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Miguel Cerrolaza

Researcher at Central University of Venezuela

Publications -  76
Citations -  990

Miguel Cerrolaza is an academic researcher from Central University of Venezuela. The author has contributed to research in topics: Finite element method & Boundary element method. The author has an hindex of 18, co-authored 74 publications receiving 946 citations. Previous affiliations of Miguel Cerrolaza include Polytechnic University of Catalonia.

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Analysis of 3D transient blood flow passing through an artificial aortic valve by Lattice–Boltzmann methods

TL;DR: The simulation of three-dimensional transient physiological flows in fixed geometries similar to a CarboMedics bileaflet heart valve at different opening angles using the Lattice Boltzmann method yields reasonable results for velocity and shear stress fields.
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A bi‐cubic transformation for the numerical evaluation of the Cauchy principal value integrals in boundary methods

TL;DR: The numerical strategies employed in the evaluation of singular integrals existing in the Cauchy principal value (CPV) sense are one of the key aspects which remarkably affect the performance and accuracy of the boundary element method (BEM).
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Structural shape optimization 3D finite-element models based on genetic algorithms and geometric modeling

TL;DR: The aim of this paper is to present and discuss the used of genetic algorithms and geometric modeling by means of β-splines surface representation in order to solve tri-dimensional shape optimization problems and to show the great applicability of the developed tool.
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Finite elements, genetic algorithms and b-splines: a combined technique for shape optimization

TL;DR: The versatility and flexibility of the proposed approach to solve bidimensional shape optimization problems by using Genetic Algorithms is tested and discussed in two numerical examples, showing that the technique is able to deal with real engineering problems.
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Optimization of 2D boundary element models using β-splines and genetic algorithms

TL;DR: Two numerical examples are presented and discussed in detail, showing that the proposed combined technique is able to optimize the shape of the domains with minimum computational effort.