Background: Kazakhstan’s transport system plays a key role in Eurasian logistics due to its position along the Middle Corridor. However, multimodal freight transport remains under-optimized due to infrastructure bottlenecks, uneven cargo flows, and limited digital tools for forecasting and planning. Methods: This study presents the development of an agent-based simulation model for analyzing multimodal transportation in Kazakhstan. The model integrates railway, road, and maritime components, simulating cargo flows across export, import, and transit scenarios. Key agents include orders, transport vehicles, logistics hubs, and border checkpoints. The model is implemented in AnyLogic 8.9 and calibrated using a mix of official statistics, industry data, and field estimates. Results: The simulation replicates key logistics processes, identifies congestion points, and evaluates delivery performance under different scenarios. Experiments demonstrate how bottlenecks at terminals and border crossings affect delivery times, vehicle utilization, and hub load. The model allows testing infrastructure development options and scheduling policies. Conclusions: The approach enables a dynamic assessment of logistics efficiency under uncertainty and can support decision-making in transport planning. The novelty lies in the integrated simulation of multimodal freight flows with infrastructure constraints. The model serves as a foundation for digital twin applications and scenario-based planning.

The drying of crushed plant-derived materials, in particular crushed cotton stems, is a complex heat-exchange and technological task. Resolving this task successfully ultimately determines the specific energy costs of the drying process and the quality of the resulting products. The rational drying regime of crushed cotton stems should ensure the minimum possible process duration, energy costs, and provide the necessary quality characteristics of the dried material. To address this issue, it is necessary to investigate the influence of technological parameters of the process (the temperature and filtration rate of the heat agent), as well as the thickness of the stationary layer of crushed cotton stems, on drying kinetics. This paper has generalized experimental studies into the kinetics of filtration drying of crushed cotton stems during the period of complete saturation of the thermal agent with moisture. The influence of the temperature of the drying agent, the speed of its filtering through a stationary layer of different heights of wet crushed cotton stems, on the kinetics of filtration drying has been shown. The study's results demonstrate the dynamics of moisture removal at different parameters of the heat agent and the heights of the stationary layer of crushed cotton stems. The resulting dependence has been established, which is used to determine the value of the kinetic coefficient η for crushed cotton stems; the value of the kinetic coefficient has been calculated, a=20.74 1⁄m. The dependence has been derived, using which makes it possible to generalize the kinetics of filtration drying of crushed cotton stems during the period of complete saturation of the heat agent with moisture within the limits of changing the moisture content of the veneer The comparison of the experimental data with those obtained theoretically has shown that the maximum absolute value of relative error does not exceed 15.2 %.

This article is devoted to the issues of creating an adaptive intelligent system, for monitoring and controlling the technological process for electrochemical corrosion protection of main pipelines (MP), which has been designed for remote control of electrochemical protection (EChP) parameters and their optimization as well as adaptive control of the parameters of cathodic protection stations while taking into account changes in external conditions. The multi-objective problem of optimizing the operating modes of cathodic protection stations (CPS) is considered because optimization is carried out according to both the criterion of optimal distribution of the protective potential (uniform distribution of the protective total (pipe-to-soil) potential along the length of the pipeline) and to the criterion of the minimum total protective current of stations. The structure of the distributed electrochemical protection system is described in the article. A more complete picture of the protection of the pipeline and solving the problems of optimizing the electrochemical protection modes in real time is possible due to remote monitoring of control and measuring points (CMP) in the middle of the pipeline between neighboring cathodic protection stations, as well as in all corrosion and hazardous zones where they are also installed. In addition to the often-used GSM/GPRS networks in electrochemical protection systems, an energy-efficient LPWAN (Low-Power Wide-Area Network) data transmission network is also used and data collection is carried out using a cloud IoT platform. The functionality of the system is described, web application screens are shown in various operating modes for remote monitoring and control of the protective parameters of cathodic protection stations is reported. Analytical data processing for the tasks assessing the protection of objects in the pipeline system against corrosion are also shown. The system ensures that the electrochemical protection process is maintained at an optimal level between the destructive zones of “underprotection” and “overprotection”, taking into account monitoring data, geological conditions at the pipeline site, climatic or seasonal changes and other factors. In general, this system provides an increase in the reliability of the electrochemical protection system as a whole and, accordingly, it prevents possible emergency situations on the pipeline system while also reducing the cost of pipeline maintenance due to the reliability and continuity of protection.

Background: In the context of the digital transformation of transport systems and the increasing complexity of logistics flows, the role of intelligent route forming methods capable of accounting for the spatial structure of transport networks, time constraints and resource limitations is growing. This issue is particularly relevant for the Republic of Kazakhstan, which is characterized by a vast territory, a distributed network of transport nodes and significant transit potential. Methods: This article presents an integrated model for the intelligent optimization of freight transportation based on the combined use of the Google OR-Tools library and simulation modeling in the AnyLogic environment with the application of geographic information technologies. The main variants of vehicle routing problems are implemented, including VRPTW, CVRP, and MDVRP. Results: The developed model enables both identification of optimal routes and simulation of their execution in a dynamic environment, forming the basis for a digital twin of the transport system. Experimental studies demonstrate the impact of time constraints, capacity limitations, and spatial structure on routing solutions. Conclusions: The results confirm the effectiveness of the proposed approach for logistics flow distribution in a distributed transport system and its potential for decision support in the digital transport sector.