4.7 Article

A hierarchical Bayesian framework embedded with an improved orthogonal series expansion for Gaussian processes and fields identification

Related references

Note: Only part of the references are listed.
Article Engineering, Multidisciplinary

Nonlinear model updating through a hierarchical Bayesian modeling framework

Xinyu Jia et al.

Summary: A new time-domain probabilistic technique based on hierarchical Bayesian modeling framework is proposed for calibration and uncertainty quantification of hysteretic type nonlinearities of dynamical systems. The technique introduces probabilistic hyper models for material hysteretic model parameters and prediction error variance parameters, considering both the uncertainty of the model parameters and the prediction error uncertainty. The technique employs a new asymptotic approximation to simplify the process of nonlinear model updating and reduce the computational burden. Numerical examples demonstrate the accuracy and performance of the proposed method.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2022)

Article Engineering, Mechanical

Statistics-based Bayesian modeling framework for uncertainty quantification and propagation

Menghao Ping et al.

Summary: A new Bayesian modeling framework is proposed to account for the uncertainties in model parameters arising from various factors. The framework incorporates uncertainty using a single level hierarchy with Normal distributions. The likelihood function is constructed based on the discrepancy between model predictions and measurements, and the posterior PDF of model parameters depends on the lower two moments of the respective PDFs.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2022)

Article Engineering, Mechanical

Hierarchical Bayesian learning framework for multi-level modeling using multi-level data

Xinyu Jia et al.

Summary: A hierarchical Bayesian learning framework is proposed for multi-level modeling in structural dynamics, which can effectively quantify uncertainties at different modeling levels and propagate them through the system.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2022)

Article Engineering, Multidisciplinary

A stochastic process discretization method combing active learning Kriging model for efficient time-variant reliability analysis

Dequan Zhang et al.

Summary: The study presents a Kriging-assisted time-variant reliability analysis method based on stochastic process discretization, which tackles two main challenges in time-variant problems and demonstrates its effectiveness through numerical analysis and engineering design examples.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2021)

Article Engineering, Mechanical

A time-variant uncertainty propagation analysis method based on a new technique for simulating non-Gaussian stochastic processes

M. H. Ping et al.

Summary: This paper presents a method for time-variant uncertainty propagation analysis, combining extended orthogonal series expansion method and sparse grid numerical integration, which effectively solves the output stochastic process of a time-variant function. By modeling the orthogonal time functions and correlated coefficients of the stochastic process and reducing dimensionality, an explicit expression for the non-Gaussian process can be obtained.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2021)

Article Engineering, Multidisciplinary

Bayesian inference with subset simulation in varying dimensions applied to the Karhunen-Loeve expansion

Felipe Uribe et al.

Summary: This article introduces a method for handling the inference problem of spatially varying parameters in random fields, combining Bayesian inference with a penalizing prior distribution for dimension parameters. The algorithm, by replacing traditional MCMC algorithms, is able to sample in discrete-continuous parameter space to address high-dimensional coefficient sets and dimensionality.

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING (2021)

Article Engineering, Civil

Bayesian calibration of hysteretic reduced order structural models for earthquake engineering applications

Dimitrios Patsialis et al.

ENGINEERING STRUCTURES (2020)

Article Engineering, Multidisciplinary

Fast sampling of parameterised Gaussian random fields

Jonas Latz et al.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2019)

Article Engineering, Mechanical

A time-variant extreme-value event evolution method for time-variant reliability analysis

M. H. Ping et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2019)

Article Engineering, Mechanical

Probabilistic hierarchical Bayesian framework for time-domain model updating and robust predictions

Omid Sedehi et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2019)

Article Engineering, Multidisciplinary

Hierarchical Stochastic Model in Bayesian Inference for Engineering Applications: Theoretical Implications and Efficient Approximation

Stephen Wu et al.

ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING (2019)

Article Mathematics, Applied

HYPERPRIORS FOR MATERN FIELDS WITH APPLICATIONS IN BAYESIAN INVERSION

Lassi Roininen et al.

