Design Of Systems Research Articles

Design and Development of LM24 plate Casting using Solid Cast Simulation Technique

Abstract: This research deals with the elimination of defects in aluminium alloy castings and enhancement in the casting yield and quality. The main intention of the work is to improve the quality of a cast component using Computer Aided Casting Simulation Software. SOLID Cast simulation software is used for simulating the solidification process of casting and visualizing outputs showing possible problematic areas or defects which may occur in the cast product. Plate Castings of aluminium alloy - LM 24 are produced with different designs of gating systems and tested for defects like porosity using Archimedes immersion Technique and also Radiographic testing is used to check the quality of the castings. The produced castings are observed to be sound, and the results obtained are in agreement with the simulation results. Hence it is verified that solidification simulation helps in improving the quality of castings without any shop-floor trails. Casting yield and percentage porosity values are determined for 12 castings produced with different gating systems. The best results are observed to be produced by the castings having a 1-Ingate system in horizontal or lateral positions.

The Optimal Speech-to-Background Ratio for Balancing Speech Recognition With Environmental Sound Recognition.

This study aimed to determine the speech-to-background ratios (SBRs) at which normal-hearing (NH) and hearing-impaired (HI) listeners can recognize both speech and environmental sounds when the two types of signals are mixed. Also examined were the effect of individual sounds on speech recognition and environmental sound recognition (ESR), and the impact of divided versus selective attention on these tasks. In Experiment 1 (divided attention), 11 NH and 10 HI listeners heard sentences mixed with environmental sounds at various SBRs and performed speech recognition and ESR tasks concurrently in each trial. In Experiment 2 (selective attention), 20 NH listeners performed these tasks in separate trials. Psychometric functions were generated for each task, listener group, and environmental sound. The range over which speech recognition and ESR were both high was determined, as was the optimal SBR for balancing recognition with ESR, defined as the point of intersection between each pair of normalized psychometric functions. The NH listeners achieved greater than 95% accuracy on concurrent speech recognition and ESR over an SBR range of approximately 20 dB or greater. The optimal SBR for maximizing both speech recognition and ESR for NH listeners was approximately +12 dB. For the HI listeners, the range over which 95% performance was observed on both tasks was far smaller (span of 1 dB), with an optimal value of +5 dB. Acoustic analyses indicated that the speech and environmental sound stimuli were similarly audible, regardless of the hearing status of the listener, but that the speech fluctuated more than the environmental sounds. Divided versus selective attention conditions produced differences in performance that were statistically significant yet only modest in magnitude. In all conditions and for both listener groups, recognition was higher for environmental sounds than for speech when presented at equal intensities (i.e., 0 dB SBR), indicating that the environmental sounds were more effective maskers of speech than the converse. Each of the 25 environmental sounds used in this study (with one exception) had a span of SBRs over which speech recognition and ESR were both higher than 95%. These ranges tended to overlap substantially. A range of SBRs exists over which speech and environmental sounds can be simultaneously recognized with high accuracy by NH and HI listeners, but this range is larger for NH listeners. The single optimal SBR for jointly maximizing speech recognition and ESR also differs between NH and HI listeners. The greater masking effectiveness of the environmental sounds relative to the speech may be related to the lower degree of fluctuation present in the environmental sounds as well as possibly task differences between speech recognition and ESR (open versus closed set). The observed differences between the NH and HI results may possibly be related to the HI listeners' smaller fluctuating masker benefit. As noise-reduction systems become increasingly effective, the current results could potentially guide the design of future systems that provide listeners with highly intelligible speech without depriving them of access to important environmental sounds.

The Potential of Self-Activating Au(I) Complexes in Gold Catalysis.

