The current legislative acts and regulatory and technical documents defining the requirements for the organization of the customer's activities are considered in the work. A review of studies with different approaches to the formation of organizational structures of the customer, depending on the types of construction, their volumes and features of objects, is carried out. The factors determining the requirements for the formation of organizational structures of the customer for various objects are highlighted.

Keywords: construction organization, technical customer, organizational structure, construction control, project approach

The purpose of the study is to improve the efficiency of Dijkstra's algorithm by using the shared memory model with OpenMP library and working on the principle of parallel execution in the implementation of the algorithm. Using Dijkstra's algorithm to find the shortest path between two nodes in a graph is quite common. However, the time complexity of the algorithm increases as the size of the graph increases, resulting in longer execution time, so parallel execution is a good option to solve the time complexity problem. In this research work, we propose a parallel computing method to improve the efficiency of Dijkstra's algorithm for large graphs.The method involves dividing the array of paths in Dijkstra's algorithm into a specified number of processors for parallel execution. We provide an implementation of the parallelized Dijkstra algorithm and access its performance using actual datasets and with different number of nodes. Our results show that Dijkstra's parallelized algorithm can significantly speed up the process compared to the sequential version of the algorithm, while reducing execution time and continuously improving CPU efficiency, making it a useful choice for finding shortest paths in large graphs.

Keywords: Dijkstra algorithm, graph, shortest paths, parallel computing, shared memory model, OpenMP library

The article discusses a method for taking into account the compression of concrete using standard formulas when calculating using an inverse numerical-analytical method, taking into account the actual rigidity of concrete filled steel tube elements. The inverse numerical-analytical method makes it possible to calculate concrete filled steel tube elements for strength and stability under eccentric compression. Dependencies are presented showing the possibility of taking compression into account at various eccentricities and flexibility.

Keywords: concrete filled steel tube elements, CFST, inverse numerical analytical method, nonlinear deformation model, concrete compression,concrete filled steel tube column, eccentric compression

The construction and substantiation of a finite element model of the capillary tube running-in process, which was obtained by drawing on a fixed mandrel, are considered. The rolling rolls are cylindrical and absolutely rigid. The condition for performing the work is a comparison of the resulting gap between the pipe and the mandrel and the facet formed during deformation. The solid-state model of the process is described by an adaptive grid. Under these conditions, an informative model was obtained, which was used in parametric analysis.

Keywords: drawing with a mandrel, capillary tube, extraction, rolling, model construction, compression selection, pipe size tolerance

The work is aimed at modeling the control system of a slitting machine of a paper machine in order to improve the quality of products and eliminate defects in winding density. The developed automated system implements the functions of controlling the operating modes of the machine, distributing the loads of the bearing shafts, braking the roll and tensioning the paper web.

Keywords: slitting machine, paper machine, automated control system, rewinder, pressure roller, decoiler, reeler, accelerating shaft, deflecting shaft, cutting section

The problem of developing an intelligent automated system for detecting defects in textile materials is considered. An analysis of machine learning and deep learning algorithms was carried out in relation to solving the problem of product quality control. The implementation of an artificial neural network implemented in a Raspberry Pi microcomputer and receiving a set of input data in the form of a large stream of images from a high-speed digital camera is considered. The stages of creating a model in Python using the TensorFlow and Keras libraries are described. The development process includes the preparation of initial data intended for training and testing the system, as well as testing the operation of the resulting neural network, which consists in recognizing images of defects on fabric according to classification criteria.

Keywords: machine learning, neural network, defect images, textile material, training, testing, accuracy

The dynamic system of the grinding machine is simulated, taking into account tool wear. The purpose of the simulation is to improve the algorithmic support of an active control microprocessor device. The vibration characteristics of the SIW-5 machine ring support have been studied at idle and during processing to determine the vibration level at the moment when the grinding wheel touches the workpiece. An algorithm for maintaining the cutting speed with a decrease in the diameter of the circle due to wear has been developed and modeled. characteristics of the ring support of the SIW-5 machine at idle and during processing for the development of algorithms for controlling the grinding process.

