Sustainable Development in Economics, Technology and Environmental Engineering

Inhaltsverzeichnis

1. Modeling in the Context of Sustainable Development

   1. Frontmatter

   2. Smart Precision Farming Using IoT-Tinker Modeling for Sustainable Agriculture

      Devasis Pradhan, C. Karthik, B. Manikanta Subbarao, Jai Karthik, S. Hemanth, B. M. Manjunath

      Abstract

      Smart farming is a concept that refers to the use of internet-connected equipment and sensors for tracking and regulating numerous components of agricultural productivity. Soil moisture, crop health, irrigation, insect control, and environmental conditions are a few examples of these factors. The fundamental goal of IoT-based smart farming is to improve agricultural efficiency, production, and sustainability. This is accomplished by reducing dependency on physical labour, optimizing resource utilization, and increasing crop quality and quantity. The implementation of IoT sensors and devices enables real-time monitoring of crucial parameters such as soil moisture, temperature, humidity, and weather conditions. Smart farming systems can offer remote control and automation of farm equipment, minimizing labor-intensive tasks and increasing operational efficiency. The proposed system employs Internet of Things (IoT) devices for real-time data collection from various sources such as soil sensors, weather stations, and crop monitoring devices. The collected data is then processed through a sophisticated Tinker modeling framework, combining IoT technology with advanced analytics and machine learning algorithms. This study explores the various applications and benefits of integrating IoT technologies into agriculture and emphasizes the role of data-driven decision-making in improving farm productivity and reducing the environmental footprint. The integration of Smart Precision Farming using IoT-Tinker modeling presents a comprehensive and sustainable solution to the challenges facing modern agriculture. This approach not only enhances agricultural productivity but also promotes resource efficiency and environmental stewardship, contributing to the realization of a resilient and sustainable future for global agriculture.

   3. Development of the System for the Digital Model of the Helianthus Phenotype

      Anna Bakurova, Kateryna Vedmedeva, Stanyslav Vedmedev, Elina Tereschenko, Dmytro Shyrokorad

      Abstract

      The creation of high-yielding varieties is a priority task for achieving the objectives of sustainable development, specifically in eradicating hunger and promoting good health and well-being for humanity. Automation of the breeding process requires expanding the capabilities of automated phenotyping. The issue of digital phenotyping of plants is the foundation for automating the breeding process. The creation of the system for the digital model of the Helianthus phenotype, which is used to implement selection programs for confectionery sunflowers, is chosen as a significant task. The work was carried out in cooperation with experts from the Institute of Oilseed Crops of the National Academy of Agricultural Sciences of Ukraine. The work results are the formalization of the concept of the Helianthus phenotype digital model and the structural scheme of the system for the digital model of the Helianthus phenotype (seed and head). In the course of work, software for image processing of confectionary sunflower seeds was developed using Python programming.

   4. Modeling of Safe Object Detection by Near-Field and Nonlinear Radar Systems

      Leonid Karpukov, Yuriy Tarasenko, Volodymyr Voskoboynyk, Iurii Savchenko, Oleksandr Shapoval

      Abstract

      The article provides a comparative analysis of short-range and nonlinear radar with a view to further modernization of inspection and surveillance complexes, depending on the signs of demasking of objects subject to customs control. In this regard, using the proven methods of near-surface (subsurface) and nonlinear radar to detect and evaluate the parameters of objects, the author considers the possibility of implementing customs express control for monitoring railway transport with large-sized objects made of optically opaque materials, including contraband radio equipment. To detect possible demasking features of objects and make final decisions, a correlation method with the maximum likelihood of information signals from, as a rule, spatially distributed targets with demasking features is proposed. At the same time, the effectiveness of the detection and evaluation of information signals and the subsequent classification of demasking features of objects usually depends on the effective backscattering surface of the objects of study. The presence of a control arsenal of the latter, experimentally obtained in an anechoic chamber, similar to fingerprinting, significantly speeds up the procedure for recognizing the demasking features of objects. The required effective surface of the receiving antenna and the imaginary effective surface of the anechoic chamber should not exceed a certain predefined value, since the measurement error will be smaller, the lower the background signal level.

