Automation and Modelling in Design and Management

The paper addresses the relevant issue of enhancing the efficiency and reliability of mold design for polymer injection molding. Traditional engineering calculation methods, relying on sequential parameter search, often prove labour-intensive and unable to achieve a global optimum of the design, particularly when dealing with multiple conflicting criteria such as minimal weight, maximal rigidity, uniform temperature distribution, and minimization of casting defects. The aim of the study is to improve productivity and enhance the quality of polymer injection molding production. The objective is to optimize the effectiveness criteria of mold design for polymer injection molding. The research methods rely on the principles of fundamental theories of geometric modeling, bio-inspired optimization algorithms, genetic algorithms, and particle swarm optimization. The novelty of the work lies in adapting hybridization operators, enabling the incorporation of the directed movement mechanism of particle swarms into genetic search to overcome premature convergence and facilitate abrupt exploration of the design variable space. The study results demonstrate that the proposed hybrid algorithm is 22% faster in convergence speed compared to classical genetic algorithms and yields Pareto-optimal front solutions, achieving a 15% reduction in tool mass and simultaneously decreasing maximum thermal deformations by 8% compared to the original design. The findings state that the developed hybrid algorithm of bio-inspired optimization proves to be an effective tool for supporting decision-making during the conceptual design of complex casting equipment.

This paper describes a mathematical model of a lithium-ion battery based on the Shepherd equation, and presents the results of its validation; describes a methodology for calculating the equation coefficients, and presents the results of experimental studies; provides coefficient adjustments for both the discharge and charge characteristics of the batteries. The work outlines the applicability limits of the described methods, and steps to ensure sustainability and scalability models. The aim of this study is to develop a simulation mathematical model of a lithium-ion battery, followed by verification using experimental data obtained during electric vehicle battery testing on a discharge-charge bench. A mathematical model of a battery will enable developers to conduct computational studies and analyse electric vehicle systems at the design stage. The simulation model is created using the MATLAB & Simulink software suite. Experimental studies are conducted using a measuring rig to record the discharge and charge characteristics of batteries. The novelty of this work lies in using a combined calculation method based on the Shepherd equation with additional coefficient adjustments to improve the convergence of the calculated and experimental data. The obtained results of convergence between the described method and the experiment (standard deviation < 0.02 V) indicate the high level of the model development and the appropriately selected calculation methods. The presented mathematical equation for the voltage dependence of a lithium-ion battery with known current characteristics on the current and the methods for calculating the coefficients of this equation can be used by engineers and developers specializing in modelling AC batteries of different application. Since the classical Shepherd equation does not account for temperature limitations, changes in internal resistance, and other battery parameters during discharge and charge, the developed mathematical model requires individual approaches to a battery type, which is expressed in correcting coefficient equation and its modifications. The presented mathematical battery model with calculated coefficients is convenient and sufficiently accurate basis for simulating lithium-ion battery operation in steady-state operating modes.

The paper describes a staged construction and application of an experimentally analytical model for determining the thermal characteristics of container greenhouses; develops an automatic system for registering microclimate parameters based on Arduino; performs an analysis of experimental data collected by the automated measuring and storage system regarding air temperatures and humidity during the autumn-spring observation period. A mathematical model of a container greenhouse has been developed and tested, allowing determining the thermal characteristics of the observed object under temperature conditions unavailable at the experiment location. The study demonstrates the effectiveness of using an experimentally analytical mathematical model at the design stage of container greenhouses to account for climatic features of the location and thermal insulation capabilities of the materials used.

The aim of this research is to design a model of an automated medical data processing system considering information security. To achieve this goal, the paper formulates the main objectives of an automated medical data processing system; proposes a design principle for an automated system considering information security; presents the architecture of an automated medical data processing system, and presents a methodology for analysing the vulnerabilities of an automated medical data processing system using the FSTEC RF and MITRE databases. The novelty of this work lies in the proposed creative concept of dividing the automated system architecture into the presentation, processing, and storage levels of medical data. The article also proposes definitions of subjects and objects of information security threats. The research results include a model of an automated medical data processing system, as well as a vulnerability analysis methodology based on the FSTEC Russian Federation vulnerability database and the MITRE database.

The paper considers several types of redundant systems for electrical engineering complexes built using uninterruptible power supplies (UPS), and examines the reliability of the selected configurations; analyses four main configurations of UPS systems, namely standard N, isolated Niz, parallel N+1, and redundant parallel 2(N+1). The results obtained in this study can play an important role in selecting and implementing UPS systems. UPS reliability parameters, such as failure rate, mean time between failures, and system availability, are assessed using the structural reliability block diagram method.