Petr Král

Inverse identification of the material parameters of a nonlinear concrete constitutive model based on the triaxial compression strength testing

The aim of this paper is to perform the inverse identification of the material parameters of a nonlinear constitutive model intended for the modeling of concrete which is known as the Karagozian & Case Concrete model. At present, inverse analysis is frequently used because it allows us to find the optimum parameter values of nonlinear material models. When applying such parameters, the resulting response of the structure obtained from a computer simulation is very similar to the real response of the structure based on the related experimental measurement. This condition then undoubtedly constitutes one of the progressive steps to refine the current numerical approaches. For the purposes of the inverse analysis performed in this paper the experimental data was obtained from the triaxial compression strength tests carried out on the concrete cylinders.

Using noise to generate the material structure of concrete

The contribution deals with the description and demonstration of an algorithm for the generation of spatial geometry – the material structure of concrete. The term “material structure of concrete” is taken to mean a mix of randomly distributed aggregate and cement binder, the latter being used to bond the aggregate. In order for the generated material structure to be as realistic as possible, a photograph of the material which is to be created is used as the input (i.e. data source) for the algorithm. The generation process itself involves the use of spatial noise functions, which are able to generate simple patterns as well as very complex fractals. The algorithm is based on the principle that similarities can be found between a suitably placed section cut through a noise space and the abovementioned input for the algorithm – a real photograph of the material. The functionality and individual steps of the algorithm are presented via two examples of concrete generation with differently shaped aggregate grains.The contribution deals with the description and demonstration of an algorithm for the generation of spatial geometry – the material structure of concrete. The term “material structure of concrete” is taken to mean a mix of randomly distributed aggregate and cement binder, the latter being used to bond the aggregate. In order for the generated material structure to be as realistic as possible, a photograph of the material which is to be created is used as the input (i.e. data source) for the algorithm. The generation process itself involves the use of spatial noise functions, which are able to generate simple patterns as well as very complex fractals. The algorithm is based on the principle that similarities can be found between a suitably placed section cut through a noise space and the abovementioned input for the algorithm – a real photograph of the material. The functionality and individual steps of the algorithm are presented via two examples of concrete generation with differently shaped aggregate gr...

Optimization of the material parameters of the continuous surface cap model for concrete

Modeling the nonlinear behavior of concrete within the problems of continuum mechanics for designing protective and military structures is now undoubtedly the subject of effort of staff of many scientific institutes. Striving for modeling real nonlinear behavior of concrete through sophisticated material models implemented in an even more sophisticated computing systems based mainly on the finite element method, however, brings with it certain problems. The main problem is especially a lack of knowledge of material constants (parameters) that must be defined to ensure proper function of a particular model. One possibility, which today enables the mentioned problem successfully solved, is the use of optimization procedures in order to find the correct values of the material parameters. Parameter optimization goes hand in hand with experimental investigation of concrete structures, while it trying to find parameter values of used material model of concrete so that the resulting data obtained from the numerical simulation will best approximate the experimental data. This paper deals with parameter optimization of nonlinear material model of concrete, which is implemented in a computing system LS-Dyna, with the use of optimization procedures and experimental data obtained from the direct tensile tests performed on specific concrete test specimens.

Simulating randomized failure of concrete targets

A new approach of involving the concrete-like materials heterogeneity into the simulations is described in the paper. The reason why the topic is so attractive is based on a need to capture the behaviour of real-world processes as well as possible. In case of protective structure design there is always a question which material should be used for the construction. And if the concrete-like material is chosen, how far one should go with its simulation complexity. With the Smoothed Particle Hydrodynamics (SPH) method we are able to simulate high speed loadings without any numerical difficulties. On the other hand, there is no approach of how to simply involve material heterogeneity (randomness) into the simulations using SPH. The main idea of this process (algorithm) is presented in the paper. The mathematical background as well as the numerical simulation example are described. All the aspects which need to be maintained to ensure algorithm functionality are described, too.

Steel Fibre Reinforced Concrete Simulation with the SPH Method

Steel fibre reinforced concrete (SFRC) is very popular in many branches of civil engineering. Thanks to its increased ductility, it is able to resist various types of loading. When designing a structure, the mechanical behaviour of SFRC can be described by currently available material models (with equivalent material for example) and therefore no problems arise with numerical simulations. But in many scenarios, e.g. high speed loading, it would be a mistake to use such an equivalent material. Physical modelling of the steel fibres used in concrete is usually problematic, though. It is necessary to consider the fact that mesh-based methods are very unsuitable for high-speed simulations with regard to the issues that occur due to the effect of excessive mesh deformation. So-called meshfree methods are much more suitable for this purpose. The Smoothed Particle Hydrodynamics (SPH) method is currently the best choice, thanks to its advantages. However, a numerical defect known as tensile instability may appear when the SPH method is used. It causes the development of numerical (false) cracks, making simulations of ductile types of failure significantly more difficult to perform. The contribution therefore deals with the description of a procedure for avoiding this defect and successfully simulating the behaviour of SFRC with the SPH method. The essence of the problem lies in the choice of coordinates and the description of the integration domain derived from them – spatial (Eulerian kernel) or material coordinates (Lagrangian kernel). The contribution describes the behaviour of both formulations. Conclusions are drawn from the fundamental tasks, and the contribution additionally demonstrates the functionality of SFRC simulations. The random generation of steel fibres and their inclusion in simulations are also discussed. The functionality of the method is supported by the results of pressure test simulations which compare various levels of fibre reinforcement of SFRC specimens.

