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Title: Parallel implementation and application of the random finite element method
Author: Nuttall, Jonathan David
ISNI:       0000 0004 2707 2557
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2011
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Geotechnical analyses have traditionally followed a deterministic approach in which materials are modelled using representative property values. An alternative approach is to take into account the spatial variation, or heterogeneity, existing in all geomaterials. In this approach the material property is represented by a mean and standard deviation and by a definition of the spatial correlation. This leads to a stochastic-type analysis resulting in reliability assessments.Random finite element methods (RFEM) have been implemented incorporating spatial variability for a series of models. This variability is incorporated using random fields, which conform to the mean, standard deviation and spatial correlation of the modelled geomaterials. For each material the set of statistical parameters produces an infinite number of possible random fields; therefore a Monte Carlo approach is followed, by executing the FE analysis for hundreds of realizations of the random field. This stochastic approach is both time and memory exhaustive computationally, limiting domain sizes and significantly increasing run-times. With the advances in commercial computational resources, the demand for more accurate and 3D models has increased, further straining the computational resources required by the method. To reduce these effects the stages of the method have been parallelized; initially the FE analysis, then the Monte Carlo framework and finally the random field generation. This has led to increases in the executable domain sizes and reductions in the run-times of the method. The new parallel codes have been used to analyse large-scale 3D slope reliability problems, which previously could not be undertaken in a serial environment. These computations have demonstrated the effectiveness of the new implementation, as well as adding confidence in the conclusions of previous research carried out on smaller 3D domains.
Supervisor: Craig, William ; Hicks, Michael Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available