Stochastic nonlinear fracture mechanics finite element analysis of concrete structures

The paper summarizes the main outcomes achieved within the framework of the research project “Nonlinear fracture mechanics of concrete using stochastic finite elements and random fields”. The project focused on randomization of nonlinear finite element analysis of concrete structures. Theoretical as well as practical application aspects are presented emphasizing the conceptual framework and key points of the solution. Efficient techniques of both nonlinear numerical analysis of concrete structures and stochastic simulation methods of Monte Carlo type have been combined in order to offer an advanced tool for the assessment of the real behavior of concrete structures from statistical and reliability points of view.

[1]  Drahomír Novák,et al.  Simulation of random fields for stochastic finite element analyses , 2005 .

[2]  Arthur H. Nilson,et al.  Design of concrete structures , 1972 .

[3]  Drahomír Novák,et al.  Role of deterministic and statistical length scales in size effect for quasibrittle failure at crack initiation , 2005 .

[4]  Qiang Yu,et al.  Designing Against Size Effect on Shear Strength of Reinforced Concrete Beams Without Stirrups: I. Formulation , 2005 .

[5]  Ferhun C. Caner,et al.  Microplane Model M4 for Concrete. I: Formulation with Work-Conjugate Deviatoric Stress , 2000 .

[6]  R. Iman,et al.  A distribution-free approach to inducing rank correlation among input variables , 1982 .

[7]  David Lehký,et al.  Neural Network Based Identification of Material Model Parameters to Capture Experimental Load-deflection Curve , 2004 .

[8]  D. Huntington,et al.  Improvements to and limitations of Latin hypercube sampling , 1998 .

[9]  Vladimir Cervenka,et al.  COMPUTER SIMULATION OF FAILURE OF CONCRETE STRUCTURES FOR PRACTICE , 2002 .

[10]  Drahomír Novák,et al.  Statistical size effect in quasibrittle materials: Computation and extreme value theory , 2004 .

[11]  Ronald L. Iman,et al.  Risk methodology for geologic disposal of radioactive waste: small sample sensitivity analysis techniques for computer models, with an application to risk assessment , 1980 .

[12]  Richard J. Beckman,et al.  A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code , 2000, Technometrics.

[13]  Drahomír Novák,et al.  Structural reliability assessment of computationally intensive problems - nonlinear FEM analysis , 2002 .

[14]  V.,et al.  IDENTIFICATION OF SHEAR WALL FAILURE MODE , 2004 .

[15]  R. Kielbasa,et al.  Efficient average quality index estimation of integrated circuits by modified Latin hypercube sampling Monte Carlo (MLHSMC) , 1997, Proceedings of 1997 IEEE International Symposium on Circuits and Systems. Circuits and Systems in the Information Age ISCAS '97.

[16]  Daniel A. Kuchma,et al.  How Safe Are Our Large, Lightly Reinforced Concrete Beams, Slabs, and Footings? , 1999 .

[17]  D. Novák,et al.  Statistical correlation in stratified sampling , 2003 .

[18]  V Cervenka,et al.  SIMULATING A RESPONSE , 2000 .

[19]  Konrad Bergmeister,et al.  Stochastische Parameteridentifikation bei Konstruktionsbeton fuer die Betonerhaltung / Probabilistic response identification and monitoring of concrete structures , 2004 .

[20]  K. Willam,et al.  Triaxial failure criterion for concrete and its generalization , 1995 .

[21]  M.R.A. van Vliet,et al.  Size Effect Of Concrete In Uniaxial Tension , 1970 .