Read Propagation of aleatory and epistemic uncertainties in the model for the design of a flood protection dike - Pedroni, Nicola; Zio, Enrico; Ferrario, Elisa; Pasanisi, Alberto; Couplet, Mathieu | PDF
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Has been utilized in this article for the uncertainty propagation of atmospheric dis- 2003) is a method that combines aleatory and epistemic uncertainties.
Feb 4, 2021 problem of epistemic-aleatory mixed uncertainty propagation in product storage performance model with time degradation factor was discussed.
Epistemic uncertainty, with aleatory uncertainty deriving from an inherent randomness in the behavior of the system under study and epistemic uncertainty deriving from a lack of knowledge about the appropriate values to use for quantities that are assumed to have fixed but poorly known values in the context of a specific study.
Flowchart showing the procedure of propagating mixed aleatory-epistemic. Uncertainty with second-order probability and quadrature-based nipc.
Separation of aleatory and epistemic uncertainties in probabilistic to epistemic) but also the way in which the uncertainties are propagated to the final results.
Home archives volume 80 number 12 an approach to deal with aleatory and epistemic uncertainty within the same framework: case study in risk assessment call for paper - august 2020 edition.
And probability-boxes (p-boxes), which describe a mix of aleatory and epistemic uncertainty. In particu-lar, parametric p-boxes allow for separation of the latter uncertainties in the input space. The introduction of an augmented input space in pce leads to a new uncertainty propagation algorithm for p-boxes.
Epistemic and aleatory uncertainty incorporation in natural language was anticipated and empirically validated (teigen and fox, üklümen and malle as cited in fox and ülkümen (2011)). For example, phrases “i am 70% sure that” and “i think there is a 75% change that” express epistemic and aleatory uncertainty respectively.
Abstract: when ignorance due to the lack of knowledge, modeled as epistemic uncertainty using dempster-shafer structures on closed intervals, is present in the model parameters, a new uncertainty propagation method is necessary to propagate both aleatory and epistemic uncertainty.
Double probabilistic settings representing separate aleatory/epistemic components. The central step c/c' - propagation and sensitivity analysis processes.
May 16, 2009 herein, a random set, a generalization of a random variable is employed to formalize expert knowledge, and fuzzy sets are used to propagate this.
When some model parameters are affected by aleatory uncertainty and other some parameters are affected by epistemic uncertainty, how far computation of the risk is concern, one can either transform all the uncertainties to one type of format or need for joint propagation of uncertainties.
Of recognition in the existence of epistemic uncertainty and aleatory variability, and framework is developed that gives a protocol for correctly propagating.
Design optimization under aleatory uncertainty is a well-researched topic in the literature. However, when epistemic uncertainty is considered, the existing methods address only parts of the entire problem scope. This paper considers epistemic uncertainty due to both data sources and model errors.
In this case, the intensive calculation required to propagate epistemic and aleatory uncertainty in two-loop approaches with usual monte carlo sampling makes.
On representation and propagation of aleatory and epistemic uncertainty. June 2014; on numerical representation of aleatory and epistemic uncertainty hans schjær-jacobsen.
Therefore, the contribution of this paper is to develop and illustrate approaches for the propagation aleatory and epistemic uncertainty due to sparse data, using probabilistic methods of uncertainty propagation.
In this paper, mixed aleatory/epistemic uncertainties in a robust design problem are propagated via the use of box-constrained optimizations and surrogate.
Mar 12, 2021 since uncertainty propagation for probabilistic validation is often unaffordable for complex computational models, surrogate models are often.
Aleatory uncertainty and other some parameters are affected by epistemic uncertainty, how far computation of the risk is concern, one can either transform all the uncertainties to one type of format or need for joint propagation of uncertainties. In this paper, an effort has been made to combine probability.
As we mentioned earlier, both aleatory and epistemic uncertainties can be described using probability theory. So, one of the first steps of predictive modeling is to come up with probability statementes for all uncertain variables.
Correlation of the epistemic uncertainty in the exceedance probability at different intensity levels. Three methods of various complexity and input requirements for the propagation of seismic hazard epistemic uncertainty to other seismic performance measures are compared and contrasted using an example of the collapse risk of a structure.
Combinations of aleatory and epistemic uncertainty forms through arithmetic alternative methods to propagate hybrid mixtures of uncertainty through.
Mar 4, 2011 incorporate separate methods for aleatoric uncertainty propagation, epistemic uncertainty quantification, and numerical error estimation.
This talk will present three approaches used in propagation of epistemic uncertainty: interval analysis, dempster-shafer evidence theory, and probability theory. The talk will present both sampling methods and optimization methods that can be used in these calculations as well as surrogate models.
Propagation of aleatory and epistemic uncertainties in the model for the design of a flood protection dike nicola pedronia*, enrico zioa,b,c, elisa ferrariob, alberto pasanisid, mathieu coupletd a politecnico di milano, milano, italy b école centrale paris, chatenay malabry, france c supélec, gif-sur-yvette, france d electricité de france.
Uncertainty propagation, epistemic uncertainty, aleatory uncertainty, udr, pce, fosm, evidence theory. Several uncertainty propagation algorithms are available in literature: (i) monte-carlo simulations based on response surfaces, (ii) approximate uncertainty propagation algo-rithms and (iii) non probabilistic algorithms.
Leonard peikoff discusses aristotle's observation-based epistemology and explains his approach to concept formation, induction, definition and scientific.