INVERSE PROBLEMS AND IMAGING (2019)

Article Computer Science, Interdisciplinary Applications

An improved TRPD method for time-variant reliability analysis

C. Jiang et al.

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION (2018)

Article Computer Science, Interdisciplinary Applications

Sensor placement for calibration of spatially varying model parameters

Paromita Nath et al.

JOURNAL OF COMPUTATIONAL PHYSICS (2017)

Article Engineering, Mechanical

Time-Dependent Reliability Analysis Through Response Surface Method

Dequan Zhang et al.

JOURNAL OF MECHANICAL DESIGN (2017)

Article Engineering, Multidisciplinary

Coordinate transformation and Polynomial Chaos for the Bayesian inference of a Gaussian process with parametrized prior covariance function

Ihab Sraj et al.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2016)

Article Engineering, Mechanical

Transitional Markov Chain Monte Carlo: Observations and Improvements

Wolfgang Betz et al.

JOURNAL OF ENGINEERING MECHANICS (2016)

Article Environmental Sciences

The relative importance of head, flux, and prior information in hydraulic tomography analysis

Chak-Hau Michael Tso et al.

WATER RESOURCES RESEARCH (2016)

Article Engineering, Mechanical

Transitional Markov Chain Monte Carlo: Observations and Improvements

Wolfgang Betz et al.

JOURNAL OF ENGINEERING MECHANICS (2016)

Article Engineering, Mechanical

Bayesian Updating with Structural Reliability Methods

Daniel Straub et al.

JOURNAL OF ENGINEERING MECHANICS (2015)

Article Engineering, Mechanical

Bayesian Updating with Structural Reliability Methods

Daniel Straub et al.

JOURNAL OF ENGINEERING MECHANICS (2015)

Article Astronomy & Astrophysics

Method for estimation of gravitational-wave transient model parameters in frequency-time maps

M. Coughlin et al.

CLASSICAL AND QUANTUM GRAVITY (2014)

Article Engineering, Multidisciplinary

A Generalized Polynomial Chaos-Based Method for Efficient Bayesian Calibration of Uncertain Computational Models

Piyush M. Tagade et al.

INVERSE PROBLEMS IN SCIENCE AND ENGINEERING (2014)

Article Engineering, Mechanical

Environmental effects on the identified natural frequencies of the Dowling Hall Footbridge

Peter Moser et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2011)

Article Construction & Building Technology

Bayesian system identification based on probability logic

James L. Beck

STRUCTURAL CONTROL & HEALTH MONITORING (2010)

Article Computer Science, Interdisciplinary Applications

Dimensionality reduction and polynomial chaos acceleration of Bayesian inference in inverse problems

Youssef M. Marzouk et al.

JOURNAL OF COMPUTATIONAL PHYSICS (2009)

Article Engineering, Mechanical

Transitional markov chain monte carlo method for Bayesian model updating, model class selection, and model averaging

Jianye Ching et al.

JOURNAL OF ENGINEERING MECHANICS (2007)

Article Engineering, Mechanical

Model selection using response measurements: Bayesian probabilistic approach

JL Beck et al.

JOURNAL OF ENGINEERING MECHANICS-ASCE (2004)

Article Engineering, Mechanical

Phase I IASC-ASCE structural health monitoring benchmark problem using simulated data

EA Johnson et al.

JOURNAL OF ENGINEERING MECHANICS (2004)

Article Engineering, Mechanical

Bayesian updating of structural models and reliability using Markov chain Monte Carlo simulation

JL Beck et al.

JOURNAL OF ENGINEERING MECHANICS (2002)

Article Engineering, Mechanical

Bayesian probabilistic approach to structural health monitoring

MW Vanik et al.

JOURNAL OF ENGINEERING MECHANICS-ASCE (2000)

Article Engineering, Mechanical

Effects of testing, analysis, damage, and environment on modal parameters

S Alampalli

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2000)