Introduction. The study is dedicated to evaluating the existing methods for monitoring the construction time of residential buildings and substantiating the advantages of the early warning system (EWS). Traditional tools such as schedules and monitoring are insufficiently effective due to their reactivity and inability to identify risks ahead of time. The aim is to demonstrate the transition from reactive management to proactive predicting likely problems [1]. Modernization of traditional methods by integrating digital tools, introducing predictive analytics and using hybrid management methodologies transforms time control from simple tracking into proactive projection becoming an important competitive edge, allowing the construction industry to effectively deal with challenges and achieve goals with a maximum accuracy.

Materials and Methods. The object of the study is a construction time management system that includes planning, monitoring, and response methods. The major drawbacks of the traditional approach are delayed identification of problems as these methods mainly record problems as they emerge. Assessments are biased and holistic information environment is lacking.

Research Results. As part of the study, the author is expected to design a unique system of EWS indicators adapted to the realities of the Russian construction conditions, a methodology for integrating predicative analytics into the BIM environment, as well as an economic and mathematical model for calculating the effect of EWS implementation. These solutions will reduce the number of missed deadlines by 20–30%, automatically detect risks a week or a week and a half before they emerge, and achieve up to a 95% accuracy in predicting project completion.

Discussion and Conclusion. The proposed measures have a high practical value as they contribute to reducing developers’ financial and reputational costs, implementing legislative norms and increasing amount of trust among those involved in the market. Integration of modern technologies, use of predictive models and flexible management approaches transform timing control from passive monitoring into active prevention of possible disruptions. It is assumed that the implemented method will provide a reduction in the number of cases of missed deadline by 20–30%, and will allow early detection of possible threats prior to the impact of negative consequences improving the quality of project time frame assessment.

Introduction. The study is aimed at solving the problem of non-systematic use of coastal areas of small rivers in Russian cities. The relevance is due to the existing fragmentary approach to their urban planning and design, while global experience has been displaying complex solutions. The aim of the study is to develop a methodology for decision-making in urban planning and design of coastal areas of small rivers in large cities based on a multi-criteria analysis.

Materials and Methods. The object of the study are coastal areas of small rivers of large cities. The authors propose making use of a systemic approach that accounts for adjacent functional zones, their mutual influence and expert assessment of significance.

Research Results. A methodology for decision-making in urban planning and design of coastal areas of small rivers has been developed, allowing for the analysis of the functional purposes of individual sections and their interaction at the predesign stage. In addition, an algorithm for identifying synergetic effects between different development zones has been designed.

Discussion and Conclusion. The approach proposed by the authors allows one to overcome the fragmentation of urban planning solutions regarding coastal areas of small rivers. The prospects of the study include expansion of the methodology due to incorporating environmental, economic, social and functional factors, as well as the application of the approach to a larger number of types of functional zones.

Introduction. Due to the latest wide-scale adoption of advanced technologies in the construction sector and the pressure to complete projects in the shortest time and at minimal cost, the principle of achieving a high-quality level in project implementation is a daunting task for those working in construction. In this context digital image analysis technology has served as a viable solution to meet the requirements for improving project management efficiency at different stages. This literature review examines the role of digital image processing technologies in monitoring construction materials and structures throughout the project lifecycle in order to improve their quality and efficiency. The aim of the study is to evaluate the efficiency of this technology compared to traditional methods, review the latest developments in digital image processing for monitoring building structures, and identify performance indicators such as time and cost, as well as mention obstacles preventing its wide-scale adoption in engineering.

Materials and Methods. More than 30 publications (2015-2024) covering AI algorithms (CNN, YOLOv4), 3D modeling (LiDAR, Structure from Motion) and BIM integration were systematically reviewed. Their applicability, scalability, and impact on structural condition monitoring were evaluated.

Research Results. According to the results, the use of digital image analysis technology as a tool for monitoring structures and quality control of construction materials at different stages of a project lifecycle caused improved project quality, reduced time and costs, and boosted decision-making at different stages of a project cycle. The integration of image processing with artificial intelligence and building information modeling systems proved to be accurate in detecting defects in buildings and building materials with a 25% increase in the project management efficiency.

Discussion and Conclusion. Digital image processing (DIP) holds a transformational potential, but it is facing some obstacles such as environmental influences, data heterogeneity and lack of standardization. LiDAR integration, development of sustainable machine learning models for multimodal data analysis, and strengthening interdisciplinary collaboration are set forth. In order to overcome the restraints, further research is required to optimize technologies for real-world operating conditions. DIP is revolutionizing design monitoring, but mass adoption is possible only by means of sustainable innovation, industry-wide partnerships, and adaptation to external factors.

