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Abstract The paper analyzes the causes of cracking in marble slabs that are embedded in the large-surface floor of a representative commercial building. In the case of many such objects, these slabs are laid on a concrete substrate and start cracking a short time after the start of operation. The "nature" of the occured cracks is presented, and the results of testing the adhesion between the marble slabs and concrete substrate using non-destructive impulse response and impact-echo methods, the results of strength tests of the marble slab specimens that were taken for laboratory tests, and also the results of visiual inspections of the concrete substrate are provided. These results were then related to the technology of laying marble slabs, and on this basis the causes of cracking were diagnosed while explaining their mechanism. The presented test results and analysis will be useful for people that implement and supervise works related to the execution of stone slab floors, in particular marble floors, with regards to an increase of the quality of such floors and the elimination of the causes of their cracking. Highlights • The paper analyses the causes of cracking in marble slabs, • The slabs were embedded in the floor of a representative commercial building, • The results of testing the adhesion between the slabs and substrate were presented, • The causes of cracking were diagnosed and the mechanism was explained, • The analysis will be useful for engineers that supervise the execution of slab floors. [ABSTRACT FROM AUTHOR]

The paper presents the results of studies of a total of 11 series of self-compacting concrete, which were modified with different amounts of the following nanoparticle additives: SiO 2 , TiO 2 and Al 2 O 3 , and also a reference concrete without the addition of nanoparticles. The study included the rheological properties of concrete mixes and the physical and mechanical properties of a hardened self-compacting concrete. The characteristics of air pores obtained using a computer image analyser and analysis of a microstructure with the use of a computer microtomograph are also presented. The paper contains the results of tests of compressive strength, flexural strength, hardness and elastic modulus, which were obtained using the nanoindentation technique. The obtained results were analyzed and commented on. [ABSTRACT FROM AUTHOR]

Non-destructive identification of the pull-off adhesion of a concrete substrate to an overlay mortar with variable thickness using artificial neural networks (ANNs) is studied in this paper. Selected ANNs with various training algorithms were tested on the basis of the parameter which describes the thickness of the overlay and also the parameters specified experimentally using non-destructive testing (NDT) methods. Real world data collected from experiments of pull-off adhesion were used for building our learner models. The tests were carried out in the same place where tests using NDT methods were performed. Three variant analyses of the possibility of such identification were conducted. The variance was calculated for these testing methods and parameters obtained with their usage, without considering the parameter that describes the thickness of the overlay in this work. [ABSTRACT FROM AUTHOR]

The paper presents the results regarding the identification of the value of the pull-off adhesion between a concrete added layer with a constant thickness and a substrate concrete layer in existing elements. A method of identification, which is based solely on the use of artificial neural networks (ANNs) and two non-destructive acoustic methods: impact-echo and impulse response on the surface of the added layer, was developed. The methodology of identifying the pull-off adhesion between a concrete added layer and a substrate layer in existing elements was developed and presented in the paper and is useful in construction practice. [ABSTRACT FROM AUTHOR]

The use of the artificial neural network (ANN) for the non-destructive identification of the moisture content of saline ceramic bricks is presented in the following article. A database was built based on conducted laboratory tests of solid ceramic bricks using dielectric, resistive and microwave methods. The database consists of parameters determined with the above-mentioned methods and also parameters describing the type and concentration of salts in the bricks. As a result of carried out research and analysis it was proved that neural identification of the moisture content of saline ceramic bricks is possible. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for the non-destructive location and identification of cracks in unilaterally accessible massive concrete walls by means of the state-of-the-art acoustic methods of impulse response and ultrasound tomography. An example of the practical verification of the methodology used to investigate the concrete structure of a hydroelectric power plant is provided. [ABSTRACT FROM AUTHOR]

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 f b 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. [ABSTRACT FROM AUTHOR]

The results of studies into the usefulness of 3D surface roughness parameters determined by 3D laser scanning, for the nondestructive evaluation of the pull-off adhesion of concrete layers are presented. Twenty-one 3D roughness parameters were identified. Their correlations with pull-off adhesion f b determined by the semi-nondestructive pull-off method were established. For two of the parameters, i.e. the texture aspect ratio ( Str ) and the peak material volume ( Vmp ) the correlation coefficient was found to be high. The possibility of the nondestructive evaluation of the pull-off adhesion on the basis of solely the existing concrete topography examinations is critically looked at. [ABSTRACT FROM AUTHOR]

This paper presents a synthetic review of the existing knowledge on the stress failure of cement concretes under compression, based on the available literature and the authors’ own research. It is pointed out that there is no knowledge on the stress failure of new-generation concretes, which needs to be acquired through proper research. The usefulness of the knowledge on the stress failure of concrete under compression for building practice is highlighted. [ABSTRACT FROM AUTHOR]

This 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. [ABSTRACT FROM AUTHOR]

The 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. [ABSTRACT FROM PUBLISHER]

