Characterisation of model uncertainty for reliability-based design of pile foundations

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dc.contributor.advisor De Wet, M.
dc.contributor.advisor Retief, J. V.
dc.contributor.advisor Phoon, K.K.
dc.contributor.author Dithinde, Mahongo
dc.contributor.other Stellenbosch University. Faculty of Engineering. Dept. of Civil Engineering. en
dc.date.accessioned 2012-07-05T10:09:51Z
dc.date.available 2012-07-05T10:09:51Z
dc.date.issued 2007-12
dc.identifier.uri http://hdl.handle.net/10019.1/21612
dc.description Dissertation (PhD)--University of Stellenbosch, 2007. en_ZA
dc.description.abstract 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. en_ZA
dc.description.abstract AFRIKAANSE OPSOMMING: Ten einde in pas te bly met internasionale neigings, is dit onafwendbaar dat geotegniese limietstaat-ontwerp in Suid Afrika ingevoer word. Ter voorbereiding vir die plaaslike toepassing van limietstaatontwerp op heipale, kwantifiseer hierdie ondersoek onsekerheid rondom die model vir klassieke statiese heipaalontwerpformules in die Suid Afrikaanse geologiese omgewing. Die statistiek van modelonsekerheid wat gegenereer is, word gebruik om parsiële weerstandsfaktore in ’n betoubaarheid-gebasseerde ontwerpraamwerk te kalibreer. ’n Reeks voorspellings van die gedrag van heipale volgens die statiese formules word vergelyk met die gemete gedrag. Om die kenmerkende grond-tipes in die geologiese gebied van Suidelike Afrika sowel as die plaaslike ondervinding met heipaalontwerp en - konstruksie vas te lê, word heipaaltoetse en die gassosieerde geotegniese data vanuit hierdie geologiese omgewing gebruik. Die metodiek vir die versameling, saamstelling en analise van heipaaltoetse om uiterste kapasiteite daarvan te bepaal, word beskryf. Terreinspesifieke geotegniese data in die databasis word getransformeer na die vereisde ingenieurseienskappe volgens gevestigde empiriese korrelasies. Vir ’n gegewe heipaaltoets word modelonsekerheid weergegee in terme van ’n modelfaktor wat bereken word as die verhouding van die gemete tot die teoretiese kapasiteit waaruit n uitkomstes van die modelfaktor dus gegenereer word. Om verdere interpretasie en veralgemening van die modelfaktordata te vergemaklik, word ’n statistiese analise daarop uitgevoer. Die statistiese analise bestaan uit grafiese voorstellings deur middel van histogramme, uitkenning van uitskieters en verbetering van foutiewe waardes, waarna die statistiese momente (gemiddeld, standaardafwyking, skeefheid en kurtose) vir gebruik in betroubaarheidsanalise bereken word. Volgens die analises toon ingedrewe heipale ’n groter veranderlikheid as geboorde pale, ongeag die grondtipe. Verder is die veranderlikheid van heipale in kohesielose materiale hoër as in kohesiewe materiale, ongeag die installasiemetode (ingedrewe of geboor). Bykomend tot bogemelde statistiek, vereis betroubaarheidsanalise die teoretiese waarskynlikheidsdistribusie van die ewekansige veranderlike onder beskouing. Ooreenkomstig word illustreer dat die log-normale verspreiding die mees toepaslike verspreiding vir die modelfaktor is. ’n Verdere sleutelvereiste vir betroubaarheidsteorie is die mate van ewekansigheid van die basiese veranderlikes. Om te bepaal of die variasie in die modelfaktor nie deur deterministiese veranderlikes in die databasis verduidelik kan word nie, word ’n ondersoek na die korrelasie van die modelfaktor met onderliggende heipaalontwerpfaktore uitgevoer. Sodanige korrelasie is in die algemeen as laag bevind. Korrelasie kan ’n belangrike invloed op die berekende betroubaarheidsindeks hê indien dit nie in ag geneem word nie. Dienooreenkomstig word die effek van die getoonde korrelasie ondersoek met behulp van die metode van regressie-analise waarin sistematiese effekte van ontwerpparameters in berekening gebring word (veralgemeende modelfaktor). Die modelfaktorstatistiek wat volg uit die konvensionele benadering en dié van die veralgemeende benadering word gebruik om betroubaarheidsindekse te bepaal wat deur die bestaande ontwerppraktyk geïmpliseer word. Die bevinding is dat daar nie ’n noemenswaardige verbetering in die waardes van die betroubaarheidsindekse is wanneer die effek van die swak korrelasie in berekening gebring word nie. Die statistiek van die modelfaktor wat afgelei is volgens die standaardbenadering word gebruik om die weerstandsfaktore te kalibreer. Vier eerste-orde betroubaarheidsmetodes word gebruik om die weerstandsfaktore te kalibreer, naamlik die Gemiddelde Waarde Eerste-Orde Tweede Moment benadering, die Benaderde Gemiddelde Waarde Eerste-Orde Tweede Moment benadering, die Gevorderde Eerste-Orde Tweede Moment benadering waarin ’n Excel sigblad gebruik word en die Gevorderde Eerste-Orde Tweede Moment benadering (die ontwerppuntmetode). Die weerstandsfaktore vanaf die verskillende kalibrasiemetodes word weergegee vir waardes van 2.0, 2.5 en 3.0 van die teikenbetroubaarheidsindeks. ’n Ontleding van die resultate toon dat vir ’n gegewe teiken betroubaarheidsindeks die weerstandsfaktore vanaf die verskillende metodes vergelykbaar is. Verder word getoon dat vir ’n gegewe grondsoort, die weerstandsfaktore vir verskillende metodes van installasie van die heipaal nie veel verskil nie. Dit wil dus voorkom asof parsiële faktore in terme van die grondsoort uitgedruk kan word. Ten slotte word weerstandsfaktore vir gebruik in plastiese limietstaatontwerp van heipale in Suid Afrika aanbeveel. af
dc.format.extent xii, 314 leaves : ill.
dc.language.iso en_ZA en_ZA
dc.publisher Stellenbosch : Stellenbosch University
dc.subject Piling (Civil engineering) en_ZA
dc.subject Theses -- Civil engineering en_ZA
dc.subject Dissertations -- Civil engineering en_ZA
dc.title Characterisation of model uncertainty for reliability-based design of pile foundations en_ZA
dc.type Thesis en_ZA
dc.rights.holder Stellenbosch University en_ZA


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