Gold catalysis has emerged as a groundbreaking field in synthetic chemistry, revolutionizing numerous organic transformations. Despite the significant achieved advancements, the mechanistic understanding behind many gold-catalyzed reactions remains elusive. This Concept article covers the so-called "self-activating" Au(I) complexes, sorting out their pivotal role in gold catalysis. We comment on how Au(I) complexes can undergo self-activation, triggering diverse catalytic transformations without the need for external additives. The most important examples reported so far that underlie the catalytic activity of these species are discussed. This intrinsic reactivity represents a paradigm shift in gold catalysis, offering new avenues for the design of efficient and sustainable catalytic systems. Furthermore, we explore the factors influencing the stability, reactivity, and selectivity of these Au(I) complexes, providing insights into their synthetic utility and potential applications in synthesis. This area of research not only advances our fundamental understanding of gold catalysis but also paves the way for the development of novel catalytic strategies with broad implications in organic synthesis and the chemical industry.

Avionics System Design using MBSE Methodology

Abstract: The West Air Sweden Flight 294 serves as a reminder of tragic crashes of aircraftdue to Avionics System failure. Due to malfunction of the Inertial Reference Unit (IRU), the aircraft lost its control resulting in tragic loss of life of the peopleon board. The Avionics System is a complex set of instruments, logical and physical links which must comply with the guidelines of Dob178c. The design of the system is complicated. This paper aims to understand the behavior of the Avionics System using the state-of-the-art Model Based System Engineering (MBSE) technology. This includes the two widely used tools – Capella and Simulink. We aim to understand the dynamic nature of avionics through these tools. Model Based System Engineering can be specifically beneficial because it will help the engineers to detect the flaws in the avionics system much earlier. This will potentially contribute to helping to prevent aircraft crashes due to avionics system failure. The idea of model-based system engineering includes the concept of taking a model as a reference to systematically solve the complex designs of any engineering stage. Before the concept of Model Based Systems Engineering came to be, Documents Based Systems Engineering was the trend in the system engineering department. However, it would take a lot of time, effort and accuracy to correctly pinpoint the information and accordingly design the system from a bunch of documents. MBSE, however, eases such kind of trouble by providing a model as a reference for the systems design

BlockEdge: Building Bridges to Safe and Efficient Distributed Systems

Abstract: In the ever-evolving landscape of distributed systems, ensuring safety, efficiency, and scalability remains a paramount challenge. BlockEdge emerges as a pioneering framework designed to address these critical issues by leveraging the principles of blockchain technology and advanced consensus mechanisms. This abstract outlines the key features, innovations, and potential impacts of BlockEdge on the realm of distributed computing. BlockEdge integrates blockchain's immutable ledger properties with a novel consensus algorithm tailored for distributed systems. Unlike traditional blockchain applications that prioritize decentralization for financial transactions, BlockEdge focuses on enhancing the performance and reliability of distributed applications. The framework employs a hybrid consensus model that combines Byzantine Fault Tolerance (BFT) with Proof-of-Stake (PoS), optimizing both security and energy efficiency. A standout feature of BlockEdge is its modular architecture, which allows seamless interoperability between different types of distributed networks. This modularity facilitates the integration of various consensus protocols, catering to the specific needs of diverse applications, from IoT networks to large-scale data processing systems. By enabling secure and efficient cross-chain communication, BlockEdge effectively mitigates the silo effect prevalent in current distributed system designs.

Multi-lane traffic flow model based on cellular automaton fine-scale under cooperative vehicle infrastructure system

