Three-Dimensional Fluorescence Absorption Imaging with Domain Decomposition

2000 ◽  
Author(s):  
Margaret J. Eppstein
Keyword(s):  
Domain Decomposition ◽  
Three Dimensional ◽  
Absorption Imaging

scholarly journals Domain Decomposition Modified with Characteristic Mixed Finite Element and Numerical Analysis for Three-Dimensional Slightly Compressible Oil-Water Seepage Displacement

2017 ◽  
Vol 9 (1) ◽  
pp. 143
Author(s):  
Yirang Yuan ◽  
Luo Chang ◽  
Changfeng Li ◽  
Tongjun Sun
Keyword(s):  
Finite Element ◽  
Domain Decomposition ◽  
Method Of Characteristics ◽  
Mixed Finite Element ◽  
Three Dimensional ◽  
Optimal Error Estimate ◽  
Computational Domain ◽  
Time Step ◽  
Slightly Compressible ◽  
The Method Of Characteristics

A parallel algorithm is presented to solve three-dimensional slightly compressible seepage displacement where domain decomposition and characteristics-mixed finite element are combined. Decomposing the computational domain into several subdomains, we define a special function to approximate the derivative at interior boundary explicitly and obtain numerical solutions of the saturation implicitly on subdomains in parallel. The method of characteristics can confirm strong stability at the fronts, and can avoid numerical dispersion and nonphysical oscillation. It can adopt large-time step but can obtain small time truncation error. So a characteristic domain decomposition finite element scheme is put forward to compute the saturation. The flow equation is computed by the method of mixed finite element and numerical accuracy of Darcy velocity is improved one order. For a model problem we apply some techniques such as variation form, domain decomposition, the method of characteristics, the principle of energy, negative norm estimates, induction hypothesis, and the theory of priori estimates of differential equations to derive optimal error estimate in $l^2$ norm. Numerical example is given to testify theoretical analysis and numerical data show that this method is effective in solving actual applications. Then it can solve the well-known problem.

A domain decomposition method for the three-dimensional shallow water equations

1995 ◽  
Vol 3 (4-5) ◽  
pp. 307-325 ◽  
Author(s):  
E.D. de Goede ◽  
J. Groeneweg ◽  
K.H. Tan ◽  
M.J.A. Borsboom ◽  
G.S. Stelling
Keyword(s):  
Domain Decomposition ◽  
Shallow Water ◽  
Shallow Water Equations ◽  
Decomposition Method ◽  
Domain Decomposition Method ◽  
Three Dimensional

Implementation of 2D Domain Decomposition in the UCAN Gyrokinetic Particle-in-Cell Code and Resulting Performance of UCAN2

2016 ◽  
Vol 19 (1) ◽  
pp. 205-225 ◽  
Author(s):  
Jean-Noel G. Leboeuf ◽  
Viktor K. Decyk ◽  
David E. Newman ◽  
Raul Sanchez
Keyword(s):  
Domain Decomposition ◽  
Parallel Implementation ◽  
Three Dimensional ◽  
Massively Parallel ◽  
Problem Size ◽  
Time Step ◽  
Particle In Cell ◽  
Minor Radius ◽  
Efficient Charge ◽  
Cartesian Geometry

AbstractThe massively parallel, nonlinear, three-dimensional (3D), toroidal, electrostatic, gyrokinetic, particle-in-cell (PIC), Cartesian geometry UCAN code, with particle ions and adiabatic electrons, has been successfully exercised to identify non-diffusive transport characteristics in present day tokamak discharges. The limitation in applying UCAN to larger scale discharges is the 1D domain decomposition in the toroidal (or z-) direction for massively parallel implementation using MPI which has restricted the calculations to a few hundred ion Larmor radii or gyroradii per plasma minor radius. To exceed these sizes, we have implemented 2D domain decomposition in UCAN with the addition of the y-direction to the processor mix. This has been facilitated by use of relevant components in the P2LIB library of field and particle management routines developed for UCLA's UPIC Framework of conventional PIC codes. The gyro-averaging specific to gyrokinetic codes is simplified by the use of replicated arrays for efficient charge accumulation and force deposition. The 2D domain-decomposed UCAN2 code reproduces the original 1D domain nonlinear results within round-off. Benchmarks of UCAN2 on the Cray XC30 Edison at NERSC demonstrate ideal scaling when problem size is increased along with processor number up to the largest power of 2 available, namely 131,072 processors. These particle weak scaling benchmarks also indicate that the 1 nanosecond per particle per time step and 1 TFlops barriers are easily broken by UCAN2 with 1 billion particles or more and 2000 or more processors.

Parallel numerical simulation with domain decomposition for the fluid-filled drum crash

2008 ◽  
Vol 222 (3) ◽  
pp. 319-328 ◽  
Author(s):  
Z Li ◽  
X-L Jin ◽  
X-D Chen
Keyword(s):  
Domain Decomposition ◽  
Structural Dynamics ◽  
Dynamic Behaviour ◽  
Three Dimensional ◽  
Structural Domain ◽  
Arbitrary Lagrangian Eulerian ◽  
Structure Interaction ◽  
Ale Finite Element Method ◽  
Control Mesh ◽  
Critical Aspects

Fluid—structure interaction (FSI) problems simultaneously bring together some of the critical aspects associated with both fluid dynamics and structural dynamics. In this research, the simulation of the three-dimensional flexible fluid-filled drum in the crash is achieved through multi-material arbitrary Lagrangian-Eulerian (ALE) finite-element method because of its ability to control mesh geometry independently from geometry. The ALE description is adopted for the fluid domain, whereas for the structural domain the Lagrangian formulation is adopted. The computation of the FSI and the crash contact between the drum and the ground is realized by the penalty-based coupling method. Then the dynamic behaviour of the drum in the crash is analysed and the parallelism is discussed because the computation of the FSI and the crash contact is quite time-consuming. Based on domain decomposition, the recursive coordinate bisection (RCB) is improved according to the time-consuming characteristics of the fluid-filled container in the crash. The results indicate, in comparison with RCB method, the improved recursive coordinate bisection method has improved the speedup and the parallel efficiency.

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