scholarly journals Energy resource of reinforced concrete elements and structures for the deformation-force model of their deformation

Author(s):  
V M Romashko ◽  
O V Romashko
Author(s):  
V.M. Romashko ◽  
◽  
O.V. Romashko-Maistruk ◽  

Abstract. The article classifies, identifies and analyzes in detail the main disadvantages of existing models and methods for calculating the resource of building structure elements. A universal model and method for calculating the general and residual resources of reinforced concrete elements and structures that are under prolonged influence to operational loads are proposed. The generalized deformation-force model of the reinforced concrete elements and structures resistance to force effects is represented by an extended system of equations of the deformable solid mechanics. It is shown that the most important force and deformation parameters of the reinforced concrete elements state diagrams at all stages are functionally interconnected not only by rigidity, but by the potential energy of deformation. Therefore, due to the application of the hypothesis of invariability in a unit of volume and independence from the loading mode of the potential energy of their limiting deformation, this model has been developed to the energy level. The main advantages of the developed model of the reinforced concrete elements to force effects resistance in comparison with the existing force and deformation models in determining the resource of such elements are demonstrated. The methodology for calculating the general and residual life of reinforced concrete elements and structures is proposed to be built according to the deflections directly measured during field surveys or the step and width of the opening of normal cracks. In practice, they can be determined by geodetic, photogrammetric or any other means. The combination of the deformation-force model and the energy criterion makes it possible to calculate the general and residual resources of reinforced concrete elements and structures from a unified methodological standpoint. Therefore, the proposed "energy" hypothesis is recommended to be used as a universal energy criterion not only for the bearing strength exhaustion of the reinforced concrete elements, but also for limiting their deflections, as well as the width of the normal cracks opening under the action of any duration loads.


Author(s):  
Л. Р. Маилян ◽  
С. А. Стельмах ◽  
Е. М. Щербань ◽  
М. П. Нажуев

Состояние проблемы. Железобетонные элементы изготавливаются, как правило, по трем основным технологиям - вибрированием, центрифугированием и виброцентрифугированием. Однако все основные расчетные зависимости для определения их несущей способности выведены, исходя из основного постулата - постоянства и равенства характеристик бетона по сечению, что реализуется лишь в вибрированных колоннах. Результаты. В рамках диаграммного подхода предложены итерационный, приближенный и упрощенный способы расчета несущей способности железобетонных вибрированных, центрифугированных и виброцентрифугированных колонн. Выводы. Расчет по диаграммному подходу показал существенно более подходящую сходимость с опытными данными, чем расчет по методике норм, а также дал лучшие результаты при использовании дифференциальных характеристик бетона, чем при использовании интегральных и, тем более, нормативных характеристик бетона. Statement of the problem. Reinforced concrete elements are typically manufactured according to three basic technologies - vibration, centrifugation and vibrocentrifugation. However, all the basic calculated dependencies for determining their bearing capacity were derived using the main postulate, i.e., the constancy and equality of the characteristics of concrete over the cross section, which is implemented only in vibrated columns. Results. Within the framework of the diagrammatic approach, iterative, approximate and simplified methods of calculating the bearing capacity of reinforced concrete vibrated, centrifuged and vibrocentrifuged columns are proposed. Conclusions. The calculation according to the diagrammatic approach showed a significantly better convergence with the experimental data than that using the method of norms, and also performs better when using differential characteristics of concrete than when employing integral and particularly standard characteristics of concrete.


2016 ◽  
Vol 38 (2) ◽  
pp. 37-46 ◽  
Author(s):  
Mateusz Kaczmarek ◽  
Agnieszka Szymańska

Abstract Nonlinear structural mechanics should be taken into account in the practical design of reinforced concrete structures. Cracking is one of the major sources of nonlinearity. Description of deflection of reinforced concrete elements is a computational problem, mainly because of the difficulties in modelling the nonlinear stress-strain relationship of concrete and steel. In design practise, in accordance with technical rules (e.g., Eurocode 2), a simplified approach for reinforced concrete is used, but the results of simplified calculations differ from the results of experimental studies. Artificial neural network is a versatile modelling tool capable of making predictions of values that are difficult to obtain in numerical analysis. This paper describes the creation and operation of a neural network for making predictions of deflections of reinforced concrete beams at different load levels. In order to obtain a database of results, that is necessary for training and testing the neural network, a research on measurement of deflections in reinforced concrete beams was conducted by the authors in the Certified Research Laboratory of the Building Engineering Institute at Wrocław University of Science and Technology. The use of artificial neural networks is an innovation and an alternative to traditional methods of solving the problem of calculating the deflections of reinforced concrete elements. The results show the effectiveness of using artificial neural network for predicting the deflection of reinforced concrete beams, compared with the results of calculations conducted in accordance with Eurocode 2. The neural network model presented in this paper can acquire new data and be used for further analysis, with availability of more research results.


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