Łukasz Sadowski

New nondestructive way of identifying the values of pull-off adhesion between concrete layers in floors

AbstractThis paper presents a new nondestructive way of identifying the values of pull-off adhesion between the concrete layers in concrete floors. It based on the roughness parameters of the base layer surface, using the nondestructive optical technique, and on the floor surface, using the nondestructive acoustic techniques and employing artificial neural networks (ANNs) for this purpose. The new way has a potential for being widely used in practice, whereby it may become possible to employ previously trained ANNs to identify the pull-off adhesion, without impairing the surface of the tested concrete floor.

Methodology of nondestructive identification of defective concrete zones in unilaterally accessible massive members

AbstractThe paper deals with the nondestructive identification of defective concrete zones in unilaterally accessible massive members, for example, access galleries in hydroelectric power plants. The concrete in such zones is, for various reasons, excessively porous. The authors propose to use state-of-the-art acoustic testing techniques, including ultrasonic tomography, integratively to detect and identify defective zones. An original methodology for such tests has been developed. The methodology is illustrated with an example of its practical application to a real civil engineering structure.

Non-destructive evaluation of the pull-off adhesion of concrete floor layers using rbf neural network

Abstract The interlayer bond is one of the primary qualities assessed during an inspection of floor concrete workmanship. The measure of this bond is the value of pull-off adhesion f b determined in practice by the pull-off method. The drawback of this method is that the tested floor is damaged in each of the test points and then needs to be repaired. This drawback can be overcome by developing a way which will make it possible to test floors in any point without damaging them locally. In this paper it is proposed to evaluate the pull-off adhesion of the top layer to the base layer in concrete floors by means of the radial basis function (RBF) artificial neural network using the parameters evaluated by the non-destructive acoustic impulse response technique and the non-destructive optical laser triangulation method. Presented RBF neural network model is useful tool in the non-destructive evaluation of the pull-off adhesion of concrete floor layers without the need to damage the top layer fragment from the...

Prediction of Concrete Compressive Strength by Evolutionary Artificial Neural Networks

Compressive strength of concrete has been predicted using evolutionary artificial neural networks (EANNs) as a combination of artificial neural network (ANN) and evolutionary search procedures, such as genetic algorithms (GA). In this paper for purpose of constructing models samples of cylindrical concrete parts with different characteristics have been used with 173 experimental data patterns. Water-cement ratio, maximum sand size, amount of gravel, cement, 3/4 sand, 3/8 sand, and coefficient of soft sand parameters were considered as inputs; and using the ANN models, the compressive strength of concrete is calculated. Moreover, using GA, the number of layers and nodes and weights are optimized in ANN models. In order to evaluate the accuracy of the model, the optimized ANN model is compared with the multiple linear regression (MLR) model. The results of simulation verify that the recommended ANN model enjoys more flexibility, capability, and accuracy in predicting the compressive strength of concrete.

ANN modeling of pull-off adhesion of concrete layers

When making and repairing concrete floors it is vital to properly prepare the interlayer bonding surface. The measure of the bond is the value of pull-off adhesion fb experimentally determined in building practice by the semi-destructive (SDT) pull-off method. In this paper it is proposed to assess pull-off adhesion by jointly the optical laser triangulation method and the acoustic impulse response method, using artificial neural networks (ANN), on the basis of a few parameters (independent of top layer thickness) determined by these methods. The proposed non-destructive (NDT) pull-off adhesion assessment method is devoid of the drawbacks and inconveniences of the pull-off method and makes possible the reliable mapping of the adhesion level on the tested surface without local damage to the latter.

New non-destructive method for linear polarisation resistance corrosion rate measurement

Corrosion of steel reinforcement is one of the most common causes of end service life in reinforced concrete structures. Corrosion is initiated and propagates unseen beneath the concrete cover and it is difficult to evaluate the severity of the problem. The most promising electrochemical method is the Linear Polarisation Resistance method which can provide a direct evaluation of the instantaneous rate of corrosion. The main drawback to this technique is that it requires a localized breakout of the concrete cover to provide an electrical connection to the steel reinforcement. This article describes an adaptation of the LPR method and the four-point Wenner resistivity method to give an assessment of the rate of steel corrosion without the requirement for a direct connection to the reinforcement. The measurements have been performed in cooperation with Construction and Infrastructure Group in University of Liverpool.

Determination of Damage in Reinforced Concrete Frames with Shear Walls Using Self-Organizing Feature Map

The paper presents the use of a self-organizing feature map (SOFM) for determining damage in reinforced concrete frames with shear walls. For this purpose, a concrete frame with a shear wall was subjected to nonlinear dynamic analysis. The SOFM was optimized using the genetic algorithm (GA) in order to determine the number of layers, number of nodes in the hidden layer, transfer function type, and learning algorithm. The obtained model was compared with linear regression (LR) and nonlinear regression (NonLR) models and also the radial basis function (RBF) of a neural network. It was concluded that the SOFM, when optimized with the GA, has more strength, flexibility, and accuracy.

Adhesion Assessment between Concrete Layers Using the Ultrasonic Pulse Velocity Method

Adhesion assessment between concrete layers with the use of the non-destructive ultrasonic pulse velocity (UPV) method has been described in the article. Two-layer concrete elements, obtained by drilling the core from a large size multilayer element, were the object of testing. The ultrasonic wave velocity of the element and the materials of which its layers were made were assigned for each element. On that basis, the comparative velocity i.e. the velocity at which an ultrasonic wave going through the boundary surface of layers wouldn’t cause any change in the velocity, was determined. The ratio of the two velocities has been compared to adhesion values obtained through the semi-destructive pull-off method. It was revealed that when the ratio of the ultrasonic wave velocity of the element to comparative velocity increases, the pull-off adhesion value also increases.

Barrage Lock Concrete Porosity Evaluation Using X-Ray Microtomography

This paper deals with the use of X-ray microtomography in evaluating the porosity of barrage lock concrete. The main parts of the lock were built in the years 1914-1917. Its high and low heads were founded on 2.70 m thick concrete slabs. Samples for laboratory tests were taken by core drilling at half of the slab thickness. The compressive strength of the concrete was determined and the porosity of the concrete was evaluated using X-ray microtomography. The compressive strength values ranged from 17.3 to 37.3 MPa. The porosity examination results are compared with the destructively determined concrete compressive strength values.

The effect of failure to comply with technological and technical requirements on the condition of newly built cement mortar floors

The article presents the results of “in situ” tests of two new cement mortar floors that were made defectively in an important public building with a large area. The performed results of organoleptic tests and extensive strength tests, which are helpful in determining the causes of numerous and various defects in floors, were presented. It was observed that the source of the aforementioned causes is not only the failure to comply with the technological and technical conditions and requirements for laying a cement mortar mix and the execution of floors but also the lack of appropriate supervision over the entire flooring process. The causes of defects were determined and should help to avoid similar situations in the future.