4.7 Article

An efficient meta-model-based method for uncertainty propagation problems involving non-parameterized probability-boxes

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Engineering, Civil

Active learning for structural reliability: Survey, general framework and benchmark

Maliki Moustapha et al.

Summary: Active learning methods have gained popularity in solving complex structural reliability problems by building inexpensive surrogate models. This paper surveys recent literature and proposes a generalized modular framework for building efficient active learning strategies. The extensive benchmark results provide recommendations for practitioners and highlight the importance of combining surrogates with sophisticated reliability estimation algorithms.

STRUCTURAL SAFETY (2022)

Article Engineering, Multidisciplinary

A GRU-based ensemble learning method for time-variant uncertain structural response analysis

Kun Zhang et al.

Summary: This paper proposes a method for analyzing time-variant uncertain structural responses using recurrent neural networks and ensemble learning. Multiple recurrent neural networks are trained to estimate the time-variant system response, and the mapping relationship between random variables and structural responses is established using Gaussian process regression. The results show that the proposed method can effectively calculate the expectation and standard deviation of system responses and has higher computational efficiency.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2022)

Article Engineering, Industrial

An active learning reliability analysis method using adaptive Bayesian compressive sensing and Monte Carlo simulation (ABCS-MCS)

Peiping Li et al.

Summary: This paper combines adaptive Bayesian compressive sensing (ABCS) with Monte Carlo simulation (MCS) and proposes an active learning reliability analysis method - ABCS-MCS. Compared with traditional methods, ABCS-MCS has better performance.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2022)

Article Engineering, Industrial

A new active learning Kriging metamodel for structural system reliability analysis with multiple failure modes

Shi-Ya Huang et al.

Summary: This study develops a new ALK-SD metamodel based on the concept of significant domain to improve the accuracy and efficiency of the structural system reliability analysis. The proposed method outperforms its counterparts in evaluating the reliability of the structural system.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2022)

Article Engineering, Mechanical

Distribution-free P-box processes based on translation theory: Definition and simulation

Matthias G. R. Faes et al.

Summary: This paper discusses the limitations of stochastic processes and random fields in industrial engineering practice, mainly due to computational burden and methodological complexity. It introduces the concept of imprecise random fields and extends it to distribution-free p-boxes. The main challenges addressed include the non-Gaussianity of realizations of the imprecise random field and maintaining the imposed auto-correlation structure while sampling from the p-box. Two case studies are provided to illustrate the presented concepts.

PROBABILISTIC ENGINEERING MECHANICS (2022)

Article Engineering, Industrial

Limit state Kriging modeling for reliability-based design optimization through classification uncertainty quantification

Xiaoke Li et al.

Summary: This paper proposed an adaptive Kriging sampling strategy based on Classification Uncertainty Quantification (KCUQ) to address the low modeling efficiency and unsatisfied modeling accuracy issues in existing Kriging-assisted RBDO methods. The KCUQ method effectively considers the classification uncertainty of the Kriging model and updates the performance function with the largest classification error in each iteration for adaptive modeling based on unique features. Two numerical case studies were conducted to demonstrate the performance of the proposed KCUQ method in vehicle crashworthiness and axle bridge optimization applications.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2022)

Article Engineering, Mechanical

A probability-box-based method for propagation of multiple types of epistemic uncertainties and its application on composite structural-acoustic system

Wenqing Zhu et al.

Summary: This paper investigates the response analysis of composite structural-acoustic systems with multiple types of epistemic uncertainties, proposing a modified interval Monte Carlo method (MIMCM) to efficiently estimate the bounds of the system response's cumulative distribution function. By transforming evidence and interval variables into p-box-form variables, the MIMCM method proves to be accurate and efficient in handling various uncertainties. Through numerical and engineering examples, the MIMCM method demonstrates its ability in risk and conservative reliability analysis, surpassing traditional algorithms in terms of accuracy and efficiency.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2021)

Article Engineering, Industrial

Reliability index function approximation based on adaptive double-loop Kriging for reliability-based design optimization

Xiaobo Zhang et al.

Summary: The study introduces a decoupled RBDO approach named RIFA-ADK for approximating the reliability index function, improving the efficiency of reliability analysis and optimization. By utilizing an adaptive gradient-enhanced Kriging model and an adaptive learning strategy, the precision of the surrogate model in the region of interest is enhanced.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2021)

Article Engineering, Industrial

A global surrogate model technique based on principal component analysis and Kriging for uncertainty propagation of dynamic systems

Yushan Liu et al.

