The API RP2A (RP2GEO) and ISO 19902 guidelines include four CPT-methods for calculating the axial capacity of piles in sands. The guidelines require that if newer methods are to be implemented in design, the same level of safety shall be documented for these methods as for existing methods. The designer is required to select an appropriate safety factor when using the newer design methods. The challenge lies in deciding which safety factor will ensure a consistent safety level for different soil conditions and pile dimensions. To evaluate the required material factor, the probability of failure was quantified in two case studies for piles designed with the API method and with the newer NGI, ICP and Fugro methods. A calibration of the required material factor for a target probability of failure of 10 -4 /yr was also performed. The results show that the annual reliability index and probability of failure vary with the axial pile capacity calculation method. The study provides a contribution to the discussion on the reliability of the API, the NGI, the ICP and the Fugro methods. The material factor needs to be associated with the characteristic soil parameters selected for design. A large number of case studies should be added to quantify the reliability and the required material factor for each pile capacity method. The findings on margin of safety and the definition of the characteristic shear strength have important implications for the design of piles offshore and can result in significant savings.

Known challenges exist with maximum (γdmax) and minimum (γdmin) dry unit weight measurements; the respective dry unit weight results depend very much on the method or standard used. A laboratory testing programme was completed to systematically determine and compare γdmax and γdmin values derived for six different sand types by using different methods. The tested sands contained a wide variety of mineralogical and fines contents. The γdmax and γdmin determinations were performed according to the following methods: British Standards Institution (BS) standards; American Society for Testing and Materials (ASTM) standards; Deutsches Institut für Normung (DIN) standards; Dansk Geoteknisk Forening (DGF) guidelines; Norwegian Geotechnical Institute (NGI), Geolabs, and Fugro proprietary methods. Differences in testing procedures, material requirements for testing, and the effects of soil degradation during testing introduce challenges and large differences in γdmax and γdmin values for each of the six sand types were observed. Therefore, it is concluded that there is a need for the development of new standards for a robust determination of γdmax and γdmin values. Specifically, a standard for determining γdmax is required to consistently obtain results at the upper bound of dry unit weight values for the likely range of sands — without crushing the sand grains.

To estimate the safety level associated with the axial capacity of a pile, one needs to know the bias and uncertainty in the calculations made the design method. This model uncertainty is usually obtained by comparing the predicted axial pile capacity with the measured axial pile capacity in reliable pile load tests. Model uncertainty can have a strong influence on the calculated annual probability of failure of a piled foundation, and thus on the estimation of the safety margin. This paper studies the model uncertainty for the API-method and the NGI, ICP, Fugro and UWA methods for predicting the axial pile capacity in clays and in sands. The study also shows that the selection of the parameter to quantify the uncertainty influences the values of the mean and standard deviation. A significant factor in the evaluation of model uncertainty is the reference database of pile load tests used to quantify the uncertainty. The paper suggests an approach for quantifying model uncertainty for pile calculation methods. There is a need to quantify specific uncertainties, such as the reduced capacity in low plasticity clays and pile diameters and lengths that become much larger than the dimensions used for the pile load tests in the reference database(s). The paper recommends that an international joint industry project be initiated to look into the databases of pile model tests and to establish a consensus on the reliable pile load tests, the soil characterization and the interpretation to be used for the evaluation of the model uncertainty. Introduction The model uncertainty in a calculation method is usually quantified in terms of a mean (or bias), a standard deviation (and/or coefficient of variation) and the probabilistic density distribution that best fits the data. For methods predicting the ultimate axial pile capacity, the model uncertainty is obtained by comparing the predicted axial pile capacity with the measured axial pile capacity in reliable pile load tests. A companion paper in the same session at OTC 2013 (1) demonstrated the importance of model uncertainty in the probabilistic calculation of axial pile capacity and probability of failure. The model uncertainty was especially significant in the probabilistic analyses of the axial pile capacity of piles in sand (1). The study of model uncertainty was undertaken as part of the design of pile foundations on jackets in the North Sea. The aim was to document compliance with governing regulations in terms of annual failure probability. This paper studies the model uncertainty for the API-method and four newer design methods. Table 1 lists the methods considered and the references for each method: the current API method, the pre 1987 API method, the NGI-05 method, the ICP-05 method, the Fugro 96/05 method and the UWA-05 method. These methods became of greater interest when API RP2A RP2GEO (2) and ISO 19902 (3) introduced them as alternative methods to the API method for the design of piles in sand.

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This paper presents the geohazard assessment for a proposed bridge across Bjørnafjorden in western Norway. The fjord is c. 5 km wide with a maximum depth of 550 m at the proposed bridge crossing. The main geohazards of concern are submarine slope instabilities. To identify locations of instability, their susceptibility to failure, and their potential runout distances, we performed the following analyses: (1) static and pseudo-static limit equilibrium analyses for the entire fjord crossing area; (2) 1D seismic slope stability sensitivity analyses for different slope angles and soil depths; (3) 2D static and pseudo-static finite element analyses for selected profiles; (4) back-analysis of a palaeolandslide; and (5) quasi-2D and quasi-3D landslide dynamic simulations calibrated using results from the back-analysis. The workflow progresses from simplified to more advanced analyses focusing on the most critical locations. The results show that the soils in many locations of the fjord are potentially unstable and could be the loci of landslides and debris flows. The evidence of numerous palaeosubmarine landslides identified on geophysical records reinforces this conclusion. However, the landslide triggers and timing are currently unknown. This paper demonstrates the need for comprehensive and multidisciplinary geohazard analyses for any infrastructure projects conducted in fjords.