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Curriculum Vitae
Experience in design


Freet – examples
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Foto of Vorechovsky

Professor, Research Fellow

Prof. Miroslav Vorechovsky, Ph.D.
Institute of Structural Mechanics
Faculty of Civil Engineering
Brno University of Technology
Veveri 95
602 00 Brno,
Czech Republic

Phone: +420 5 4114 7370
Fax: +420 5 4124 0994
E-mail: Vorechovsky.ME-mail addressvut.cz

Researcher ID: A-1759-2010
OrcID: 0000-0002-3366-5557
Scopus ID: 9633063900
Google Scholar

Miroslav Vořechovský serves as a Fulbright Honorary Ambassador at Brno University of Technology.

Research activities

Dr. Vorechovsky focuses on challenging research topics listed bellow. For more information see his Curriculum Vitae. Also the sources of sponsorship and current scientific projects are named therein. Nonlinear fracture mechanics with focus on stochastic aspects. Size effects, scaling in structures.
Behavior of fibers, yarns and fiber-reinforced composites. Efficient methods of reliability engineering, mathematical statistics (random variables, random fields and processes, extreme value theories) connected with nonlinear fracture mechanics methods (study of behavior of quasibrittle materials/structures).
Stochastic optimization techniques, structural safety and reliability, stochastic computational mechanics, Monte Carlo simulation techniques, genetic algorithms.
Programming and software development.

Malpasset Dam before and after failure in 1956 (France, 12/02, 9:15 pm).
Malpasset dam before failure
Malpasset dam after failure
Both figures were obtained at RWTH Aachen, Germany within the framework of my cooperation with Dr. Chudoba. Sponsored by the German research foundation (DFG) in context of the Collaborative Research Center 532.
Microspe photo
Electron-microscope photo of fiber-reinforced composite cut.
Testing specimen
Yarn specimen after a tensile test.
Random field realizations of local material strength in 4-point bending tested beams and corresponding crack patterns.
Random Fields
Examples of 2 realizations of two cross-correlated 2-D random fields. For the simulation, advanced Monte-Carlo technique (Latin Hypercube Sampling) used in combination with orthogonal transformation of covariance matrix.
Random Fields

Updated on 06-06-07 Copyright © Miroslav Vorechovsky