scholarly journals High-Performance Simulation of Mold Filling Using Porous Media Method

2008 ◽  
Vol 2 (4) ◽  
pp. 247-252 ◽  
Author(s):  
Yasuhiro Maeda ◽  
◽  
Yukio Otsuka ◽  
Keyword(s):  
Porous Media ◽  
High Performance ◽  
Control Volume ◽  
Computation Time ◽  
Mold Filling ◽  
Performance Simulation ◽  
Speed Up ◽  
Analytical Accuracy ◽  
Filling Simulation ◽  
Porous Media Method

The need to speed up calculation and improve analytical accuracy of Casting CAE has grown with optimized casting planning and speeded-up product design. A finite difference method using regular grid of Cartesian coordinates is often used in simulating mold filling because it reduces memory requirements, computation time and easier grid generation. Its disadvantage is that shape expression becomes less precise so that casting slopes and curved surfaces are replaced to stair-step shape. The mold filling simulation developed using porous media method in this paper provides uses two control volume parameters -- porosity rate of grid volume and permeability of grid surface -- to maintain shape expression and analytical accuracy. Results used larger grids than conventionally have with almost the same accuracy as analysis with fine grids. It has also advantages saving on memory and computation time.

scholarly journals Numerical Simulation of Multiphase Multicomponent Flow in Porous Media: Efficiency Analysis of Newton-Based Method

Fluids ◽  
2021 ◽  
Vol 6 (10) ◽  
pp. 355
Author(s):  
Timur Imankulov ◽  
Danil Lebedev ◽  
Bazargul Matkerim ◽  
Beimbet Daribayev ◽  
Nurislam Kassymbek
Keyword(s):  
Porous Media ◽  
Linear Equations ◽  
Computation Time ◽  
Flow In Porous Media ◽  
Multicomponent Flow ◽  
Original Matrix ◽  
Sparsity Pattern ◽  
Speed Up ◽  
Systems Of Linear Equations ◽  
The One

Newton’s method has been widely used in simulation multiphase, multicomponent flow in porous media. In addition, to solve systems of linear equations in such problems, the generalized minimal residual method (GMRES) is often used. This paper analyzed the one-dimensional problem of multicomponent fluid flow in a porous medium and solved the system of the algebraic equation with the Newton-GMRES method. We calculated the linear equations with the GMRES, the GMRES with restarts after every m steps—GMRES (m) and preconditioned with Incomplete Lower-Upper factorization, where the factors L and U have the same sparsity pattern as the original matrix—the ILU(0)-GMRES algorithms, respectively, and compared the computation time and convergence. In the course of the research, the influence of the preconditioner and restarts of the GMRES (m) algorithm on the computation time was revealed; in particular, they were able to speed up the program.

scholarly journals FACE RECOGNITION SYSTEM FOR MACHINE READABLE TRAVEL DOCUMENTS

2014 ◽  
pp. 32-38
Author(s):  
Sergey Tulyakov ◽  
Rauf Kh. Sadykhov
Keyword(s):  
Face Recognition ◽  
High Performance ◽  
Computation Time ◽  
Recognition System ◽  
Detection And Identification ◽  
Face Recognition System ◽  
High Processing Speed ◽  
Speed Up ◽  
Machine Readable ◽  
High Processing

This paper presents an upright frontal face recognition system, aimed to recognize faces on machine readable travel documents (MRTD). The system is able to handle large image databases with high processing speed and low detection and identification errors. In order to achieve high accuracy eyes are detected in the most probable regions, which narrows search area and therefore reduces computation time. Recognition is performed with the use of eigenface approach. The paper introduces eigenface basis ranking measure, which is helpful in challenging task of creating the basis for recognition purposes. To speed up identification process we split the database into males and females using high - performance AdaBoost classifier. At the end of the paper the results of the tests in speed and accuracy are given.

scholarly journals AMIDE v2: High-Throughput Screening Based on AutoDock-GPU and Improved Workflow Leading to Better Performance and Reliability

2021 ◽  
Vol 22 (14) ◽  
pp. 7489
Author(s):  
Pierre Darme ◽  
Manuel Dauchez ◽  
Arnaud Renard ◽  
Laurence Voutquenne-Nazabadioko ◽  
Dominique Aubert ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
High Performance ◽  
Graphics Processing Unit ◽  
Target Identification ◽  
Computation Time ◽  
Processing Unit ◽  
Biological Target ◽  
Speed Up ◽  
Graphics Processing

