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QUANTIFYING UNCERTAINTY: MODERN COMPUTATIONAL REPRESENTATION OF PROBABILITY AND APPLICATIONS

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Extreme Man-Made and Natural Hazards in Dynamics of Structures

Part of the book series: NATO Security through Science Series ((NASTC))

Abstract

Uncertainty estimation arises at least implicitly in any kind o f modelling of the real world. A recent development is to try and actually quantify the uncertainty in probabilistic terms. Here the emphasis is on uncertain systems, where the randomness is assumed spatial. Traditional computational approaches usually use some form of perturbation or Monte Carlo simulation. This is contrasted here with more recent methods based on stochastic Galerkin approximations. Also some approaches to an adaptive uncertainty quantification are pointed out.

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  1. Institute of Scientific Computing, Technische Universität Braunschweig, Brunswick, Germany

    Hermann G. Matthies

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  1. Ecole Normale Supérieure de Cachan, France

    Adnan Ibrahimbegovic

  2. University of Rijeka, Croatia

    Ivica Kozar

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Matthies, H.G. (2007). QUANTIFYING UNCERTAINTY: MODERN COMPUTATIONAL REPRESENTATION OF PROBABILITY AND APPLICATIONS. In: Ibrahimbegovic, A., Kozar, I. (eds) Extreme Man-Made and Natural Hazards in Dynamics of Structures. NATO Security through Science Series. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-5656-7_4

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