Microscopic traffic flow modeling is crucial for predicting future traffic demand and optimizing the design of transportation systems. At the microscopic level, a well-crafted model is capable of describing the interactions and dynamic variations among vehicles with greater accuracy. The cell scale in the classical cellular automaton (CA) multi-lane traffic flow model is a critical parameter to accurately express the location relationship of vehicles. In this paper, a new method based on Symmetric Two-lane Cellular Automaton (STCA), entitled STCA-X, is proposed for the cell scale selection. Firstly, the position, velocity, acceleration, and interaction of vehicle operation in the urban multi-lane environment are analyzed, and a feature model is built based on CA. One important drawback of the existing models is that they do not match the vehicle movement in the actual lane. To handle this problem, a fine-scale CA multi-lane model is developed. Secondly, a new traffic flow model is created by redefining several key behaviors such as road following, lane changing, and blocking in the STCA model. The experimental results are analyzed and compared with several of the state-of-the-art methods. Analysis of the simulation results proves that STCA-X improves vehicle lane change frequency and lane utilization efficiency. However, the enhancements in the model have resulted in increased computational complexity. Consequently, future research will delve into novel approaches to boost computational efficiency, thereby propelling the progress of traffic flow modeling technology.

Innovative fertilizers with added plant extracts in the cultivation of Valeriana officinalis and Raphanus sativus and in the control of Botrytis and powdery mildew

Research objective: The main objective of this article is to report the results obtained from the use of innovative fertilisers with added plant extracts in agriculture. In particular, this article will deal with two important topics: i) study of the effect of innovative fertilisers on the biomass of vegetable plants; ii) possible control on mortality due to diseases such as Botrytis and powdery mildew. The information reported in this research work can support the design of cultivation systems in which agricultural sustainability is fundamental due to the presence of plant extracts as an alternative to synthetic plant protection products. Materials and Methods: The plants were grown in pots under controlled conditions; 30 seedlings per thesis, divided into 3 replications of 10 plants each, were planted in early January 2024. The plants used in the trial were Valeriana officinalis L. and Raphanus sativus. The five experimental groups in cultivation were: i) group control, irrigated with water and previously fertilised substrate; ii) group with Aktigen, irrigated with water and previously fertilised substrate, (3 ml per plant once a week); iii) group with Lifegen, irrigated with water and previously fertilised substrate, (3 ml per plant once a week); iv) group with QI-gen, irrigated with water and previously fertilised substrate, (3 ml per plant once a week); v) Group with Ecklonia maxima (EK): (peat 70% + pumice 20%), irrigated with water and previously fertilised substrate, (3 ml per plant once a week). On 5 May 2024, plant height, number of leaves, primary root length (mm), biomass of the aerial and root system, and number of dead plants (Botrytis and powdery mildew) were recorded. Results and Discussion: The experiment showed that the use of innovative fertilisers enriched with plant extracts can indeed significantly improve the vegetative and root growth of Valeriana officinalis L. and Raphanus sativus. All treatments showed a significant improvement over the untreated control and the commercial Ecklonia maxima treatment for the agronomic parameters analysed, but the Qi-gen treatment was significantly the best for increasing vegetative and root biomass. Improvements were also found in plant height, leaf number and root length. The trial also revealed the significant effect on Botrytis control of the product Aktigen and on powdery mildew of the product Lifegen, in fact they reduced the mortality of Valeriana officinalis and Raphanus sativus seedlings. Conclusions: A number of scientific studies have shown that the application of biofertilizers can improve plant growth, productivity, quality, and tolerance to biotic and abiotic stresses. Because of their multiple properties, they have become increasingly important as advanced agricultural techniques in global agriculture. This type of product, which includes natural substances, will contribute significantly to ecologically and economically sustainable agricultural production systems in the coming years, as well as serving as the foundation for large-scale sustainable agriculture in the future.

Dynamic modeling of a sliding ring on an elastic rod with incremental potential formulation

Abstract Mechanical interactions between rigid rings and flexible cables find broad application in both daily life (hanging clothes) and engineering system (closing a tether-net). A reduced-order method for the dynamic analysis of sliding rings on a deformable one-dimensional (1D) rod-like object is proposed. In contrast to the conventional approach of discretising joint rings into multiple nodes and edges for contact detection and numerical simulation, a single point is used to reduce the order of the model. To ensure that the sliding ring and flexible rod do not deviate from their desired positions, a new barrier function is formulated using the incremental potential theory. Subsequently, the interaction between tangent frictional forces is obtained through a delayed dissipative approach. The proposed barrier functional and the associated frictional functional are C2 continuous, hence the nonlinear elastodynamic system can be solved variationally by an implicit time-stepping scheme. The numerical framework is initially applied to simple examples where the analytical solutions are available for validation. Then, multiple complex practical engineering examples are considered to showcase the effectiveness of the proposed method. The simplified ring-to-rod interaction model has the capacity to enhance the realism of visual effects in image animations, while simultaneously facilitating the optimisation of designs for space debris removal systems.