   5. Simulation Modeling of Rapidly Changing Loads of a Multi-parameter Object on the Basis of Hybrid Neural Networks

      Volodymyr Zinovkin, Mykola Antonov, Vira Savchenko, Mykhailo Zaluzhnyi

      Abstract

      A simulation model based on hybrid neural networks is proposed, which allows predicting likely parameters of rapidly changing loads of a multi-parameter electro-technological object. The implementation of a predictive simulation model in the structure of an automatic control system for a rapidly changing technological process is considered using the example of an electric arc furnace. The analysis of real and simulated modes of the phase current varying in time according to the probability law was performed. Structural diagram of the implementation of the developed model in the structure of the system of automatic control of the electric rapid-changing mode of the technological complex as part of the electric arc furnace is proposed.

   6. A Review on IoT-Based Intelligent Modeling for Environmental and Ecological Engineering

      A. Rashmi, K. P. Prashanth

      Abstract

      A new era of data collecting, analysis, and modeling for the monitoring and sustainable management of our planet's ecosystems has been ushered in by the Internet of Things (IoT), which has emerged as a transformative force in the field of environmental and ecological engineering. This thorough review paper highlights the critical role that IoT technologies play in resolving urgent environmental and ecological concerns by examining the dynamic synergy between IoT technology and cutting-edge data analytics and modeling methodologies. The review starts off by providing a thorough analysis of the state of IoT-based intelligent modeling in ecological and environmental engineering today, emphasizing how this paradigm shift has been driven by the quick developments in sensor technology, data processing capabilities, and communication protocols. It highlights how crucial the Internet of Things is to providing high-resolution, real-time data from far-off, previously unreachable places, allowing for a better understanding of biological systems and environmental events. IoT-based intelligent modeling's real-world applications are demonstrated in a variety of ecological and environmental settings. IoT technology has created a wide range of opportunities, from regulating the use of natural resources, reducing the effects of climate change, and assisting with precision agriculture, to tracking biodiversity changes, monitoring wildlife populations, and evaluating the quality of the air and water. The significance of these applications in research and real-world conservation initiatives is shown by case studies and success stories. Examined are the difficulties in applying IoT technologies to ecological and environmental engineering. These include worries about managing enormous datasets, integrating with current infrastructure, protecting privacy and security of data, and the moral implications of placing monitoring equipment in delicate environments. The review highlights cutting-edge tactics and industry best practices for overcoming these obstacles. The paper examines the bright future of IoT-based intelligent modeling, imagining a time when these technologies will develop further and contribute even more to ecological and environmental sustainability. It talks about how increasing automation, AI-powered decision assistance, and improved predictive modeling could result in proactive and successful ecosystem management techniques. An innovative era of ecological and environmental engineering has been brought about by the combination of IoT technologies with sophisticated data analytics and modeling techniques. With its thorough examination of the field, real-world applications, difficulties, and promising future of IoT-based intelligent modeling, this review highlights the critical role that this technology plays in protecting the environment and maintaining the sustainability of the planet's ecosystems.

   7. Modeling the Sustainable Development of Agrarian Sphere

      Olena Vasyl’yeva, Andrii Sokolov, Denis Morozov, Lidiia Horoshkova, Vasyl Yuriechko

      Abstract

      The article deals with the modeling of the influence of production factors on the volume of gross output of the agricultural sector of Ukraine and Zaporizhzhia region using the modified Cobb–Douglas production function, taking into account the needs of sustainable development. The four-factor Cobb–Douglas function was used to estimate the parameters of production functions that describe the impact of variables (physical and human capital, pollutant emissions) on the gross output of agricultural enterprises in Ukraine and Zaporizhzhia region. Balance equations and construction of isoquants in the form of surfaces in three-dimensional space are used to model optimal combinations of production function factors (balance of three factors with the fourth factor fixed). The Python ecosystem is used to process the array of data and visualize it. The result of using the Cobb–Douglas production function for modeling, which takes into account economic, social, and environmental factors, shows increasing returns to scale for agricultural enterprises in Ukraine. It is shown that the economic growth in the agricultural sector of Ukraine is mainly due to the quantitative and qualitative parameters of human potential, and is also associated with the growth of capital investments and the reduction of pollutant emissions. The political and institutional processes that take place in different periods also affect the value of the coefficients of the production function. Therefore, the modeling of economic growth in agriculture in Zaporizhzhia region needs to take into account other factors of competitiveness (institutional, political, infrastructural, etc.).

