Article
Engineering, Mechanical
Jian Ji, Le-Pei Wang
Summary: Efficient reliability methods are crucial for probabilistic analysis involving uncertain factors in engineering practice. This paper proposes a modified weighted uniform simulation (WUS) method, which utilizes Nataf transformation to effectively transform correlated nonnormal random variables into independent standard normal variables, reducing computational burden and improving reliability analysis accuracy.
JOURNAL OF ENGINEERING MECHANICS
(2022)
Article
Engineering, Electrical & Electronic
Dorde Novakovic, Dragan Pejic, Tatjana Grbic, Marko Pejic, Platon Sovilj, Slavica Medic
Summary: An efficient method for generating samples of two uniformly distributed random variables with prescribed correlation coefficients on the interval (-1, 1) is proposed. The experiment results indicate that the proposed method works well in determining the voltage ratio of a resistive divider.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Engineering, Mechanical
Zhibao Zheng, Marcos Valdebenito, Michael Beer, Udo Nackenhorst
Summary: This paper focuses on the simulation of random fields on random domains, which is an important problem in topology optimization and multiphase material analysis. The authors propose the stochastic Karhunen-Loeve expansion (SKLE) as an extension of the classical Karhunen-Loeve expansion (KLE) to solve this issue. They present three numerical algorithms, including an extended Monte Carlo simulation (MCS), a domain transformation-based method, and a reduced-order method, to efficiently solve the stochastic integral equations in the SKLE. Numerical examples demonstrate the effectiveness of the proposed methods.
PROBABILISTIC ENGINEERING MECHANICS
(2023)
Article
Mathematics
Vladimir E. Bening, Victor Y. Korolev
Summary: This paper introduces a new approach to comparing the distributions of sums of random variables using the notion of deficiency from mathematical statistics. The approach is used to determine the distribution of a separate random variable in the sum that guarantees a desired quantile or probability, with the fewest possible number of summands. The paper also considers the case of comparing distributions when the number of summands is random, and applies the approach to determining the distribution of insurance payments for minimum portfolio size under specified risk or non-ruin probability.
Article
Engineering, Geological
Chao Zhao, Wenping Gong, Tianzheng Li, C. Hsein Juang, Huiming Tang, Hui Wang
Summary: Accurate characterization of subsurface stratigraphic configuration is crucial to geotechnical engineering work, but uncertainty can be significant due to complexity and limited data availability. This paper presents a method for characterizing subsurface stratigraphy with limited borehole data, demonstrating its effectiveness and advantages through comparative analyses and a case study in Western Australia.
ENGINEERING GEOLOGY
(2021)
Review
Chemistry, Multidisciplinary
Oliver T. Unke, Stefan Chmiela, Huziel E. Sauceda, Michael Gastegger, Igor Poltaysky, Kristof T. Schuett, Alexandre Tkatchenko, Klaus-Robert Mueller
Summary: The use of machine learning in computational chemistry has led to significant advancements, particularly in the development of machine learning-based force fields to bridge the gap between accuracy and efficiency. The key concept is to learn the statistical relations between chemical structure and potential energy, without preconceived notions of fixed bonds. Challenges remain for the next generation of machine learning force fields.
Article
Computer Science, Interdisciplinary Applications
Xiangfeng Guo, Daniel Dias, Claudio Carvajal, Laurent Peyras, Pierre Breul
Summary: The study uses different types of RF for soil spatial modeling and investigates their effects on dam reliability. The results show that using a simple RF is sufficient for satisfactory results in well-controlled dam constructions, while non-typical RFs may require more accurate data.
ENGINEERING WITH COMPUTERS
(2022)
Article
Computer Science, Hardware & Architecture
Chengning Zhou, Ning-Cong Xiao, Ming Jian Zuo, Wei Gao
Summary: In this article, an active kriging-based learning method for hybrid reliability analysis (HRA) with random and interval variables is proposed. The method includes an improved sampling strategy targeting specific areas, a U-based learning function considering multiple samples of the interval, a hybrid convergence criterion, and an improved optimization strategy based on the DIRECT algorithm for Monte Carlo simulation in HRA. Results from four numerical cases demonstrate the accuracy and efficiency of the proposed method for HRA.