Enhancing Hydrogels with Quantum Dots

This manuscript explores the interdisciplinary integration of quantum dot–hydrogel composites and smart materials and their applications across a spectrum of fields, including biomedical engineering, environmental sensing, and energy harvesting. It covers the synthesis of novel materials like fluorescent hydrogel nanocomposites that display enhanced chemical stability, mechanical strength, and thermal resistance, highlighting their utility in environmental monitoring and catalysis. In the biomedical sector, innovations include hydrogel composites for targeted drug delivery and advanced therapies such as photothermal DNA hydrogels for tumor treatment. This review also discusses the application of these materials in imaging, diagnostics, and the development of smart sensors capable of detecting various biological and environmental changes. Its scope further extends to optoelectronics and the design of energy-efficient systems, underscoring the versatile functionalities of hydrogels in modern technological applications. Challenges remain in scaling up these technologies for commercial use and ensuring their long-term stability and safety, necessitating future research focused on sustainable, scalable solutions that can be integrated into existing systems.

Innovations and strategies for optimizing lithium-ion battery performance: From material advancements to system management

This paper explores the multifaceted advancements in lithium-ion battery (LIB) technology, focusing on material innovations and engineering strategies aimed at optimizing performance, safety, and efficiency. We delve into the development of advanced cathode materials like lithium nickel manganese cobalt oxide (NMC) and lithium iron phosphate (LFP), highlighting their contributions to enhancing energy density and safety. The investigation extends to silicon-based anode materials, underscoring their potential to significantly increase energy storage capacity despite challenges related to volume expansion. Furthermore, we discuss electrolyte optimization techniques that promise to improve battery safety through the use of non-flammable ionic liquids and solid-state electrolytes. Engineering strategies, including microstructure design of electrodes and thermal management systems, are analyzed for their role in improving electrochemical performance and extending battery lifespan. Smart battery management systems (BMS) are also examined for their ability to optimize battery usage through real-time monitoring and predictive analytics. Through a comprehensive review and quantitative analysis, this study presents a cohesive overview of current trends and future directions in LIB technology.

Optimization of a hybrid system (PV-fuel cell) of energy production for an isolated site

In recent years, there has been a significant shift in the design and implementation of autonomous micro-grid systems, moving away from the traditional reliance on fossil fuels. Instead, these systems are now integrating existing renewable energy sources available in specific geographic locations to promote sustainability and environmental responsibility in the energy sector. One particularly promising approach for energy storage and transmission is through the utilization of hydrogen and solar energy, especially in remote regions where hybrid techniques can effectively meet the required energy demands. Our research focuses on electrifying an agricultural site located in the SBAA region, specifically in the city of ADRAR, southwest Algeria. We propose the implementation of an independent small electric network that combines various renewable energy sources, including photovoltaic (PV) systems and fuel cells. To ensure cost-effectiveness and optimize the system's performance, we aim to carefully control and size the system's components through a meticulous selection process. The primary objective of this study is to evaluate the technical and economic feasibility of implementing renewable energy systems in the targeted region. Our goals are to reduce the total net cost, minimize energy expenses and unfulfilled load, while simultaneously mitigating CO2 emissions. To achieve these objectives, we employ the HOMER Pro simulation program, which enables us to conduct a comprehensive analysis of the proposed system's performance and economic viability. The proposed system incorporates a hybrid configuration of PV panels and fuel cells, leveraging the complementary nature of these two renewable energy sources. PV panels harness the abundant solar energy during daytime hours, while fuel cells provide a reliable and consistent energy source during periods of low solar irradiance or at night. By integrating these two technologies, we aim to establish a self-sufficient and sustainable energy system capable of meeting the energy demands of the remote agricultural site. Overall, the proposed renewable energy system demonstrates positive results in electrifying remote areas while maintaining a conservative cost of electrical energy. By implementing this system, we not only contribute to the establishment of sustainable regions but also promote environmental stewardship by reducing carbon emissions and dependence on fossil fuels.