Keywords: grinding, bearing rings, active control, mathematical model of grinding, algorithmic support

The article analyzes the features of aspects of architectural activity in relation to the integration of cultural heritage objects into the structure of the modern urban environment. The cultural and historical environment, expressed in the format of material and artistic and aesthetic symbols and formations, remains a significant urban planning factor, a material objects of cultural heritage (subject-spatial structure of the cultural environment) they are considered as the most important city-forming elements that are in continuous interaction with other functional zones of the urban environment. Reorganization of the historical part of the urban environment or integration of objects of cultural and historical heritage the functional and territorial framework of a modern city appears to be multifactorial, a complex and responsible task of architectural design.

Keywords: modern architecture, urban environment, cultural and historical resource, traditions, heritage and modernity

This research presents a methodology for classifying construction objects with critical defects. The presented work is part of a larger research effort dedicated to a comprehensive systemic approach to solving the problem of restoring various types of housing and social infrastructure objects damaged by different types of events. The paper discusses an algorithm for classifying construction objects with critical defects, introduces the concept of "degree of defect criticality", proposes a hypothesis about quantitative values of defect criticality degree intervals, and describes the classification algorithm. The presented examples demonstrate a holistic systemic approach to solving the scientific problem of restoring damaged objects affected by various types of events such as fires, explosions, impacts, and floods. Research methods employed include synthesis and scientific analysis, data collection, statistical analysis, as well as destructive and non-destructive testing methods at different stages of the study. Conclusions and tasks for further research are formulated.

Keywords: critical defect, degree of criticality of defects, construction object, organizational structure, organizational and technological solutions, technical condition

Economic development directly depends on the creation of a network of roads of the highest category. Major road construction requires large capital investments and less funds are allocated for the operation of existing roads and infrastructure. Instead of replacing bridge structures, it is necessary to use their reconstruction. The article discusses the problem of reconstruction of bridge structures, namely the restoration of carrying capacity, which has decreased during many years of operation. The relevance of the study, its goals and objectives are noted. A classification of reinforcement structures according to various criteria is proposed. The types of bridge reinforcements often used in practice, their advantages and disadvantages, are analyzed. The presented material is illustrated with photographs of objects. Successful reconstruction directly depends on the qualifications of designers and contractors, since with insufficient reinforcement, the span continues to work and is overloaded and gradually collapses. A modern method of reinforcement based on the use of carbon composite is presented. Significant disadvantages of this method for strengthening bridges and its modification using a tensioning device to secure and tension the carbon lamellas have been noted. The use of a tensioning device allows the superstructure to be partially unloaded from permanent and temporary loads. The main conclusions are presented.

Keywords: bridge, strengthening, reconstruction, truss, carbon composite, lamella, load-carrying capacity, load-bearing capacity, tension

The modern cycle of creating simulation models is not complete without analysts, modelers, developers, and specialists from various fields. There are numerous well-known tools available to simplify simulation modeling, and in addition, it is proposed to use large language models (LLMs), consisting of neural networks. The article considered the GPT-4 model as an example. Such models have the potential to reduce costs, whether financial or time-related, in the creation of simulation models. Examples of using GPT-4 were presented, leading to the hypothesis that LLMs can replace or significantly reduce the labor intensity of employing a large number of specialists and even skip the formalization stage. Work has been conducted comparing the processes of creating models and conducting experiments using different simulation modeling tools, and the results have been formatted into a comparative table. The comparison was conducted based on the main simulation modeling criteria. Experiments with GPT-4 have successfully demonstrated that the creation of simulation models using LLMs is significantly accelerated and has great perspective in this field.

Keywords: Simulation modeling, large language model, neural network, GPT-4, simulation environment, mathematical model

A new building structure is proposed - a welded steel I-beam with a prestressed perforated wall. The prestress in the beam is created by stretching the web and subsequent welding with chords. Before prestressing, holes are cut in the wall. Using the LIRA-SAPR software package, a model is proposed that can be used to study the operation of a prestressed perforated beam (PNPB) structure. The influence of various forms of voids in the wall on the change in the stress-strain state of steel I-beams prestressed by the wall drawing is studied. A preliminary assessment was made of the favorable effect of prestressing in a conventional perforated beam on the stress-strain state of beams with different forms of perforations in the web.

