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The paper represents original development of thermodynamic criteria of occurrence conditions of steam-gas explosions in the process of severe accidents. The received results can be used for modelling of processes of severe accidents in…

General Physics · Physics 2012-04-03 V. I. Skalozubov , V. N. Vashchenko , S. S. Jarovoj , V. Yu. Kochnyeva

The problem of detecting variance breaks in the case of smooth time-varying variance structure is studied. It is highlighted that the tests based on (piecewise) constant specification of the variance are not able to distinguish between…

Methodology · Statistics 2017-07-24 Ben Hajria Raja , Khardani Salah , Raïssi Hamdi

The great majority of engineered products are subject to thermo-mechanical loads which vary with the product environment during the various phases of its life-cycle (machining, assembly, intended service use...). Those load variations may…

Classical Physics · Physics 2009-05-07 Guillaume Mandil , Alain Desrochers , Alain Rivière

Accurate simulation of complex physical systems enables the development, testing, and certification of control strategies before they are deployed into the real systems. As simulators become more advanced, the analytical tractability of the…

Robotics · Computer Science 2020-05-27 Lucas Barcelos , Rafael Oliveira , Rafael Possas , Lionel Ott , Fabio Ramos

A driven Monte Carlo dynamics is introduced to study resistivity scaling in XY-type models in the phase representation. The method is used to study the phase transition of the three-dimensional XY spin glass with a Gaussian coupling…

Disordered Systems and Neural Networks · Physics 2009-11-10 Enzo Granato

Reliability sensitivity analysis is concerned with measuring the influence of a system's uncertain input parameters on its probability of failure. Statistically dependent inputs present a challenge in both computing and interpreting these…

Applications · Statistics 2023-06-21 Max Ehre , Iason Papaioannou , Daniel Straub

Flow over bluff bodies has multiple engineering applications and thus, has been studied for decades. The lift and drag coefficients are practically important in the design of many components such as automobiles, aircrafts, buildings etc.…

Fluid Dynamics · Physics 2021-10-29 Shantanu Shahane , Purushotam Kumar , Surya Pratap Vanka

We perform Monte Carlo simulations to determine the average excluded volume <V_{ex}> of randomly oriented rectangular prisms, randomly oriented ellipsoids and randomly oriented capped cylinders in 3-D. There is agreement between the…

Disordered Systems and Neural Networks · Physics 2007-05-23 Sameet Sreenivasan , Don R. Baker , Gerald Paul , H. Eugene Stanley

In this paper the application of the multi-level Monte Carlo (MLMC) method on numerical simulations of turbulent flows with uncertain parameters is investigated. Several strategies for setting up the MLMC method are presented, and the…

Computation · Statistics 2016-08-22 Qingsha Chen , Ju Ming

By considering the effect of varying the target radii and detector aperture width on the scattering angle in experimental Compton scattering, mathematical models were developed and subsequently incorporated into Monte Carlo simulations. By…

High Energy Physics - Experiment · Physics 2021-04-30 Assunta Sophia Felice

We describe a Monte Carlo procedure which allows sampling of the disjoint configuration spaces associated with crystalline and fluid phases, within a single simulation. The method utilises biased sampling techniques to enhance the…

Statistical Mechanics · Physics 2009-10-31 N. B. Wilding , A. D. Bruce

This work introduces a novel multilevel Monte Carlo (MLMC) metamodeling approach for variance function estimation. Although devising an efficient experimental design for simulation metamodeling can be elusive, the MLMC-based approach…

Methodology · Statistics 2025-04-22 Jingtao Zhang , Xi Chen

The aim of this paper is to describe a new an integrated methodology for project control under uncertainty. This proposal is based on Earned Value Methodology and risk analysis and presents several refinements to previous methodologies.…

Risk Management · Quantitative Finance 2024-06-06 Fernando Acebes , M Pereda , David Poza , Javier Pajares , Jose M Galan

Monte Carlo computer simulations are virtually the only way to analyze the thermodynamic behavior of a system in a precise way. However, the various existing methods exhibit extreme differences in their efficiency, depending on model…

Statistical Mechanics · Physics 2011-07-05 Michael Bachmann

The main focus of the analysts who deal with clustered data is usually not on the clustering variables, and hence the group-specific parameters are treated as nuisance. If a fixed effects formulation is preferred and the total number of…

Methodology · Statistics 2019-01-01 Claudia Di Caterina , Giuliana Cortese , Nicola Sartori

An intercomparison of microdosimetric and nanodosimetric quantities simulated Monte Carlo codes is in progress with the goal of assessing the uncertainty contribution to simulated results due to the uncertainties of the electron interaction…

In a multi-fidelity setting, data are available from two sources, high- and low-fidelity. Low-fidelity data has larger size and can be leveraged to make more efficient inference about quantities of interest, e.g. the mean, for high-fidelity…

Methodology · Statistics 2026-03-12 Minji Kim , Brendan Brown , Vladas Pipiras

We perform a probabilistic investigation on the effect of systematically removing imperfections on the buckling behavior of pressurized thin, elastic, hemispherical shells containing a distribution of defects. We employ finite element…

Soft Condensed Matter · Physics 2024-10-16 Fani Derveni , Florian Choquart , Arefeh Abbasi , Dong Yan , Pedro M. Reis

We study random compressible viscous magnetohydrodynamic flows. Combining the Monte Carlo method with a deterministic finite volume method we solve the random system numerically. Quantitative error estimates including statistical and…

Numerical Analysis · Mathematics 2024-10-24 Eduard Feireisl , Maria Lukacova-Medvidova , Bangwei She , Yuhuan Yuan

To improve the efficiency of Monte Carlo estimation, practitioners are turning to biased Markov chain Monte Carlo procedures that trade off asymptotic exactness for computational speed. The reasoning is sound: a reduction in variance due to…

Machine Learning · Statistics 2019-01-03 Jackson Gorham , Lester Mackey
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