Summary: This paper introduces a global surrogate model technique PCA-AK to improve the efficiency of uncertainty propagation in dynamic systems and enhance the reliability analysis capability of PCA-K. By utilizing principal component analysis (PCA) and Kriging model to reduce output dimensions, and using an adaptive sampling method to select more training samples near the limit state function, this method aims to improve prediction accuracy.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2021)

Article Engineering, Civil

Engineering analysis with probability boxes: A review on computational methods

Matthias G. R. Faes et al.

Summary: The paper discusses the importance of considering imprecise probability in engineering analysis and the application of probability-boxes in this context. Despite the straightforward concept of p-boxes, numerical propagation of uncertainties in model responses remains challenging and requires further research.

STRUCTURAL SAFETY (2021)

Article Engineering, Industrial

Global and local Kriging limit state approximation for time-dependent reliability-based design optimization through wrong-classification probability

Chen Jiang et al.

Summary: Time-dependent reliability-based design optimization is important for ensuring high product reliability throughout its full life cycle. This study proposes global and local Kriging modeling methods to approximate time-consuming probabilistic constraints, aiming to reduce computational burden and improve accuracy in limit state evaluations.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2021)

Article Engineering, Mechanical

Efficient uncertainty propagation for parameterized p-box using sparse-decomposition-based polynomial chaos expansion

H. B. Liu et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2020)

Article Engineering, Mechanical

An active learning method combining deep neural network and weighted sampling for structural reliability analysis

Zhengliang Xiang et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2020)

Article Engineering, Industrial

Uncertainty and sensitivity analysis of functional risk curves based on Gaussian processes

Bertrand Iooss et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2019)

Article Computer Science, Interdisciplinary Applications

Uncertainty propagation analysis using sparse grid technique and saddlepoint approximation based on parameterized p-box representation

H. B. Liu et al.

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION (2019)

Article Engineering, Industrial

Time-variant reliability analysis using the parallel subset simulation

Weiqi Du et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2019)

Article Engineering, Mechanical

Non-intrusive stochastic analysis with parameterized imprecise probability models: II. Reliability and rare events analysis

Pengfei Wei et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2019)

Article Engineering, Mechanical

Non-intrusive stochastic analysis with parameterized imprecise probability models: I. Performance estimation

Pengfei Wei et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2019)

Article Engineering, Industrial

A new uncertainty propagation method for problems with parameterized probability-boxes

H. B. Liu et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2018)

Article Computer Science, Interdisciplinary Applications

Uncertainty propagation of p-boxes using sparse polynomial chaos expansions

Roland Schobi et al.

JOURNAL OF COMPUTATIONAL PHYSICS (2017)

Article Computer Science, Interdisciplinary Applications

Quantile-based optimization under uncertainties using adaptive Kriging surrogate models

Maliki Moustapha et al.

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION (2016)

Article Mathematics, Applied

A FUZZY HYBRID SEQUENTIAL DESIGN STRATEGY FOR GLOBAL SURROGATE MODELING OF HIGH-DIMENSIONAL COMPUTER EXPERIMENTS

J. van der Herten et al.

SIAM JOURNAL ON SCIENTIFIC COMPUTING (2015)

Article Engineering, Geological

Probabilistic characterization of Young's modulus of soil using equivalent samples

Yu Wang et al.

ENGINEERING GEOLOGY (2013)

Article Engineering, Mechanical

Computationally Efficient Imprecise Uncertainty Propagation

Dipanjan D. Ghosh et al.

JOURNAL OF MECHANICAL DESIGN (2013)

Article Engineering, Mechanical

Structural reliability analysis on the basis of small samples: An interval quasi-Monte Carlo method

Hao Zhang et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2013)

Article Engineering, Mechanical

Imprecise probabilities in engineering analyses

Michael Beer et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2013)

Article Engineering, Civil

Interval Monte Carlo methods for structural reliability

Hao Zhang et al.

STRUCTURAL SAFETY (2010)

Article Public, Environmental & Occupational Health

Uncertainty Analysis Based on Probability Bounds (P-Box) Approach in Probabilistic Safety Assessment

Durga Rao Karanki et al.

RISK ANALYSIS (2009)

Article Computer Science, Theory & Methods

Representing parametric probabilistic models tainted with imprecision

C. Baudrit et al.

FUZZY SETS AND SYSTEMS (2008)

Article Statistics & Probability

Sequential Experiment Design for Contour Estimation From Complex Computer Codes

Pritam Ranjan et al.

TECHNOMETRICS (2008)

Article Engineering, Industrial

Representation and problem solving with Distribution Envelope Determination (DEnv)

D Berleant et al.

RELIABILITY ENGINEERING & SYSTEM SAFETY (2004)