𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Assessment of low probability events of dynamical systems by controlled Monte Carlo simulation

✍ Scribed by H.J. Pradlwarter; G.I. Schuëller

Publisher
Elsevier Science
Year
1999
Tongue
English
Weight
535 KB
Volume
14
Category
Article
ISSN
0266-8920

No coin nor oath required. For personal study only.

✦ Synopsis

Various procedures to extend the applicability and to increase the ef®ciency of Monte Carlo simulation (MCS) for the analysis of complex dynamical systems are discussed. In particular, the capabilities of the methods denoted Russian Roulette and Splitting (RR&S) and Double and Clump (D&C) are reviewed with regard to their capabilities to analyze such systems. In this context, the dif®culties in identifying the important' regions for simulation are detailed. It is shown that these dif®culties may be circumvented by a newly introduced distance controlled' MCS. This procedure, which allows the prediction of very low probability events and the analysis of systems of higher dimension, is applicable not only to mechanical systems and structures but also to complex dynamical systems encountered, for example, in economics, physics, etc. The procedure is shown to be particularly suited to cases where exact analytical methods and direct Monte Carlo simulation are infeasible, hence, being well suited for practical application.

📜 SIMILAR VOLUMES

Stochastic analysis of dynamical systems
Stochastic analysis of dynamical systems by phase-space-controlled Monte Carlo simulation
✍ N. Harnpornchai; H.J. Pradlwarter; G.I. Schnëller 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 850 KB

## A simulation technique for the stochastic analysis of dynamical systems subjected to stochastic excitation is presented. The proposed technique is applied in conjunction with the Monte Carlo Simulation (MCS) procedure. The concept is based on the manipulation of the generated samples in phase

On the probability of chaos in large dyn
On the probability of chaos in large dynamical systems: A Monte Carlo study
✍ W.Davis Dechert; Julien C. Sprott; David J. Albers 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 222 KB

In this paper we report the result of a Monte Carlo study on the probability of chaos in large dynamical systems. We use neural networks as the basis functions for the system dynamics and choose parameter values for the networks randomly. Our results show that as the dimension of the system and the

Monte Carlo Simulation of Controlled/Liv
Monte Carlo Simulation of Controlled/Living Radical Polymerization in Emulsified Systems
✍ Hidetaka Tobita; Fumihiko Yanase 📂 Article 📅 2007 🏛 John Wiley and Sons 🌐 English ⚖ 249 KB

## Abstract A new MC simulation method is proposed for the controlled/living radical polymerization in a dispersed medium, assuming an ideal miniemulsion system. This tool is used to consider the effects of particle size on the polymerization rates and the molecular weight distributions. For NMP, t