Theory, Application, and Implementation of Monte Carlo Method in Science and Technology

Bidokhti, Pooneh Saidi

doi:10.5772/intechopen.78141

Cited by 4 publications

References 14 publications

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A Monte Carlo algorithm to improve the measurement efficiency of low-field nuclear magnetic resonance

Guo

Zhang

et al. 2023

Sci Rep

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Nuclear magnetic resonance (NMR) has shown good applications in engineering fields such as well logging and rubber material ageing assessment. However, due to the low magnetic field strength of NMR sensors and the complex working conditions of engineering sites, the signal-to-noise ratio (SNR) of NMR signals is low, and it is usually necessary to increase the number of repeated measurements to improve the SNR, which means a longer measurement time. Therefore, it is especially important to set the measurement parameters appropriately for onsite NMR. In this paper, we propose a stochastic simulation using Monte Carlo methods to predict the measurement curves of $${\mathrm{T}}_{1}$$ T 1 and $${\mathrm{D}}_{0}$$ D 0 and correct the measurement parameters of the next step according to the previous measurement results. The method can update the measurement parameters in real time and perform automatic measurements. At the same time, this method greatly reduces the measurement time. The experimental results show that the method is suitable for the measurement of the self-diffusion coefficient D0 and longitudinal relaxation time T1, which are frequently used in NMR measurements.

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A Monte Carlo algorithm to improve the measurement efficiency of low-field nuclear magnetic resonance

Guo

Zhang

et al. 2023

Sci Rep

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Propagation of Uncertainty in Experimental Dynamic Coefficients of Fluid Film Journal Bearings

Herrera,

Goyne,

Rockwell

2024

Journal of Tribology

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The stiffness and damping coefficients of fluid film bearings play a key role in predicting levels of vibration and stability margins in high-performance industrial rotating machinery. However, variability in the coefficients calculated by numerical bearing codes creates inaccuracies in the rotodynamic predictions. Therefore, there is a strong need for accurate experimental measurement of bearing coefficients for validation purposes. This work examines new propagation uncertainty strategies in bearing coefficients estimation, and for the first time examines the effect of non-linearity of the dynamic coefficients on the experimental uncertainty estimated by the Taylor Series Method. The Montecarlo Method is presented as a more accurate approach to estimating experimental uncertainty. Results of the analyses are compared to published values from previously reported studies. This paper also proposes a novel method to convert the random behavior in the output of a sensor in the time domain to the frequency domain. It is found this conversion is quite beneficial for the accuracy of the coefficients; in one example, uncertainty estimations of ±84% are reduced to just ±6%, when using the proposed method. This work also reveals that the uncertainty estimations from the Taylor Series Method are not entirely reliable, without additional checks of non-linearity; and that converting data to the frequency domain, by using the novel method here, is useful for achieving smaller uncertainty estimations than with traditional methodology.

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Feasibility of Using Hypothetical Fractal Structures to Determine Water Outflow Zones After a Pipe Failure

Iwanek,

Suchorab

2024

Sustainability

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Failures of water supply pipes are undesirable events with a random nature, yet they are an inevitable part of the operation of water infrastructure. Therefore, ongoing research is being conducted to develop methods for minimising their effects or securing underground infrastructure. One of the methods of limiting the effects of the suffosion phenomenon is determination of the water outflow zone, within which water will possibly flow to the soil surface after a pipe leak. The aim of this paper was to assess hypothetical structures created by outflowing water in terms of their potential use in determining the water outflow zone on the soil surface after a water pipe failure. Based on the laboratory test results, the Monte Carlo method was applied to generate the hypothetical population of points representing the places of water outflow. Three parameters characterising hypothetical structures were analysed: fractal dimension, length of a section, and the product of above parameters. The conducted research showed that it is possible to build a reliable hypothetical structure that allows for estimating the water outflow zone radius, knowledge of which would facilitate sustainable management of the water supply network by water utilities by enabling the estimation of the water outflow zone radius in practice.

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Theory, Application, and Implementation of Monte Carlo Method in Science and Technology

Cited by 4 publications

References 14 publications

A Monte Carlo algorithm to improve the measurement efficiency of low-field nuclear magnetic resonance

A Monte Carlo algorithm to improve the measurement efficiency of low-field nuclear magnetic resonance

Propagation of Uncertainty in Experimental Dynamic Coefficients of Fluid Film Journal Bearings

Feasibility of Using Hypothetical Fractal Structures to Determine Water Outflow Zones After a Pipe Failure

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