Uncertainty Quantification Spectral Technique for the Stochastic Point Reactor with Random Parameters
نویسندگان
چکیده
منابع مشابه
Polynomial regression with derivative information in nuclear reactor uncertainty quantification
We introduce a novel technique of uncertainty quantification using polynomial regression with derivative information and apply it to analyze the performance of a model of a sodium-cooled fast reactor. We construct a surrogate model as a goal-oriented projection onto an incomplete space of polynomials, find coordinates of projection by collocation, and use derivative information to reduce the nu...
متن کاملSparse multiresolution stochastic approximation for uncertainty quantification
Most physical systems are inevitably affected by uncertainties due to natural variabili-ties or incomplete knowledge about their governing laws. To achieve predictive computer simulations of such systems, a major task is, therefore, to study the impact of these uncertainties on response quantities of interest. Within the probabilistic framework, uncertainties may be represented in the form of r...
متن کاملStochastic Polynomial Interpolation for Uncertainty Quantification With Computer Experiments
Abstract: Multivariate polynomial metamodels are widely used for uncertainty quantification due to the development of polynomial chaos methods and stochastic collocation. However, these metamodels only provide point predictions. There is no known method that can quantify interpolation error probabilistically and design interpolation points using available data to reduce the error. We shall intr...
متن کاملUncertainty quantification of silicon photonic devices with correlated and non-Gaussian random parameters.
Process variations can significantly degrade device performance and chip yield in silicon photonics. In order to reduce the design and production costs, it is highly desirable to predict the statistical behavior of a device before the final fabrication. Monte Carlo is the mainstream computational technique used to estimate the uncertainties caused by process variations. However, it is very ofte...
متن کاملUncertainty Quantification for Stochastic Subspace Identification of Multi-Setup Measurements
In Operational Modal Analysis, the modal parameters (natural frequencies, damping ratios and mode shapes) obtained from Stochastic Subspace Identification (SSI) of a structure, are afflicted with statistical uncertainty. For evaluating the quality of the obtained results it is essential to know the appropriate confidence intervals of these figures. In this paper we present algorithms that autom...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Energies
سال: 2020
ISSN: 1996-1073
DOI: 10.3390/en13061297