Review
Engineering, Industrial
Giray Okten, Yaning Liu
Summary: Randomized quasi-Monte Carlo methods are becoming more popular in applications due to their faster convergence rate and the availability of simple statistical tools for analyzing estimation errors.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Materials Science, Multidisciplinary
Somayajulu L. N. Dhulipala, Wen Jiang, Benjamin W. Spencer, Jason D. Hales, Michael D. Shields, Andrew E. Slaughter, Zachary M. Prince, Vincent M. Laboure, Chandrakanth Bolisetti, Promit Chakroborty
Summary: This paper presents four statistical methods for fuel failure analysis in Bison, using TRISO-coated particle fuel as a case study. Among these methods, subset simulation (SS) and the Weibull theory are deemed the most efficient, and can be applied to both 1-D and 2-D TRISO models to compute failure probabilities.
JOURNAL OF NUCLEAR MATERIALS
(2022)
Article
Mathematics
Helio M. de Oliveira, Raydonal Ospina, Carlos Martin-Barreiro, Victor Leiva, Christophe Chesneau
Summary: This paper presents a new approach to source coding, which takes into account information variation. The approach uses Shannon entropy to encode source sequences and is suitable for short sequences where the central limit theorem does not apply. The paper also provides an interpretation of typical sequences and uses Monte Carlo simulation to evaluate the performance of the approach.
Article
Nuclear Science & Technology
Inyup Kim, Yonghee Kim
Summary: The Improved Deterministic Truncation of Monte Carlo (iDTMC) is a powerful acceleration and variance reduction scheme in Monte Carlo analysis. In this paper, the concept of the iDTMC method and correlated sampling-based real variance estimation are introduced. The application of the iterative scheme to correlated sampling is also discussed. The iDTMC method is applied to a 3-dimensional small modular reactor (SMR) model problem, and the real variances of burnup-dependent criticality and power distribution are evaluated and compared.
NUCLEAR ENGINEERING AND TECHNOLOGY
(2023)
Article
Energy & Fuels
Qincong Wang, Zhengyao Xv, Huawei Wang, Xincheng Li, Longmei Tian, Shixiong Yuan, Rui Deng
Summary: In the middle and late stages of oilfield production and development, the difference in reservoir physical properties and the complexity of the oil-water relationship pose challenges to the accurate evaluation of remaining oil. Improving logging interpretation and evaluation technology can provide a basis for finding oil layers with development potential and adjusting judgment in the later stages of oilfield development.
Review
Engineering, Mechanical
Chenxiao Song, Reiichiro Kawai
Summary: Monte Carlo methods have been widely used in structural reliability analysis, and this survey provides a comprehensive guidebook on Monte Carlo simulation and its variance reduction techniques. The review covers 444 references and summarizes the formulations, techniques, numerical methods, and advantages of Monte Carlo methods.
PROBABILISTIC ENGINEERING MECHANICS
(2023)
Article
Food Science & Technology
Alberto Garre, Annemarie Pielaat, Marcel H. Zwietering, Heidy M. W. den Besten, Joost H. Smid
Summary: This study compares three statistical methods for estimating the variability in kinetic parameters of microbial populations. The algebraic method overestimates the contribution of between-strain and within-strain variability, while the mixed-effects model and multilevel Bayesian models provide unbiased estimates for all levels of variability.
INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY
(2022)
Article
Chemistry, Physical
Yuan Feng, Jiaping Wu, Baohui Li, Qiang Wang
Summary: This article introduces a method to address the mismatch between periodic boundary conditions and bulk periodicity in molecular simulations of periodic ordered morphologies. By calculating and enumerating the orientations and periodicities of hexagonally packed cylinders, a global order parameter is designed to quantify and monitor the formation and orientation of cylinders in the simulation box.
Article
Nuclear Science & Technology
M. Brovchenko, K. W. Burn, P. Console Camprini
Summary: Monte Carlo with variance reduction is utilized to calculate radiation-induced responses in fixed source problems. A new all-Monte Carlo approach is evaluated for calculating differential in-core and ex-core responses without decoupling. The results are compared with an empirical method involving analog Monte Carlo in-core with VR ex-core.
ANNALS OF NUCLEAR ENERGY
(2022)
Article
Astronomy & Astrophysics
Cagin Yunus, William Detmold
Summary: In Monte Carlo calculations of lattice quantum field theories, the variance of the sampling procedure defines the precision of the calculation. If the variance of an estimator is infinite or significantly larger than the square of the mean, the quantity cannot be reliably estimated. The Gross-Neveu model provides an example where the variances of estimators involving fermion fields are divergent, and alternative sampling methods are proposed.
Article
Mathematics, Applied
Eduard Feireisl, Maria Lukacova-Medvidova, Bangwei She, Yuhuan Yuan
Summary: The goal of this paper is to study convergence and error estimates of the Monte Carlo method for the Navier-Stokes equations with random data. By combining the Monte Carlo method with a suitable deterministic discretization scheme, the statistical convergence rates and approximation errors are investigated. The paper applies intrinsic stochastic compactness arguments to analyze the random Navier-Stokes equations and proves the convergence of the Monte Carlo finite volume method to a statistical strong solution.
MATHEMATICAL MODELS & METHODS IN APPLIED SCIENCES
(2022)
Article
Spectroscopy
Shaohui Yu, Jing Liu
Summary: This paper proposes an ensemble calibration model FDA-EM-PLS (functional data analysis-ensemble learning-partial least squares) for near-infrared spectroscopy, based on the functional data analysis method. By dividing the near-infrared spectroscopy into intervals and conducting functional data analysis, clustering, and Monte Carlo sampling, this model achieves accurate detection of corn and soil data.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2022)
Article
Engineering, Multidisciplinary
Alireza Entezami, Hassan Sarmadi, Carlo De Michele
Summary: This article proposes innovative methods to address challenges in data-based damage localization, including a hybrid feature extraction algorithm, a symmetric information measure, and a probabilistic threshold estimation approach. Experimental results confirm the success of these methods in identifying damage.
Article
Nuclear Science & Technology
Ozgur Akcali, Ozan Toker, Bayram Bilmez, Orhan Icelli
Summary: The article introduces some variance reduction methods and compares them with conventional narrow beam geometry for radiation transport problems. A new method using source-biased quadruplet and octuplet detection geometries is proposed, showing efficiency and accuracy in testing.
PROGRESS IN NUCLEAR ENERGY
(2021)
Article
Computer Science, Theory & Methods
Xinzhu Liang, Shangda Yang, Simon L. L. Cotter, Kody J. H. Law
Summary: This paper addresses the problem of estimating expectations when the normalizing constant of the target distribution is unknown and the unnormalized target needs to be approximated at finite resolution. Building upon a recently introduced multi-index sequential Monte Carlo (SMC) ratio estimator, this work combines the complexity improvements of multi-index Monte Carlo (MIMC) with the efficiency of SMC for inference. The proposed method uses a randomization strategy to remove bias entirely, simplifying the estimation process, particularly in the context of MIMC.
STATISTICS AND COMPUTING
(2023)