A CFD Methodology for the Modelling of Animal Thermal Welfare in Hybrid Ventilated Livestock Buildings

Computational fluid dynamics (CFD) may aid the design of barn ventilation systems by simulating indoor cattle thermal welfare. In the literature, CFD models of mechanically and naturally ventilated barns are proposed separately. Hybrid ventilation relies on cross effects between air change mechanisms that cannot be studied using existing models. The objective of this study was to develop a CFD methodology for modelling animal thermal comfort in hybrid ventilated barns. To check the capability of CFD as a design evaluation tool, a real case study (with exhaust blowers) and an alternative roof layout (with ridge gaps) were simulated in summer and winter weather. Typical phenomena of natural and mechanical ventilation were considered: buoyancy, solar radiation, and wind together with high-speed fans and exhaust blowers. Cattle thermal load was determined from a daily animal energy balance, and the assessment of thermal welfare was performed using thermohygrometric indexes. Results highlight that the current ventilation layout ensures adequate thermal welfare on average, despite large nonuniformity between stalls. The predicted intensity of heat stress was successfully compared with experimental measurements of heavy breathing duration. Results show strong interactions between natural and mechanical ventilation, underlining the need for an integrated simulation methodology.

AI-Based Metamaterial Design.

The use of metamaterials in various devices has revolutionized applications in optics, healthcare, acoustics, and power systems. Advancements in these fields demand novel or superior metamaterials that can demonstrate targeted control of electromagnetic, mechanical, and thermal properties of matter. Traditional design systems and methods often require manual manipulations which is time-consuming and resource intensive. The integration of artificial intelligence (AI) in optimizing metamaterial design can be employed to explore variant disciplines and address bottlenecks in design. AI-based metamaterial design can also enable the development of novel metamaterials by optimizing design parameters that cannot be achieved using traditional methods. The application of AI can be leveraged to accelerate the analysis of vast data sets as well as to better utilize limited data sets via generative models. This review covers the transformative impact of AI and AI-based metamaterial design for optics, acoustics, healthcare, and power systems. The current challenges, emerging fields, future directions, and bottlenecks within each domain are discussed.

Data-driven model reduction for pipes conveying fluid via spectral submanifolds

Pipes conveying fluid have non-linearizable dynamics when the flow velocity is large enough. Developing analytical models that accurately capture these highly nonlinear and complex dynamics is challenging. Efficient analysis and predictions of these nonlinear dynamics are essential in the design and control of pipe systems in engineering applications. To address these challenges, here we construct low-dimensional reduced-order models in a data-driven setting. In particular, we perform model reduction on spectral submanifolds (SSMs) via SSMLearn. This open-source package automates the identification of low-dimensional SSMs and their associated reduced-order models (ROMs). Our reduction via SSMs treats pipes with various boundary conditions and flow velocities in a unified way. It achieves a significant reduction because the ROMs are two-dimensional, which enables efficient and even analytical predictions on the nonlinear vibration of the pipes, paving the way for real-time prediction of the non-linearizable dynamics. In addition, our SSM-based reduction shows remarkable extrapolation capability because it is built on invariant manifolds and normal form theory. We demonstrate that the ROMs trained on unforced responses can be directly extrapolated to make reliable predictions on forced vibrations under various excitation frequencies and amplitudes, including periodic and quasi-periodic orbits and their bifurcations.

