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In many applications, such as plasma edge simulation of a nuclear fusion reactor, a coupled PDE/kinetic description is required, which is usually solved with a coupled finite-volume/Monte-Carlo method. Different procedures have been…

Numerical Analysis · Mathematics 2020-12-17 Bert Mortier , Martine Baelmans , Giovanni Samaey

A series of monte carlo studies were performed to compare the behavior of some alternative procedures for reasoning under uncertainty. The behavior of several Bayesian, linear model and default reasoning procedures were examined in the…

Artificial Intelligence · Computer Science 2013-03-26 Paul E. Lehner , Azar Sadigh

In engineering applications almost all processes are described with the help of models. Especially forming machines heavily rely on mathematical models for control and condition monitoring. Inaccuracies during the modeling, manufacturing…

Model-based process simulation can be used to derive designs and operating conditions of chemical processes that optimally balance multiple objectives, such as quality, costs, or environmental impacts. This work focuses on identifying…

The flexible capacitive pressure sensors are one of the most essential and famous devices with vast applications in automobile, aerospace, marine, healthcare, wearables, consumer, and portable electronics. The fabrication of pressure…

Systems and Control · Electrical Eng. & Systems 2021-06-22 Rishabh Bhooshan Mishra

Monte Carlo simulation is an essential component of experimental particle physics in all the phases of its life-cycle: the investigation of the physics reach of detector concepts, the design of facilities and detectors, the development and…

Computational Physics · Physics 2012-08-02 Maria Grazia Pia , Georg Weidenspointner

This paper proposes strategies for designing a system whose computational model is subject to aleatory and epistemic uncertainty. Aleatory variables, which are caused by randomness in physical parameters, are draws from a possibly unknown…

Methodology · Statistics 2026-02-18 Luis G. Crespo

Statistical uncertainties complicate engineering design -- confounding regulated design approaches, and degrading the performance of reliability efforts. The simplest means to tackle this uncertainty is double loop simulation; a nested…

Methodology · Statistics 2018-11-02 Zachary del Rosario , Richard W. Fenrich , Gianluca Iaccarino

We propose a Monte Carlo simulation method to generate stress tests by VaR scenarios under Solvency II for dependent risks on the basis of observed data. This is of particular interest for the construction of Internal Models and…

Risk Management · Quantitative Finance 2020-12-17 Dietmar Pfeifer , Olena Ragulina

We use the Multi Level Monte Carlo method to estimate uncertainties in a Henry-like salt water intrusion problem with a fracture. The flow is induced by the variation of the density of the fluid phase, which depends on the mass fraction of…

Numerical Analysis · Mathematics 2025-01-17 Dmitry Logashenko , Alexander Litvinenko , Raul Tempone , Gabriel Wittum

Standard optimality criteria (e.g. A-, D-optimality criterion, etc.) have been commonly used for obtaining optimal designs. For a given statistical model, standard criteria assume the error variance is known at the design stage. However, in…

Methodology · Statistics 2017-01-27 Md. Shaddam Hossain Bagmar , Wasimul Bari , A. H. M. Mahbub Latif

Molecular dynamics (MD) simulations are widely used to provide insights into fracture mechanisms while maintaining chemical specificity. However, particle-based techniques such as MD are limited in terms of accessible length scales and…

Materials Science · Physics 2025-10-14 Felix Weber , Maxime Vassaux , Lukas Laubert , Sebastian Pfaller

Monte Carlo (MC) simulation includes a wide range of stochastic techniques used to quantitatively evaluate the behavior of complex systems or processes. Microsoft Excel spreadsheets with Visual Basic for Applications (VBA) software is,…

Mathematical Software · Computer Science 2015-07-22 Alexei Botchkarev

While kinetic Monte Carlo simulations can provide long-time simulations of the dynamics of physical and chemical systems, it is not yet possible in general to identify the inverse Monte Carlo attempt frequency with a physical timescale.…

Materials Science · Physics 2007-05-23 I. Abou Hamad , P. A. Rikvold , G. Brown

We present a Monte Carlo simulation framework for analysing the risk involved in deploying real-time control systems in safety-critical applications, as well as an algorithm design technique allowing one (in certain situations) to robustify…

Optimization and Control · Mathematics 2022-08-04 Mads R. Bisgaard , Lukas Hewing , Alexander Domahidi

This paper introduces an open-ended sequential algorithm for computing the p-value of a test using Monte Carlo simulation. It guarantees that the resampling risk, the probability of a different decision than the one based on the theoretical…

Statistics Theory · Mathematics 2013-07-30 Axel Gandy

Monte Carlo methods are used to approximate the means, $\mu$, of random variables $Y$, whose distributions are not known explicitly. The key idea is that the average of a random sample, $Y_1, ..., Y_n$, tends to $\mu$ as $n$ tends to…

Statistics Theory · Mathematics 2015-01-16 Fred J. Hickernell , Lan Jiang , Yuewei Liu , Art Owen

Torsional-space Monte Carlo simulations of flexible molecules are usually based on the assumption that all values of dihedral angles have equal probability in the absence of atomic interactions. In the present paper it is shown that this…

Chemical Physics · Physics 2007-05-23 Andreas Kraemer

Molecular dynamics simulations using semi-empirical potentials are examined for three liquids to check the reliability of reverse Monte Carlo (RMC) simulations to reproduce atomic configurations when only total pair correlation functions…

Materials Science · Physics 2018-10-22 R. Ashcraft , K. F. Kelton

Monte Carlo simulations are the primary methodology for evaluating Item Response Theory (IRT) methods, yet marginal reliability - the fundamental metric of data informativeness - is rarely treated as an explicit design factor. Unlike in…

Methodology · Statistics 2026-01-14 JoonHo Lee
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