The article is devoted to the study of the influence of the choice of the calculation scheme on the accuracy of the engineering assessment of the behavior of monolithic reinforced concrete frame structures. Various types of models are considered: rod, plate and volumetric, taking into account both linear and physical nonlinearity. It is emphasized that the adequacy of accounting for the spatial interaction of elements, the reliability of the assessment of forces and stresses, as well as the possibility of optimizing design solutions, especially under seismic and wind loads, depend on the correctness of the adopted calculation scheme. As part of the study, a single-span reinforced concrete frame was modeled, the load on which varied from 5 to 55 kN. A comparison of the calculated results with experimental data was carried out. It is shown that models that take into account physical nonlinearity and use more detailed modeling (for example, volumetric finite elements) provide the greatest accuracy in predicting deflections and stresses in the structure. The obtained results confirm the necessity of a careful approach to the choice of the calculation scheme in design, especially in the design of high-rise buildings and structures in seismically dangerous areas. Recommendations are made on the rational use of models of different levels of detail in engineering practice.

Keywords: linear calculation, nonlinear calculation, frames, reinforced concrete, deflections, modeling

Introduction: Mobile Gaming Addiction (MGA) has emerged as a significant public health concern, with the World Health Organization recognizing it as a gaming disorder. Russia, with its growing mobile gaming market, is no exception. Aims and Objectives: This study aims to explore the feasibility of using neural networks for early MGA detection and intervention, with a focus on the Russian context. The primary objective is to develop and evaluate a neural network-based model for identifying behavioral patterns associated with MGA. Methods: A proof of concept study was conducted, employing a simplified neural network architecture and a dataset of 101 observations. The model's performance was evaluated using standard metrics, including accuracy, precision, recall, F1-score, and AUC-ROC score. Results: The study demonstrated the potential of neural networks in detecting MGA, achieving an F1-score of 0.75. However, the relatively low AUC-ROC score (0.58) highlights the need for addressing dataset limitations. Conclusion: This study contributes to the growing body of literature on MGA, emphasizing the importance of considering regional nuances and addressing dataset limitations. The findings suggest promising avenues for future research, including dataset expansion, advanced neural architectures, and region-specific mobile applications.

Keywords: neural networks, neural network architectures, autoencoder, digital addiction, gaming addiction, digital technologies, machine learning, artificial intelligence, mobile game addiction, gaming disorder

The article focuses on the application of machine learning methods for predicting failures in industrial equipment. A review of modern approaches such as Random Forest, SVM, and XGBoost is presented, with emphasis on their accuracy, robustness, and suitability for engineering tasks. Based on the analysis of real-world data (temperature, pressure, vibration, humidity), models were trained and compared, with XGBoost demonstrating the best performance. Key parameters influencing failures were identified, and a recommendation system was proposed, combining statistical analysis and predictive modeling. The developed solution enables timely detection of failure risks and optimization of maintenance processes.

Keywords: machine learning, predictive modeling, equipment management, failure prediction, data analysis

The article provides a comparative analysis of the approaches to forecasting rutting used in Russia and the USA. Mechanistic–Empirical Pavement Design Guide (MEPDG) and domestic regulatory documents are reviewed, and their key differences in forecast accuracy, applicability, and calculation complexity are identified.

Keywords: rutting, forecasting of road structures, MEPDG, monitoring of road conditions, regulatory methodologies

In the process of civil engineering, the role of the technical client is extremely important, since it is he who ensures control and coordination of all stages of construction, from the development of project documentation to commissioning of the facility. However, despite the importance of this role, technical client activities often face problems associated with ineffective management, high costs, schedule delays and quality deficiencies. Optimizing its activities can significantly increase the efficiency of the project and reduce risks. This article provides an analysis of possible ways to optimize the work of a technical client. Considered methods using modern software, training and improving the abilities of personnel, Total Quality Management and Lean Construction.

Keywords: technical client, project efficiency, civil engineering process management, lean construction

This article discusses the problem of determining the dynamicity coefficients in case of local damage to the truss in the steel frame of an industrial building. The analysis of the resistance of steel frames to local damage is an important area in the design of industrial buildings, especially those that belong to the category of increased responsibility. Damage to individual elements of the load-bearing system can cause a redistribution of forces and lead to a progressive collapse.

Keywords: diversification of management, production diversification, financial and economic purposes of a diversification, technological purposes of ensuring flexibility of production

In territorial planning, the choice of industrial territories is crucial for the state. The advantageous location will allow for the creation of labor application points to ensure stable economic growth. Understanding and taking into account the parameters of the formation and further functioning of such territories always require an integrated approach, that is, taking into account both economic and social, spatial and environmental factors. When planning, the accessibility of transport infrastructure, the availability of raw materials, tax incentives and other economic incentives can be key when choosing a particular area for the location of industrial facilities on it. An integrated approach can become especially relevant not only when planning new undeveloped territories, but also when converting existing large production areas.

