The article presents a systematic review of scientific works by domestic and foreign authors devoted to modeling fires in tunnels for various purposes. Using the search results in the databases of scientific publications eLIBRARY.RU and Google Scholar, 30 of the most relevant articles were identified that meet the following criteria: the ability to access the full-text version, the material was published in a peer-reviewed publication, the article has a significant number of citations, and the presence of a description of the results of the authors’ own experiments. An analysis was made of the methodology used in the research, as well as the results of studying fires in transport tunnels (road, railway, subway) and mine workings presented in the works. A classification of publications was carried out according to the types of tunnel structures, cross-sectional shape, subject of research, mathematical model used to describe the processes of heat and mass transfer in a gaseous environment and heating of enclosing structures, software used, validation of experimental data, and the use of scaling in modeling. It has been established that the problems of mathematical modeling of fires in deep tunnel structures, as well as modeling of a fire in a tunnel taking into account the operation of fire protection systems, are poorly studied.

Keywords: fire modeling, tunnel, mathematical model, fire prediction, heat transfer, structures, systematic review

Gantry piles have been developed to transfer a large load to the load-bearing foundation when erecting critical structures due to the larger contact area of the piles with the ground compared to vertical piles. The design of gantry pile foundations is the most labour-intensive. The responsibility of making a mistake increases when designing this foundation under seismic conditions. This paper deals with the modelling of the performance of cargo piles under seismic loading conditions in the construction of foundations for bridge piers. The results obtained are part of a larger scientific study on the feasibility of using gantry piles in high-rise construction in earthquakes of 6 to 10 on the Richter scale.

Keywords: gantry piles, deep foundation, seismic effects, overpass, modelling, finite element method, soil mass, stresses, deformations, foundation-soil mass system

The article is based on the results of a scientific study on modelling the operation of the system ‘foundation - ground mass’ of a special type of deep foundation - gantry piles in conditions of ground mass during the construction of the overpass of the M-12 ‘Vostok’ highway. Gantry inclined piles are designed to transfer more load to the foundation than traditional vertical piles. The purpose of this study is to select the angle of inclination of gantry piles for overpass support on the basis of mathematical modelling. The scientific novelty consists in the selection of the gantry pile foundation design for the support of a motorway overpass by mathematical modelling.

Keywords: gantry piles, deep foundation, overpass, modelling, finite element method, soil massif, stresses, deformations, stanchion, foundation-soil massif system

The large-scale development of Russia's lands led to the creation of a railroad network. Along with the laying of the railroad, the entire transportation infrastructure, such as bridges, tunnels and overpasses, was erected. Many structures are already more than 100 years old. The structures are deteriorating and approaching the end of their life cycle. It is therefore necessary to reconstruct or dismantle these structures. Due to the increased freight traffic between China, Russia and Western Europe, it is necessary to reconstruct all tunnels on the BAM. This paper presents one of the tunnel reconstruction options and investigates by mathematical modeling the stress-strain state of the system "array-construction" by which the tunnel can be reconstructed.

Keywords: mathematical modeling, stress-strain state, railway tunnel, reconstruction, finite element method, drilling and blasting, mechanized tunneling, mining machine, displacements, Baikal-Amur Mainline

Road surface quality assessment is one of the most urgent tasks in the world. To solve it, there are many systems that mainly interact with images of the roadway. They work on the basis of both traditional methods (machine learning is not used) and machine learning algorithms. Traditional approaches, for example, include methods for edge detection in images that are the object of this study. However, each of the algorithms has certain features. For example, some of them allow to get a processed version of the original photo faster. The following methods were selected for analysis: "Canny algorithm", "Kirsch operator", "Laplace Operator", "Marr-Hildreth algorithm", "Prewitt operator" and "Sobel Operator". The main indicator of effectiveness in the study is the average time to receive the processed photo. The initial material of the experiment is 10 different images of the road surface in 5 sizes (1000x1000, 894x894, 775x775, 632x632, 447x447) in bmp, jpg, png formats. The study found that the "Kirsch operator", "Laplace Operator" and "Prewitt Operator" and "Sobel operator" have a linear dependence of O(n), the "Canny algorithm" and the "Marr-Hildreth algorithm" have a quadratic character of O(n2). The best results are demonstrated by the "Prewitt Operator" and the "Sobel Operator".

Keywords: comparison, effectiveness, method, edge detection, image, photo, road surface, dependence, size, format

Asphalt concrete mixes are the primary construction material for road surfaces, and precise design of their composition plays a key role in the quality and durability of road pavements. This article discusses the challenges associated with designing asphalt concrete mix compositions and presents a developed system for automatic mix selection. The automatic asphalt concrete mix composition selection system is a powerful tool for optimizing the material selection process used in road construction. This system can calculate the optimal mix composition, taking into account technical and economic constraints, leading to increased accuracy and reliability in mix selection. The advantages of this system include reducing the time and cost of the selection process, enabling testing and analysis of various mix options, ultimately improving the quality and durability of road pavements.

