Bending of Concrete and Reinforced Concrete Elements Partially Filled with Steel Fibres

1989 ◽  
pp. 75-83
Author(s):  
Konstantin Yamboliev
Keyword(s):  
Reinforced Concrete ◽  
Steel Fibres ◽  
Concrete Elements

SETTING A DIAGRAM APPROACH TO CALCULATING VIBRATED, CENTRIFUGED AND VIBROCENTRIFUGED REINFORCED CONCRETE COLUMNS WITH A VARIATROPIC STRUCTURE

2020 ◽  
pp. 22-34
Author(s):  
Л. Р. Маилян ◽  
С. А. Стельмах ◽  
Е. М. Щербань ◽  
М. П. Нажуев
Keyword(s):  
Experimental Data ◽  
Reinforced Concrete ◽  
Bearing Capacity ◽  
Cross Section ◽  
Concrete Columns ◽  
Reinforced Concrete Columns ◽  
The Cross ◽  
Concrete Elements ◽  
Diagram Approach

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.

scholarly journals Application of artificial neural networks to predict the deflections of reinforced concrete beams

2016 ◽  
Vol 38 (2) ◽  
pp. 37-46 ◽  
Author(s):  
Mateusz Kaczmarek ◽  
Agnieszka Szymańska
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Network ◽  
Reinforced Concrete ◽  
Concrete Beams ◽  
Reinforced Concrete Beams ◽  
The Neural Network ◽  
Eurocode 2 ◽  
Artificial Neural ◽  
Concrete Elements

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.

scholarly journals Analyzing of Coatings on Steel - Reinforced Concrete Elements by Mobile NMR

2016 ◽  
Vol 62 (1) ◽  
pp. 65-82 ◽  
Author(s):  
J. Orlowsky
Keyword(s):  
Reinforced Concrete ◽  
Potential Effect ◽  
Building Site ◽  
Steel Reinforced Concrete ◽  
Mobile Nmr ◽  
The Individual ◽  
First Time ◽  
Concrete Elements ◽  
Non Destructive

Abstract A large number of infrastructural concrete buildings are protected against aggressive environments by coating systems. The functionality of these coating systems is mainly affected by the composition and thickness of the individual polymeric layers. For the first time ever, a mobile nuclear magnetic resonance (NMR) sensor allows a non-destructive determination of these important parameters on the building site. However, before this technique can be used on steel-reinforced concrete elements, the potential effect of the reinforcement on the measurement, i.e. the NMR signal, needs to be studied. The results show a shift of the NMR profile as well as an increase of the signals amplitude in the case of the reinforced samples, while calculating the thickness of concrete coating leading to identical results.

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