Browsing by Author "Dithinde, Mahongo"

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    Characterisation of model uncertainty for reliability-based design of pile foundations
    (Stellenbosch : Stellenbosch University, 2007-12) Dithinde, Mahongo; De Wet, M.; Retief, J. V.; Phoon, K. K.; Stellenbosch University. Faculty of Engineering. Dept. of Civil Engineering.
    ENGLISH ABSTRACT: To keep pace with international trends, the introduction of geotechnical limit state design in South Africa is inevitable. To pave the way for implementation of limit state pile design in the country, the study quantifies model uncertainty in the classic static pile design formula under the Southern African geologic environment. The generated model uncertainty statistics are used to calibrate partial resistance factors in a reliability-based design framework. A series of pile performance predictions by the static formula are compared with measured performances. To capture the distinct soil types for the geologic region of Southern Africa as well as the local pile design and construction experience base, pile load tests and associated geotechnical data from the Southern African geologic environment are used. The methodology of collecting, compiling, and analyzing the pile load tests to derive the measured ultimate pile capacities is described. To facilitate the computation of the theoretical capacities, the site specific geotechnical data in the database are transformed to the desired engineering soil properties through well established empirical correlations. For a given pile test case, model uncertainty is presented in terms of a model factor computed as the ratio of the measured to the theoretical capacity, leading to n realisations of the model factor. To facilitate further interpretation and generalisation of the model factor realisation data, statistical analysis is carried out. The statistical analysis comprises of graphical representation by histograms, outliers detection and correction of erroneous values, and using the corrected data to compute the sample moments (mean, standard deviations, skewness and kurtosis) needed in reliability analysis. The analyses demonstrate that driven piles depict higher variability compared to bored piles irrespective of materials type. Furthermore, for a given pile installation method (driven or bored) the variability in non-cohesive materials is higher than that in cohesive materials. In addition to the above statistics, reliability analysis requires the theoretical probability distribution for the random variable under consideration. Accordingly it is demonstrated that the lognormal distribution is the most appropriate theoretical model for the model factor. Another key basis for reliability theory is the notion of randomness of the basic variables. To verify that the variation in the model factor is not explainable by deterministic variations in the database, an investigation of correlation of the model factor with underlying pile design parameters is carried out. It is shown that such correlation is generally weak. Correlation can have a significant impact on the calculated reliability index if not accounted for. Accordingly, the effects of the exhibited correlation is investigated through an approach based on regression theory in which systematic effects of design parameters are taken into account (generalised model factor). The model factor statistics from the conventional approach and those from the generalised model factor approach are used to determine reliability indexes implied by the current design practice. It is demonstrated that no significant improvement in values of the reliability indexes is gained by taking into account the effects of the weak correlation. The model factor statistics derived on the basis of the standard model factor approach are used to calibrate resistance factors. Four first order reliability methods are employed for the calibration of resistance factors. These include; the Mean Value First-Order Second Moment approach, an Approximate Mean Value First-Order Second Moment approach, the Advanced First-Order Second Moment approach using Excel spreadsheet, and the Advanced First-Order Second Moment approach (design point method). The resistance factors from the various calibration methods are presented for the target reliability index values of 2.0, 2.5, and 3.0. The analyses of the results demonstrate that for a given target reliability index, the resistance factors from the different methods are comparable. Furthermore, it is shown that for a given material type, the resistance factors are quite close irrespective of the pile installation method, suggesting differentiation of partial factors in terms of materials types only. Finally, resistance factors for use in probabilistic limit state pile design in South Africa are recommended.
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    Resistance model uncertainty factors for ultimate limit state design of pile foundations
    (South African Institution of Civil Engineering, 2014-08) Dithinde, Mahongo; Retief, Johan V.
    ENGLISH ABSTRACT: The current limit state design procedure for pile foundations presented in geotechnical codes (e.g. SANS 10160-5, EN 1997-1) stipulates that, when the pile capacity is determined using an analytical approach, such as the static analysis using engineering properties of the soil as determined from laboratory or in-situ field testing, the prescribed partial resistance factors (γr) need to be corrected by a partial factor for the uncertainty in the resistance model (γR, d) or the resistance model uncertainty factor. The international position is to derive model uncertainty factors for both actions and resistances from available experimental data. Accordingly this paper makes use of a local pile load test database to derive the appropriate γR, d values for ultimate limit state design of pile foundations. The analysis indicates that γR, d values of 1.3 and 1.5 for piles in cohesive and non-cohesive materials respectively are appropriate. Alternatively, a single value of γR, d = 1.4 for all piles in all soils can be adopted with different γr values for the two distinctive pile classes of piles in cohesive and non-cohesive soils.