Keywords: asphalt concrete, asphalt concrete mix, composition selection, least squares method, linear programming method, software, automation, Python, Microsoft Access

Roads have a huge impact on the life of a modern person. One of the key characteristics of the roadway is its quality. There are many systems for assessing the quality of the road surface. Such technologies work better with high-resolution images (HRI), because it is easier to identify any features on them. There are a sufficient number of ways to improve the resolution of photos, including neural networks. However, each neural network has certain characteristics. For example, for some neural networks, it is quite problematic to work with photos of a large initial size. To understand how effective a particular neural network is, a comparative analysis is needed. In this study, the average time to obtain the HRI is taken as the main indicator of effectiveness. EDSR, ESPCN, ESRGAN, FSRCNN and LapSRN were selected as neural networks, each of which increases the width and height of the image by 4 times (the number of pixels increases by 16 times). The source material is 5 photos of 5 different sizes (141x141, 200x200, 245x245, 283x283, 316x316) in png, jpg and bmp formats. ESPCN demonstrates the best performance indicators according to the proposed methodology, the FSRCNN neural network also has good results. Therefore, they are more preferable for solving the problem of improving image resolution.

Keywords: comparison, dependence, effectiveness, neural network, neuronet, resolution improvement, image, photo, format, size, road surface

Road surface quality assessment is one of the most popular tasks worldwide. To solve it, there are many systems, mainly interacting with images of the roadway. They work on the basis of both traditional methods (without using machine learning) and machine learning algorithms. To increase the effectiveness of such systems, there are a sufficient number of ways, including improving image quality. However, each of the approaches has certain characteristics. For example, some of them produce an improved version of the original photo faster. The analyzed methods for improving image quality are: noise reduction, histogram equalization, sharpening and smoothing. The main indicator of effectiveness in this study is the average time to obtain an improved image. The source material is 10 different photos of the road surface in 5 sizes (447x447, 632x632, 775x775, 894x894, 1000x1000) in png, jpg, bmp formats. The best performance indicator according to the methodology proposed in the study was demonstrated by the "Histogram equalization" approach, the "Sharpening" method has a comparable result.

Keywords: comparison, analysis, dependence, effectiveness, approach, quality improvement, image, photo, format, size, road surface

The quality of asphalt concrete mixture at the output of an asphalt concrete plant is unstable due to disturbances that we cannot control or control with significant delay. Disturbances may include factors such as inaccuracies in the existing relationships between the properties of asphalt concrete mixture components and the parameters of the technological process with the quality of the finished product. Disturbances can also be attributed to our lack of knowledge about the relationships between individual indicators and the quality of the mixture. Forecasting these disturbances to determine the actual quality at the output becomes a key task. Previously, determining the optimal length of data series for forecasting was a challenging task. Nowadays, with the use of modern technologies, this problem has been successfully solved. In this article, the authors propose an adaptive forecasting method to determine the optimal length of data series. The research results include forecasting error values with and without adaptation. The adaptive forecasting method demonstrated smaller values of mean absolute error (MAE) compared to the non-adaptive forecasting method (where the length of the time series is always equal to 100). This allows for more efficient and accurate prediction of cumulative disturbances, which is critically important for ensuring high and stable quality of asphalt concrete mixture.

Keywords: asphalt concrete, asphalt concrete mixture, disturbance, control system, autoregressive model, forecasting, adaptive forecasting method, optimal length of series, forecast accuracy, mean absolute error

The transitional type of pavement of highways is widespread in Russia. At the same time, the increased estimated time between repairs cannot be fully ensured by the adoption of existing design solutions for the installation of transitional pavement pavements. This is confirmed by the dynamics of changes in the operational state, presented on the example of the road of regional importance Birakan - Kuldur in the section km 0+000 - km 25+000 in the Jewish Autonomous Region. Non-failure operation during the estimated overhaul and estimated service life of the pavement is assessed by the destruction coefficient, the limit values of which are set in the regulatory documentation. A significant decrease in the pavement destruction coefficient during the first few years of operation indicates insufficient strength and stability of the transition pavement pavement, which determines the need to develop special measures to ensure them.

