Currently, there is a scientific and practical deficit in new methods of integrated technological and design solutions based on improving the properties of concrete as the primary material that perceives compressive loads, and its joint work with various types of reinforcing rods. A new system using an integrated engineering approach to the design of building structures is proposed, which involves minimizing their cost and weight through numerical simulations and an experimental verification of the operation of reinforcing bars made of various materials in concrete of various densities. The control of the bearing capacity of reinforced building structures on the example of compressed elements is proposed to be carried out using the developed recipe-technological methods at the manufacturing stage. The economic and environmental efficiency of nano modification with the help of production waste and the use of lightweight dispersion-reinforced concrete to obtain such structures was revealed. The most effective concrete formulations showed strength gains ranging from 10% to 34%. Ultimately, this led to an increase in the bearing capacity of the elements up to 30%. The application of such an integrated lean approach will allow saving up to 20% of resources during construction.

Currently, in civil engineering, the relevant direction is to minimize the cost of the manufacture of the hollow structures of annular sections, as well as their construction and installation efficiency. To optimize the costs associated with building products and structures, it is proposed to apply the technology of vibrocentrifugation, to reconsider and comprehensively approach the raw materials for the manufacture of such products and structures. The purpose of this study is a theoretical substantiation and experimental verification with analytical numerical confirmation of the possibility of creating improved variotropic structures of vibrocentrifuged concrete nano-modified with ground granulated blast-furnace slag. The study used the methods of electron microscopy, laser granulometry, and X-ray diffraction. Slag activation was carried out in a planetary ball mill; samples were prepared on a special installation developed by the authors—a vibrocentrifuge. The optimal and effective prescription–technological factors were experimentally derived and confirmed at the microlevel using structural analysis. The mathematical dependencies among the composition, macrostructure, microstructure, and final properties of vibrocentrifuged concrete nano-modified by slag are determined. Empirical relationships were identified to express the variation of some mechanical parameters and identify the relationship between them and the composition of the mixture. The optimal dosage of slag was determined, which is 40%. Increases in strength indicators ranged from 16% to 27, density—3%.

Promising areas of concrete material science are maximum greening, reducing the carbon footprint, and, at the same time, solving the problems of increasing the cost of raw materials using industrial waste as modifiers for self-compacting concrete mixtures. This study aimed to review, investigate and test from the point of view of theory and practice the possibility of using various industrial types as a nano-modifier in self-compacting concrete with improved performance. The possibility of nano-modification of self-compacting concrete with a complex modifier based on industrial waste has been proved and substantiated theoretically and experimentally. The possibility of improving the technological properties of concrete mixtures using such nanomodifiers was confirmed. The recipe and technological parameters of the process were revealed and their influence on the characteristics of concrete mixes and concretes were expressed and determined. Experimental technological and mathematical dependencies between the characteristics of the technological process and raw materials and the characteristics of concrete mixtures and concretes were determined. The optimization of these parameters was carried out, a theoretical substantiation of the obtained results was proposed, and a quantitative picture was presented, expressed in the increment of the properties of self-compacting concrete mixtures using nano-modifiers from industrial waste concretes based on them. The mobility of the concrete mixture increased by 12%, and the fluidity of the mixture increased by 83%. In relation to the control composition, the concrete strength increased by 19%, and the water resistance of concrete increased by 22%. The ultimate strains decreased by 14%, and elastic modulus increased by 11%.

One of the unifying factors for all countries is the large consumption of chicken, and other, eggs in food and other types of economic activity. After using various types of eggs for their intended purpose, a large amount of waste accumulates in the form of eggshells. Currently, this problem exists and needs a non-trivial, original solution. The aim of the work was to fill the scientific gap in the direction of studying the microstructure formation of improved nano-modified environmentally-friendly concrete based on eggshell powder and obtaining a concrete composition for the manufacture of an industrial sample of such a material. An environmentally-friendly concrete was obtained, the characteristics of which were improved relative to standard concrete by modifying it with eggshell powder, for which the optimal dosage was determined. The most effective was the replacement of part of the cement with eggshell powder in the amount of 10%. The maximum increase in strength characteristics ranged from 8% to 11%. The modulus of elasticity increased by 4% compared to the control samples without eggshell powder. The maximum reduction in deformations under axial compression and tension in comparison with the control values ranged from 5% to 10%. The study of the composite’s microstructure nano-modified with eggshell powder, and an analysis of the changes occurring in this microstructure due to nano-modification, confirmed the improvement in characteristics and the optimal dosage of eggshell powder.

Currently, one of the topical areas of application of machine learning methods in the construction industry is the prediction of the mechanical properties of various building materials. In the future, algorithms with elements of artificial intelligence form the basis of systems for predicting the operational properties of products, structures, buildings and facilities, depending on the characteristics of the initial components and process parameters. Concrete production can be improved using artificial intelligence methods, in particular, the development, training and application of special algorithms to determine the characteristics of the resulting concrete. The aim of the study was to develop and compare three machine learning algorithms based on CatBoost gradient boosting, k-nearest neighbors and support vector regression to predict the compressive strength of concrete using our accumulated empirical database, and ultimately to improve the production processes in construction industry. It has been established that artificial intelligence methods can be applied to determine the compressive strength of self-compacting concrete. Of the three machine learning algorithms, the smallest errors and the highest coefficient of determination were observed in the KNN algorithm: MAE was 1.97; MSE, 6.85; RMSE, 2.62; MAPE, 6.15; and the coefficient of determination R2, 0.99. The developed models showed an average absolute percentage error in the range 6.15−7.89% and can be successfully implemented in the production process and quality control of building materials, since they do not require serious computing resources.