Random sets of probability measures in slope hydrology and stability analysis

Rubio, E.; Anderson, M. G.

doi:10.1002/zamm.200410146

Cited by 25 publications

(17 citation statements)

References 32 publications

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“…Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | oratory measurements of parameters such as cohesion and coefficient of friction but the resulting values may not be directly applicable at the large scale because of the effects of spatial heterogeneities, and additional factors such as root strength (Christian et al, 1994;Rubio et al, 2004;Hall et al, 2004;Hencher, 2010). Although spatial variability of soil properties has been recognised as an important source of epistemic 5 uncertainty in the literature (e.g.…”

Section: Discussionmentioning

confidence: 99%

Epistemic uncertainties and natural hazard risk assessment – Part 2: Different natural hazard areas

Beven

Almeida

Aspinall

et al. 2016

Preprint

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This paper discusses how epistemic uncertainties are considered in a number of different natural hazard areas including floods, landslides and debris flows, dam safety, droughts, earthquakes, tsunamis, volcanic ash clouds and pyroclastic flows, and wind storms. In each case it is common practice to treat most uncertainties in the form of 5 aleatory probability distributions but this may lead to an underestimation of the resulting uncertainties in assessing the hazard, consequences and risk. It is suggested that such analyses might be usefully extended by looking at different scenarios of assumptions about sources of epistemic uncertainty, with a view to reducing the element of surprise in future hazard occurrences. Since every analysis is necessarily conditional 10 on the assumptions made about the nature of sources of epistemic uncertainty it is also important to follow the guidelines for good practice suggested in the companion Part 1 by setting out those assumptions in a condition tree.

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Section: Discussionmentioning

confidence: 99%

Epistemic uncertainties and natural hazard risk assessment – Part 2: Different natural hazard areas

Beven

Almeida

Aspinall

et al. 2016

Preprint

View full text Add to dashboard Cite

show abstract

“…Parameter variability is often assessed by making small scale laboratory measurements of parameters such as cohesion and coefficient of friction but the resulting values may not be 10 directly applicable at the large scale because of the effects of spatial heterogeneities, and additional factors such as root strength (Christian et al, 1994;Rubio et al, 2004;Hall et al, 2004;Hürlimann et al, 2008;Hencher, 2010). Although spatial variability of soil properties has been recognised as an important source of epistemic uncertainty in the literature (e.g.…”

Section: Uncertainty Quantification In Landslide Hazard Estimationmentioning

confidence: 99%

Epistemic uncertainties and natural hazard risk assessment. 1. A review of different natural hazard areas

Beven¹,

Almeida²,

Aspinall³

et al. 2017

Preprint

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This paper discusses how epistemic uncertainties are considered in a number of different natural hazard areas including floods, landslides and debris flows, dam safety, droughts, earthquakes, tsunamis, volcanic ash clouds and pyroclastic flows, and wind storms. In each case it is common practice to treat most uncertainties in the form of aleatory 20 probability distributions but this may lead to an underestimation of the resulting uncertainties in assessing the hazard, consequences and risk. It is suggested that such analyses might be usefully extended by looking at different scenarios of assumptions about sources of epistemic uncertainty, with a view to reducing the element of surprise in future hazard occurrences. Since every analysis is necessarily conditional on the assumptions made about the nature of sources of epistemic uncertainty it is also important to follow the guidelines for good practice suggested in the companion Part 2. 25

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“…Discussions and engineering applications are provided in the context of sets of probability measures to derive lower and upper probabilities of events [140]. The elds of application include, for instance, structural optimization [141], reliability assessment [99], and geotechnical stability investigations [142].…”

Section: Evidence Theorymentioning

confidence: 99%

Imprecise probabilities in engineering analyses

Beer

Ferson

Kreinovich

2013

Mechanical Systems and Signal Processing

384

193

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Probabilistic uncertainty and imprecision in structural parameters and in environmental conditions and loads are challenging phenomena in engineering analyses. They require appropriate mathematical modeling and quantication to obtain realistic results when predicting the behavior and reliability of engineering structures and systems. But the modeling and quantication is complicated by the characteristics of the available information, which involves, for example, sparse data, poor measurements and subjective information. This raises the question whether the available information is sucient for probabilistic modeling or rather suggests a set-theoretical approach. The framework of imprecise probabilities provides a mathematical basis to deal with these problems which involve both probabilistic and non-probabilistic information. A common feature of the various concepts of imprecise probabilities is the consideration of an entire set of probabilistic models in one analysis. The theoretical dierences between the concepts mainly concern the mathematical description of the set of probabilistic models and the connection to the probabilistic models involved.This paper provides an overview on developments which involve imprecise probabilities for the solution of engineering problems. Evidence theory, probability bounds analysis with p-boxes, and fuzzy probabilities are discussed with emphasis on their key features and on their relationships to one another.

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Random sets of probability measures in slope hydrology and stability analysis

Cited by 25 publications

References 32 publications

Epistemic uncertainties and natural hazard risk assessment – Part 2: Different natural hazard areas

Epistemic uncertainties and natural hazard risk assessment – Part 2: Different natural hazard areas

Epistemic uncertainties and natural hazard risk assessment. 1. A review of different natural hazard areas

Imprecise probabilities in engineering analyses

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