Wyniki wyszukiwania - BazTech

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Discrete phase model of blood flow in a roughness microchannel simulating the formation of pseudointima

Kopernik Magdalena, Dyrda Karina, Kurtyka Przemysław, Major Roman

Acta of Bioengineering and Biomechanics

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2022

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Vol. 24, no. 1

132--144

EN

The goal of the present study was the development of discrete phase model to simulate the phenomenon of backfilling a morphologically complex surface by red blood cells (RBCs) in a flow microchannel and to anticipate the conditions of forming a pseudointima. The objective of the experimental studies that inspired the development of the simulation was to create a surface that stimulates the formation of the pseudointima layer. Methods: The finite volume method (FVM) and discrete particle method (DPM) were applied to develop the target model. In addition, a mixture model and a roughness model of bottom layer were tested in the present study to show their influence on simulation the phenomenon of backfilling a morphologically complex surface by RBCs in a flow microchannel. Results: Numerical models were developed including: a) FVM models to compare the effect of applying boundary conditions with/without roughness and cubes, as well as the analysis of their influence on blood velocity and shear stress; b) mixture models to compare the effect of applying different boundary conditions and cubes on computed results; c) DPM models to compare the effect of applying and not applying roughness as a boundary condition; d) DPM models with a morphologically complex surface and RBCs collisions to present RBCs concentration, velocity and time distributions during flow in a channel. Conclusions: The analysis carried out for the developed numerical models indicates that DPM model with cubes computes the best results. It also shows the backfilling of a morphologically complex surface of the bottom microchannel with RBCs.

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Gaussian mixture model for time series-based structural damage detection

Słoński M.

Computer Assisted Methods in Engineering and Science

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2012

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Vol. 19, no. 4

331-338

EN

In this paper, a time series-based damage detection algorit hm is proposed using Gaussian mixture model (GMM) and expectation maximization (EM) framework. The vib ration time series from the structure are modelled as the autoregressive (AR) processes. The first AR coefficients are used as a feature vector for novelty detection. To test the efficacy of the damage detec tion algorithm, it has been tested on the pseudo-experimental data obtained from the FEM model of the ASCE benchmark frame structure. Results suggest that the presented approach is able to detect mainly major and moderate damage patterns

3

Mixed model for interoccurrence times of earthquakes based on the expectation-maximization algorithm

Tahernia N., Khodabin M., Noorbakhsh M.

Acta Geophysica

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2011

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Vol. 59, no. 5

872-890

EN

In this paper, the goodness-of-fit test based on a convex combination of Akaike and Bayesian information criteria is used to explain the features of interoccurrence times of earthquakes. By analyzing the seismic catalog of Iran for different tectonic settings, we have found that the probability distributions of time intervals between successive earthquakes can be described by the generalized normal distribution. This indicates that the sequence of successive earthquakes is not a Poisson process. It is found that by decreasing the threshold magnitude, the interoccurrence time distribution changes from the generalized normal distribution to the gamma distribution in some seismotectonic regions. As a new insight, the probability distribution of time intervals between earthquakes is described as a mixture distribution via the expectation-maximization algorithm.