Linear static analysis of large structural models on pc clusters

Download

index.pdf

Date

2009

Author

Özmen, Semih

Metadata

Show full item record

Item Usage Stats

239
views

122
downloads

This research focuses on implementing and improving a parallel solution framework for the linear static analysis of large structural models on PC clusters. The framework consists of two separate programs where the first one is responsible from preparing data for the parallel solution that involves partitioning, workload balancing, and equation numbering. The second program is a fully parallel nite element program that utilizes substructure based solution approach with direct solvers. The first step of data preparation is partitioning the structure into substructures. After creating the initial substructures, the estimated imbalance of the substructures is adjusted by iteratively transferring nodes from the slower substructures to the faster ones. Once the final substructures are created, the solution phase is initiated. Each processor assembles its substructure's stiffness matrix and condenses it to the interfaces. The interface equations are then solved in parallel with a block-cyclic dense matrix solver. After computing the interface unknowns, each processor calculates the internal displacements and element stresses or forces. Comparative tests were done to demonstrate the performance of the solution framework.

Subject Keywords

Civil engineering.

URI

http://etd.lib.metu.edu.tr/upload/2/12610763/index.pdf
https://hdl.handle.net/11511/18612

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Optimal load and resistance factor design of geometrically nonlinear steel space frames via tabu search and genetic algorithm DEĞERTEKİN, SADIK ÖZGÜR; Saka, M. P.; HAYALİOĞLU, MEHMET SEDAT (Elsevier BV, 2008-01-01) In this paper, algorithms are presented for the optimum design of geometrically nonlinear steel space frames using tabu search and genetic algorithm. Tabu search utilizes the features of short-term memory facility (tabu list) and aspiration criteria. Genetic algorithm employs reproduction, crossover and mutation operators. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange...
Dynamic characteristics and performance assessment of reinforced concrete structural walls Kazaz, İlker; Gülkan, Polat; Department of Civil Engineering (2010) The analytical tools used in displacement based design and assessment procedures require accurate strain limits to define the performance levels. Additionally, recently proposed changes to modeling and acceptance criteria in seismic regulations for both flexure and shear dominated reinforced concrete structural walls proves that a comprehensive study is required for improved limit state definitions and their corresponding values. This is due to limitations in the experimental setups, such that most previous...
Numerical integration of a class of 3d plastic-damage concrete models and condensation of 3d stress-strain relations for use in beam finite elements Sarıtaş, Afşin (Elsevier BV, 2009-10-01) This paper presents a method for the integration of a class of plastic-damage material models. The integration of the evolution equations results in a nonlinear problem, which is linearized and solved with the Newton-Raphson method using a sub-stepping strategy. The consistent tangent matrix can be formulated either in terms of the stress components in a general reference system or in terms of the principal stress and strain components with the former then transformed to the general reference system. In ord...
Optimization of water distribution networks using genetic algorithm Güç, Gerçek; Merzi, Nuri; Department of Civil Engineering (2006) This study gives a description about the development of a computer model, RealPipe, which relates genetic algorithm (GA) to the well known problem of least-cost design of water distribution network. GA methodology is an evolutionary process, basically imitating evolution process of nature. GA is essentially an efficient search method basically for nonlinear optimization cases. The genetic operations take place within the population of chromosomes. By means of various operators, the genetic knowledge in chro...
Discrete Sizing of Steel Frames Using Adaptive Dimensional Search Algorithm Hasançebi, Oğuzhan (Periodica Polytechnica Budapest University of Technology and Economics, 2019-01-01) Adaptive dimensional search (ADS) algorithm is a recently proposed metaheuristic optimization technique for discrete structural optimization problems. In this study, discrete sizing optimization problem of steel frames is tackled using the ADS algorithm. An important feature of the algorithm is that it does not use any metaphor as an underlying principle for its implementation. Instead, the algorithm employs an efficient performance-oriented methodology at each iteration for convergence to the optimum or a ...

Citation Formats

S. Özmen, “Linear static analysis of large structural models on pc clusters,” M.S. - Master of Science, Middle East Technical University, 2009.