Multi-modal reliability analysis of slope stability
- Reale, Cormac, Gavin, Kenneth, Prendergast, Luke, Xue, Jianfeng
- Authors: Reale, Cormac , Gavin, Kenneth , Prendergast, Luke , Xue, Jianfeng
- Date: 2016
- Type: Text , Conference proceedings
- Relation: 6th Transport Research Arena; Warsaw, Poland; 18th-21st April 2016; published inTransportation Research Procedia Vol. 14, p. 2468-2476
- Full Text:
- Reviewed:
- Description: 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.
- Authors: Reale, Cormac , Gavin, Kenneth , Prendergast, Luke , Xue, Jianfeng
- Date: 2016
- Type: Text , Conference proceedings
- Relation: 6th Transport Research Arena; Warsaw, Poland; 18th-21st April 2016; published inTransportation Research Procedia Vol. 14, p. 2468-2476
- Full Text:
- Reviewed:
- Description: 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.
System reliability of slopes using multimodal optimisation
- Reale, Cormac, Xue, Jianfeng, Gavin, Kenneth
- Authors: Reale, Cormac , Xue, Jianfeng , Gavin, Kenneth
- Date: 2016
- Type: Text , Journal article
- Relation: Geotechnique Vol. 66, no. 5 (2016), p. 413-423
- Full Text:
- Reviewed:
- Description: 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.
- Authors: Reale, Cormac , Xue, Jianfeng , Gavin, Kenneth
- Date: 2016
- Type: Text , Journal article
- Relation: Geotechnique Vol. 66, no. 5 (2016), p. 413-423
- Full Text:
- Reviewed:
- Description: 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.
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