[go: up one dir, main page]

Glimm et al., 2004 - Google Patents

Statistical riemann problems and a composition law for errors in numerical solutions of shock physics problems

Glimm et al., 2004

View PS
Document ID
6152142381264375843
Author
Glimm J
Grove J
Kang Y
Lee T
Li X
Sharp D
Yu Y
Ye K
Zhao M
Publication year
Publication venue
SIAM Journal on Scientific Computing

External Links

Snippet

We seek error models for shock physics simulations that are robust and understandable. The purpose of this paper is to formulate and validate a composition law to estimate errors in the solutions of composite problems in terms of the errors from simpler ones. We illustrate …
Continue reading at ftp.ams.sunysb.edu (PS) (other versions)

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
    • G06F17/5018—Computer-aided design using simulation using finite difference methods or finite element methods
    • 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
    • G06F17/504—Formal methods
    • 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
    • G06F17/5036—Computer-aided design using simulation for analog modelling, e.g. for circuits, spice programme, direct methods, relaxation methods
    • 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
    • G06F17/10—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
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment
    • G06F11/3457—Performance evaluation by simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F2217/00—Indexing scheme relating to computer aided design [CAD]
    • 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
    • G06Q30/00—Commerce, e.g. shopping or e-commerce
    • G06Q30/02—Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0202—Market predictions or demand forecasting
    • G06Q30/0203—Market surveys or market polls
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
    • G01N29/46—Processing the detected response signal, e.g. electronic circuits specially adapted therefor by spectral analysis, e.g. Fourier analysis or wavelet analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
    • G01N29/4472—Mathematical theories or simulation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups

Similar Documents

Publication Publication Date Title
Sigrist et al. Stochastic partial differential equation based modelling of large space–time data sets
Oberkampf et al. Verification and validation in computational fluid dynamics
Bulygina et al. Estimating the uncertain mathematical structure of a water balance model via Bayesian data assimilation
Schumacher et al. Toward a probabilistic acoustic emission source location algorithm: A Bayesian approach
Williamson et al. Evolving Bayesian emulators for structured chaotic time series, with application to large climate models
Iaccarino Quantification of uncertainty in flow simulations using probabilistic methods
Giri et al. Exploring KSZ velocity reconstruction with N-body simulations and the halo model
Yan et al. Generalized proper complex Gaussian ratio distribution and its application to statistical inference for frequency response functions
Glimm et al. Statistical riemann problems and a composition law for errors in numerical solutions of shock physics problems
Hemez Uncertainty quantification and the verification and validation of computational models
Heredia et al. Bayesian calibration of an avalanche model from autocorrelated measurements along the flow: application to velocities extracted from photogrammetric images
Chen et al. Data-driven arbitrary polynomial chaos expansion on uncertainty quantification for real-time hybrid simulation under stochastic ground motions
Harter Unconditional and conditional simulation of flow and transport in heterogeneous, variably saturated porous media
Warner et al. Probabilistic damage characterization using the computationally-efficient bayesian approach
Zhong Ground motion simulation validation for building design and response assessment
Srinivasan et al. Selection of Surrogate Models with Metafeatures
Zhuang Statistical seismology
Ivanov et al. Sensitivity analysis of nonlinear models to parameter perturbations for small size ensembles of model outputs
Castello et al. Bayesian model selection for structural damage identification: comparative analysis of marginal likelihood estimators
Kim et al. Updated layer coefficients for GDOT flexible pavement design
Bouatay et al. An approach for imperfection propagation: Application to land cover change prediction
Ballisat A general approach to model assisted qualification of non-destructive inspections
Dumelle A Linear Mixed Model Framework for Spatio-Temporal Random Processes using the Separable and Product-Sum Covariance Structures
Kashiwaya Dynamic process model parameter estimation by global system analysis
Koh et al. Successive over-relaxation method for arithmetic Asian option pricing