Sustainable Fishing Livelihoods: Exploring the Potential of Sail Technology Using Computational Fluid Dynamic in Traditional Fishing Boats

The potential of using sails and Computational Fluid Dynamics (CFD) to improve the sustainability of traditional fishing boats in the Maluku region. This study highlights the importance of cost-effectiveness and environmental sustainability in the fishing industry. This study shows that Computational Fluid Dynamics (CFD) is effective in simulating the thrust force generated by sails. Sails were used to generate thrust forces on conventional fishing vessels by implementing CFD methodology with three different models. Various sail shapes were incorporated into the modelling process to assess their impact on the thrust force. Subsequently, a comprehensive analysis was conducted to evaluate the sail thrust force under typical operating conditions, focusing specifically on the average speed of the vessel at 15 knots in the waters surrounding the Maluku Islands. The results reveal that sail model 1 has the highest thrust force, amounting to 240.2 N. Sail models 3 and 2 generate thrust forces of 238.9 N and 227.9 N, respectively. The fluid flow conditions around sail model 1 and screen model 2 provide valuable insights into how the sail interacts with the fluid environment to produce thrust. By understanding and optimizing these fluid dynamics, designers and engineers can enhance the performance of sail models and improve their efficiency in harnessing wind power for propulsion. This study highlights the importance of ship science and technology in the design of appropriate propulsion systems for traditional fishing vessels.

Integrated urban land cover analysis using deep learning and post‐classification correction

AbstractThe quantification of urban impervious area has important implications for the design and management of urban water and environmental infrastructure systems. This study proposes a deep learning model to classify 15‐cm aerial imagery of urban landscapes, coupled with a vector‐oriented post‐classification processing algorithm for automatically retrieving canopy‐covered impervious surfaces. In a case study in Corpus Christi, TX, deep learning classification covered an area of approximately 312 km2 (or 14.86 billion 0.15‐m pixels), and the post‐classification effort led to the retrieval of over 4 km2 (or 0.18 billion pixels) of additional impervious area. The results also suggest the underestimation of urban impervious area by existing methods that cannot consider the canopy‐covered impervious surfaces. By improving the identification and quantification of various impervious surfaces at the city scale, this study could directly benefit a variety of environmental and infrastructure management practices and enhance the reliability and accuracy of processed‐based models for urban hydrology and water infrastructure.

Nominal GSM-R Radio Network Design for Signalling and Train Control Systems: Case Study Dar-Moro Electrified SGR Line in Tanzania

Nominal GSM-R Radio Network Design for Signalling and Train Control Systems: Case Study Dar-Moro Electrified SGR Line in Tanzania

СТІЙКІСТЬ РОБОЧИХ РЕЖИМІВ АВТОНОМНИХ АСИНХРОННИХ ГЕНЕРАТОРІВ ІЗ САМОЗБУДЖЕННЯМ

The paper presents the results of investigation the stability conditions of self-excited induction generators. A mathematical model of the generating system with an analytical description of the dependence of the magnetization inductance on the current is used. It allows to avoid the iterative procedure and to scale the dependence to determine the magnetization inductance for induction machines of different types and power. The influence of the load inductance on the stability of the generating system at different rotational speeds is investigated. It is shown that an increase in the inductance value increases the system stability margins in the self-excitation zone. Also this article deals with the issues of system stability within the self-excitation zone of an induction generator at different rotational speeds depending on the value of the capacitance of self-excitation capacitors. It is depicted that at low rotational speeds there may not exist a stable operation mode in the self-excitation zone regardless of the value of the capacitance in the motor stator circuit. This method of determination the stability of the operation modes of the generation system will be useful both for the design of new systems and for the modification and adjustment of existing ones. References 9, figures 4.

Self-assembly of discrete multi-chromophoric systems.

