Krzysztof Schabowicz

State-of-the-art non-destructive methods for diagnostic testing of building structures - anticipated development trends

The paper presents a survey of state-of-the-art non-destructive diagnostic techniques of testing building structures and examples of their applications. Much attention is devoted to acoustic techniques since they have been greatly developed in recent years and there is a clear trend towards acquiring information on a tested element or structure from acoustic signals processed by proper software using complex data analysis algorithms. Another trend in the development of non-destructive techniques is towards assessing characteristics other than strength in elements or structures, particularly the ones made of concrete or reinforced concrete. The paper focuses on techniques suitable for: detecting defects invisible on the surface, estimating the depth of cracks, determining the dimensions of elements accessible from one side only and 2D and 3D imaging of reinforcement distribution in such elements. Finally, directions of further development in this field are indicated.

Application of artificial neural networks to determine concrete compressive strength based on non‐destructive tests

Abstract The paper deals with the neural identification of the compressive strength of concrete on the basis of non‐destructively determined parameters. Basic information on artificial neural networks and the types of artificial neural networks most suitable for the analysis of experimental results are given. A set of experimental data for the training and testing of neural networks is described. The data set covers a concrete compressive strength ranging from 24 to 105 MPa. The methodology of the neural identification of compressive strength is presented. Results of such identification are reported. The results show that artificial neural networks are highly suitable for assessing the compressive strength of concrete. The neural identification of the compressive strength of concrete has been verified in situ.

Identification of moisture content in brick walls by means of impedance tomography

Purpose – This paper aims to present a new non‐destructive method of brick wall dampness testing in real building structures. The electrical impedance tomography (EIT) method makes it possible to obtain a distribution of wall dampness. The paper aims to give basic information about the measuring system, including prototype equipment. The setup was used to determine the dampness of test brick walls on a specially built laboratory test rig. The paper seeks to compare test results obtained by the non‐destructive impedance tomography method with the results obtained by the conventional destructive dry‐weight method.Design/methodology/approach – The paper adopts a tomography approach to control humidity inside of the brick walls. In case of brick walls other nondestructive methods fields, for example, the ultrasonic tomography is useless. On the other hand the most popular dry‐weight method is strictly forbidden for historical buildings. As a forward solver, functionally graded material boundary element method...

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.

Application of artificial neural networks in predicting earthmoving machinery effectiveness ratios

Many constructional processes are carried out by machines working together and forming technological systems. An example here can be an earthmoving machinery set made up of excavators and means of transport. For process design purposes most important are the effectiveness ratios relating to the profits and losses stemming from system use, i.e. the system efficiency per unit work ratio W(N); the index of losses due to the idle times of the machines working in the system Sj; the output transport unit cost index Kj. This paper presents the results of applying neural networks in predicting effectiveness ratios, i.e. W(N), Sj and Kj for earthmoving machinery systems consisting of c excavators and N means of transport. It is showing the relevance to practitioners and researchers industry. The values of the characteristics can form a standard basis for designing construction earthworks. Having a dataset consisting of the technical parameters of earthmoving machinery systems and the corresponding effectiveness ratios one can train neural networks and then use the latter for the reliable prediction of W(N), Sj and Kj.

Methodology of Neural Identification of Strength of Concrete

In this article, a new technique of the neural identification of the compression strength of concrete on the basis of nondestructive tests is described. The neural training and testing processes were carried out on a data set created on the basis of nondestructive tests. The data set covers a concrete compression strength range from 24 to 105 MPa after 28 days of curing. The methodology of the neural identification of the compression strength of concrete is presented. The results presented herein demonstrate that the identification of compressive strength of concrete by neural networks on the basis of such nondestructive methods as ultrasonic, sclerometric, and pull-out is a viable technique.

METHODOLOGY FOR NON-DESTRUCTIVE IDENTIFICATION OF THICKNESS OF UNILATERALLY ACCESSIBLE CONCRETE ELEMENTS BY MEANS OF STATE-OF-THE-ART ACOUSTIC TECHNIQUES

Abstract The paper presents a methodology for comprehensive use of ultrasonic tomography and impact-echo – the state-of-the-art acoustic techniques – for non-destructive identification of the thickness of unilaterally accessible concrete elements. Since the techniques are not commonly used, they are little known. Therefore, a brief description of the techniques is given to facilitate the understanding of the subsequently presented methodology. The article gives a practical example of the use of the methodology, which demonstrates its suitability for non-destructive identification of the thickness of concrete elements, particularly those only accessible from one side. In the example, the concrete shell of a heat pipe, carrying tunnel located under a river was tested using the ultrasonic tomography and impact-echo techniques. The tests were carried out according to the proposed methodology. It should be noted that the test results yielded by the two methods were similar. In this way, the proposed methodolog...

Analysis of failure conditions for a dynamically loaded composite floor system of an industrial building

Abstract Results of examination and analysis of cracks formation in a composite slab floor in an industrial warehouse hall is presented in the paper. During exploitation of the floor, on which lift trucks and presses worked, a lot of deep cracks occurred in the slab. In order to define characteristics of cracks and properties of concrete there were made different NDT examinations. Measurements of vibrations due to work of presses were also realized with aim to evaluate their possible influence on cracks formation. Static, dynamic and strength structural calculations were also made based on the model of continuous, multi-bay plate. They showed that applied slab reinforcement was sufficient and acting loads did not have to cause cracks. After 3D modelling of the building and taking into consideration the flexibility of main steel beams it was gained that in the RC floor slab over supports bending moments could occur nearly three times greater than calculated from the 2D model. Taking into consideration wron...