Introduction. The heat supply system is one of the most important infrastructural components of the engineering support of the construction site. However, the process of modeling its life cycle, particularly in terms of information support, has not been sufficiently researched in the academia.

One of the main stages of the life cycle of any engineering system is design. The need to increase energy efficiency, reduce the cost of designing and, thereby, building central heating systems, and improve the environmental situation highlights the special urgency of introducing innovative technologies, in particular, artificial intelligence that can become an effective tool for solving the existing problems. The aim of the study is to increase the efficiency of the design stage of district heating systems based on the use of artificial intelligence and to assess the prospects for such an approach.

Materials and Methods. The research methodology includes comparative analysis, modeling, statistical data processing and expert assessment. The research results can be used in the development of new approaches to the design of heat supply systems using modern digital technologies.

Research Results. The proposed concept of life cycle management of heat supply systems, which includes the sequential implementation of five key stages (from pre-design preparation to disposal) allows for an integrated approach to optimizing all of the processes. At the same time, the design stage, which determines the basic parameters of energy efficiency, efficiency and reliability of heat supply, is of critical importance. In the context of digitalization of thermal power engineering, the integration of intelligent automated systems implementing multifactorial algorithmic modeling and optimization calculations is becoming particularly relevant. Modern artificial intelligence-based solutions provide comprehensive automation of design and engineering work, including creating detailed information models of facilities, high-precision forecasting of heat consumption, hydraulic control and optimization of the energy balance of the system. The introduction of such technologies not only compensates for the lack of qualified specialists and improves the quality of project documentation, but also contributes to significant optimization of operational performance: reducing fuel costs and minimizing the carbon footprint through rational allocation of energy resources and reduction in greenhouse gas emissions.

Discussion and Conclusion. The article discusses modern approaches to automated design of district heating systems using artificial intelligence technologies. A technique based on the use of machine learning, neural networks, and optimization algorithms is proposed to improve design efficiency, minimize energy loss, and reduce operating costs.

Introduction. In this paper, we consider the problem of predicting the strength of square-section centrally compressed short concrete-filled tubular columns using machine learning methods. Traditional methods, such as the finite element method and the theoretical-experimental approach involving selection of empirical formulas require significant computational resources and time. At the same time, these methods are not always capable of accounting for complex nonlinear dependencies between the parameters. The key objective is to develop a high-precision model capable of predicting the load-bearing capacity of columns using the major parameters.

Materials and Methods. For the current study, a database was generated containing the results of numerical experiments on calculating the load-bearing capacity of square-section concrete-filled tubular columns in a physically nonlinear formulation. As part of the study, models based on machine learning methods were designed and implemented using the Jupyter Notebook interactive computing platform. The main method is the CatBoost mechanism (Gradient Boosting Regressor). The resulting models were trained by means of nonlinear optimization methods.

Results. The article evaluates the degree of impact of each of the input parameters on the final predictions of the model. The results on the degree of impact for the CatBoost and Random Forrest Regressor (RFR) models are obtained. The quality of the resulting models evaluated using the R² value was 98% for CatBoost and 94% for RFR.

Discussion and Conclusions. The resulting approach has proved to be highly efficient in predicting the load-bearing capacity of concrete-filled tubular columns, providing a balance between the accuracy of the results and computational complexity.

Introduction. Precast reinforced concrete ribbed slabs are broadly used as floors and coverings for industrial, residential and public buildings. Their use in this capacity is due to the high technological efficiency of manufacturing, efficient use of concrete and the possibility of automating factory production. One of the critical tasks in designing such structures is to calculate the bearing capacity of normal cross sections. Traditional calculation methods are reliable, but they are outdated. Machine learning methods are increasingly being employed in engineering, where researchers are opting for artificial neural networks (ANNs). The use of traditional methods in processing structured data such as tables and databases has its limitations. Neural networks are capable of analyzing unstructured data such as text, images, and videos, which opens up new prospects for analyzing and comprehending information. The article sets forth an approach to neural network modeling of the bearing capacity of normal sections of prefabricated reinforced concrete ribbed slabs.

Materials and Methods. A structured and processed data array (dataset) includes 20 samples for which a computational model based on a multilayer perceptron has been developed and verified. The input parameters are the geometric as well as physical and mechanical characteristics of the slabs and the applied load, the output parameter is the limiting bending moment calculated using the limit state method.

Research Results. Training on a limited sample did not lead to retraining of the model due to the correct division of data into test, training and control batches and the use of the quasi-Newton optimization method. The model has displayed a high level accuracy and reliability. Artificial neural networks are capable of identifying nonlinear dependencies between the parameters with no a priori assumptions.

