Numerical strategy for developing a probabilistic model for elements of reinforced concrete

Abstract

This paper introduces a new approach to model cracking processes in large reinforced concrete structures, like dams or nuclear power plants. For these types of structures it is unreasonable, due to calculation time, to explicitly model rebars and steel-concrete bonds. To solve this problem, we developed, in the framework of the finite element method, a probabilistic macroscopic cracking model based on a multiscale simulation strategy: the probabilistic model for (finite) elements of reinforced concrete (PMERC). The PMERC's identification strategy is case-specific because it holds information about the local behavior, obtained in advance via numerical experimentations. This information is then projected to the macroscopic finite element scale via inverse analysis. The numerical experimentations are performed using a validated cracking model allowing a fine description of the cracking processes. The method used in the inverse analysis is inspired from regression (supervised learning) algorithms: data on the local scale-the training data coupled with working knowledge of the mechanical problem-would shape the macroscopic model. Although the identification phase can be relatively time-consuming, the structural simulation is as a result, very fast, leading to a sensitive reduction of the overall computational time. It is proposed a first validation of this multiscale modeling strategy on a reinforced concrete slab-beam subjected to three-point bending. We achieved promising results in terms of global behavior and macrocracking (mainly crack openings), and an important reduction in calculation time-up to 99% reduction! So we believe this is a promising approach to solve bigger and more complex structures in shorter time.

Development and application of a new discrete element into simulation of nonlinear behavior of concrete

“…The first three features are the improvements compared to RBSM element while the last three are the advantage of discrete modeling compared to conventional continuum models like FEM methods that usually do not feature last three capabilities unless with implementation of specific methods. 24 The analysis software is developed in Visual Studio 25 compiled by Intel Fortran compiler 26 implementing Math Kernel Library 27 for matrixial calculations. Further advances achieved in this field can improve the ability to simulate and predict the behavior of engineering structures and estimate their durability and contribute to attaining a better understanding of the complicated behavior of materials.…”

“…In a nutshell, the merits of the RBCS model include: (a) the ability to incorporate Poisson effect without performing an iterative process, (b) retaining from modification of mechanical properties of the contact springs to incorporate Poisson effect, (c) improvement in capturing nonlinear behavior of concrete in compression by introduction of new material models, (d) the ability to so represent cracking and discontinuities in the model, (e) ability to capture stress transfer due to crack closure, (f) the ability to take the effect of the random possibilities for crack formation. The first three features are the improvements compared to RBSM element while the last three are the advantage of discrete modeling compared to conventional continuum models like FEM methods that usually do not feature last three capabilities unless with implementation of specific methods …”

Comparison between the cracking process of reinforced concrete and fibres reinforced concrete railway tracks by using non-linear finite element analysis

“…Then, this model was extended to analyze reinforced concrete and fibre reinforced concrete structures. All these numerical models have been, today, fully and deeply validated [1][2][3][4][5][6][7][8][9].…”