Abstract: A new technique of nondestructively assessing the compression strength of concrete, which employs artificial neural networks, is presented. A data set based on results of testing concretes (with a 28-day strength of 24–105MPa) by different nondestructive methods was used to train and test an artificial neural network. The methodology of neural identification of the strength is described. The obtained results, including those of the practical verification of the technique, are reported. [Copyright &y& Elsevier]

This article provides a new paradigm of concrete surface morphology and discusses the fundamental definitions of concrete surface metrology. The basic phenomena of the morphology of concrete are discussed. It also presents a synthetic description of widespread metrological methods used for characterizing the morphology of concrete surfaces. The critical analysis lists the advantages and weaknesses of the described methods. The classification and definitions of parameters useful for describing the morphology of surfaces is also presented. This classification particularly includes three-dimensional parameters (height, spatial, hybrid parameters, functions and related parameters, as well as miscellaneous parameters), which are also discussed in the context of concrete surfaces. The application of surface morphology methods in concrete has been widely investigated over the past decades. For this purpose, the selected examples of applications of the discussed methods and parameters for the measurement of the morphology of concrete surfaces are also specified. [ABSTRACT FROM AUTHOR]

• The failure of floors made of polyurethane-cement composites was presented. • The reason that led to the failure was improper use of the floor. • The forklift drive wheels allowed to spin pallets in order to deliver them. • The consequence of spinning was the rapid local increase in floor temperature. • The increased temperature caused a thermal shock to which the floor was not resistant. The article presents the results of microstructural and mechanical testing of a floor made of polyurethane-cement composite significantly damaged after short-term use. The floor is located in a large-scale production and warehouse building. There was a lot of damage, including local abrasions, roughness, burns, and burning of the floor, which all threaten the safety of its use. Based on the carried out tests, errors in the execution of the tested floor were excluded and it was shown that the technology of its execution was correct. It was demonstrated, on the basis of research, that the reason that led to the damage was the improper use of the floor. This improper use consisted of allowing forklift drive wheels to spin pallets in order to deliver them with goods when adding or picking pallets to or from the pallet stack. The consequence of spinning was the rapid local increase in floor temperature, which caused a thermal shock to which the floor was not resistant. [ABSTRACT FROM AUTHOR]

Taking into consideration the wide use of self-compacting concrete in engineering practice and the need to better understand its mechanical work, while at the same time attempting to use additives with a smaller grain size as a component of concrete, the paper presents the results of the authors' own research, conducted using the acoustic emission method, on the failure process of self-compacting compressed concrete both with and without the addition of 2.0% and 4.0% of SiO 2 and TiO 2 nanoparticles with regards to cement weight. The levels of crack initiation stresses σ i and critical stresses σ cr , which distinguish the individual stages of the investigated process, were determined. The obtained results were used to calculate the fatigue strength of all the concretes that were tested in the paper. Based on the achieved results, it can be concluded that the durability and safety of structures made of self-compacting concrete with the addition of SiO 2 and TiO 2 nanoparticles that are subjected to repeatedly variable loads will be higher when compared to structures made of concrete without these additives. • Failure process of SCC modified with SiO 2 and TiO 2 nanoparticles was investigated. • Course of the compressive stress failure was confirmed to have 3 stages. • Addition of nanoparticles increases levels of crack initiation and critical stresses. • SCC modified with nanoparticles may have higher fatigue strength. • Durability of SCC with nanoparticles subjected to variable loads is increased. [ABSTRACT FROM AUTHOR]

The article presents the results of multi-sensor evaluation of the concrete within the interphase between overlay and existing substrate with regard to pull-off adhesion. It has been shown that both the effective surface area of the existing concrete substrate and the contribution of the exposed aggregate on this substrate, as a result of concrete substrate surface treatment, have a significant impact on pull-off adhesion. The highest adhesion was obtained when the surface of the existing concrete substrate was shot-blasted. This method of surface treatment provides both a high coarseness of the surface of the existing concrete substrate and considerable exposure of the aggregate on this surface. In order to clarify why this method of surface treatment of existing concrete substrate is advantageous with regard to the possibility of obtaining high adhesion, scanning electron microscopy (SEM) was used. SEM microstructural analysis was performed on concrete cubic specimens taken from the interphase zone between the overlay and existing concrete substrate. The results of these studies, including the contact type between the overlay made of cement mortar and the existing concrete substrate, are presented in the study. [ABSTRACT FROM AUTHOR]

The article focus on the effect of the porosity within the interfacial zone on pull-off adhesion using X-ray micro computed tomography. The study shows that grinding of the concrete substrate causes a decrease of the thickness of the interfacial zone. However, shotblasting does not cause such decrease. It was shown that the fraction and the number of pores in the material within the interfacial zone between layers is different in three divided zones. Moreover, the relation between the fraction and the number of pores in the three zones and the pull-off adhesion f b between the layers was also shown. [ABSTRACT FROM AUTHOR]

