature drops to low values once the freezing interface moves into the healthy lung, and (c) the outer boundary temperature has a point of sharp inflection corresponding to the time at which the tumor is completely frozen.

Numerical Modelling of Nanocomposites Using GA and FD Techniques

2019 ◽  
Vol 969 ◽  
pp. 478-483 ◽  
Author(s):  
Siddhartha Kosti ◽  
Jitender Kundu
Keyword(s):  
Genetic Algorithm ◽  
Heat Conduction ◽  
Finite Difference ◽  
Numerical Modelling ◽  
Structural Properties ◽  
Heat Conduction Equation ◽  
Conduction Equation ◽  
Weight Percentage ◽  
Finite Difference Technique ◽  
Finite Difference Techniques

Use of nanocomposites is increasing rapidly due to their enhanced thermal and structural properties. In the present work, the numerical modelling of nanocomposites is conducted with the help of the (GA) genetic algorithm and (FD) finite difference techniques to find out a set of nanocomposites with best thermal and structural properties. The genetic algorithm is utilized to find out the best set of nanocomposites on the basis of thermal and structural properties while the finite difference technique is utilized to solve the heat conduction equation. Different nanocomposites considered in the present work are Al-B4C, Al-SiC and Al-Al2O3. The weight percentage of these nanocomposites is varied to see its effect on the nanocomposites properties. In the end, the solidification curve for all the nanocomposites is plotted and analysed. Result reveals that GA helps in identifying the best set of nanocomposites while FD technique helps in predicting the solidification curve accurately. Increment in the wt. % of nanocomposites makes the solidification curve steeper.

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