Discussion and Conclusion. The suggested model is not a substitute for the existing calculations, but it serves as an efficient digital tool for quick verification of design solutions, optimization of reinforcement and improvement of structural reliability. Its implementation into BIM systems and digital construction platforms is in compliance with the requirements of Industry 4.0 and creates new opportunities for designing prefabricated reinforced concrete structures.

Introduction. Due to the high volumes of lumber production in the Russian Federation, there is an issue of recycling used band saw blades (UBSB) with a service life of 20–500 hours. A way to tackle the problem at hand is to make use of UBSB as a reinforcement material for wood elements. This solution also contributes to a reduction in the cost of such structures by making a reinforcement material more affordable to purchase. This study focuses on investigating the adhesive strength of a UBSB-wood bond.

Materials and Methods. Studies of the adhesive strength of a “wood-reinforcement” adhesive joint have been a comparative analysis of the test results of samples with the inclusion of UBSB, as well as rods of a steel and composite reinforcement. Reinforcement elements were glued into pine wood blanks with an adhesive composition based on epoxy resin ED-20 (a hardener is polyethylene polyamine, a filler is quartz sand, a plasticizer is dibutyl phthalate). The tests were conducted by means of pulling out using the REM-100 machine at a speed of 5 mm/min. Statistical processing of the experimental results included the calculation of the average value of the destructive load for each group of the samples, as well as the variance, standard deviation, and coefficient of variation.

Research Results. The wooden samples with glued reinforcement bars showed a high strength of the wood–reinforcement joint which was close to the samples with a steel reinforcement with a difference of about 4% and was considerably beyond the strength of the samples with a composite reinforcement — up to 20%.

Discussion and Conclusion. The adhesive joint of wood with reinforcing elements made of reinforced concrete has a sufficiently high adhesive strength which was close to that of the samples with a steel reinforcement. Hence the use of UBSB as a material for reinforcing wooden elements and structures is an appropriate and efficient way of enhancing the performance of load-bearing structures made of wood. On top of that, such a solution would tackle the problem of the disposal of reinforced concrete, as well as to a degree reduce the cost of reinforced wooden structures (RWSs) "in action" due to the low cost of a reinforcing material.

Introduction. China's construction industry developed in three phases: the first peak occurred in the 1950s, and the second one in the 1980s and 1990s. Generally, buildings constructed during the construction boom were characterized by relatively low design and construction standards resulting in poor quality. Currently, buildings constructed during the first and second phases are entering a phase of "aging" due to some factors such as low construction standards and outdated construction methods. Both the buildings themselves and their structures are flawed. Over time, most buildings exhibit varying degrees of deterioration and serious damage requiring urgent inspection, repair, and reinforcement. To meet the needs of social development, proper repair, reinforcement, and reconstruction of existing buildings is essential. The aim of this study is to identify the possibilities of reinforcing defective building structures with modern composite materials manufactured in China.

Materials and Methods. The object of the research are methods of strengthening reinforced concrete pillars. The author suggests using a systematic approach that accounts for the adjacent functional areas, their mutual influence and an expert assessment of their significance.

Research Results. The analysis showed that the strengthening mechanism for reinforced concrete columns subjected to axial compression and strengthened with carbon fiber sheets is a combination of carbon fiber sheets and concrete influenced by a host of factors. The strengthening method is strictly regulated, and the lateral restraint provided by the carbon fiber sheets under loading is capable of improving the compressive strength, structural stability, and durability of the columns.

Discussion and Conclusion. The strengthening methods for existing buildings vary widely, each with its own unique advantages and limitations. For example, bonded steel is fast to construct but requires a high quality; section enlargement is cost-effective but reduces space; carbon fiber strengthening offers numerous advantages but has limitations in investigating nodes and calculating load-bearing capacity. Although extensive research has been conducted on strengthening reinforced concrete axial compressed columns, the effectiveness depends on a host of factors. The discussion demonstrates that the choice of a strengthening method should be tailored to actual conditions. Carbon fiber strengthening requires further research, while strengthening axial compressed columns requires technological optimization. Furthermore, existing standards and regulations should be revised to reflect new advances and best practices.

Introduction. The major task in designing warehouse and storage facilities whose building structures experience horizontal operational loads is not only ensuring strength, load-bearing capacity and permissible vertical deformations (residue), but also stability and operability under the action of horizontal operational loads caused by lateral pressure from the weight of liquids or bulk materials. Traditional constructions of such structures made of monolithic reinforced concrete or metal are characterized by high material consumption, labor intensity and duration of construction (assembly). The article explores the prospects for constructing warehouse and storage facilities from prefabricated blocks of various structures.