Optimization-Based Inverse Identification of the Parameters of a Concrete Cap Material Model

Issues concerning the advanced numerical analysis of concrete building structures in sophisticated computing systems currently require the involvement of nonlinear mechanics tools. The efforts to design safer, more durable and mainly more economically efficient concrete structures are supported via the use of advanced nonlinear concrete material models and the geometrically nonlinear approach. The application of nonlinear mechanics tools undoubtedly presents another step towards the approximation of the real behaviour of concrete building structures within the framework of computer numerical simulations. However, the success rate of this application depends on having a perfect understanding of the behaviour of the concrete material models used and having a perfect understanding of the used material model parameters meaning. The effective application of nonlinear concrete material models within computer simulations often becomes very problematic because these material models very often contain parameters (material constants) whose values are difficult to obtain. However, getting of the correct values of material parameters is very important to ensure proper function of a concrete material model used. Today, one possibility, which permits successful solution of the mentioned problem, is the use of optimization algorithms for the purpose of the optimization-based inverse material parameter identification. Parameter identification goes hand in hand with experimental investigation while it trying to find parameter values of the used material model so that the resulting data obtained from the computer simulation will best approximate the experimental data. This paper is focused on the optimization-based inverse identification of the parameters of a concrete cap material model which is known under the name the Continuous Surface Cap Model. Within this paper, material parameters of the model are identified on the basis of interaction between nonlinear computer simulations, gradient based and nature inspired optimization algorithms and experimental data, the latter of which take the form of a load-extension curve obtained from the evaluation of uniaxial tensile test results. The aim of this research was to obtain material model parameters corresponding to the quasi-static tensile loading which may be further used for the research involving dynamic and high-speed tensile loading. Based on the obtained results it can be concluded that the set goal has been reached.

Study on Identification of Material Model Parameters from Compact Tension Test on Concrete Specimens

Identification of a concrete material model parameters using optimization is based on a calculation of a difference between experimentally measured and numerically obtained data. Measure of the difference can be formulated via root mean squared error that is often used for determination of accuracy of a mathematical model in the field of meteorology or demography. The quality of the identified parameters is, however, determined not only by right choice of an objective function but also by the source experimental data. One of the possible way is to use load-displacement curves from three-point bending tests that were performed on concrete specimens. This option shows the significance of modulus of elasticity, tensile strength and specific fracture energy. Another possible option is to use experimental data from compact tension test. It is clear that the response in the second type of test is also dependent on the above mentioned material parameters. The question is whether the parameters identified within three-point bending test and within compact tension test will reach the same values. The presented article brings the numerical study of inverse identification of material model parameters from experimental data measured during compact tension tests. The article also presents utilization of the modified sensitivity analysis that calculates the sensitivity of the material model parameters for different parts of loading curve. The main goal of the article is to describe the process of inverse identification of parameters for plasticity-based material model of concrete and prepare data for future comparison with identified values of the material model parameters from different type of fracture tests.

Comparison of responses of concrete damage material models with respect to optimization-based material parameter identification

Today, the inverse identification or optimization of material model parameters is very often used to find input parameter values for use in relevant nonlinear material models. These parameter values should enable the responses of structures obtained from numerical simulations to very closely approximate the real responses of such structures obtained from experiments. Due to the popularity of concrete as a construction material, much attention is paid to nonlinear material models that aim to describe its behavior. This paper is focused on the optimization-based inverse identification of the parameters of two related nonlinear concrete material models which are known as the Karagozian & Case Concrete model and the Karagozian & Case Concrete model - Release III. Within this paper, the identification of the material model parameters is performed on the basis of interaction between nonlinear numerical simulations, optimization algorithms and experimental data, the latter of which take the form of a loading curve measured during a triaxial compression test. A comparison of the responses of both of the used material models when the optimized parameters are employed is, of course, part of this paper.Today, the inverse identification or optimization of material model parameters is very often used to find input parameter values for use in relevant nonlinear material models. These parameter values should enable the responses of structures obtained from numerical simulations to very closely approximate the real responses of such structures obtained from experiments. Due to the popularity of concrete as a construction material, much attention is paid to nonlinear material models that aim to describe its behavior. This paper is focused on the optimization-based inverse identification of the parameters of two related nonlinear concrete material models which are known as the Karagozian & Case Concrete model and the Karagozian & Case Concrete model - Release III. Within this paper, the identification of the material model parameters is performed on the basis of interaction between nonlinear numerical simulations, optimization algorithms and experimental data, the latter of which take the form of a loading cur...

Concept and numerical simulations of a reactive anti-fragment armour layer

The contribution describes the concept and numerical simulation of a ballistic protective layer which is able to actively resist projectiles or smaller colliding fragments flying at high speed. The principle of the layer was designed on the basis of the action/reaction system of reactive armour which is used for the protection of armoured vehicles. As the designed ballistic layer consists of steel plates simultaneously combined with explosive material – primary explosive and secondary explosive – the technique of coupling the Finite Element Method with Smoothed Particle Hydrodynamics was used for the simulations. Certain standard situations which the ballistic layer should resist were simulated. The contribution describes the principles for the successful execution of numerical simulations, their results, and an evaluation of the functionality of the ballistic layer.