2. Innovative Technologies in Mechanical Engineering

   1. Frontmatter

   2. About Cut Thickness in Vibration Tracking Cutting

      Yuriy Vnukov, Pavlo Tryshyn, Serhiy Dyadya, Olena Kozlova

      Abstract

      Regenerative chatter is the main cause of vibration in cutting, having a negative impact on the machining process. The paper reviews the fundamental theories of regenerative chatter developed by J. Tlusty and S. A. Tobias et al. and stability analysis methods using feedback control theory presented by N. Merritt. In order to determine more accurately the thickness of the sheared layer during cutting by vibration trace, it is proposed to revise the application of existing formulas and approaches to analytical calculations of cutting dynamics. The authors of the paper highlight a disadvantage existing in these theories associated with the assumption that the vibration level depends on the phase shift between waves on the cutting surface of neighbouring passes. The conducted studies have shown that even in the absence of phase shear, the thickness of the cut layer is not a constant value, and the delay time between neighbouring revolutions does not remain constant, decreasing at each moment of time by the value Δτ. It is also shown that even in the absence of phase shear, the equality of the natural oscillation frequency of the cutter and the oscillation frequency of the chip-forming force creates a condition for resonance, which leads to the occurrence of maximum vibrations. Thus, the study questions the widespread assertion that the absence of phase shear ensures vibration-free cutting.

   3. Influence of Fused Deposition Modeling Parameters on the Process Intensification of Functional Products Manufacturing

      Larysa Tumarchenko, Yevhen Vyshnepolskyi, Dmytro Pavlenko

      Abstract

      The paper investigated the impact of Fused Deposition Modeling (FDM) parameters on the process intensification of functional products manufacturing. FDM is a widely used method of additive manufacturing that allows to produce parts by deposition of thermoplastic material layer by layer. However, its applying in the production of functional products is rather limited. The paper discussed various combinations of FDM process parameters that would increase production rate of parts without reducing their quality characteristics. The object of research was additive manufacturing technology—Fused Deposition Modeling (FDM). The research subject was the regularities of FDM process parameters’ influence on the manufacturing time of parts. The paper examined the influence of different combinations of FDM process parameters (printing speed, layer height, infill geometry, and infill density) on the manufacturing time of products. The main factors affecting the manufacturing time were established. A regression equation was obtained which allowed predicting the influence of the FDM process parameters on the manufacturing time of parts. The study included an analysis of process parameters’ impact on the printing time, quality, and geometric accuracy of the resulting products. The authors put forward hypotheses about the rational values of process parameters to achieve the best results in the production of functional parts by FDM. The study can be useful for engineers and designers who create products by FDM, as well as to expand the scope of this method in the production of functional parts.

   4. Additive Manufacturing in the Production of Aircraft Parts

      Oleksii Pedash, Valeriy Naumyk, Pavlo Kasay, Yevhen Milonin, Serhii Chigileychyk

      Abstract

      The article outlines results of microstructure evaluation and mechanical testing of Ni-based Superalloy parts obtained via innovative Laser Powder Bad Fusion (LPBF) and Direct Laser Metal Deposition (DLMD) Processes. The aviation purpose details for promising and serial gas turbine engines, which were manufactured using the above technologies, were investigated. It was shown that after hot isostatic pressing with subsequent heat treatment, strengthening of the considered alloy Ni-Cr-Fe-Mo-Nb-Ti-Al is provided by intermetallic γ’’-phase and carbides, also the lamellar δ-phase in microstructure was identified. In the microstructure of Ni-Cr-W-Mo-Ti-Al alloy along with intermetallic γ’-phase and carbides, also the needle-like α-Cr phase was identified. Mechanical properties of the specimens produced by Laser Powder Bad Fusion and Direct Laser Metal Deposition simultaneously along with both considered parts at the same process parameters meet the specification requirements for deformed materials.