Materials and Methods. Applied structures and technologies for constructing warehouse and storage facilities have been analyzed, their main disadvantages and issues arising at the stages of construction and operation have been identified. New structures of LEGO blocks and technology for the assembly of prefabricated buildings and structures using the method of vertical reinforcement of masonry for perceiving horizontal operational loads are set forth. Mathematical modeling and calculation of the parameters of the stress-strain state (hereinafter referred to as SSS) of warehouse structures made of LEGO blocks under the action of permanent and temporary operational loads from the weight of liquids or bulk materials has been conducted.

Research Results. New designs of LEGO blocks have been developed, a technology of constructing prefabricated warehouse and capacitive objects from them has been set forth, the regional parameters of vertical reinforcement of masonry from LEGO blocks have been identified depending on the height of the structure and the level of filling containers with liquid and bulk materials.

Discussion and Conclusion. The results are recommended for use in the design and construction of warehouse and storage facilities for agricultural and other purposes. The introduction of such structures implies an increase in the pace of construction, enhanced quality control of construction and a scientific justification for monitoring a technical condition during operation of a facility.

Introduction. The existing methods of non-destructive testing of concrete strength entail access to the concrete surface, which is not always possible to accomplish in concrete work technology. E.g., while continuously forming a structure in a sliding formwork, it is required that the strength of the concrete is identified during the molding process with no direct access to the layers of the hardening concrete mix being laid. The well-known method of identifying concrete strength by means of measuring its electrical resistance is neither commonly used nor standardized, and tends to yield contradictory results. The aim of the study of the first part of the article is to investigate the previously identified correlations between the concrete strength and its electrical resistance, to identify the advantages and disadvantages of measurement methods in order to find how feasible such an approach is for identifying a method for sinking concrete.

Materials and Methods. The classical method of literature review is employed with grouping of certain features into separate comparative tables followed by generalization assisting understanding an extent to which the research topic has been studied. Those were only the most important and informative, largely foreign, sources that were selected from the reviewed sources.

Research Results. The analysis of the review data enabled us to identify the methods of measuring electrical resistance (surface, volumetric, internal, direct ones), types of the investigated concrete, sample sizes, test dates, concrete strength ranges, types of dependencies and correlation coefficients. Among the factors affecting the measurement result were the following: water-cement ratio, type of binder and aggregates, type of additives, temperature of concrete, its porosity, etc. To explain the essence of the methods for identifying concrete electrical resistance, a brief overview is provided.

Discussion and Conclusion. The major difficulty of the indirect methods of identifying the strength lies in designing calibration dependencies with the results affected by a wide range of factors. There are also some difficulties with fastening of ohmic contacts to the formwork or concrete. All of these will be accounted for in follow-up studies to identify the relationship between the concrete strength and electrical resistance and to improve the measurement accuracy. The advantages of the method of strength control, such as maintaining the integrity of the structure, efficiency and low measurement complexity enable it to be employed in automated concrete technologies.

Introduction. When assessing the strength of concrete based on standard tests, there may be doubts about its compliance. The procedure for assessing the strength of concrete in such cases is carried out in accordance with GOST R 57360-2016 (Russian Federation) and STB EN 13791-2012 (Republic of Belarus). Fundamentally different approaches to assessing concrete strength are contained in EN 13791-2019 (introduced in 2020), many provisions of which differ significantly from the previous version and are new to specialists who monitor concrete strength during the construction stage and during the inspection of reinforced concrete structures.

Materials and Methods. The object of the study is a section of a concrete or reinforced concrete structure where the concrete strength is assessed when there is doubt about its compliance with established requirements. In such cases, the following concrete tests are conducted: preliminary indirect testing; indirect testing followed by the selection and testing of concrete specimens by the direct method from areas with the lowest concrete strength; testing of concrete specimens by the direct method.

Research Results. Information is provided on the selection of test areas and sites, their number, methods of core sampling and assessment of compressive strength of concrete based on the results of core testing, combined tests, including the indirect method and core testing. An analysis of concrete strength evaluation methods is performed in cases of doubt as to the compliance of concrete with the established requirements.

Discussion and Conclusion. The paper presents the fundamental differences in the methods for assessing the strength of concrete in structures in cases of doubt as to the compliance of concrete with the established requirements provided in in the European standard and the national standards of Russia and the Republic of Belarus. The disadvantages of the methodology set forth in EN 13791-2019 are outlined.