Keywords: road, pavement, transitional type of pavement, pavement, destruction coefficient, overhaul life, longitudinal evenness, strength

Prompt adjustment of the composition of the asphalt concrete mixture is key to achieving high quality asphalt concrete. To enable easy and rapid adjustment of the asphalt concrete mixture formulation, predicting the properties of asphalt concrete (Marshall stability) is critically important. There are many methods for predicting the properties of asphalt concrete, but the choice of one method or another is a very pressing problem. This article proposes two methods for forecasting Marshall stability: forecasting using a multiple linear regression model and forecasting using an autoregressive model. To evaluate the forecasting accuracy of models, we use two metrics: average absolute error (MAE) and average absolute percentage error (MAPE). The results of the study show that the autoregressive model exhibits better forecasting results, especially the second-order autoregressive model.

Keywords: asphalt concrete, control, composition adjustment, forecasting, multiple linear regression model, autoregression model, Marshall stability, forecast accuracy, mean absolute error, mean absolute percentage error

The article is devoted to mathematical modeling of construction of underwater tunnels intended for subway. This type of tunnels can also be used as railway and road tunnels. The most interesting are underwater tunnels-bridges and floating tunnels, but the most perspective and most frequent are tunnels located at the bottom of water barrier.

Keywords: underwater tunnel, subway, finite element method, leave section method, mathematical modeling, construction technology stages, transport tunnel, stress-strain state

Highways are a fairly significant part of the Iraqi transport system, characterized by increased accidents on the roads. Analysis of the causes of accidents showed their main cause – speeding cars in conditions of increased slipperiness and destruction of the road surface. The influence of the coefficient of adhesion and the degree of destruction of the roadway on the risk of an accident is investigated. Measures to reduce accidents on the roads of the republic are proposed.

Keywords: road safety, the risk of an accident, the coefficient of adhesion, the destruction of the coating, accident analysis, road repairs, the causes of increased accidents

To assess the quality of the road surface, there are many systems that work on the basis of specific algorithms, including image segmentation methods. Time complexity and classification accuracy are two key indicators when evaluating the effectiveness of a particular algorithm. In this article, the following image segmentation methods are used as the analyzed methods: k-means clustering, Linear clustering, Adaptive thresholding, Global thresholding. Based on the methods described in the section "Methodology of experiments", the "Global thresholds" method has the best indicators of classification accuracy and time complexity (38.2% - classification accuracy; time complexity is linear (other methods have the same type of complexity, however, GT has much less absolute time indicators).

Keywords: comparison, method, segmentation, image, photo, road, surface, condition, accuracy, classification, time, complextion

Road surface quality assessment is one of the most popular tasks around the world. To solve it, there are a large number of systems that work using certain algorithms, including methods of morphological image processing. One of the key criteria for the effectiveness of an algorithm is its time complexity. The following approaches of morphological processing is considered in the article: Dilation, Erosion, Morphological Gradient, Morphological Smoothing. Photos of the road surface of various conditions were used as the material for the study. Based on the proposed methodology of the experiment, it turned out that each of the selected algorithms has a linear time complexity, but the "Dilation" and "Erosion" algorithms have lower absolute time indicators.

Keywords: comparison, efficiency, morphological technique, processing, image, photo, road, condition, time, complexity

The article discusses the effect of adhesive additives on the performance properties of asphalt concrete. The authors give a comprehensive overview of the problem of durability of asphalt concrete layers, in particular in the autumn-spring period, emphasizing the importance of this issue for traffic safety. Then they discuss the role of adhesive additives in improving the performance of asphalt concrete by improving its physical and mechanical properties. The authors selected a number of adhesive additives, and also carried out the selection of asphalt concrete mixture according to the methodology of volumetric and functional design. The article contains a detailed description of the method for determining water resistance and adhesive properties. The authors also consider the effect of adhesive additives on the fatigue life of asphalt concrete. The text of the article provides a detailed description of the method for determining fatigue strength during repeated bending. In conclusion, the article emphasizes the importance of using adhesive additives to improve the performance and durability of asphalt concrete. The authors emphasize the importance of the study for extending the service life of asphalt concrete layers and increasing their repair time.

Keywords: bitumen, adhesive additive, low temperature property, water resistance, fatigue properties, composition selection, volumetric and functional design, durability, road, asphalt concrete, testing

The influence of surfactants, in particular adhesive and reducing additives, on the low-temperature and rheological properties of road bitumen is considered. Tests of the low-temperature properties of road bitumen with and without the use of appropriate additives were carried out, followed by a comparison of the results. Also, in order to assess the effect of the above surfactants on the ability of road bitumen to retain its properties over time, a comparative analysis of bitumen samples subjected to the aging process was carried out. In general, the results of this study indicate that the use of surfactants can lead to an increase in the durability of road bitumen, even at low temperatures.

Keywords: bitumen, surfactant, additive, low-temperature property, durability, road, asphalt concrete, rheology, aging process, testing