Keywords: socio-economic development, comprehensive assessment, factors of the urban planning system, industrial park, industrial zone

The article considers the issues of improving the technology of preparing concrete mixtures for road surfaces at existing concrete mixing units without additional costs for their technical re-equipment. The essence of improving the preparation of concrete mixtures lies in the complex use of carbonate microfiller and superplasticizer additives in combination with the developed innovative method of preparing concrete mixture. The article shows that when using a polycarboxylate superplasticizing additive and a microfiller based on porous shell limestone in combination with the proposed method of preparing concrete mixture, it is possible to obtain road concrete with the required strength properties with a cement consumption reduced by 50 kg/m³.

Keywords: road concrete, superplasticizer, mineral micro filler, method of preparation of concrete mix

In this article, we examined the permeability of concrete and the effect of corrosion processes on the durability and reliability of reinforced concrete structures. Attention is paid not only to the causes and mechanisms of corrosion, but also modern methods and strategies for protecting concrete and reinforced concrete structures from it are provided, aimed at extending their service life and ensuring operational safety. This knowledge will allow engineers and builders to plan and implement projects more efficiently, reducing the risks and economic losses associated with corrosion processes.

Keywords: corrosion of concrete, corrosion of steel reinforcement, permeability, reinforced concrete, durability, strength, reliability

The article is devoted to the development and calculation of cable-stayed structures used as protective barriers against unmanned aerial vehicles (UAVs). The analysis of the design and calculation of cable-stayed structures for protective enclosing structures designed to counter UAVs is carried out. The main stages of the calculation are considered, including the determination of external loads, dynamic modeling of shock effects, finding the dynamicity coefficient through energy loss, and the conversion of kinetic energy into potential energy. The prospects for the development of this area are discussed with an emphasis on modularity, adaptability and integration of systems. It is concluded that cable-stayed structures are a promising solution for protecting critical facilities, providing high strength with minimal weight and cost.

Keywords: cable-stayed structures, impact impacts, protective enclosing structures, unmanned aerial vehicles, dynamic loads, dynamic coefficient, impact energy, inelastic impact

The article discusses the use of a recurrent neural network in the task of predicting pollutants in the air based on simulated data in the form of a time series. Neural recurrent network models with long Short-Term Memory (LSTM) are used to build the forecast. Unidirectional LSTM (hereinafter simply LSTM), as well as bidirectional LSTM (Bidirectional LSTM, hereinafter Bi-LSTM). Both algorithms were applied for temperature, humidity, pollutant concentration, and other parameters, taking into account both seasonal and short-term changes. The Bi-LSTM network showed the best performance and the least errors.

Keywords: environmental monitoring, data analysis, forecasting, recurrent neural networks, long-term short-term memory, unidirectional, bidirectional

The article contains the results of stress analysis in dangerous sections of a single-span steel box beam made of two channels, strengthened with two metal strips welded at the top and bottom between the channels, with different geometric characteristics of the strengthened elements. The results of a numerical experiment of strengthened beams are presented. According to the results of the numerical experiment, it was found that equalization of stresses in dangerous sections allows to reduce the material consumption of the structure in comparison with beams selected according to the assortment for the required moment of resistance.

Keywords: steel beam, load-bearing capacity, stresses, displacements, finite element method, structural strengthening

Steel hoisting ropes play an important role in metallurgical equipment, ensuring reliability and efficiency of lifting operations. One of the key features of their operation is the high level of contamination typical of metallurgical operations. Metallurgical processes are often accompanied by dust, metal chips and other abrasive particles that can significantly degrade ropes, causing wear and corrosion. To maintain the efficient operation of equipment it is necessary to monitor the condition of hoisting ropes in real time, which makes the task of improving automatic systems for monitoring the condition of ropes urgent. The paper reviews the methods of optical control of defects in hoisting steel ropes, the advantages and limitations of different approaches are considered. The aim of the work is to justify the effectiveness of the authors' developed method of analyzing rope defect images using neural networks in relation to the method based on the discrete Fourier transform. It is revealed that one of the most promising in terms of technical and economic efficiency of inspection methods is the application of vision system with image processing based on convolutional neural network technology, which allows to effectively detect defects in complex and changing operating conditions, such as metallurgical and mining production, where the background of the image may be non-uniform, and the distance between the camera and the rope varies.

Keywords: lifting ropes, vision systems, optical control methods, fast Fourier transform, hidden Markov models, convolutional neural networks

The article considers the issues of imitation modeling of fibrous material mixing processes using Markov processes. The correct combination and redistribution of components in a two-component mixture significantly affects their physical properties, and the developed model makes it possible to optimize this process. The authors propose an algorithm for modeling transitions between mixture states based on Markov processes.

Keywords: modeling, imitation, mixture, mixing, fibrous materials

This article discusses the basic concepts and practical aspects of programming using the actor model on the Akka platform. The actor model is a powerful tool for creating parallel and distributed systems, providing high performance, fault tolerance and scalability. The article describes in detail the basic principles of how actors work, their lifecycle, and messaging mechanisms, as well as provides examples of typical patterns such as Master/Worker and Proxy. Special attention is paid to clustering and remote interaction of actors, which makes the article useful for developers working on distributed systems.

Keywords: actor model, akka, parallel programming, distributed systems, messaging, clustering, fault tolerance, actor lifecycle, programming patterns, master worker, proxy actor, synchronization, asynchrony, scalability, error handling