Yurko et al., 2015 - Google Patents
Demonstration of Emulator‐Based Bayesian Calibration of Safety Analysis Codes: Theory and FormulationYurko et al., 2015
View PDF- Document ID
- 4844838257980867674
- Author
- Yurko J
- Buongiorno J
- Youngblood R
- Publication year
- Publication venue
- Science and Technology of Nuclear Installations
External Links
Snippet
System codes for simulation of safety performance of nuclear plants may contain parameters whose values are not known very accurately. New information from tests or operating experience is incorporated into safety codes by a process known as calibration, which …
- 238000009472 formulation 0 title abstract description 11
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computer systems based on specific mathematical models
- G06N7/005—Probabilistic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Yates et al. | Cross validation for model selection: a review with examples from ecology | |
Wu et al. | Variational approach for learning Markov processes from time series data | |
Le Maître et al. | Spectral methods for uncertainty quantification: with applications to computational fluid dynamics | |
Oladyshkin et al. | Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion | |
Bruna et al. | Neural Galerkin schemes with active learning for high-dimensional evolution equations | |
Couckuyt et al. | Blind Kriging: Implementation and performance analysis | |
Gu | Jointly robust prior for Gaussian stochastic process in emulation, calibration and variable selection | |
Howard et al. | Learning to simulate high energy particle collisions from unlabeled data | |
Peremezhney et al. | Combining Gaussian processes, mutual information and a genetic algorithm for multi-target optimization of expensive-to-evaluate functions | |
Moon et al. | Amortized inference with user simulations | |
Yu et al. | Robust adaptive algorithm for nonlinear systems with unknown measurement noise and uncertain parameters by variational Bayesian inference | |
Klise et al. | Parmest: Parameter estimation via pyomo | |
Tabandeh et al. | Numerical solution of the Fokker–Planck equation using physics-based mixture models | |
Bacsa et al. | Symplectic encoders for physics-constrained variational dynamics inference | |
Bürkner et al. | A fully Bayesian sparse polynomial chaos expansion approach with joint priors on the coefficients and global selection of terms | |
Zhang et al. | A hybrid sequential sampling strategy for sparse polynomial chaos expansion based on compressive sampling and Bayesian experimental design | |
Yurko et al. | Demonstration of Emulator‐Based Bayesian Calibration of Safety Analysis Codes: Theory and Formulation | |
Strahan et al. | Inexact iterative numerical linear algebra for neural network-based spectral estimation and rare-event prediction | |
Wormell | Non-hyperbolicity at large scales of a high-dimensional chaotic system | |
Choi et al. | Estimation of structural reliability for Gaussian random fields | |
He et al. | Stationary-Sparse Causality Network Learning. | |
Ge et al. | Nonlinear quality prediction for multiphase batch processes | |
Uribe et al. | Bayesian inference with subset simulation in varying dimensions applied to the Karhunen–Loève expansion | |
Zhai et al. | Nonlinear variable selection algorithms for surrogate modeling | |
Chan et al. | Constructing a simulation surrogate with partially observed output |