Molecular docking is widely used in computed drug discovery and biological target identification, but getting fast results can be tedious and often requires supercomputing solutions. AMIDE stands for AutoMated Inverse Docking Engine. It was initially developed in 2014 to perform inverse docking on High Performance Computing. AMIDE version 2 brings substantial speed-up improvement by using AutoDock-GPU and by pulling a total revision of programming workflow, leading to better performances, easier use, bug corrections, parallelization improvements and PC/HPC compatibility. In addition to inverse docking, AMIDE is now an optimized tool capable of high throughput inverse screening. For instance, AMIDE version 2 allows acceleration of the docking up to 12.4 times for 100 runs of AutoDock compared to version 1, without significant changes in docking poses. The reverse docking of a ligand on 87 proteins takes only 23 min on 1 GPU (Graphics Processing Unit), while version 1 required 300 cores to reach the same execution time. Moreover, we have shown an exponential acceleration of the computation time as a function of the number of GPUs used, allowing a significant reduction of the duration of the inverse docking process on large datasets.

Speed Up of Lattice Gas Automata Simulation of Polymer Flow Using a Cluster System

2012 ◽  
Author(s):  
Muhammad Taufiq Fathaddina ◽  
Mariyamni Awang
Keyword(s):  
Porous Media ◽  
Parallel Programming ◽  
Lattice Gas ◽  
Computation Time ◽  
Cluster System ◽  
Polymer Flooding ◽  
Flow In Porous Media ◽  
Polymer Flow ◽  
Lattice Gas Automata ◽  
Speed Up

Prestasi banjiran polimer boleh dianggar daripada tingkah laku mikroskopik partikel polimer dalam pori–pori media berliang. Kaedah kekisi gas automata adalah suatu kaedah pemodelan yang telah digunakan oleh penyelidik–penyelidik untuk mengkaji kelakuan aliran pada skala pori. Ia juga boleh digunakan untuk menyelaku aliran polimer dalam media berliang untuk mengkaji interaksi antara batuan dengan polimer. Namun, masa penghitungan terlalu panjang, walaupun untuk sampel media yang panjangnya 5 cm. Dalam kajian ini, penghitungan selari menggunakan komputer berdiri sendiri and sistem gugusan disiasati dalam usaha untuk mengurangkan masa penghitungan pemodelan banjiran polimer menggunakan kekisi gas automata. Daripada hasil kajian, speedup yang berasaskan pengolahan selari didapati lebih daripada 3.75 kali ganda, untuk empat pemprosesan atau kurang. Perbezaan dalam anggaran kecekapan penyesaran dan penepuan antara pengaturcaraan berjujukan dengan pengaturcaraan selari adalah kurang daripada tiga peratus. Oleh itu, dapatlah disimpulkan bahawa pengaturcaraan selari telah berjaya digunakan untuk melajukan penghitungan banjiran polimer tanpa menyebabkan variasi yang bererti daripada hasil keputusan. Kata kunci: Pengiraan selari; kekisi gas automata; penyesaran polimer The performance of polymer flooding may be estimated from microscopic behaviour of polymer particles in the pores of porous media. Lattice gas automata method is a modelling method that has been used by researchers to study flow behaviour on a particle scale. It had been also used to simulate polymer flow in porous media for studying microscopic interactions between rock and polymer. However, the computation time was too lengthy for even a 5 cm long porous media sample. On this study, parallel computing using standalone computers and a cluster system was investigated in an effort to decrease the computation time of modelling polymer flooding using lattice gas automata. From the results, speedup due to parallel processing was greater than 3.75 times for four processors and less. Differences in the estimations of displacement efficiency and saturations between sequential and parallel programming were less then three percent. It was concluded that parallel programming was successfully used to speed up computations in polymer flooding without causing significant variations in the results. Key words: Parallel computation; lattice gas automata; polymer displacement

A cross-platform, high-performance SPH toolkit for image-based flow simulations on the pore scale of porous media

2021 ◽  
pp. 108059
Author(s):  
M. Osorno ◽  
M. Schirwon ◽  
N. Kijanski ◽  
R. Sivanesapillai ◽  
H. Steeb ◽  
...  
Keyword(s):  
Porous Media ◽  
High Performance ◽  
Pore Scale ◽  
Flow Simulations ◽  
Cross Platform
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