Impact of geotechnical uncertainty on the preliminary design of monopiles supporting offshore wind turbines

The growing demand for clean renewable energy sources and the lack of suitable nearshore sites is moving the offshore wind industry toward developing larger wind turbines in deeper water locations further offshore. This is adding significant uncertainty to the geotechnical design of monopiles used as foundations for these systems. Soil testing becomes more challenging, rigid monopile behaviour is less certain, and design methods are being applied outside the bounds of the datasets from which they were originally derived. This paper examines the potential impact of certain elements of geotechnical uncertainty on monotonic load-displacement behaviour and design system natural frequency of an example monopile-supported offshore wind turbine (OWT). Geotechnical uncertainty is considered in terms of spatial variability in soil properties derived from Cone Penetration Tests (CPT), parameter transformation uncertainty using the rigidity index, and design choice for subgrade reaction modelling. Results suggest that spatial variability in CPT properties exhibits limited impact on design load-displacement characteristics of monopiles as vertical spatial variability tends to be averaged out in the process to develop discrete soil reaction-lateral displacement (p-y) models. This highlights a potential issue whereby localised variations in soil properties may not be captured in certain models. Spatial variability in CPT data has a noticeable effect on predicted system frequency responses of OWTs employing a subgrade reaction model approach, and the influence of subgrade reaction model choice is significant. The purpose of this paper is to investigate the effect of uncertainty in soil data, model transformation, and design model choice on resulting structural behaviour for a subset of available design approaches. It should be noted that significant further uncertainty exists and a wide variety of alternative models can be used by designers, so the results should be interpreted qualitatively

A multi-objective decision making model for risk-based maintenance scheduling of railway earthworks

Aged earthworks constitute a major proportion of European rail infrastructures, the re-placement and remediation of which poses a serious problem. Considering the scale of the networks involved, it is infeasible both in terms of track downtime and money to replace all of these assets. It is, therefore, imperative to develop a rational means of managing slope infrastructure to determine the best use of available resources and plan maintenance in order of criticality. To do so, it is necessary to not just consider the structural performance of the asset but also to consider the safety and security of its users, the socioeconomic impact of remediation/failure and the relative importance of the asset to the network. This paper addresses this by looking at maintenance planning on a network level using multi‐attribute utility theory (MAUT). MAUT is a methodology that allows one to balance the priorities of different objectives in a harmonious fashion allowing for a holistic means of ranking assets and, subsequently, a rational means of investing in maintenance. In this situation, three different attributes are considered when examining the utility of different maintenance options, namely availability (the user cost), economy (the financial implications) and structural reliability (the structural performance and subsequent safety of the structure). The main impact of this paper is to showcase that network maintenance planning can be carried out proactively in a manner that is balanced against the needs of the organization.Geo-engineerin

Developing correlations between the soil fines content and CPT results using neural networks

Knowledge of the fines content is necessary for all soil classification systems and an important factor in the evaluation of soil strength in liquefaction and seismic settlement analysis. This paper presents the application of cone penetration test, CPT data for estimating the soil fines content. The correlation can be used either as a first estimate of fines content (for example in the offshore environment) or to provide statistical information on the variation of fines content within a given area of interest (e.g. for a regional liquefaction study). The paper shows how field and laboratory test data were used with a neural network to correlate the CPT results and the fines content. Data from five site investigation locations across Northern Croatia were utilised. Verification of the approach is performed using field and lab test data from the Veliki vrh landslide.Geo-engineerin

System reliability of slopes using multimodal optimisation

Many engineered and natural slopes have complex geometries and are multi-layered. For these slopes traditional stability analyses will tend to predict critical failure surfaces in layers with the lowest mean strength. A move toward probabilistic analyses allows a designer to account for uncertainties with respect to input parameters that allow for a more complete understanding of risk. Railway slopes, which in some cases were built more than 150 years ago, form important assets on the European rail network. Many of these structures were built at slope angles significantly higher than those allowed in modern design codes. Depending on the local geotechnical conditions these slopes may be susceptible to deepseated failure; however, a significant number of failures each year occur as shallow translational slips that develop during periods of high rainfall. Thus, for a given slope, two potential failure mechanisms might exist with very similar probabilities of failure. In this paper a novel multimodal optimisation algorithm (‘Slips’) that is capable of detecting all feasible probabilistic slip surfaces simultaneously is presented. The system reliability analysis is applied using polar co-ordinates, as this approach has been shown to be less sensitive to local numerical instabilities, which can develop due to discontinuities on the limit state surface. The approach is applied to two example slopes where the complexity in terms of stratification and slope geometry is varied. In addition the methodology is validated using a real-life case study involving failure of a complex slope. © 2016 ICE Publishing. All rights reserved

Multi-modal reliability analysis of slope stability

Probabilistic slope stability analysis typically requires an optimisation technique to locate the most probable slip surface. However, for many slopes particularly those containing many different soil layers or benches several distinct critical slip surfaces may exist. Furthermore, in large slopes these critical slip surfaces may be located at significant distances from each other. In such circumstances, finding and rehabilitating the most probable failure surface is of little merit, as rehabilitating that surface does not improve the safety of the slope as a whole. Unfortunately, existing slip surface search techniques were developed to converge on one global minimum. Therefore, to implement such methods to evaluate the stability of a slope with multiple failure mechanisms requires the user to define probable slip locations prior to calculation. This requires extensive engineering experience and places undue responsibility on the engineer in question. This paper proposes the use of a locally informed particle swarm optimisation method which is able to simultaneously converge to multiple critical slip surfaces. This optimisation model when combined with a reliability analysis is able to define all areas of concern within a slope. A case study of a railway slope is presented which highlights the benefits of the model over single objective optimisation models. The approach is of particular benefit when evaluating the stability of large existing slopes with complicated stratigraphy as these slopes are likely to contain multiple viable slip surfaces. © 2016 The Authors

Using reliability theory to assess the stability and prolong the design life of existing engineered slopes

Modern engineered slopes are designed to exceed certain safety targets set out in design codes. This is in stark contrast to earthen infrastructure inherited from the 18th century which typically was constructed in a haphazard manner without design. This infrastructure seldom meets modern deterministic guidelines yet clearly exhibits some degree of safety, as a failure has not occurred in the intervening years. This paper highlights the use of reliability theory for evaluating the stability of existing engineered slopes. A comprehensive review of geotechnical uncertainty and existing reliability based techniques are outlined. Furthermore, the paper highlights the issue of finding the critical slip surface and gives a brief summary of the current state of the art. Finally a case study of an Irish railway embankment is presented and both a deterministic and reliability analysis is performed on it highlighting the benefits of probabilistic methods over traditional techniques

Fragility curves for rainfall-induced shallow landslides on transport networks

Many of the earthworks assets on rail transport networks were constructed in the 1800â s and have thus operated for periods far in excess of their expected service life. Incidences of failure, particularly shallow planar landslides are increasing, in part due to the effect of more intense and longer duration rainfall events. Network owners have difficulty in targeting scarce resources to reduce risk across networks. This paper proposes a methodology for developing fragility curves for rainfall induced landslides on transport networks. Fragility curves provide the probability of exceedance of different limit states for a given hazard considering a range of magnitudes. In this paper the vulnerability of slopes as expressed by a loss of performance, is quantified for rainfall events of various intensities and duration. The approach expands upon probabilistic slope stability analysis and provides a rational logical framework for considering how vulnerable a slope is to rainfall induced failure.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author