   5. Development of a Digital Twin of an Articulated Robot

      S. N. Naveen Kumar, R. M. Devarajaiah, M. Arun Kumar, R. Hema, Mohammed Usman

      Abstract

      Digital twin technology is a virtual representation or a digital copy of an object, person, process, system, device, or location, and its fundamental architecture is made up of a variety of sensors and measurement technologies, IoT, and AI. The objectives of digital twin technology are to create a digital twin of an articulated robot that will co-exist and replicate its physical counterpart, and to design a digital twin ecosystem using IoT, CAD Modelling, data acquisition, and processing. The manufacturing industry is plagued by several challenges that hinder its efficiency and productivity. One of the most significant problems is the lack of visibility, which makes it difficult to detect issues in real time and results in a waste of resources, time, and money. Additionally, high costs are associated with developing prototypes and running physical tests, which often led to costly mistakes. Digital twin technology has revolutionized the manufacturing industry by providing solutions to the challenges that existed before its development. It provides a virtual platform for testing and optimizing products before they are manufactured, reducing the risk of errors and saving time and resources. It also allows for simulations to be run, enabling manufacturers to optimize their processes and adapt quickly to changes in the market. These benefits have the potential to transform the manufacturing industry, making it more efficient, productive, and competitive in the market. Therefore, in this work, an attempt is made to develop and implement a digital twin of an articulated robotic arm.

   6. Design of an LSRB Algorithm-Based Intelligent Maze Solving Robot

      K. N. Manjunatha, B. Kiran, Attel Manjunath, N. Raghu, Aditya Ganapati Nimbalkar

      Abstract

      The challenge of solving a maze has been around for approximately three decades, yet it continues to be regarded as a significant domain within robotics. This task is rooted in one of the important aspects of robotics, namely, “Decision Making.” The design of the robot comprises three primary subsystems: the drive system, an array of sensors, and the control system. The objective of the robot is to navigate through a maze. This undertaking can be perceived as a system that incorporates interdisciplinary engineering elements. Design choices and compromises encompass considerations such as weight, speed, power, sensing techniques, turning methods, and programming. Autonomous robots have extensive applications, ranging from bomb detection and locating individuals in wreckage to home automation. In all these scenarios, the robot operates in an unknown environment, necessitating decision-making capabilities. The envisioned design involves a robot specifically crafted for maze-solving tasks. The project entailed creating a program capable of simulating the step-by-step process to solve a maze, in addition to constructing a robot and conducting maze tests. The key aspect of this project is solving the maze. The solving stage will involve an implementation of left priority algorithm used for graph traversal.

   7. Conceptual Computer-Aided Design of a Two-Wheeled Jumping Robot

      Attel Manjunath, Akshaya Simha, C. S. Vinod Kumar, K. N. Manjunatha, H. Manjushree

      Abstract

      This paper describes a conceptual design of a two-wheeled jumping robot to take the advantage of rolling and jumping for surveillance activities. The proposed design is simple and can achieve high efficiency in the jumping process. The jumping mechanism for this robot is derived from a basic single slider-crank chain that is driven by a single DC motor. The mechanism of the robot was first modelled using ADAMS software, and then it was validated using multibody dynamics simulation. The mechanism’s jumping frame makes 62° to the horizontal plane. Simulated results show that the two-wheeled jumping robot can jump up to a height of 30 cm and can have a span of around 20 cm. The centre of gravity was also observed to be one key reason for stable jumping of two-wheeled jumping robots. This jumping mechanism can be installed in robots that can be used in difficult terrains that standard robots will not be able to handle. This research is floated to make significant contributions, particularly in military domains where it can enhance surveillance and navigation capabilities in challenging terrains. These advancements go beyond the capabilities of conventional military forces and traditional robotic systems.