Quantification of Uncertainty in Flow Simulations Using Probabilistic Methods

Gianluca Iaccarino

29 citations0/0 files stored

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Probabilistic and Robust Engineering Design Risk and Safety Analysis Nuclear Engineering Thermal-Hydraulics

Abstract

Abstract : In the last three decades, computer simulation tools have achieved wide spread use in the design and analysis of engineering devices. This has shortened the overall product design cycle and it has also provided bet- ter understanding of the operating behavior of the systems of interest. As a consequence numerical simulations have lead to a reduction of physical prototyping and to lower costs. In spite of this considerable success, it remains difficult to provide objec- tive confidence levels in quantitative information obtained from numerical predictions. The complexity arises from the amount of uncertainties related to the inputs of any computation attempting to represent a physical system. As a result, especially in the area of reliability and safety, physical testing remains the dominant mechanism of certification of new devices. Rigor- ous quantification of the errors and uncertainties1 introduced in numerical simulations is required to establish objectively their predictive capabilities.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 29 citations exist upstream.

References

1991Stochastic Finite Elements: A Spectral Approach 2002The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations 2003Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems 2006Measures of agreement between computation and experiment: Validation metrics 2007Sparse grid collocation schemes for stochastic natural convection problems 2006On the construction and analysis of stochastic models: Characterization and propagation of the errors associated with limited data 2002Investigation of Evidence Theory for Engineering Applications 2006Stochastic analysis of transport in tubes with rough walls

Cited by

2012Hydroelastic optimization of a keel fin of a sailing boat: a multidisciplinary robust formulation for ship design 2015Ensemble Kalman Filters and geometric characterization of sensitivity spaces for uncertainty quantification in optimization 2014Uncertainty quantification by geometric characterization of sensitivity spaces 2022Uncertainty quantification: data assimilation, propagation and validation of the numerical model of the Arade river cable-stayed bridge

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.