Keywords: steel structures, prestressing, numerical experiment, normal and shear stresses, bearing capacity

This article discusses the issue of the features of measuring and predicting changes in the surface electric field strength in the atmosphere. The results of measurements of the atmospheric electric field strength are presented. The possibilities of forecasting changes in the surface electric field strength, including the use of numerical models, as well as the use of measurement results as an indicator of dangerous weather phenomena, are considered. The prospects of using the prediction of variations in the surface electric field intensity to predict adverse weather events and the importance of monitoring the intensity of the atmospheric electric field for understanding global climate change processes and the impact of the electric field on human health and the environment are discussed. For the research, a model was created that allows predicting electric field variations based on meteorological data. The developed neural network has shown good results. It is demonstrated that the use of neural networks can be an effective approach for predicting the parameters of the electric field of the surface layer of the atmosphere. In further research, it is planned to expand the measurement area by including additional parameters such as temperature, pressure and humidity in the analysis, as well as using more complex machine learning models to improve the accuracy of forecasts. In general, the results show that machine learning models can be effective in predicting variations of the electric field in the surface layer of the atmosphere. This can have practical applications in various fields such as aeronautics, meteorology, geology and others. Further research in this area contributes to the development of new methods and technologies in the field of electric power and communications and to improving our knowledge about the nature of the impact of atmospheric electrophysical phenomena on the environment and human health.

Keywords: electric field, surface layer of the atmosphere, measurements, methods, forecasting, modeling of variations in field strength

Repair and restoration binders and compositions based on them are needed primarily for the repair, restoration and restoration of cultural heritage sites both in the Russian Federation and abroad. They are subject to special requirements, so the conduct of related engineering and survey, research and development work is an important condition for the development of modern scientifically verified, practically tested and in demand in practice repair and restoration materials. One of the main conditions for the practical implementation of the proposed investment project is the presence of a mineral resource base in the region and the country. The resource potential of carbonate, halogen and clayey rocks is fully represented in the mountainous part of the Chechen Republic (CR). Based on the results of research and prospecting work on the territory of the Czech Republic, 6 forecast areas have been identified that are promising for the identification of deposits of carbonate, halogen and clay raw materials, mainly as lime, cement and multi-purpose. The work uses methods of analytical research and scientific generalizations, expert assessments, process modeling and system analysis. The classification of inorganic binders was performed, which for the first time included organic-inorganic binders and additives in repair and restoration binders and compositions. As a result of exploratory research, it was proposed to repair, restore and restore historical and cultural monuments using the ones developed at the Kh.I. Ibragimov RAS of modern technologies and materials for repair and restoration work. To assess and correct the scientific problem associated with the development of repair and restoration binders and repair and restoration compositions, a review of historical experience was made. A concept for the development of a new scientific direction "High-strength composite materials based on lime (hydraulic and hydrate), gypsum (gypsum and anhydrite) and magnesia binders for the repair and restoration of cultural heritage sites" has been developed.

Keywords: repair and restoration binders, repair and restoration compositions, hydraulic lime, hydrated lime, gypsum, anhydrite, dolomite, magnesian binders, carbonization, decarbonization, carbonate raw materials, cement raw materials, clays, limestones

The aim of this work is the implementation and comparison of genetic algorithms in the framework of the problem of reinforcement learning for the control of unstable systems. The unstable system will be the CartPole Open AI GYM object, which simulates the balancing of a rod hinged on a cart that moves left and right. The goal is to keep the pole in a vertical position for as long as possible. The control of this object is implemented using two learning methods: the neuroevolutionary algorithm (NEAT) and the multilayer perceptron using genetic algorithms (DEAP).

Keywords: machine learning, non-revolutionary algorithms, genetic algorithms, reinforcement learning, neural networks