Ideas underlying quantification of margins and             uncertainties(QMU):  a white paper.

Helton, Jon C.; Trucano, Timothy Guy; Pilch, M.

doi:10.2172/891369

Cited by 9 publications

(1 citation statement)

References 51 publications

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“…The concept of the QMU methodology was first proposed in 2003 for the safety assessment and decision-making process of nuclear weapons stockpile under the limited number of test data [31]. The main components such as performance gates, margins, and uncertainties [32], conceptual and computational basis [33] of the QMU methodology had been illustrated. Recently, there has been many discussions of the QMU application in many engineering problems such as radiative shock system [34], radioactive waste disposal [35], satellite power system evaluation [36], and missile reliability [37].…”

Section: Introductionmentioning

confidence: 99%

A Two-Phase Monte Carlo Simulation/Non-Intrusive Polynomial Chaos (MSC/NIPC) Method for Quantification of Margins and Mixed Uncertainties (QMMU) in Flutter Analysis

Zhang

Yang

2020

IEEE Access

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A two-phase Monte Carlo Simulation/Non-intrusive Polynomial Chaos (MCS/NIPC) method for quantification of margins and mixed uncertainties (aleatory and epistemic uncertainties) is proposed in this paper for the flutter speed boundary analysis. Compared with the traditional MCS/MCS method which needs lots of numerical simulations, the MCS/NIPC method can reduce the computational cost without losing accuracy due to the use of point collocation non-intrusive polynomial chaos in the inner loop. Based on the results of uncertainty quantification, a novel practical quantification of margins and mixed uncertainties (QMMU) framework is proposed considering both aleatory and epistemic uncertainties such as the parametric uncertainties in complicated models. A two-dimensional airfoil and a three-dimensional benchmark wing, the AGARD 445.6 wing, are both employed to illustrate the practical application of the proposed methods for flutter speed computation in the presence of mixed uncertainties arising from the material properties and flight conditions. Within the analysis, aleatory and mixed uncertainty quantification are conducted to prove the effectiveness and efficiency of the MCS/NIPC method. Then the QMMU metrics are accomplished for the flutter speed boundary analysis of the two airfoil models. The results demonstrate the potential of the proposed QMMU framework to analyze the stability of engineering systems. INDEX TERMS Flutter, non-intrusive polynomial chaos, probability bounds, quantification of margins and mixed uncertainties, uncertainty quantification

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Section: Introductionmentioning

confidence: 99%

A Two-Phase Monte Carlo Simulation/Non-Intrusive Polynomial Chaos (MSC/NIPC) Method for Quantification of Margins and Mixed Uncertainties (QMMU) in Flutter Analysis

Zhang

Yang

2020

IEEE Access

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Nuclear Energy Advanced Modeling and Simulation (NEAMS) waste Integrated Performance and Safety Codes (IPSC) : gap analysis for high fidelity and performance assessment code development.

Lee¹,

Siegel²,

Argüello³

et al. 2011

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This report describes a gap analysis performed in the process of developing the Waste Integrated Performance and Safety Codes (IPSC) in support of the U.S. Department of Energy (DOE) Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Campaign. The goal of the Waste IPSC is to develop an integrated suite of computational modeling and simulation capabilities to quantitatively assess the long-term performance of waste forms in the engineered and geologic environments of a radioactive waste storage or disposal system. The Waste IPSC will provide this simulation capability (1) for a range of disposal concepts, waste form types, engineered repository designs, and geologic settings, (2) for a range of time scales and distances, (3) with appropriate consideration of the inherent uncertainties, and (4) in accordance with rigorous verification, validation, and software quality requirements.The gap analyses documented in this report were are performed during an initial gap analysis to identify candidate codes and tools to support the development and integration of the Waste IPSC, and during follow-on activities that delved into more detailed assessments of the various codes that were acquired, studied, and tested. The current Waste IPSC strategy is to acquire and integrate the necessary Waste IPSC capabilities wherever feasible, and develop only those capabilities that cannot be acquired or suitably integrated, verified, or validated.The gap analysis indicates that significant capabilities may already exist in the existing THC codes although there is no single code able to fully account for all physical and chemical iv processes involved in a waste disposal system. Large gaps exist in modeling chemical processes and their couplings with other processes. The coupling of chemical processes with flow transport and mechanical deformation remains challenging. The data for extreme environments (e.g., for elevated temperature and high ionic strength media) that are needed for repository modeling are severely lacking. In addition, most of existing reactive transport codes were developed for nonradioactive contaminants, and they need to be adapted to account for radionuclide decay and ingrowth. The accessibility to the source codes is generally limited. Because the problems of interest for the Waste IPSC are likely to result in relatively large computational models, a compact memory-usage footprint and a fast/robust solution procedure will be needed. A robust massively parallel processing (MPP) capability will also be required to provide reasonable turnaround times on the analyses that will be performed with the code.A performance assessment (PA) calculation for a waste disposal system generally requires a large number (hundreds to thousands) of model simulations to quantify the effect of model parameter uncertainties on the predicted repository performance. A set of codes for a PA calculation must be sufficiently robust and fast in terms of code execution. A PA system as a whole must be able to provide multi...

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Nuclear Energy Advanced Modeling and Simulation Waste Integrated Performance and Safety Codes (NEAMS Waste IPSC) verification and validation plan. version 1.

Bartlett¹,

Argüello²,

Urbina³

et al. 2011

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The objective of the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation Waste Integrated Performance and Safety Codes (NEAMS Waste IPSC) is to provide an integrated suite of computational modeling and simulation (M&S) capabilities to quantitatively assess the long-term performance of waste forms in the engineered and geologic environments of a radioactive-waste storage facility or disposal repository. To meet this objective, NEAMS Waste IPSC M&S capabilities will be applied to challenging spatial domains, temporal domains, multiphysics couplings, and multiscale couplings. A strategic verification and validation (V&V) goal is to establish evidence-based metrics for the level of confidence in M&S codes and capabilities. Because it is economically impractical to apply the maximum V&V rigor to each and every M&S capability, M&S capabilities will be ranked for their impact on the performance assessments of various components of the repository systems. Those M&S capabilities with greater impact will require a greater level of confidence and a correspondingly greater investment in V&V. This report includes five major components: (1) a background summary of the NEAMS Waste IPSC to emphasize M&S challenges; (2) the conceptual foundation for verification, validation, and confidence assessment of NEAMS Waste IPSC M&S capabilities; (3) specifications for the planned verification, validation, and confidenceassessment practices; (4) specifications for the planned evidence information management system; and (5) a path forward for the incremental implementation of this V&V plan.

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Ideas underlying quantification of margins and uncertainties(QMU): a white paper.

Cited by 9 publications

References 51 publications

A Two-Phase Monte Carlo Simulation/Non-Intrusive Polynomial Chaos (MSC/NIPC) Method for Quantification of Margins and Mixed Uncertainties (QMMU) in Flutter Analysis

A Two-Phase Monte Carlo Simulation/Non-Intrusive Polynomial Chaos (MSC/NIPC) Method for Quantification of Margins and Mixed Uncertainties (QMMU) in Flutter Analysis

Nuclear Energy Advanced Modeling and Simulation (NEAMS) waste Integrated Performance and Safety Codes (IPSC) : gap analysis for high fidelity and performance assessment code development.

Nuclear Energy Advanced Modeling and Simulation Waste Integrated Performance and Safety Codes (NEAMS Waste IPSC) verification and validation plan. version 1.

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