Eco-Design of Energy Production Systems: The Problem of Renewable Energy Capacity Recycling

Machine Learning in the Analysis of the Mechanical Shredding Process of Polymer Recyclates

Artificial intelligence methods and techniques creatively support the processes of developing and improving methods for selecting shredders for the processing of polymer materials. This allows to optimize the fulfillment of selection criteria, which may include not only indicators related to shredding efficiency and recyclate quality but also energy consumption. The aim of this paper is to select methods of analysis based on artificial intelligence (AI) with independent rule extraction, i.e., data-based methods (machine learning-ML). This study took into account real data sets (feature matrix 1982 rows × 40 columns) describing the shredding process, including energy consumption used to optimize the parameters for the energy efficiency of the shredder. Each of the 1982 records in a .csv file (feature vector) has 40 numbers divided by commas. The data were divided into a learning set (70% of the data), a testing set (20% of the data), and a validation set (10% of the data). Cross-validation showed that the best model was LbfgsLogisticRegressionOva (0.9333). This promotes the development of the basis for an intelligent shredding methodology with a high level of innovation in the processing and recycling of polymer materials within the Industry 4.0 paradigm.

Clustering of EU Countries by the Level of Circular Economy: An Object-Oriented Approach

In order to effectively regulate the circular economy (CE) at the national and international levels, it is essential to have a unified and informative system of indicators for monitoring the progress in the CE. The lack of standard indicators for measuring the progress of cyclicality leads to contradictions and misunderstandings, which is a problem for the implementation of CE strategies. This paper aims to adapt dynamic clustering approaches to solving strategic management problems of circular production and consumption processes. To achieve this goal, the authors performed the following tasks: (1) tested clustering algorithms by ranking EU countries by the level of development of the circular economy; (2) identified the approach that allows the best classification of EU countries, considering changes in the indicators of the level of CE development in 2000–2019 (dynamic classification); (3) developed a software module using python libraries to classify and visualize the results. The results illustrate that the k-means algorithm has a good discriminatory ability in division of all countries of the training sample (EU countries) into several clusters with different dynamics in the development of the CE. The best quality of classification is obtained by the indicator “Generation of municipal waste per capita”; satisfactory quality of the classification is obtained by the indicator “Generation of waste excluding major mineral wastes per GDP unit”. The study results demonstrate the fundamental applicability of the object-oriented and classical statistical approach to solving strategic management problems of the CE and their potential effectiveness in terms of the clarity and information content of reflecting cyclical processes.

Potential Impact of Renewable Energy on the Sustainable Development of Russian Arctic Territories

In recent decades, there has been a positive trend in world politics in the field of promoting territories’ sustainable development. At the same time, one of the most relevant areas is to promote the transition to renewable energy sources (RES), which correspond to one of the UN’s goals—Sustainable Development Goal 7 (SDG 7) “Ensuring universal access to affordable, reliable, sustainable and modern energy sources for all”. This article is devoted to the study of the renewable energy sources’ impact on the sustainable development of the Russian Arctic zone. The authors chose the level of carbon dioxide (CO2) emissions as an indicator reflecting the impact of RES on sustainable development, since this factor is one of the main factors for assessing trends in the activities of countries aimed at achieving progress on most of the Sustainable Development Goals of territories. The hypothesis of the relationship between the use of renewable energy sources and the achievement of progress on the Sustainable Development Goals, one of the indicators of which is the level of CO2 emissions, was tested and confirmed. An econometric analysis of panel data for 15 countries that are actively implementing the concept of sustainable development, including decarbonizing policies, was carried out, where the resulting indicator for achieving progress on the SDG was the amount of CO2 emissions. The factors influencing the resulting variable were indicators selected based on a review of existing models, as well as indicators of the Sustainable Development Goals’ achievement. Using an econometric analysis of interdependence, the indicators of progress towards the Sustainable Development Goals that are more likely to have an impact on the level of CO2 emissions were identified. These are electricity consumption, the share of renewable energy sources in the energy balance, the average per capita income of the population, and carbon intensity. Based on the results obtained, it can be concluded that renewable energy sources are a factor contributing to the achievement of progress on the Sustainable Development Goals. The results obtained are also applicable to the Arctic region, since all countries that have territories in the Arctic zone adhere to the policy of decarbonization and try to reduce the use of fossil fuels.

Design and Management of Manufacturing Systems

Although the design and management of manufacturing systems have been explored in the literature for many years now, they still remain topical problems in current scientific research [...]

The Development of Efficient Contaminated Polymer Materials Shredding in Recycling Processes

Recently, a dynamic increase in the number of polymer elements ending their life cycle has been observed. There are three main ways of dealing with polymer waste: reuse in an unchanged form, recycling (both material and energy), and disposal (mainly in the form of landfilling or incineration). The legislation of European countries promotes in particular two forms of waste management: reuse and recycling. Recycling processes are used to recover materials and energy especially from contaminated waste, which are structurally changed by other materials, friction, temperature, machine, process, etc. The recycling of polymers, especially of multi-plastic structural elements, requires the use of special technological installations and a series of preparatory operations, including crushing and separating. Due to the universality and necessity of materials processing in recycling engineering, in particular size reduction, the aim of this study is to organize and systematize knowledge about shredding in the recycling process of end-of-life polymeric materials. This could help properly design these processes in the context of sustainable development and circular economy. Firstly, an overview of the possibilities of end-of-life plastics management was made, and the meaning of shredding in the end-of-life pathways was described. Then, the development of comminution in recycling processes was presented, with special emphasis given to quasi-cutting as the dominant mode of comminution of polymeric materials. The phenomenon of quasi-cutting, as well as factors related to the material, the operation of the shredding machine, and the technological process affecting it were described. Research conducted on quasi-cutting as a phenomenon when cutting single material samples and quasi-cutting as a machine process was characterized. Then, issues regarding recycling potentials in the context of shredding were systematized. Considerations included the areas of material, technical, energy, human, and control potentials. Presented bases and models can be used to support the innovation of creative activities, i.e., environmentally friendly actions, that produce specific positive environmental results in the mechanical processing of recycled and reused materials. The literature survey indicates the need to explore the environmental aspect of the shredding process in recycling and connect the shredding process variables with environmental consequences. This will help to design and control the processes to get the lowest possible environmental burdens.

PV Waste Thermal Treatment According to the Circular Economy Concept

Photovoltaic panels (PV) are one of the most popular technological solutions used to produce green renewable energy. They are known as green technology, but by analyzing a life cycle of a common panel, we can find out that production of these panels is strictly associated with generation of a large waste stream. PV modules are constantly modified and, therefore, it is required to consider the impact of the applied materials on the environment during the whole lifecycle of the product. The most important aspect of the assessment of a life cycle of a photovoltaic module in the phase of decommissioning is material recycling. The process of material recycling is very difficult, due to the lamination used in the currently exploited technology. This paper presents the results of pyrolysis for a sample of a silicon module. The results of the presented research show a weight loss of 48.16 in case of the tested samples. This paper presents the outcome of a quantitative analysis of the content of polycyclic aromatic for liquid and concentrations of Br, Cl and F for a gaseous fraction of pyrolysis products. The goal of the research presented in the paper was to find the optimal parameters for thermal separation, as well as the influence of the energy consumption and materials separation efficiency on the final thermal efficiency of the process.