• epistemic characterization for overall system (“ propagation”).
An important issue in risk analysis is the distinction between epistemic and aleatory uncertainties. In this paper, the use of distinct representation formats for aleatory and epistemic uncertainties is advocated, the latter being modelled by sets of possible values.
In this paper, we use probability distributions to represent aleatory uncertainty and possibility distributions to describe the epistemic uncertainty associated to the poorly known parameters of such probability distributions. A hybrid method is used to hierarchically propagate the two types of uncertainty.
Dempster-shafer theory of evidence finally, we have one way which is generally used to propagate uncertainty in combined analysis, where we are propagating both aleatory and epistemic uncertainty.
Aleatory variability is determined in the context of the models and is based on the parameterization used in the model. With this approach, a model that only uses distance for the wave propagation will include the variability due to different wave propagation effects as part of the aleatory variability even though it is potentially knowable.
In this paper we propose a strategy based on line sampling to propagate both aleatory and epistemic uncertainty through black-box codes to obtain interval.
In this lesson, we'll consider the impact of injustice on one's knowledge about the world.
Uncertainty propagation where the outer loop samples the epistemic uncertainties and for each realization, an inner loop samples and propagates the aleatory.
As a result, the prediction as the simulation output is inherently imprecise. When macroscopic quantities as statistical ensembles are of our interest, the output is also inaccurate. Therefore, the simulation output contains both epistemic and aleatory uncertainties.
Evidence and probability theories to propagate aleatory and epistemic uncertainty types for tolerance analysis.
1 key features of epistemic and aleatory uncertainty availability impose a constraint on the analysis depth; uncertainty propagation.
May 25, 2014 epistemic: uncertainty due to gaps in knowledge aleatory: uncertainty due to variability or randomness [like throwing dice or flipping a coin].
Influence is evident in the spread of bayesian methods throughout able representation of uncertainty, whether aleatory or epistemic, is probability.
Uncertainty quantification (uq) is the process of determining the effect of input uncertainties on response metrics of interest. These input uncertainties may be characterized as either aleatory uncertainties, which are irreducible variabilities inherent in nature, or epistemic uncertainties, which are reducible uncertainties resulting from a lack of knowledge.
When ignorance due to the lack of knowledge, modeled as epistemic uncertainty using dempster-shafer structures on closed intervals, is present in the model parameters, a new uncertainty propagation method is necessary to propagate both aleatory and epistemic uncertainty. The new framework proposed here, combines both epistemic and aleatory uncertainty into a second-order uncertainty.
Both probabilistic and non-probabilistic methods for representation and propagation of aleatory and epistemic uncertainties, model calibration, and to develop.
Representation and propagation of aleatory and epistemic uncertainties in this section, we first recall basics about probability and possibility theories, the former being used to represent.
Hybrid uncertain problem, in which the aleatory and epistemic uncertainties both uncertainty modeling, uncertainty propagation analysis, structural reliability.
Of methods that are used for analyzing and propagating aleatory and epistemic uncertainties in engineering models.
Els, different calculation methods are required to propagate aleatory and epistemic uncertainty. However, the segrega-tion of both types of uncertainty during propagation, as well as the accurate propagation of either one of them are two challenges in creating a method to propagate both epistemic and aleatory uncertainty.
Propagation of aleatory and epistemic uncertainties in the mode l for the design of a flood protection dike nicola pedroni.
In a multidisciplinary design system, uncertainty propagation refers to the analysis that quantifies the overall uncertainty of system qois resulting from all sources of aleatory and epistemic uncertainty originating in the individual disciplines.
For epistemic uncertainties, probability-box, dempster-shafer evidence theory or fuzzy theory are all available methods to reflect the lack-of-knowledge. Since probability represents the degree of belief in the bayesian paradigm, bayesian analysis can easily handle both aleatory and epistemic uncertainties.
Affected by aleatory distribution functions (pdfs) with fuzzy interval analysis on uncertainty and some others are affected by epistemic uncertainty. In this paper we propose a hybrid method to deal with propagation of both kinds of uncertainty within the same computation of risk.
Couplet, propagation of aleatory and epistemic uncertainties in the model for the design of a flood protection dike, in psam 11 and esrel (helsinki, finland, 2012) google scholar.
Dakota provides a variety of methods for propagating both aleatory and epistemic uncertainty. At a high level, uncertainty quantification (uq) or nondeterministic analysis is the process of characterizing input uncertainties, forward propagating these uncertainties through a computational model, and performing statistical or interval assessments on the resulting responses.
Potential system uncertainties are then categorized using aleatory and epistemic uncertainties. As a result, both the time-varying and epistemic randomness can be characterized. Finally, the stochastic behavior of the harmonic propagation and amplification is studied using the monte carlo simulation technique.
May 28, 2018 the uncertainties consist of aleatory and epistemic uncertainties in uncertainty propagation characteristic, and failure physical process.
Propagation sensitivity analysis 4 uncertainties are characterized, propagated and analysed, epistemic and aleatory uncertainty quantification of a grid-connected.
Epistemic uncertainties are reducible through increased understanding (research), or increased data, or through more relevant data. Epistemic uncertainties are characterized degrees of “belief” and should not be given a frequensic interpretation. Currently, the following methods are commonly used to characterize and propagate aleatory.
Jun 6, 2012 in this study, we make a first attempt to identify, model, and jointly propagate aleatory and epistemic uncertainties in the context of dg systems.
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