IEEE TRANSACTIONS ON RELIABILITY
(2022)
Article
Construction & Building Technology
Vahid Asghari, Shu-Chien Hsu
Summary: This paper presents a new machine learning-based methodology to estimate optimal intervention timings and demonstrates its feasibility and efficiency through experiments. The proposed method can assist practitioners in making better decisions in asset management systems and furthering sustainability objectives.
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
(2022)
Article
Engineering, Multidisciplinary
Jia-Yi Ou-Yang, Dian-Qing Li, Xiao-Song Tang, Yong Liu
Summary: The study utilizes random field theory to characterize spatial variability of material properties and develops a patching algorithm to incorporate sampled data into simulations, which outperforms the conventional Kriging algorithm. The proposed algorithm restricts the influence domain of sampled data within a reasonable range determined by the scale of fluctuation, resulting in a stationary conditional random field in mean and variance suitable for situations with limited known data. Additionally, the algorithm is effective in reducing uncertainty in response prediction and applicable with sparse sampling pattern as demonstrated in a tunnel excavation model.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2021)
Article
Materials Science, Multidisciplinary
Xiang Peng, Tong Ye, Jiquan Li, Huaping Wu, Shaofei Jiang, Guohai Chen
Summary: This paper proposes a multi-scale uncertainty quantification framework for composite laminated plates, which utilizes data-driven Polynomial Chaos Expansion model to achieve high accuracy and computational superiority in various conditions.
MECHANICS OF ADVANCED MATERIALS AND STRUCTURES
(2021)
Article
Physics, Particles & Fields
Arkaprava Mukherjee, Shinobu Hikami
Summary: Quantum chaos is linked to a Gaussian random matrix model, showing specific behaviors in the spectral form factor for large N, with time-dependent models displaying similar features but with a rounding behavior near Heisenberg time instead of a kink. The model can be converted into two matrix models, comprising M-1 and M-2, for numerical evaluation and comparison between finite N and large N analytic expressions for the spectral form factor.
JOURNAL OF HIGH ENERGY PHYSICS
(2021)
Article
Chemistry, Multidisciplinary
Zhenping Wu, Zhijun Meng, Wenlong Zhao, Zhe Wu
Summary: Fast-RRT is a pathfinding algorithm based on RRT that aims to quickly find a near-optimal path by introducing strategies such as Fast-Sampling, Random Steering expansion, and path fusion and adjustment. It outperforms RRT and RRT* in speed and stability during experiments.
APPLIED SCIENCES-BASEL
(2021)
Article
Construction & Building Technology
Xiaolu Gan, Jianlin Yu, Xiaonan Gong, Min Zhu
Summary: This paper performs a probabilistic-based analysis to evaluate the longitudinal responses of an existing shield tunnel to twin tunneling. A deterministic model and an efficient metamodel are proposed for the analysis, and the results show the significant impact of random parameter uncertainties on tunnel responses and failure probabilities, highlighting the importance of probabilistic analysis.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2022)
Article
Energy & Fuels
Bin Yang, Zhanran Xia, Xinyun Gao, Jing Tu, Hao Zhou, Jun Wu, Mingzhen Li
Summary: This paper investigates the impact of line parameter uncertainty on fault location in HV cable technology, using different uncertainty quantification methods. The study shows that UDRM has potential application prospects, with higher accuracy and shorter running time compared to MCS and PCE.
Article
Engineering, Multidisciplinary
Aravinda Kumar, Satyajit Panda, S. Kumar, D. Chakraborty
COMPOSITES PART B-ENGINEERING
(2015)
Article
Mechanics
Sandeep Kumar, Amit Kumar Onkar, Manjuprasad Maligappa
Correction
Mechanics
Sandeep Kumar, Amit Kumar Onkar, Manjuprasad Maligappa
Article
Mechanics
Sandeep Kumar, Amit Kumar Onkar, M. Manjuprasad
Summary: In this paper, the stochastic finite element method and the first order reliability method (FORM) are used to investigate the stochastic aeroelastic stability and flutter reliability of a wing. Three stability conditions are proposed to estimate flutter onset, and a general FORM method is developed to provide invariant reliability estimates for different limit state functions.
Article
Engineering, Civil
M Manjuprasad, S Gopalakrishnan, KB Rao
STRUCTURAL ENGINEERING AND MECHANICS
(2003)