Self-assembly of chromophoric systems is a prerequisite to create well-ordered, processable nanomaterials with multiple functionalities. In the past two decades, the field of functional organic materials has primarily focused on systems featuring only one type of dye/π-conjugated unit. Consequently, many reports with mechanistic insights on the self-assembly of the dyes featuring different molecular packing have been reported. Subsequently, we have witnessed several attempts to organize the multi-chromophoric systems in solution and solid-state via different approaches using self-assembly as a tool. Incorporation of more than one dye is important in creating materials with tuneable optoelectronic properties. Consequently, self-assembly of more than one chromophoric systems have been investigated to some extent. This review aims to discuss the self-assembled materials derived from discrete π-conjugated systems comprising more than one dye units connected through covalent bonding (multi-chromophoric systems). Molecular design of various multi-chromophoric systems leading to the formation of crystals, liquid crystals and supramolecular polymers have been correlated with corresponding properties. We envisage that classification of self-assembled multi-chromophoric systems, with a note on tuneable optoelectronic properties, can provide a deeper understanding on the molecular design strategies, which is important in the fabrication of functional organic materials with optimum performances.

Проектирование морских интеллектуальных транспортных систем, опирающихся на показатели устройств обработки информации

Цифровые проекты, к которым относится и проект НТИ «Цифровая верфь», строятся на математических моделях принятия решений по управлению когерентностью движения. Модели по управлению когерентностью движения судов на каналах судопропуска являются предметом исследования. В работе описаны методы современной теории автоматического управления по расчёту критериев абсолютной устойчивости нелинейных систем, а именно метод фазового пространства и метод гармонического баланса. Прибор управления движением судна работает в двух режимах – реальном времени и в режиме счисления. В математической модели движения необходимо заложить разностное уравнение в таком виде, что его можно будет использовать для программирования контроллера вектора направления движения, а именно, путевой вектор смещения: курс и скорость с учётом внешних воздействий. Одноконтурные системы устройств промышленного интернета вещей состоят из нелинейного безынерционного преобразователя и линейной динамической части и обладают единичной отрицательной обратной связью. Вид связи нелинейного безынерционного преобразователя с линейной частью модели влияет на выбор вида корректирующей обратной связи модели. Предложена и доказана способность линеаризации модели расчёта амплитуды преобразователя системы устройств управления на судоходно-шлюзовом канале нейронной сетью. Для детектирования амплитуды гармонического сигнала в предыдущих работах создана сеть Элмана, которым генерируется сигнал входа. Создана искусственная нейронная сеть Хопфилда с четырьмя устойчивыми точками, генерирующая решение модели управления. Решение задачи определения параметров шлюзования или настройки нелинейной части модели выполнено. Digital projects, which include “Digital Shipyard” project, are built on mathematical models of decision-making for managing motion coherence. Models for managing the coherence of vessel traffic on shipping channels are the subject of research. The current work describes methods of modern automatic control theory for calculating criteria for the absolute stability of nonlinear systems, namely the phase space method and the harmonic balance method. The vessel motion control device operates in two modes - real time and dead reckoning mode. In the mathematical model of movement, it is necessary to include a difference equation in such a form that it can be used to program the controller of the movement direction vector, namely, the displacement path vector: course and speed, taking into account external influences. Single-loop systems of industrial Internet of things devices consist of a nonlinear inertia-free converter and a linear dynamic part and have a single negative feedback. It is the type of connection between the nonlinear inertia-free converter and the linear part of the model influences the choice of the type of corrective feedback of the model. The work proposes and proves the ability to linearize a model for calculating the amplitude of the transducer of a system of control devices on a shipping lock channel using a neural network. To detect the amplitude of a harmonic signal, previous works have created an Elman network, which generates an input signal. In the current work, an artificial Hopfield neural network with four stable points is created generates a solution to the control model. The solution to the problem of determining the gateway parameters or setting up the nonlinear part of the model is been completed.