Validation Challenge Workshop

Hills, R. G.; Pilch, M.; Dowding, Kevin J.; Red-Horse, John; Paez, Thomas L.; Babuška, Ivo; Tempone, Raúl

doi:10.1016/j.cma.2007.10.016

Cited by 37 publications

(10 citation statements)

References 15 publications

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“…The 2006 Validation Challenge Workshop posed problems with a hierarchical flow of information (i.e., materials level calibration, which informs validation at an "exploratory" level and "accreditation" level) [26][27][28][29][30]. The hierarchy is a visualization of how data and model predictions are used during multiple V&V analyses [31].…”

Section: A History Of Challenge Workhopsmentioning

confidence: 99%

Introduction: The 2014 Sandia Verification and Validation Challenge Workshop

Carnes

Romero

2016

Journal of Verification, Validation and Uncertainty Quantification

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Section: A History Of Challenge Workhopsmentioning

confidence: 99%

Introduction: The 2014 Sandia Verification and Validation Challenge Workshop

Carnes

Romero

2016

Journal of Verification, Validation and Uncertainty Quantification

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“…As the main case study, we consider a benchmark thermal problem presented at the 2006 Sandia Validation Challenge Workshop [30,37,57,58,124,134]. As the main case study, we consider a benchmark thermal problem presented at the 2006 Sandia Validation Challenge Workshop [30,37,57,58,124,134].…”

Section: How Accurate Is Prediction? Quantifying the Uncertainty Of Tmentioning

confidence: 99%

Algorithmic Aspects of Analysis, Prediction, and Control in Science and Engineering

Nava¹,

Kreinovich²

2015

Studies in Systems, Decision and Control

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The series "Studies in Systems, Decision and Control" (SSDC) covers both new developments and advances, as well as the state of the art, in the various areas of broadly perceived systems, decision making and control-quickly, up to date and with a high quality. The intent is to cover the theory, applications, and perspectives on the state of the art and future developments relevant to systems, decision making, control, complex processes and related areas, as embedded in the fields of engineering, computer science, physics, economics, social and life sciences, as well as the paradigms and methodologies behind them. The series contains monographs, textbooks, lecture notes and edited volumes in systems, decision making and control spanning the areas of Cyber-Physical SystemsSocial Systems, Economic Systems and other. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution and exposure which enable both a wide and rapid dissemination of research output.More information about this series at

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“…This is a large field encompassing stochastic equations and processes, inverse problems, frequency analysis and Bayesian statistics among others. For specific application to model validation, see for example [4,5,[8][9][10].…”

Section: Introductionmentioning

confidence: 99%

“…The reliability of the model belongs to the field of validation (for more on Verification and Validation, see e.g. [1,5,10,15,41]). …”

Section: Introductionmentioning

confidence: 99%

Numerical treatment of engineering problems with uncertainties. The fuzzy set approach and its application to the heat exchanger problem

Babuška

Silva

2010

Numerical Meth Engineering

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SUMMARYAn important part of predicting responses with computational models is the definition of systems parameters such as material properties. The reliability of model-based predictions depends on the quality of these data, and the knowledge of their uncertainties. When experiments cannot be performed to determine parameter values, they must be obtained from the literature, namely handbooks, standards, specification sheets, etc. This paper addresses the use of literature-based parameters and other information for assessing uncertainty in computational predictions. The uncertainties in the data and the solution (prediction) are described in the framework of fuzzy sets. A double-pipe heat exchanger thermal analysis problem is used to illustrate the difficulties with computational predictions when only informations from the literature are available. It is shown that the resulting uncertainties are significant and cannot be neglected.

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Validation Challenge Workshop

Cited by 37 publications

References 15 publications

Introduction: The 2014 Sandia Verification and Validation Challenge Workshop

Introduction: The 2014 Sandia Verification and Validation Challenge Workshop

Algorithmic Aspects of Analysis, Prediction, and Control in Science and Engineering

Numerical treatment of engineering problems with uncertainties. The fuzzy set approach and its application to the heat exchanger problem

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