Degradacja budynków zabytkowych wskutek nadmiernego zawilgocenia – wybrane problemy

The article presents selected, however, according to the author significant problems concerning the progressive degradation of historic buildings due to excessive moisture. The most important causes and effects of excessive moisture and salinity were highlighted. A decrease in the safety of a structure, a reduction of the thermal insulation of a building’s partitions and the deterioration of the operating conditions in rooms were, among others, indicated as the effects. The conditions of testing moisture using non-destructive methods, indicating those methods that are useful in historic buildings, were described. Moreover, the possibility of using artificial neural networks for a reliable moisture assessment was indicated. Actions that should be taken to prevent the progressive degradation of historic buildings, which is caused by excessive moisture and salinity, were signalled in chronological order.W artykule przedstawiono wybrane, ale zdaniem autora, istotne problemy dotyczące postępującej degradacji budynków zabytkowych wskutek nadmiernego zawilgocenia. Naświetlono najważniejsze przyczyny i skutki nadmiernego zawilgocenia i zasolenia. Mówiąc o skutkach wskazano między innymi na obniżenie bezpieczeństwa konstrukcji, zmniejszenie izolacyjności cieplnej przegród zewnętrznych oraz na pogorszenie warunków eksploatacyj-nych w pomieszczeniach. Omówiono uwarunkowania badania wilgotności metodami nieniszczącymi wraz ze wskazaniem użytecznych metod w budynkach zabytkowych, zasygnalizowano możliwości wykorzystania do wiarygodnej oceny wilgotności sztucznych sieci neuronowych. Sygnalnie sprecyzowano w ujęciu chronologicznym działania, które należy podejmować w celu zapobieżenia postępującej degradacji budynków zabytkowych powodowanej nadmiernym zawilgoceniem i zasoleniem

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

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

Stress failure of cement concretes under compression – synthesis of knowledge, conclusions

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. First published online: 04 Jul 201

Methodology for Controlling the Technological Process of Executing Floors Made of Cement-Based Materials

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

Non-Destructive Testing in Civil Engineering

The progressive development of civil engineering has forced scientists to improve the known methods and techniques of testing building materials, and also to search for new ones, e.g., non-destructive testing (NDT) methods [...

Non-Destructive Testing in Civil Engineering

The progressive development of civil engineering has forced scientists to improve the known methods and techniques of testing building materials, and also to search for new ones, e.g., non-destructive testing (NDT) methods [...

Attempts of modification the composition of concrete with nanoparticles in the light of the literature reports and own research

W pracy podkreślono, że w modyfikacji składu betonu nanocząstkami upatruje się możliwości poprawy cech fizycznych i mechanicznych otrzymanego z ich udziałem tworzywa. Zauważono, że w tym celu prowadzone są badania w wielu laboratoriach na świecie, a ich rezultaty są obiecujące, pomimo tego, że na chwilę obecną badania są niepełne i mocno rozproszone. Stwierdzono, że brak jest między innymi badań betonu samozagęszczającego się modyfikowanego nanododatkami. W pracy zaprezentowane zostały rezultaty badań własnych takiego betonu, mające na celu wypełnienie luki w literaturze. Łącznie badaniom poddano 11 serii betonu samozagęszczającego się modyfikowanego różną ilością trzech nanododatków, w zakresie cech reologicznych mieszanek betonowych, porowatości stwardniałego betonu, wytrzymałości na ściskanie i twardości. Otrzymano rezultaty wskazujące na to, że nanododatki wpływają na poprawę niektórych cech uzyskanego z ich udziałem betonu.The study emphasized that a possibility of improving physical and mechanical properties of concrete is seen in its modification with nanoparticles. It was observed that towards this goal studies are conducted in many laboratories in the world and their results are promising, even though research at the moment are not complete and highly scattered. It was concluded, that among others, there are no tests of self-compacting concrete modified with nanoadditives. In the paper results of own research of above mentioned concrete are presented, aimed at fulfilling gaps in the literature. In total 11 series of self-compacting concrete modified with various amount of three nanoadditives were investigated, in the scope of rheological properties of the concrete mix, porosity of the hardened concrete, compressive strength and hardness. Obtained results indicate that nanoadditives impact on improving some properties of the concrete made with their participation

The influence of an additive in the form of selected nanoparticles on the physical and mechanical characteristics of self-compacting concrete

The influence of nanoparticle additives on the physical and mechanical characteristics of hardened self-compacting concrete (SCC) was studied. Research included SCC concretes modified with different amounts of SiO2, TiO2 and Al2O3 nanoparticle additives and one reference concrete made without nanoparticles. Rheological properties, microstructure and compressive strength were determined. The obtained results showed that SiO2 and Al2O3 additions worsened the workability while the compressive strength was increased in the case of SiO2 addition. All studied nanomaterials densified the microstructure of the hydrated binder matrix.Peer reviewe

Historical Buildings Dampness Analysis Using Electrical Tomography and Machine Learning Algorithms

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