In this work, the results of experimental research and numerical analyses considering using non-destructive testing and machine learning algorithms are presented. They were used to evaluate the interlayer bonding between the concrete repair mortar and repaired element. The analyses of using different machine learning algorithms for this purpose are presented and compared. Based on non-destructive and destructive measurements performed in 300 measuring places, the database was built. In order to predict the output, which was the pull-off adhesion, the artificial neural network, support vector machine and random forest algorithm were used. For simplifications of the numerical model as input only a few parameters were selected. Based on the numerical analyses, the most accurate algorithm for non-destructive evaluation of the pull-off adhesion in concrete repaired elements was selected. Its potential for using in construction practice was strengthened by performing experimental verification on separately made model element especially for this purpose. • The usefulness of machine learning algorithms for engineering purposes. • Evaluating pull-off adhesion by means of nondestructive measurements. • Comparative analyses of selected machine learning algorithm and NDT. • Simplified method for investigating the interlayer bonding. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the state of conservation of ceramic building materials (clay masonry units) containing a large share of waste materials in the form of ash and slag from coal combustion and sawdust from wood processing, operated for several decades in facing walls of religious buildings, in external environment conditions. For the purpose of this analysis, comparative tests were carried out on the samples of ceramic materials cut out from facing walls and samples extracted from the same ceramic materials; they were stored in laboratory conditions for the entire time. The following were investigated: initial water absorption, capillary rise, and porosity structure determined with mercury intrusion porosimetry (MIP). The research has shown, among other things, that the ceramic materials exploited in the external environment are characterized by an almost twofold increase in the initial rate of water absorption and by a different size of dominant pores and a pore size distribution in comparison with ceramic materials stored in laboratory conditions. The results, obtained for ceramic building materials (clay masonry units) containing the above-mentioned waste materials in their composition, constitute a novelty. They fill a gap in the literature by establishing how decades-long operation in natural conditions affected the capillary properties and the porosity structure of the ceramics under investigation. Based on the obtained research results, conclusions of cognitive and practical significance have been formulated that relate to the possibility of the exploitation of facing walls made of investigated ceramic materials. [ABSTRACT FROM AUTHOR]

• New method of evaluation of the bonding between the repair overlay and concrete element was presented. • The database was created based on laboratory tests of layered concrete elements. • Database was determined using non-destructive methods and pull-off method. • Selected artificial neural network algorithms such as: Levenberg-Marquardt, Broyden-Fletcher-Goldfarb-Shano and Conjugate Gradients were tested. • The new method has been experimentally verified. The article presents the application of artificial neural networks (ANNs) for the non-destructive identification of the pull-off adhesion f b values between the repair overlay with variable thickness and the substrate in concrete surface-repaired elements. For this purpose, a large database was built on the basis of the tests of model concrete elements. The numerical analyses were performed using this data and ANNs with various learning algorithms. Based on these analyses, it was shown that the ANN with the Broyden-Fletcher-Goldfarb-Shanno learning algorithm, with thirty-one input parameters and twenty hidden neurons, is the most useful for identifying the interlayer pull-off adhesion in repaired concrete elements. The reliability of the presented application of ANNs was confirmed on the basis of carried out validation, using a part of the database not used in the learning and testing. The application's reliability was also confirmed on the basis of experimental verification carried out using the results of tests performed on an additional model element made exclusively for this purpose. This is an important and original issue presented in the article. Another novelty presented in the article is the application of ANNs for a much more difficult case, which is the identification of the pull-off adhesion f b value of the repair overlay of variable thickness from the repaired element and in a very wide range of identified pull-off adhesion f b within the range of 0.5–3.60 MPa. Moreover, the unique value of the article is the use for the first time of spatial and function related parameters to describe the concrete surface morphology of a repaired element. The investigation presented in the article has also confirmed the high usefulness of these parameters for identifying the value of pull-off adhesion f b. [ABSTRACT FROM AUTHOR]

The article presents original complex methodology for the effective control of the entire process of executing floors made of cement-based materials. This methodology has been lacking in literature so far. The methodology was developed on the basis of many years of the authors' experience, which was acquired when diagnosing the technical condition of such floors. The methodology was preceded by a synthetic summary of the most important technological and technical requirements for floors made of cement-based materials. It was also enriched with a discussion of the problem documented by sample research results showing the state that may be the result of disregarding and not performing the necessary control activities. [ABSTRACT FROM AUTHOR]

The article deals with the problem of detecting moisture in the walls of historical buildings. As part of the presented research, the following four methods based on mathematical modeling and machine learning were compared: total variation, least-angle regression, elastic net, and artificial neural networks. Based on the simulation data, the systems for the reconstruction of "pixel by pixel" tomographic images were trained. In order to test the reconstructive algorithms obtained during the research, images were generated based on real measurements and simulation cases. The method comparison was performed on the basis of three indicators: mean square error, relative image error, and image correlation coefficient. The above indicators were applied to four selected variants that corresponded to various parts of the walls. The variants differed in the dimensions of the tested wall sections, the number of electrodes used, and the resolution of the 3D image meshes. In all analyzed variants, the best results were obtained using the elastic net algorithm. In addition, all machine learning methods generated better tomographic reconstructions than the classic Total Variation method. [ABSTRACT FROM AUTHOR]